MODELING, OBSERVATION & ANALYSIS

Biggerstaff, M. I., D. W. Burgess, G. D. Carrie, E. R. Mansell, L. J. Wicker, C. L. Ziegler, 2008: Storm-Scale Sampling Strategies for the Mobile C-Band Doppler Radars during VORTEX2. Extended Abstracts, 24th Conference on Severe Local Storms, Savannah, GA, USA, American Meteorological Society, 5.2.

Biggerstaff, M. I., D. P. Betten, C. L. Ziegler, D. R. McGorman, L. J. Wicker, D. W. Burgess, E. R. Mansell, 2010: Rear-flank downdraft dynamics in tornadic and non-tornadic supercell thunderstorms. Extended Abstracts, 25th Conference on Severe Local Storms, Denver, CO, USA, AMS, 8A.1.

Bodine, D., R. D. Palmer, C. Ziegler, P. L. Heinselman, 2010: High-resolution radar analysis during tornadogenesis from OU-PRIME on 10 May 2010. Extended Abstracts, 25th Conference on Severe Local Storms, Denver, CO, USA, Amer. Meteor. Soc., 15.4.

High-resolution polarimetric radar measurements in numerous supercells and tornadoes were obtained by the Polarimetric Radar for Innovations in Meteorology and Engineering (OU-PRIME) during the 10 May 2010 tornado outbreak. These observations include a supercell that produced an EF-4 tornado that developed near Moore, Oklahoma, only 10–15 km from OU-PRIME. The supercell's reflectivity appendage developed cyclonic curvature 15 min prior to the first tornado observations, coincident with an increase in low-level mesocyclone intensity and a protrusion of the rear-flank downdraft into the inflow region. Numerous cyclonic and anticyclonic flares were observed along the rear-flank downdraft (RFD) with cyclonic and anticyclonic rotation below 100 m, indicative of possible tornadoes or gustnadoes. As the RFD gust front extended further into the inflow region, vortices developed along the RFD gust front after a significant increase in near-surface convergence along the RFD gust front. In general, the vortex diameter and the spatial concentration both decreased as height increased.

To analyze the evolution of low-level rotation during tornadogenesis, single-radar approximations of vorticity and convergence in the RFD region are computed. Vorticity and convergence are computed using radial velocity differences between two gates over a fixed number of gates. The possible role of vorticity along the RFD gust front in tornadogenesis will be discussed, along with other vorticity sources identified in the analysis.

Available online at http://ams.confex.com/ams/25SLS/techprogram/paper_175834.htm.

Buban, M. S., C. L. Ziegler, E. N. Rasmussen, Y. P. Richardson, 2007: The Dryline on 22 May 2002 during IHOP: Ground-Radar and In Situ Data Analyses of the Dryline and Boundary Layer Evolution. Monthly Weather Review, 135, 2473-2505.

On the afternoon and evening of 22 May 2002, high-resolution observations of the boundary layer (BL) and a dryline were obtained in the eastern Oklahoma and Texas panhandles during the International H2O Project. Using overdetermined multiple-Doppler radar syntheses in concert with a Lagrangian analysis of water vapor and temperature fields, the 3D kinematic and thermodynamic structure of the dryline and surrounding BL have been analyzed over a nearly 2-h period. The dryline is resolved as a strong (2–4 g/kg/km) gradient of water vapor mixing ratio that resides in a nearly north–south-oriented zone of convergence. Maintained through frontogenesis, the dryline is also located within a gradient of virtual potential temperature, which induces a persistent, solenoidally forced secondary circulation. Initially quasi-stationary, the dryline retrogrades to the west during early evening and displays complicated substructures including small wavelike perturbations that travel from south to north at nearly the speed of the mean BL flow. A second, minor dryline has similar characteristics to the first, but has weaker gradients and circulations. The BL adjacent to the dryline exhibits complicated structures, consisting of combinations of open cells, horizontal convective rolls, and transverse rolls. Strong convergence and vertical motion at the dryline act to lift moisture, and high-based cumulus clouds are observed in the analysis domain. Although the top of the analysis domain is below the lifted condensation level height, vertical extrapolation of the moisture fields generally agrees with cloud locations. Mesoscale vortices that move along the dryline induce a transient eastward dryline motion due to the eastward advection of dry air following misocyclone passage. Refractivity-based moisture and differential reflectivity analyses are used to help interpret the Lagrangian analyses.

Buban, M., C. Ziegler, Y. Richardson, 2008: Numerical simulations of the dryline and surrounding boundary layer on 22 May 2002 during IHOP. Extended Abstracts, 24th Conference on Severe Local Storms, Savannah, GA, USA, AMS, 18.4.

On the afternoon and evening of 22 May 2002, high-resolution data of the dryline and surrounding boundary layer (BL) were collected in the Oklahoma and Texas panhandles as part of the International H2O Project. Using over-determined multiple Doppler radar syntheses in concert with an innovative Lagrangian analysis technique, the 3-D kinematic and thermodynamic structure of the dryline and surrounding BL have been obtained over nearly a 2-hour period. A past study utilizing these analysis tools has delineated the 22 May dryline as a strong gradient of water vapor mixing ratio embedded in a zone of multi-Doppler radar-derived convergence. Misocyclones are observed to propagate from south to north along the dryline. The BL on both sides of the dryline exhibits complicated structures such as horizontal convective rolls, transverse rolls, and open convective cells.

In the present study, the time-varying radar and Lagrangian analyses have been used as initial and time-dependent lateral inflow boundary conditions to run high-resolution simulations of the dryline and BL. Simulations are conducted with the COllaborative Model for Multiscale Atmospheric Simulation (COMMAS), a 3-dimensional non-hydrostatic community cloud model which includes both short- and long-wave radiation, a force-restore surface physics parameterization, and a cloud microphysics parameterization. The simulations reproduce a nearly north-south oriented dryline with horizontal moisture and temperature gradients similar to observed values, as well as misocyclones, horizontal convective rolls, transverse rolls, and open convective cells. These simulated BL features are similar to analogous structures manifested in the observations and the Lagrangian analyses, although the modeled features are typically of higher spatial and temporal resolutions and may have larger amplitudes than the equivalent observed features. The simulated BL features are internally consistent with the model dynamics, with the high spatial and temporal resolution potentially permitting a better understanding of their evolution processes.

A feature of special interest are the misocyclones which develop and propagate northward along the dryline. Apparently forced in the simulations via longer wavelength undulations in the momentum and thermodynamic fields that are introduced at the lateral inflow boundaries, these perturbations collapse in scale and amplify into intense misovortices as they move downstream. The misocyclones act to modulate the moisture fields along the dryline, bringing larger moisture values westward ahead of and drier air eastward behind the misocyclone relative to its motion. The vertical motion within the deeper moist layer north of the misocyclone enhances simulated cumulus formation along and north of the axis of rotation.

The model simulations are compared to observations to qualitatively evaluate the strengths and weaknesses of the Lagrangian analyses. Aspects of the dryline circulation and other BL features are discussed along with their potential role in the convection initiation process.

Cao, J., Q. Xu, 2011: Computing Rossby potential vorticity in terrain-following coordinates. Monthly Weather Review, 139, 2955-2961.

Cao, J., Q. Xu, 2011: Computing streamfunction and velocity potential in a limited domain. Part II: Numerical methods and test experiments. Adv. Atmos. Sci., 28, 1445-1458.

Built on the integral formulas in Part I, numerical methods are developed for computing velocity potential and streamfunction in a limited domain. When there is no inner boundary (around a data hole) inside the domain, the total solution is the sum of the internally and externally induced parts. For the internally induced part, three numerical schemes (grid-staggering, local-nesting and piecewise continuous integration) are designed to deal with the singularity of the Green's function encountered in numerical calculations. For the externally induced part, by setting the velocity potential (or streamfunction) component to zero, the other component of the solution can be computed in two ways: (1) Solve for the density function from its boundary integral equation and then construct the solution from the boundary integral of the density function. (2) Use the Cauchy integral to construct the solution directly. The boundary integral can be discretized on a uniform grid along the boundary. By using local-nesting (or piecewise continuous integration), the scheme is refined to enhance the discretization accuracy of the boundary integral around each corner point (or along the entire boundary). When the domain is not free of data holes, the total solution contains a data-hole--induced part, and the Cauchy integral method is extended to construct the externally induced solution with irregular external and internal boundaries. An automated algorithm is designed to facilitate the integrations along the irregular external and internal boundaries. Numerical experiments are performed to evaluate the accuracy and efficiency of each scheme relative to others.

Clark, A. J., W. A. Gallus, M. Xue, F. Kong, 2010: Convection-allowing and Convection-parameterizing ensemble forecasts of a mesoscale convective vortex and associated severe weather environment. Weather and Forecasting, 25, 1052-1081.

Clark, A. J., J. S. Kain, D. J. Stensrud, M. Xue, F. Kong, M. C. Coniglio, K. W. Thomas, Y. Wang, K. Brewster, J. Gao, X. Wang, S. J. Weiss, J. Du, 2011: Probabilistic precipitation forecast skill as a function of ensemble size and spatial scale in a convection-allowing ensemble. Monthly Weather Review, 139, 1410-1418.

Available online at http://journals.ametsoc.org/doi/pdf/10.1175/2010MWR3624.1.

Clark, A. J., S. J. Weiss, J. S. Kain, I. L. Jirak, M. C. Coniglio, C. J. Melick, C. Siewert, R. A. Sobash, P. T. Marsh, A. R. Dean, M. Xue, F. Kong, K. W. Thomas, Y. Wang, K. Brewster, J. Gao, X. Wang, J. Du, D. R. Novak, F. E. Barthold, M. J. Bodner, J. J. Levit, C. B. Entwistle, T. L. Jensen, J. C. Correia, 2012: An Overview of the 2010 Hazardous Weather Testbed Experimental Forecast Program Spring Experiment. Bulletin of the American Meteorological Society, 139, 55-74.

The NOAA Hazardous Weather Testbed (HWT) conducts annual spring forecasting experiments organized by the Storm Prediction Center and National Severe Storms Laboratory to test and evaluate emerging scientific concepts and technologies for improved analysis and prediction of hazardous mesoscale weather. A primary goal is to accelerate the transfer of promising new scientific concepts and tools from research to operations through the use of intensive real-time experimental forecasting and evaluation activities conducted during the spring and early summer convective storm period. The 2010 NOAA/HWT Spring Forecasting Experiment (SE2010), conducted 17 May through 18 June, had a broad focus, with emphases on heavy rainfall and aviation weather, through collaboration with the Hydrometeorological Prediction Center (HPC) and the Aviation Weather Center (AWC), respectively. In addition, using the computing resources of the National Institute for Computational Sciences at the University of Tennessee, the Center for Analysis and Prediction of Storms at the University of Oklahoma provided unprecedented real-time conterminous United States (CONUS) forecasts from a multimodel Storm-Scale Ensemble Forecast (SSEF) system with 4-km grid spacing and 26 members and from a 1-km grid spacing configuration of the Weather Research and Forecasting model. Several other organizations provided additional experimental high-resolution model output. This article summarizes the activities, insights, and preliminary findings from SE2010, emphasizing the use of the SSEF system and the successful collaboration with the HPC and AWC.

Cohn, S. J., J. Hallett, J. M. Lewis, 2006: Teaching graduate atmospheric measurement. Bulletin of the American Meteorological Society, 87, 1673-1678.

Coniglio, M. C., J. S. Kain, S. J. Weiss, M. Xue, M. L. Weisman, Z. I. Janjic, 2007: Evaluating storm-scale model output for severe-weather forecasting: The 2007 NOAA HWT Spring Experiment.. Preprints, 4th European Conference on Severe Storms, Trieste, Italy, International Centre for Theoretical Physics, CD-ROM, 03.11.

Coniglio, M. C., J. S. Kain, S. J. Weiss, D. R. Bright, J. J. Levit, M. Xue, M. L. Weisman, Z. I. Janjic, M. Pyle, J. Du, D. J. Stensrud, 2007: Evaluating WRF model output for severe-weather forecasting: The 2007 NOAA HWT Spring Experiment.. Extended Abstracts, 22th Conference on Weather Analysis and Forecasting/18th Conference on Numerical Weather Prediction, Park City, UT, USA, American Meteorological Society, CD-ROM, 11A.2.

Coniglio, M. C., J. S. Kain, S. J. Weiss, D. R. Bright, J. J. Levit, G. W. Carbin, K. W. Thomas, F. Kong, M. Xue, M. L. Weisman, M. E. Pyle, K. L. Elmore, 2008: Evaluation of WRF model output for severe-weather forecasting from the 2008 NOAA Hazardous Weather Testbed Spring Experiment. Preprints, 24th Conference on Severe Local Storms, Savannah, GA, USA, Amer. Meteor. Soc., CD-ROM, 12.4. [Available from Michael C. Coniglio, NSSL, 120 David L. Boren Blvd., Norman, OK, USA, 73072.]

Available online at http://ams.confex.com/ams/24SLS/techprogram/paper_142060.htm.

Coniglio, M. C., K. L. Elmore, J. S. Kain, S. J. Weiss, M. Xue, M. L. Weisman, 2010: Evaluation of WRF model output for severe weather forecasting from the 2008 NOAA Hazardous Weather Testbed Spring Experiment. Weather and Forecasting, 25, 408-427.

This study assesses forecasts of the preconvective and near-storm environments from the convectionallowing
models run for the 2008 National Oceanic and Atmospheric Administration (NOAA) Hazardous
Weather Testbed (HWT) spring experiment. Evaluating the performance of convection-allowing models
(CAMs) is important for encouraging their appropriate use and development for both research and operations.
Systematic errors in theCAMforecasts included a cold bias in mean 2-m and 850-hPa temperatures over most
of the United States and smaller than observed vertical wind shear and 850-hPa moisture over the high plains.
The placement of airmass boundaries was similar in forecasts from the CAMs and the operational North
American Mesoscale (NAM) model that provided the initial and boundary conditions. This correspondence
contributed to similar characteristics for spatial and temporalmean error patterns. However, substantial errors
were found in the CAM forecasts away from airmass boundaries. The result is that the deterministic CAMs
do not predict the environment as well as the NAM. It is suggested that parameterized processes used at
convection-allowing grid lengths, particularly in the boundary layer, may be contributing to these errors.
It is also shown that mean forecasts from an ensemble of CAMs were substantially more accurate than
forecasts from deterministic CAMs. If the improvement seen in the CAM forecasts when going from a deterministic
framework to an ensemble framework is comparable to improvements in mesoscale model forecasts
when going from a deterministic to an ensemble framework, then an ensemble of mesoscale model
forecasts could predict the environment even better than an ensemble of CAMs. Therefore, it is suggested that
the combination of mesoscale (convection parameterizing) andCAMconfigurations is an appropriate avenue
to explore for optimizing the use of limited computer resources for severe weather forecasting applications.

Dawson II, D. T., M. Xue, J. A. Milbrandt, M. K. Yau, 2010: Comparison of Evaporation and Cold Pool Development between Single-Moment and Multimoment Bulk Microphysics Schemes in Idealized Simulations of Tornadic Thunderstorms. Monthly Weather Review, 138, .

Idealized simulations of the 3 May 1999 Oklahoma tornadic supercell storms are conducted at various horizontal grid spacings ranging from 1 km to 250 m, using a sounding extracted from a prior 3-km grid spacing real-data simulation. A sophisticated multimoment bulk microphysics parameterization scheme capable of predicting up to three moments of the particle or drop size distribution (DSD) for several liquid and ice hydrometeor species is evaluated and compared with traditional single-moment schemes. The emphasis is placed on the impact of microphysics, specifically rain evaporation and size sorting, on cold pool strength and structure, and on the overall reflectivity structure of the simulated storms. It is shown through microphysics budget analyses and examination of specific processes within the low-level downdraft regions that the multimoment scheme has important advantages, which lead to a weaker and smaller cold pool and better reflectivity structure, particularly in the forward-flank region of the simulated supercells. Specifically, the improved treatment of evaporation and size sorting, and their effects on the predicted rain DSDs by the multimoment scheme helps to control the cold bias often found in the simulations using typical single-moment schemes. The multimoment results are more consistent with observed (from both fixed and mobile mesonet platforms) thermodynamic conditions within the cold pools of the discrete supercells of the 3 May 1999 outbreak.

Dodson, A., S. Van Cooten, K. Howard, J. Zhang, X. Xu, 2008: Assessing Vertical Profiles of Reflectivity (VPR's) To Detect Extreme Rainfall: Implications for Flash Flood Monitoring and Prediction. Preprints, 22nd Conference on Hydrology- Session 1, Weather To Climate Scale Hydrological Forecasting, New Orleans, LA, USA, AMS, CD-ROM, 1.5.

Tropical Storm Barry moved across the state of Florida from Tampa to Jacksonville on June 2 and then became extratropical as it moved northeast along the coastlines of Georgia, South Carolina and North Carolina from June 3 to June 4, 2007. Rainfall reports from gauges located within the surveillance areas of the Wakefield, Virginia (AKQ), Raleigh-Durham, North Carolina (RDU), and Morehead City, North Carolina (MHX), NEXRAD sites were collected and processed to document hourly rainfall rates associated with the system. In addition to the gauge data, atmospheric soundings from six area upper air observing sites were archived and analyzed to determine the response of atmospheric conditions, specifically freezing level, precipitable water, and atmospheric instability, as the system affected the region.

NOAA's National Severe Storms Laboratory (NSSL) Q2 System (www. nmq.nssl.noaa.gov) produces Vertical Profiles of Reflectivity (VPR) every five minutes for each continental United States (CONUS) NEXRAD site. These VPRs are used in the production of five-minute multi-sensor Quantitative Precipitation Estimates (QPE) to provide constantly updated relationships between radar reflectivity factor, Z, and rain rate, R (Z-R). VPRs were archived for June 3 and 4 for AKQ, RDU, and MHX. The VPRs were analyzed to quantify radar reflectivity trends over the course of the storm event. These trends were then correlated with rainfall rates, atmospheric sounding data, and surface observations, to investigate the characteristics of the VPRs associated with the highest rainfall rates. Results of this analysis indicate VPRs associated with the highest hourly rainfall rates observed with the storm system occurred as VPRs lost a concentrated area of high reflectivities around the atmospheric freezing level. Additionally, the gradient of radar reflectivities above and below this dissipating high reflectivity area diminished. Atmospheric soundings and surface map analysis indicated the air mass characteristics were acquiring tropical characteristics as surface dew points and atmospheric water content were increasing, wind directions transitioned from westerly to an easterly fetch off the Atlantic Ocean, and the atmospheric freezing level was rising. As the storm system moved away from the Carolinas, VPRs began to regain a concentrated area of high reflectivities around the atmospheric freezing level and the gradient of radar reflectivities began to increase once again above and below the area of higher reflectivities.

To quantify the implications of these VPR characteristics on the accuracy of the Q2 system's five-minute multi-sensor Quantitative Precipitation Estimates (QPE), the Q2 statistical verification tools were used to evaluate the performance of the system during the periods of the most intense rainfall. The Q2 system has recently implemented a tropical rain Z-R when VPRs and atmospheric sounding data meet criteria which have been identified by NSSL scientists as common factors in intense rainfall events. The VPRs observed through this June, 2007 storm event, were consistent with their findings. Results of this assessment show the Q2 tropical Z-R relationship produced highly accurate precipitation estimates which are available at a 1 km grid mesh resolution every five minutes. Additionally, the dynamic VPR system captured the air mass changes which occurred during the event. This feature provides improved information on a storm's environment to determine appropriate radar Z-R adjustments. This case demonstrates the ability to increase the accuracy of precipitation estimates especially in ungauged locations which can improve NOAA and our nation's flash flood monitoring and prediction programs.

Available online at http://ams.confex.com/ams/88Annual/techprogram/paper_135143.htm.

Elmore, K. L., H. D. Reeves, T. M. Smith, K. L. Ortega, 2011: A winter hydrometeor classification algorithm. Preprints, 9th Conference on Artificial Intelligence, Seattle, WA, USA, American Meteorological Society, J6.1.

Over the past two winter seasons, the National Severe Storms Laboratory (NSSL) has collected observations of precipitation type from anonymous, volunteer public observers though the Winter Precipitation Identification Near the Ground (W-PING) project. To date, nearly 3,000 observations of winter precipitation type have been logged through a web based form hosted by the NSSL. Analysis of these reports shows that the current hydrometeor classification algorithm (HCA), which was developed with warm season convection in mind, performs poorly when confronted with winter precipitation. This project proposes to use these data, along with new capabilities within the warning decision support system integrated information (WDSSII) system, to build a data driven winter surface precipitation classifier and implement it within WDSSII.
The WDSSII system has the ability to extract vertical profiles of environmental data from rapid update cycle (RUC) model grids at designated times and locations. In addition, these profiles may be tilted at angles from the vertical to take into account the fact that precipitation source and generating regions are upwind from the surface observation location. Environmental data is on a rectilinear grid, but WDSSII can now interpolate the rectilinear data onto the spherical grid used by radar data. Hence, the radar range gates and the environmental data can be colocated.

With these capabilities it is possible to construct a complete set of radar and model based environmental attributes associated with any given observation within the W-PING data base. With these capabilities also comes the ability to build a hybrid winter surface precipitation classifier using a mixture of rule-based and data driven, statistically principled methods. The algorithm will generate classifications for surface precipitation type only; it will not create classifications for precipitation aloft because there are no verification data aloft.

The resulting classifier is evaluated statistically through various performance scores such as POD, FAR and CSI along with various other skill scores, such as the Heidke and Peirce skill scores. As envisioned, the classifier will define at least four basic categories: liquid, freezing, frozen and none. The frozen category may be divided into two subcategories: “snow” and “not snow,” depending upon the quality and quantity of appropriate W-PING data.

Available online at http://ams.confex.com/ams/91Annual/webprogram/Paper185800.html.

Fast, J. D., R. K. Newsom, K. J. Allwine, Q. Xu, P. Zhang, J. H. Copeland, J. Sun, 2007: Using NEXRAD wind retrievals as input to atmospheric dispersion models. Extended Abstracts, Seventh Symposium on the Urban Environment, San Diego, CA, USA, Amer. Meteor. Soc., 8.2.

Available online at http://ams.confex.com/ams/7Coastal7Urban/techprogram/paper_127244.htm.

Fast, J. D., R. K. Newsom, K. J. Allwine, Q. Xu, P. Zhang, J. Copeland, J. Sun, 2008: An evaluation of two NEXRAD wind retrieval methedologies and their use in atmospheric dispersion models. Journal of Applied Meteorology and Climatology, 47, 2351-2371.

Fierro, A. O., L. Leslie, E. Mansell, J. Straka, D. MacGorman, C. Ziegler, 2007: A High-resolution Simulation of Microphysics and Electrification in an Idealized Hurricane-like Vortex. Meteorology and Atmospheric Physics, 98, 13-33.

Cloud-to-ground (CG) lightning bursts in the eyewall of mature tropical cyclones (TCs) are believed to be good indicators of imminent intensification of these systems. While numerous well-documented observational cases exist in the literature, no modeling studies of the electrification processes within TCs have previously been conducted. At present, little is known about the evolution of charge regions and lightning activity in mature TCs. Towards this goal, a numerical cloud model featuring a 12-class bulk microphysics scheme with electrification and lightning processes is utilized to investigate the evolution of the microphysics fields and subsequent electrical activity in an idealized hurricane-like vortex.

Preliminary results show that the highest total lightning flash rates (CG plus intracloud) are primarily found within the eyewall where updraft speeds tend to be larger than elsewhere in the TC, though rarely exceeding 10 m s^-1. Smaller total flash rates are also found within the strongest cells forming the outer bands, where updraft speeds sometimes reach 15 m s^-1. As expected, these two regions of the storm are generally characterized by moderate total graupel mixing ratio (> 0.5 g kg^-1) and moderate cloud water content (> 0.2 g m^-3). When the model uses the Saunders and Peck non-inductive (NI) charging scheme and moderate inductive charging settings, the inner eyewall region exhibits a complex charge structure. However, the charge regions involved in lightning can be described as a normal tripole charge structure in the eyewall, while a normal dipole is observed in the outer eyewall stratiform region and in the strongest cells forming the outer rainbands. The charges forming the normal dipole in the outer eyewall are generated within the eyewall via NI charging in the mixed-phase region at mid-levels (near the -10 deg C isotherm) and later, are ejected radially outward by the storm’s intense circulation.

Gao, J., M. Xue, S. Lee, A. Shapiro, Q. Xu, K. K. Droegemeier, 2006: A three-dimensional variational single-doppler velocity retrieval method with simple conservation equation constraint. Meteorol. Atmos. Phys., 94, 11-26.

James, K. A., D. J. Stensrud, N. Yussouf, 2009: Value of Real-Time Vegetation Fraction to Forecasts of Severe Convection in High-Resolution Models. Weather and Forecasting, 24, 187-210.

Near-real-time values of vegetation fraction are incorporated into a 2-km nested version of the Advanced Research Weather Research and Forecasting (ARW) model and compared to forecasts from a control run that uses climatological values of vegetation fraction for eight severe weather events during 2004. It is hypothesized that an improved partitioning of surface sensible and latent heat fluxes occurs when incorporating near-real-time values of the vegetation fraction into models, which may result in improved forecasts of the low-level environmental conditions that support convection and perhaps even lead to improved explicit convective forecasts. Five of the severe weather events occur in association with weak synoptic-scale forcing, while three of the events occur in association with moderate or strong synoptic-scale forcing.

Results show that using the near-real-time values of the vegetation fraction alters the values and structure of low-level temperature and dewpoint temperature fields compared to the forecasts using climatological
vegetation fractions. The environmental forecasts that result from using the real-time vegetation fraction are more thermodynamically supportive of convection, including stronger and deeper frontogenetic circulations, and statistically significant improvements of most unstable CAPE forecasts compared to the control run. However, despite the improved environmental forecasts, the explicit convective forecasts using real-time vegetation fractions show little to no improvement over the control forecasts. The convective forecasts are generally poor under weak synoptic-scale forcing and generally good under strong synoptic-scale forcing. These results suggest that operational forecasters can best use high-resolution forecasts to help diagnose environmental conditions within an ingredients-based forecasting approach.

Kain, J. S., M. Xue, M. C. Coniglio, S. J. Weiss, F. Kong, T. L. Jensen, B. G. Brown, J. Gao, K. Brewster, K. W. Thomas, Y. Wang, C. S. Schwartz, J. J. Levit, 2010: Assessing advances in the assimilation of radar data within a collaborative forecasting-research environment. Weather and Forecasting, 25, 1510-1521.

The impacts of assimilating radar data and other mesoscale observations in real-time, convection-allowing model forecasts were evaluated during the spring seasons of 2008 and 2009 as part of the Hazardous Weather Test Bed Spring Experiment activities. In tests of a prototype continental U.S.-scale forecast system, focusing primarily on regions with active deep convection at the initial time, assimilation of these observations had a positive impact. Daily interrogation of output by teams of modelers, forecasters, and verification experts provided additional insights into the value-added characteristics of the unique assimilation forecasts. This evaluation revealed that the positive effects of the assimilation were greatest during the first 3–6 h of each forecast, appeared to be most pronounced with larger convective systems, and may have been related to a phase lag that sometimes developed when the convective-scale information was not assimilated. These preliminary results are currently being evaluated further using advanced objective verification techniques.

Kaplan, M., C. Adaniya, P. Marzette, K. King, S. Underwood, J. Lewis, 2009: The role of upstream mid-tropospheric circulations in Sierra Nevada leeside (spillover precipitation): Part II: Secondary atmospheric river accompanying a mid-level jet. J. Hydrometeor., 10, 1327-1354.

Kaplan, M. L., R. K. Vellore, J. M. Lewis, M. Young, 2011: The role of unbalanced mesoscale circulations in dust storms. Journal of Geophysical Research - D: Atmospheres, 116, 218-247.

In this study, two dust storms in northwestern Nevada (February 2002 and April 2004) are investigated through the use of Weather Research and Forecasting (WRF) model simulations. The focus of the study is twofold: (1) Examination of dynamic processes on the meso‐b scale for both cases, and (2) analysis of extreme upper‐air cooling prior to storm formation and the development of a nearly discontinuous gust front in the 2002 case that could not be validated in an earlier synoptic‐scale study. Results of the simulations suggest that the driving mechanism for dust storm dynamics derives from the breakdown and subsequent balance between the advection of geostrophic wind and total wind in the exit region of the polar jet. In this process, the deviation from quasi‐geostrophic (Q‐G) balance creates a plume of ascent along and to the right of the jet’s exit region. The cold pool generation in the mid‐lower troposphere in consequence of this adjustment sets up the kinetic energy in the planetary boundary layer and creates a forward leaning (slope from north to south) cold front under the jet exit region. Surface heating is coupled with this frontal structure, and rapid surface pressure falls (rises) occur initially (later) in response to diabatic (adiabatic) processes. The adjustments occur at fast time scales, scales that are radically different from those in studies that followed the Q‐G tenets of the Danielsen paradigm. The results of this study indicate that meso‐b scale features associated with subgeostrophy in the exit region of the curved jet aloft and associated thermal wind imbalance (700–500 hPa) lead to significant velocity divergence aloft. Mass/momentum adjustments and the associated cooling strengthen the baroclinic zone aloft. The restoration to thermal wind balance accompanying this cooling resulted in a narrow zone of surface pressure rise and strong low‐level isallobaric winds. The turbulent momentum for dust ablation comes

Kong, F., M. XUE, D. R. Bright, M. C. Coniglio, K. W. Thomas, Y. Wang, D. Weber, J. S. Kain, S. J. Weiss, J. Du, 2007: Preliminary analysis on the real-time storm-scale ensemble forecasts produced as a part of the NOAA Hazardous Weather Testbed 2007 Spring Experiment.. Preprints, Preprints, 22th Conference on Weather Analysis and Forecasting/18th Conference on Numerical Weather Prediction, Park City, UT, USA, Amer. Meteor. Soc, CD-ROM, 3B.2.

Kong, F., M. Xue, D. R. Bright, M. C. Coniglio, K. W. Thomas, Y. Wang, D. B. Weber, J. S. Kain, S. J. Weiss, J. Du, 2007: Preliminary analysis on the real-time storm-scale ensemble forecasts produced as a part of the NOAA Hazardous Weather Testbed 2007 Spring Experiment. Preprints, 22th Conference on Weather Analysis and Forecasting/18th Conference on Numerical Weather Prediction, Park City, UT, USA, Amer. Meteor. Soc., CD-ROM, 3B.2. [Available from Fanyou Kong, CAPS, 120 David L. Boren Blvd., Norman, OK, USA, 73072.]

A real-time storm-scale WRF-ARW-based ensemble forecast system at 4-km resolution is being developed at CAPS and will be run daily for 33 hours as part of the NOAA Hazardous Weather Testbed (HWT) 2007 Spring Experiment, for a domain covering the eastern 2/3 of the continental U.S. This pilot system consists of ten hybrid perturbation members that consist of a combination of perturbed initial conditions and various microphysics and PBL physics parameterization schemes. The design considerations and the scientific questions that the system intends to address will be presented and discussed.

In addition to traditional ensemble products widely used in large-scale and mesoscale ensemble forecasting systems, such as the mean, spread, and probability of selected forecast fields, emphases are given to the generation and assessment of products specific to storm-scale, cloud-resolving ensemble forecasts. Such products include but are not limited to: probability of storm type (e.g., linear vs. cellular), large hail probability, icing potential (high super-cooled water content probability), damaging wind gusts at surface, reflectivity exceedance, updraft rotation, and supercell thunderstorm detection in the form of probability or joint probability for Supercell Composite Parameter, Significant Tornado Parameter, Supercell Detection Index, and Updraft Helicity. Many of these products are created in real time through existing capabilities in the SPC version of the N-AWIPS system for the use and evaluation by researchers and operational forecasters during the experiment. The statistical consistency of the ensemble system, in terms of spread-error relation, is assessed using the two-months of data after the experiment. The performance of the ensemble forecasts, in terms of quantitative skill scores, is compared with the NCEP operational SREF and 12 km NAM forecasts, and a CAPS 2-km WRF forecast over the same domain and period. Skill scores for sub-groups of the ensemble will be examined to assess the effectiveness of initial condition and physics perturbations.

Available online at http://ams.confex.com/ams/pdfpapers/124667.pdf.

Kong, F., M. Xue, K. W. Thomas, Y. Wang, J. S. Kain, S. J. Weiss, D. R. Bright, J. Du, K. K. Droegemeier, 2008: Real-Time Storm-Scale Ensemble Forecast 2008 Spring Experiment. Preprints, 24th Conference on Severe Local Storms, Savannah, GA, USA, Amer. Meteor. Soc., CD-ROM, 12.3. [Available from Fanyou Kong, CAPS, 120 David L. Boren Blvd, Norman, OK, USA, 73072.]

Available online at http://ams.confex.com/ams/24SLS/techprogram/paper_141827.htm.

Kong, F., M. Xue, K. W. Thomas, Y. Wang, K. A. Brewster, J. Gao, K. K. Droegemeier, J. S. Kain, S. J. Weiss, D. R. Bright, M. C. Coniglio, J. Du, 2009: A real-time storm-scale ensemble forecast system: 2009 Spring Experiment. Preprints, 23rd Conference on Weather Analysis and Forecasting/19th Conference on Numerical Weather Prediction, Omaha, NE, USA, Amer. Meteor. Soc., CD-ROM, 16A.3. [Available from Fanyou Kong, CAPS, 120 David L. Boren Blvd, Norman, OK, USA, 73072.]

Available online at http://ams.confex.com/ams/23WAF19NWP/techprogram/paper_154118.htm.

Kuhlman, K. M., C. L. Ziegler, E. R. Mansell, D. R. MacGorman, J. M. Straka, 2006: Numerically Simulated Electrification and Lightning of the 29 June 2000 STEPS Supercell Storm. Monthly Weather Review, 134, 2734-2757.

A three-dimensional dynamic cloud model incorporating airflow dynamics, microphysics, and thunderstorm electrification mechanisms is used to simulate the first 3 h of the 29 June 2000 supercell from the Severe Thunderstorm Electrification and Precipitation Study (STEPS). The 29 June storm produced large flash rates, predominately positive cloud-to-ground lightning, large hail, and an F1 tornado. Four different simulations of the storm are made, each one using a different noninductive (NI) charging parameterization. The charge structure, and thus lightning polarity, of the simulated storm is sensitive to the treatment of cloud water dependence in the different NI charging schemes. The results from the simulations are compared with observations from STEPS, including balloon-borne electric field meter soundings and flash locations from the Lightning Mapping Array. For two of the parameterizations, the observed “inverted” tripolar charge structure is well approximated by the model. The polarity of the ground flashes is opposite that of the lowest charge region of the inverted tripole in both the observed storm and the simulations. Total flash rate is well correlated with graupel volume, updraft volume, and updraft mass flux. However, there is little correlation between total flash rate and maximum updraft speed. Based on the correlations found in both the observed and simulated storm, the total flash rate appears to be most representative of overall storm intensity.

Available online at http://www.ametsoc.org.

Kuhlman, K., D. MacGorman, M. Biggerstaff, W. D. Rust, T. Schuur, C. Ziegler, P. Krehbiel, 2006: Lightning and radar observatons of the 29 May 2004 supercell during TELEX. Preprints, 2nd Conference on Meteorological Applications of Lightning Data, Atlanta, GA, USA, American Meteorological Society, 3.3.

Kuhlman, K. M., E. R. Mansell, C. L. Ziegler, M. I. Biggerstaff, D. R. MacGorman, D. C. Dowell, 2008: EnKF data assimilation and dual-Doppler analysis of the 29 May 2004 Geary, Oklahoma supercell. Proc. 24th Conference on Severe Local Storms, Savannah, GA, USA, American Meteorological Society, P5.1.

On 29 May 2004, a long-track supercell storm moved across Oklahoma producing multiple tornadoes and numerous reports of large hail. Two mobile, C-band, Doppler (SMART-R) radars collected data in 2.5 min volume scans almost continuously for more than three hours. Dual-Doppler analyses were completed for select times using a1 km grid spacing and a 2-pass Barnes objective analysis in the interpolation of radial velocities and reflectivity to a Cartesian grid following Majcen et al (2008).

The focus of the radar data assimilation for this study is to retrieve the state of the storm rather than to develop forecast applications. For this purpose, the ensemble Kalman filter (EnKF) technique is used to assimilate reflectivity and/or radial velocity data into the model from SMART radar at approximately five minute intervals. Comparisons of the simulations employing EnKF to a simulation without data assimilation and to the dual-Doppler syntheses at various times of the storm's life-cycle will be presented. These results will be used to quantify the agreement between the simulation and the observations providing background such that future studies may use the simulations in order to to retrieve unobserved fields.

Available online at http://ams.confex.com/ams/24SLS/techprogram/paper_142031.htm.

Kuhlman, K. M., D. R. MacGorman, E. R. Mansell, C. L. Ziegler, M. I. Biggerstaff, 2010: A SIMULATION OF ELECTRIFICATION AND LIGHTNING IN A SUPERCELL STORM USING ENKF TO ASSIMILATE DOPPLER RADAR OBSERVATIONS. Proc. International Lightning Meteorology Conferance, Orlando, FL, USA, Vaisala, 1-8.

Available online at http://www.vaisala.com/Vaisala%20Documents/Scientific%20papers/14.Kuhlman,%20MacGorman,%20Mansell.pdf.

Kuhlman, K. M., E. R. Mansell, D. R. MacGorman, C. L. Ziegler, M. I. Biggerstaff, 2010: Electrification and Lightning in Simulations of the 29 May 2004 Geary, OK Storm Using EnKF Data Assimilation. Extended Abstracts, 25th Conference on Severe Local Storms, Denver, CO, USA, American Meteorological Society, 13A.7.

On 29 May 2004, a line of convective cells formed along a dryline near Elk City, OK; one intensified to a heavy-precipitation (HP) supercell north of Weatherford, OK as it moved into the TELEX domain (MacGorman et al. 2008). The data set established through this field campaign provides an excellent opportunity for using Ensemble Kalman Filter (EnKF) assimilation of radar data to produce a storm simulation having characteristics similar to those of the observed storm, so that we can examine hypotheses concerning the storm's electrification and lightning.

The Collaborative Model for Multiscale Atmospheric Simulation (COMMAS) was used to produce the simulations. Radial velocity and reflectivity data from a single mobile doppler radar were assimilated into the the COMMAS model using two-moment microphysics, including seven hydrometeor categories, and parameterizations for electrification and lightning with a horizontally homogeneous base state. The simulated precipitation and wind fields were similar to those of the observed storm. Simulated lightning flash rates were very large, as was observed, and the distribution of charge in the main body of the storm revealed in the simulation details the lightning dependence on storm kinematics that could not be directly observed. The simulation produced the observed lightning holes and the high-altitude lightning seen in the observations. However, the simulation failed to produce the observed lightning initiations (or even lightning channels) in the distant downstream anvil; instead, the simulated lightning was confined to the main body of the storm.

Lakshmivarahan, S., J. M. Lewis, 2010: Forward Sensitivity Approach to Dynamic Data Assimilation. Advances in Meteorology, 2010, 1-13.

The least squares fit of observations with known error variance to a strong-constraint dynamical model has been developed through use of the time evolution of sensitivity functions – the derivatives of model output with respect to the elements of control (initial conditions, boundary conditions, and physical/empirical parameters). Model error is assumed to stem from incorrect specification of the control elements. The optimal corrections to control are found through solution to an inverse problem. Duality between this method and the standard 4D-Var assimilation using adjoint equations has been proved. The paper ends with an illustrative example based on a simplified version of turbulent heat transfer at the sea/air interface.

Lewis, J., R. Maddox, C. Crisp, 2006: Architect of severe storms forecasting: Colonel Robert C. Miller. Bulletin of the American Meteorological Society, 87, .

Lewis, J. M., 2007: Use of a mixed-layer model to investigate problems in operational prediction of return flow. Monthly Weather Review, 135, 2610-2628.

Lewis, J. M., 2007: A Forecaster's Story: Robert H. Johns. Electronic Journal of Severe Storm Meteorology, 2, 1-19.

The stages in the life of a severe storms forecaster, Robert H. Johns, are reconstructed from information in a series of interviews with him. The traditional interview format, question-and-answer mode, has been converted to a first-person narrative that leads to a more-continuous train of thought.
The storyline begins by describing Johns’ entrainment into meteorology as a youngster. By virtue of his contact and conversations with farmers in rural Indiana, he became interested in weather’s impact on the farmers and their crop yields. Early stimulation also came from a challenging weather project in the 6th grade and reading George Stewart’s novel Storm. From these experiences, Bob Johns decided to pursue a science career in service to society. This service took the form of work as a weather forecaster for the United States Weather Bureau (USWB)/National Weather Service (NWS).
The arduous path to severe storms forecaster is traced by highlighting his youthful experiences, his academic training, and the stepwise progression from student trainee to lead forecaster at the Severe Local Storms (SELS) unit of the USWB/NWS.

Available online at http://ejssm.org/ojs/index.php/ejssm/article/view/29/32.

Lewis, J. M., S. Lakshmivarahan, 2008: Sasaki's Pivotal Contribution: Calculus of Variations Applied to Weather Map Analysis. Monthly Weather Review, 136, 3553-3567.

Yoshikazu Sasaki developed a variational method of data assimilation, a cornerstone of modern-day analysis and prediction in meteorology. Fundamentally, he formulated data assimilation as a constrained minimization problem with equality constraints. The generation of this idea is tracked by analyzing his education and research at the University of Tokyo in the immediate post-WWII period. Despite austere circumstances — including limited financial support for education, poor living conditions, and a lack of educational resources — Sasaki was highly motivated and overcame these obstacles on his path to developing this innovative method of weather map analysis. We follow the stages of his intellectual development where information comes from access to his early publications, oral histories, and letters of reminiscence.
It has been argued that Sasaki’s unique contribution to meteorological data assimilation stems from his deterministic view of the problem – a view founded on the principles of variational mechanics. Sasaki’s approach to the problem is compared and contrasted with the stochastic view that was pioneered by Arnt Eliassen. Both of these optimal approaches are viewed in the context of the pragmatic/operational objective analysis schemes that were developed in the 1950s – 1960s. Finally, current-day methods, 3D-Var and 4D-Var, are linked to the optimal methods of Eliassen and Sasaki.

Lewis, J. M., 2008: Book Review: The Emergence of Numerical Weather Prediction: Richardson's Dream. Bulletin of the American Meteorological Society, 89, 1178-1179.

Lewis, J. M., S. Lakshmivarahan, S. Dhall, 2006: Dynamic Data Assimilation: A Least Squares Approach. Cambridge University Press, 654 pp.

NOAA Outstanding Publication Award in 2006

Lewis, J., 2008: Smagorinsky's GFDL; Building the team. Bulletin of the American Meteorological Society, 89, 1339-1353.

Joseph Smagorinsky (1924 - 2005) was a forceful and powerful figure in meteorology during the last half of the twentieth century. He served as director of the Geophysical Fluid Dynamics Laboratory (GFDL) for nearly thirty years (1955 - 1983); and during his tenure as director, this organization substantially contributed to advances in weather forecasting and climate diagnostics/prediction. The purpose of this research is to explore Smagorinsky’s philosophy of science and style of management that were central to the success of GFDL. Information comes from his early scientific publications, personal letters and notes in the possession of his family, several oral histories, and letters of reminiscence from scientists who worked within and outside GFDL.
The principal results of the study are: (1) early inspiration and development of Smagorinsky’s scientific philosophy came from his contact with Jule Charney and Harry Wexler, (2) his doctoral dissertation ideally prepared him for appointment as director of the U. S. Weather Bureau’s long-range numerical prediction project in 1955 — the General Circulation Research Section [later renamed GFDL], (3) he masterfully assembled a team of researchers to attack the challenging problem of general circulation modeling, and (4) he exhibited an authoritarian style of rule tempered by protection of the scientists from disrupting outside influence while celebrating the elitism and esprit de corps that characterized the laboratory.
A list of Smagorinsky’s management principles is found in the Appendix. Several of these tenets have been interspersed in the main body of the paper in support of actions he took at GFDL.

Lewis, J. M., 2009: Sasaki's Pathway to Deterministic Data Assimilation. Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications, S. K. Park, L. Xu, Ed(s)., Springer, 1-19.

Yoshikazu Sasaki developed the variational method of data assimilation, a cornerstone of modern-day analysis and prediction in meteorology. The generation of this idea is tracked by analyzing his education at the University of Tokyo in the immediate post-WWII period. Despite austere circumstances — including limited financial support for education, poor living conditions, and a lack of educational resources — Sasaki was highly motivated and overcame these obstacles on his path to developing this innovative method of weather map analysis. We follow the stages of his intellectual development where information comes from access to his early publications, oral histories, letters of reminiscence, and biographical data from the University of Tokyo and the University of Oklahoma. Based on this information, key steps in the development of his idea were: (1) a passion for science in his youth, (2) an intellectually stimulating undergraduate education in physics, mathematics, and geophysics, (3) a fascination with the theory of variational mechanics, and (4) a ‘bridge to America’ and the exciting new developments in numerical weather prediction (NWP).
A comparison is made between Sasaki’s method and Optimal Interpolation (OI), a contemporary data assimilation strategy based on the work of Arnt Eliassen and Lev Gandin. Finally, a biographical sketch of Sasaki including his scientific genealogy is found in the appendix.

Lewis, J. M., D. Martin, R. Rabin, H. Moosmuller, 2010: Suomi: Pragmatic Visionary. Bulletin of the American Meteorological Society, 91, 561-577.

The steps on Verner Suomi's path to becoming a research scientist are examined. We argue that his research style – his natural interests in science and engineering, and his methodology in pursuing answers to scientific questions – was developed in his youth on the Iron Range of northeastern Minnesota, as an instructor in the cadet program at the University of Chicago (U of C) during World War II and as a fledgling academician at University of Wisconsin - Madison. We examine several of his early experiments that serve to identify his style. The principal results of the study are: 1) despite austere living conditions on the Iron Range during the Great Depression, Suomi benefitted from excellent industrial arts courses at Eveleth High School; 2) with his gift for designing instruments, his more practical approach to scientific investigation flourished in the company of world-class scientific thinkers at U of C; 3) his dissertation on the heat budget over a cornfield in the mid-1950s served as a springboard for studying the Earth-atmosphere energy balances in the space-age environment of the late 1950s; and 4) his design of radiometers – the so-called ping-pong radiometer and its sequel, the hemispheric bolometer – flew aboard Explorer VI and VII in the late 1950s, and analysis of the radiances from these instruments led to the first accurate estimate of the Earth's mean albedo.

Lewis, J. M., M. L. Kaplan, R. K. Vellore, R. M. Rabin, J. Hallett, S. A. Cohn, 2011: Dust Storm over the Black Rock Desert: Larger-scale Dynamic Signatures. Journal of Geophysical Research - D: Atmospheres, 116, 1-23.

A dust storm that originated over the Black Rock Desert (BRD) of northwestern Nevada is investigated. Our primary goal is to more clearly understand the sequence of dynamical processes that generate surface winds responsible for entraining dust from this desert. In addition to reliance on conventional surface and upper-air observations, we make use of reanalysis datasets (NCAR/NCEP and NARR) — blends of primitive equation model forecasts and observations. From these datasets, we obtain the evolution of vertical motion patterns and ageostrophic motions associated with the event. In contrast to earlier studies that have emphasized the importance of indirect transverse circulations about an upper-level jet streak, our results indicate that the transition from indirect to direct circulation across the exit region of upper-level jet streak is central to creation of low-level winds that ablate dust from the desert. It is further argued that the transition of vertical circulation patterns is in response to adjustments to geostrophic imbalance — where the adjustment time scale is the order of 6-9 h. Although unproven, we suggest that precedent rainfall over the alkali desert two weeks prior to the event was instrumental in lowering the bulk density of sediments and thereby improved the chances for dust ablation. We comprehensively compare/contrast our results with those of earlier investigators, and we present an alternative view of key dynamical signatures in atmospheric flow that portend the likelihood of dust storms over the western United States.

Liang, X. Z., M. Xu, K. E. Kunkel, G. A. Grell, J. S. Kain, 2007: Regional Climate Model Simulation of U.S.–Mexico Summer Precipitation Using the Optimal Ensemble of Two Cumulus Parameterizations. Journal of Climate, 20, 5201-5207.

Liu, S., M. Xue, Q. Xu, 2007: Using wavelet analysis to detect tornadoes from doppler radar radial-velocity observations. Journal of Atmospheric and Oceanic Technology, 24, 344-359.

Liu, L., Q. Xu, P. Zhang, S. Liu, 2008: Automated Detection of Contaminated Radar Image Pixels in Mountain Areas. Adv. Atmos. Sci., 25, 778-790.

In mountain areas, radar observations are often contaminated (1) by echoes from high-speed moving vehicles and (2) by point-wise ground clutter under either normal propagation (NP) or anomalous propagation (AP) conditions. Level II data are collected from KMTX (Salt Lake City, Utah) radar to analyze these two types of contamination in the mountain area around the Great Salt Lake. Human experts provide the ``ground truth" for possible contamination of either type on each individual pixel. Common features are then extracted for contaminated pixels of each type. For example, pixels contaminated by echoes from high-speed moving vehicles are characterized by large radial velocity and spectrum width. Echoes from a moving train tend to have larger velocity and reflectivity but smaller spectrum width than those from moving vehicles on highways. These contaminated pixels are only seen in areas of large terrain gradient (in the radial direction along the radar beam). The same is true for the second type of contamination - point-wise ground clutters. Six quality control (QC) parameters are selected to quantify the extracted features. Histograms are computed for each QC parameter and grouped for contaminated pixels of each type and also for non-contaminated pixels. Based on the computed histograms, a fuzzy logical algorithm is developed for automated detection of contaminated pixels. The algorithm is tested with KMTX radar data under different (clear and rainy) weather conditions.

Liu, S., G. DiMego, K. V. Kumar, D. Keyser, S. Guan, Q. Xu, K. Nai, P. Zhang, L. Liu, J. Zhang, X. Xu, K. Howard, 2009: WSR-88D radar data processing at NCEP. Extended Abstracts, 34rd Conference on Radar Meteorology, Williamsburg, VA, USA, AMS, CD-ROM, 14.2.

Available online at http://ams.confex.com/ams/34Radar/techprogram/paper_156011.htm.

Lu, H., Q. Xu, 2009: Trade-offs between observation accuracy and resolutions in configuring phased-array radar velocity scans for ensemble-based storm-scale data assimilation. Journal of Applied Meteorology and Climatology, 48, 1230-1244.

Assimilation experiments are carried out with simulated radar radial-velocity observations to examine the impacts of observation accuracy and resolutions on storm-scale wind assimilation with an ensemble square root filter (EnSRF) on a storm-resolving grid (Δx = 2 km). In this EnSRF, the background covariance is estimated from an ensemble of 40 imperfect-model predictions. The observation error includes both measurement error and representativeness error, and the error variance is estimated from the simulated observations against the simulated “truth.” The results show that the analysis is not significantly improved when the measurement error is overly reduced (from 4 to 1 m s−1) and becomes smaller than the representativeness error. The analysis can be improved by properly coarsening the observation resolution (to 2 km in the radial direction) with an increase in measurement accuracy and further improved by properly enhancing the temporal resolution of radar volume scans (from every 5 to 2 or 1 min) with a decrease in measurement accuracy. There can be an optimal balance or trade-off between measurement accuracy and resolutions (in space and time) for configuring radar scans, especially phased-array radar scans, to improve storm-scale radar wind analysis and assimilation.

Lu, H., Q. Xu, M. Yao, S. Gao, 2011: Time-expanded sampling for ensemble-based filters: assimilation experiments with real radar observations. Advances in Atmospheric Sciences, 28, 743-757.

By sampling perturbed state vectors from each ensemble prediction run at properly selected time levels in the vicinity of the analysis time, the recently proposed time-expanded sampling approach can enlarge the ensemble size without increasing the number of prediction runs and, hence, can reduce the computational cost of an ensemble-based filter. In this study, this approach is tested for the first time with real radar data from a tornadic thunderstorm. In particular, four assimilation experiments were performed to test the time-expanded sampling method against the conventional ensemble sampling method used by ensemble-based filters. In these experiments, the ensemble square-root filter (EnSRF) was used with 45 ensemble members generated by the time-expanded sampling and conventional sampling from 15 and 45 prediction runs, respectively, and quality-controlled radar data were compressed into super-observations with properly reduced spatial resolutions to improve the EnSRF performances. The results show that the time-expanded sampling approach not only can reduce the computational cost but also can improve the accuracy of the analysis, especially when the ensemble size is severely limited due to computational constraints for real-radar data assimilation. These potential merits are consistent with those previously demonstrated by assimilation experiments with simulated data.

MacGorman, D. R., W. D. Rust, T. J. Schuur, M. I. Biggerstaff, J. M. Straka, C. L. Ziegler, E. R. Mansell, E. C. Bruning, K. M. Kuhlman, N. R. Lund, N. S. Biermann, C. Payne, L. D. Carey, P. R. Krehbiel, W. Rison, K. B. Eack, W. H. Beasley, 2008: TELEX: The Thunderstorm Electrification and Lightning Experiment. Bulletin of the American Meteorological Society, 89, 997-1013.

The field program of the Thunderstorm Electrification and Lightning Experiment (TELEX) took place in central Oklahoma, May–June 2003 and 2004. It aimed to improve understanding of the interrelationships among microphysics, kinematics, electrification, and lightning in a broad spectrum of storms, particularly squall lines and storms whose electrical structure is inverted from the usual vertical polarity. The field program was built around two permanent facilities: the KOUN polarimetric radar and the Oklahoma Lightning Mapping Array. In addition, balloon-borne electric-field meters and radiosondes were launched together from a mobile laboratory to measure electric fields, winds, and standard thermodynamic parameters inside storms. In 2004, two mobile C-band Doppler radars provided high-resolution coordinated volume scans, and another mobile facility provided the environmental soundings required for modeling studies. Data were obtained from twenty-two storm episodes, including several small isolated thunderstorms, mesoscale convective systems, and supercell storms. Examples are presented from three storms. A heavy-precipitation supercell storm on 29 May 2004 produced greater than 3 flashes per second for 1.5 h. Holes in the lightning density formed and dissipated sequentially in the very strong updraft and bounded weak echo region of the mesocyclone. In a small squall line on 19 June 2004, most lightning flashes in the stratiform region were initiated in or near strong updrafts in the convective line and involved positive charge in the upper part of the radar bright band. In a small thunderstorm on 29 June 2004, lightning activity began as polarimetric signatures of graupel first appeared near lightning initiation regions.

Available online at http://ams.allenpress.com/archive/1520-0477/89/7/pdf/i1520-0477-89-7-997.pdf.

MacGorman, D. R., T. Mansell, C. Ziegler, J. Straka, 2008: Detailed storm simulations by a numerical cloud model with electrification and lightning parameterizations. Preprints, 20th International Lightning Detection Conference, Tucson, AZ, USA, Vaisala, 28.

We have further developed our three-dimensional cloud model, which includes parameterizations of lightning, corona from ground, ion production and capture, and inductive and noninductive electrification mechanisms, as well as advanced treatments of advection, microphysics, and dynamics. Our most recent improvements have been to improve the model's treatment of microphysics, particularly particle size distributions. This model has been used to simulate many types of storms, from small isolated storms to extensive storm systems, supercell storms, and an idealized hurricane, with excellent similitude to observed kinematic structure in many cases. We will show examples of our simulations and will discuss relationships among the model fields, particularly between lightning and other storm properties. Lightning usually is correlated with precipitation ice mass and with the mass flux through the mixed phase region for updrafts >10 m/s.

Mansell, T., C. Ziegler, D. MacGorman, 2006: A Lightning Data Assimilation Technique for Mesoscale Forecast Models. Preprints, 1st International Lightning Meteorology Conference, Tucson, AZ, USA, Vaisala, CD-ROM, N/A. [Available from Vaisala, Inc., Tucson Operations, 2705 E. Medina Rd., Tucson, AZ, USA, 85706.]

Lightning observations have been assimilated into the COAMPS mesoscale model for improvement of forecast initial conditions. Data are used from the National Lightning Detection Network (NLDN, cloud-to-ground lightning detection) and a Lightning Mapping Array (LMA; total lightning detection) that was installed in western Kansas/eastern Colorado. The assimilation method uses lightning as a proxy for the presence or absence of deep convection. During assimilation, lightning data are used to control the Kain-Fritsch (KF) convection parameterization scheme (CPS). The KF scheme can be forced to try to produce convection where lightning indicated storms, and, conversely, can optionally be prevented from producing spurious convection where no lightning was observed. Up to 1 g/kg of water vapor may be added to the boundary layer when the KF convection is too weak. The method does not make any use lightning-rainfall relationships, rather allowing the KF scheme to generate heating and cooling rates from its modeled convection. The method could therefore be used easily for real-time assimilation of any source of lightning observations.

Results will be presented for a warm-season test case 20-21 July 2000, when storms initiated and developed in large systems in Kansas both days. The second round of convection began by 22:00 UTC (20 July), and storm system with strong outflow had developed by 00 UTC on 21 July. Lightning data were assimilated over a 24 hour period (starting at 00 UTC on 20 July), covering the first round of convection and the start of the second. A control run was spun up over the same period only with the usual 12-hourly update cycle. As expected, during the assimilation period the model produces substantially more accurate precipitation (rates and location) than the control forecast. Even when water vapor was added to enhance convection, the rainfall rates were generally less than those indicated by rain gauge data. A forecast was started from the resulting initial condition at 00 UTC on 21 July 2000.

The lightning assimilation was successful in generating the cold pool that was present in the surface observations at initialization of the forecast. The resulting forecast showed considerably more skill than the control forecast, especially in the first few hours as convection was triggered by the propagation of the cold pool boundary.

Mansell, E. R., C. L. Ziegler, D. R. MacGorman, 2006: A Lightning Data Assimilation Technique for Mesoscale Forecast Models. Preprints, Second Conference on Meteorological Applications of Lightning Data, Atlanta, GA, USA, American Meteorological Society, 4.2.

Lightning observations have been assimilated into the COAMPS mesoscale model for improvement of forecast initial conditions. Data are used from the National Lightning Detection Network (NLDN, cloud-to-ground lightning detection) and a Lightning Mapping Array (LMA; total lightning detection) that was installed in western Kansas/eastern Colorado. The assimilation method uses lightning as a proxy for the presence or absence of deep convection. During assimilation, lightning data are used to control the Kain-Fritsch (KF) convection parameterization scheme (CPS). The KF scheme can be forced to try to produce convection where lightning indicated storms, and, conversely, can optionally be prevented from producing spurious convection where no lightning was observed. Up to 1 g/kg of water vapor may be added to the boundary layer when the KF convection is too weak. The method does not make any use lightning-rainfall relationships, rather allowing the KF scheme to generate heating and cooling rates from its modeled convection. The method could therefore be used easily for real-time assimilation of any source of lightning observations.

Results will be presented for a warm-season test case 20-21 July 2000, when storms initiated and developed in large systems in Kansas both days. The second round of convection began by 22:00 UTC (20 July), and storm system with strong outflow had developed by 00 UTC on 21 July. Lightning data were assimilated over a 24 hour period (starting at 00 UTC on 20 July), covering the first round of convection and the start of the second. A control run was spun up over the same period only with the usual 12-hourly update cycle. As expected, during the assimilation period the model produces substantially more accurate precipitation (rates and location) than the control forecast. Even when water vapor was added to enhance convection, the rainfall rates were generally less than those indicated by rain gauge data. A forecast was started from the resulting initial condition at 00 UTC on 21 July 2000.

The lightning assimilation was successful in generating the cold pool that was present in the surface observations at initialization of the forecast. The resulting forecast showed considerably more skill than the control forecast, especially in the first few hours as convection was triggered by the propagation of the cold pool boundary.

Available online at http://ams.confex.com/ams/Annual2006/techprogram/paper_104180.htm.

Mansell, E. R., C. L. Ziegler, D. R. MacGorman, 2007: A Lightning Data Assimilation Technique for Mesoscale Forecast Models. Monthly Weather Review, 135, 1732-1748.

Lightning observations have been assimilated into a mesoscale model for improvement of forecast initial conditions. Data are used from the National Lightning Detection Network (cloud-to-ground lightning detection) and a Lightning Mapping Array (total lightning detection) that was installed in western Kansas–eastern Colorado. The assimilation method uses lightning as a proxy for the presence or absence of deep convection. During assimilation, lightning data are used to control the Kain–Fritsch (KF) convection parameterization scheme. The KF scheme can be forced to try to produce convection where lightning indicated storms, and, conversely, can optionally be prevented from producing spurious convection where no lightning was observed. Up to 1 g/kg of water vapor may be added to the boundary layer when the KF convection is too weak. The method does not employ any lightning–rainfall relationships, but rather allows the KF scheme to generate heating and cooling rates from its modeled convection. The method could therefore easily be used for real-time assimilation of any source of lightning observations. For the case study, the lightning assimilation was successful in generating cold pools that were present in the surface observations at initialization of the forecast. The resulting forecast showed considerably more skill than the control forecast, especially in the first few hours as convection was triggered by the propagation of the cold pool boundary.

Mansell, E., C. L. Ziegler, E. Bruning, 2007: Simulated electrification of a TELEX multicell storm. Preprints, 13th International Conference on Atmospheric Electricity, Beijing, China, International Commission on Atmospheric Electricity, 290-293.

Mansell, E. R., C. L. Ziegler, E. C. Bruning, 2010: Simulated electrification of a small thunderstorm with two-moment bulk microphysics. Journal of the Atmospheric Sciences, 67, 171-194.

Electrification and lightning are simulated for a small continental multicell storm. The results are consistent with observations and thus provide additional understanding of the charging processes and evolution of this storm. The first six observed lightning flashes were all negative cloud-to ground (CG) flashes, after which intracloud (IC) flashes also occurred between middle and upper levels of the storm. The model simulation reproduces the basic evolution of lightning from low and middle levels to upper levels. The observed lightning indicated an initial charge structure of at least an inverted dipole (negative charge above positive). The simulations show that noninductive charge separation higher in the storm can enhance the main negative charge sufficiently to produce negative CG flashes before upper level IC flashes commence. The result is a ‘‘bottom-heavy’’ tripole charge structure with midlevel negative charge and a lower positive charge region that is more significant than the upper positive region, in contrast to the traditional tripole structure that has a less significant lower positive charge region. Additionally, the occurrence of cloud-to-ground lightning is not necessarily a result of excess net charge carried by the storm, but it is primarily caused by the local potential imbalance between the lowest charge regions.

The two-moment microphysics scheme used for this study predicted mass mixing ratio and number concentration of cloud droplets, rain, ice crystals, snow, and graupel. Bulk particle density of graupel was also predicted, which allows a single category to represent a greater range of particle characteristics. (An additional hail category is available but was not needed for the present study.) The prediction of hydrometeor number concentration is particularly critical for charge separation at higher temperatures (-5 < T < -20 deg C) in the mixed phase region, where ice crystals are produced by rime fracturing (Hallett–Mossop process) and by splintering of freezing drops. Cloud droplet concentration prediction also affected the rates of inductive charge separation between graupel and droplets.

Available online at http://journals.ametsoc.org/doi/pdf/10.1175/2009JAS2965.1.

Mansell, E. R., C. L. Ziegler, 2011: CCN Effects on Simulated Storm Electrification and Precipitation. Extended Abstracts, 18th Conf. Planned and Inadvertent Weather Modification, Seattle, WA, USA, Amer. Met. Soc., J15.2.

The effects of concentration of cloud condensation nuclei (CCN) on cloud microphysics have long been recognized, but the resultant effects on storm electrification are relatively unexplored. In the present study, a high-resolution 3D model is employed with 2-moment microphysics (hydrometeor mass and number concentration) and electrification and lightning to simulate a storm observed in Oklahoma during the TELEX-2004 experiment (Mansell et al. 2010, J. Atmos. Sci.). CCN concentration is predicted as a single category monodisperse size spectrum approximating small aerosols. Graupel and hail particle densities are also predicted and are mainly determined by rime density. Rime density in turn is a function of droplet size (affected by CCN concentration) and impact speed. Graupel density is also used as a crude roughness parameter to scale the drag coefficient in the fall speed.

A range of CCN concentrations (50 to 15000 cm-3) were tested in a weak CAPE (Convective Available Potential Energy) environment (918 J/kg) that produced weakly multicell convection. Greater CCN concentration has the expected effects of shifting the initial formation of rain drops via collision-coalescence to later times and higher altitudes. Even at the highest CCN concentrations, however, vapor supply in the updraft remains sufficient for droplets eventually to grow large enough for coalescence to become appreciable before the appearance of graupel, so the warm-rain process is not completely shut down in this case. Peak updraft values increased modestly with increasing CCN from 16.8 m/s (50 cm-3) to 19.5 m/s (500 cm-3). Above CCN of 500 cm-3, peak updraft varied little from 19.5 m/s.

Time-integrated mass of graupel increases monotonically with increasing CCN up to about 2000-3 and decreases somewhat at higher CCN concentrations (Fig. 1). Time-integrated updraft volume generally increases with greater CCN concentrations, as well, but reached a plateau for CCN greater than 500 cm-3. Other effects of CCN concentration were variable. The simulated storms had maximum flash rates of 0 to 17 per minute and from 0 to 150 total flashes (Fig. 1). The most intense electrification (total lightning sources) was for CCN concentrations of 1000 to 3000 cm-3, dropping off toward lower and higher CCN values (Fig. 1; no flashes at 50-100 cm-3, and 3-4 total flashes for CCN >= 8000 cm-3.

Available online at http://ams.confex.com/ams/91Annual/webprogram/Paper180497.html.

Mansell, E. R., C. L. Ziegler, 2011: Aerosol (CCN) Effects on Simulated Storm Electrification and Precipitation. Preprints, 14th International Conference on Atmospheric Electricity, Rio de Janeiro, Brazil, International Commission on Atmospheric Electricity, CD-ROM, NA.

The effects of cloud condensation nuclei (CCN) concentrations strongly affected the microphysical and electrical evolution of a numerically simulated small storm. Graupel and lightning production increased monotonically as CCN increase from 50 cm-3 to about 2000 cm-3, where graupel production leveled off (up to 8000 cm-3 ). At higher CCN concentrations (>2000 cm-3 ), lightning activity either dropped dramatically (HM1) or remained steady (HM2), depending on the parameterization of Hallett-Mossop riming ice multiplication (HM1/HM2).

Marsh, P. T., J. S. Kain, S. J. Weiss, I. L. Jirak, R. A. Sobash, F. Kong, K. W. Thomas, M. Xue, 2010: INVESTIGATING A FUNDAMENTAL COMPONENT OF A WARN-ON FORECAST SYSTEM IN A COLLABORATIVE REAL-TIME EXPERIMENT. Extended Abstracts, 11th Severe Local Storms Conference, Denver, CO, USA, American Meteorological Society, 14.4.

The Warn-on-Forecast paradigm (WoF) envisions probabilistic prediction of severe convective phenomena based on ensemble forecasts using high-resolution models. One of many scientific challenges facing Warn-on-Forecast is how to construct reliable probabilistic information regarding severe convective phenomena when these phenomena will not be explicitly resolvable for many years to come. One approach to address this issue is to identify “extreme” model-generated features that have strong correlations with observed extreme convective phenomena, and then use the former as surrogates for the extreme phenomena in question. This “surrogate-severe” (SS) approach is fundamentally different from traditional applications of NWP for severe weather because it is phenomenon based. In particular, it relies on identification of explicit convective phenomena rather than environmental conditions to predict the likelihood of severe thunderstorms.

Sobash et al. (2009) established the viability of this approach using several different SS diagnostic quantities. Their work used a “neighborhood” approach based on the concepts in Theis et al. (2005) and Brooks et al. (1998) to produce severe-weather probability forecasts based on the locations of SS features in a deterministic model. In the current study, we extend the concepts developed by Sobash et al. (2009) to a 26-member storm-scale ensemble. This ensemble was produced by the Center for Analysis and Prediction of Storms (CAPS) during the 2010 NOAA HWT Spring Experiment. In the ensemble-based application it was found that interpretation of derived probabilistic forecasts depends strongly on the parameters used for post-processing. This presentation examines examples of various derived products, their potential utility for current Outlook-scale severe weather forecasts, and their possible application within the focused scales of WoF for severe weather.

References:
Brooks, H. E., M. Kay, and J. A. Hart, 1998: Objective limits on forecasting skill of rare events. Preprints, 19th Conference on Severe Local Storms, Minneapolis, Minnesota, Amer. Meteor. Soc., 552-555.

Sobash, R. A., J. S. Kain, D. R. Bright, A. R. Dean, M. C. Coniglio, S. J. Weiss, and J. J. Levit, 2009: Forecast guidance for severe thunderstorms based on identification of extreme phenomena in convection-allowing model forecasts. Preprints, 23rd Conference on Weather Analysis and Forecasting/19th Conference on Numerical Weather Prediction, Amer. Meteor. Soc., Omaha, NE. CD-ROM 4B.6

Theis, S. E., A. Hense, and U. Damrath, 2005: Probabilistic precipitation forecasts from a deterministic model: A pragmatic approach. Meteor. Appl., 12, 257–268.

Available online at http://ams.confex.com/ams/25SLS/techprogram/paper_176218.htm.

McLaughlin, D., D. Pepyne, B. Philips, J. Kurose, M. Zink, D. Westbrook, E. Lyons, E. Knapp, A. Hopf, A. Defonzo, R. Contreras, T. Djaferis, E. Insanic, S. Frasier, V. Chandrasekar, F. Junyent, N. Bharadwaj, Y. Wang, Y. Liu, B. Dolan, K. Droegemeier, J. Brotzge, M. Xue, K. Kloesel, K. Brewster, F. Carr, S. Cruz-Pol, K. Hondl, P. Kollias, 2009: Short-Wavelength Technology and the Potential For Distributed Networks of Small Radar Systems. Bulletin of the American Meteorological Society, 90, 1797-1817.

Dense networks of short-range radars capable of mapping storms and detecting atmospheric hazards are described. Composed of small X-band (9.4 GHz) radars spaced tens of kilometers apart, these networks defeat the Earth curvature blockage that limits today's long-range weather radars and enables observing capabilities fundamentally beyond the operational state-of-the-art radars. These capabilities include multiple Doppler observations for mapping horizontal wind vectors, subkilometer spatial resolution, and rapid-update (tens of seconds) observations extending from the boundary layer up to the tops of storms. The small physical size and low-power design of these radars permits the consideration of commercial electronic manufacturing approaches and radar installation on rooftops, communications towers, and other infrastructure elements, leading to cost-effective network deployments. The networks can be architected in such a way that the sampling strategy dynamically responds to changing weather to simultaneously accommodate the data needs of multiple types of end users. Such networks have the potential to supplement, or replace, the physically large long-range civil infrastructure radars in use today.

Park, H., A. Ryzhkov, H. Reeves, T. Schuur, 2009: Classification of precipitation types during transitional winter weather using the RUC model and polarimetric radar retrievals. Extended Abstracts, 34th Conference on Radar Meteorology, Williamsburg, VA, USA, AMS, P2.20.

Available online at http://ams.confex.com/ams/pdfpapers/155580.pdf.

Pinto, J., C. Kessinger, B. Hendrickson, D. Megenhardt, P. Harasti, Q. Xu, P. Zhang, Q. Zhao, M. Frost, J. Cook, S. Potts, 2007: Storm characterization and short term forecasting potential using a phase array radar. Extended Abstracts, 33rd Conference on Radar Meteorology, Cairns, Australia, Amer. Meteor. Soc., P5.18.

Available online at http://ams.confex.com/ams/pdfpapers/123703.pdf.

Potvin, C. K., A. Shapiro, M. Xue, 2012: Impact of a Vertical Vorticity Constraint in Variational Dual-Doppler Wind Analysis: Tests with Real and Simulated Supercell Data. Journal of Atmospheric and Oceanic Technology, 29, 32-49.

One of the greatest challenges to dual-Doppler retrieval of the vertical wind is the lack of low-level divergence information available to the mass conservation constraint. This study examines the impact of a vertical vorticity equation constraint on vertical velocity retrievals when radar observations are lacking near the ground. The analysis proceeds in a three-dimensional variational data assimilation (3DVAR) framework with the anelastic form of the vertical vorticity equation imposed along with traditional data, mass conservation, and smoothness constraints. The technique is tested using emulated radial wind observations of a supercell storm simulated by the Advanced Regional Prediction System (ARPS), as well as real dual-Doppler observations of a supercell storm that occurred in Oklahoma on 8 May 2003. Special attention is given to procedures to evaluate the vorticity tendency term, including spatially variable advection correction and estimation of the intrinsic evolution. Volume scan times ranging from 5 min, typical of operational radar networks, down to 30 s, achievable by rapid-scan mobile radars, are considered. The vorticity constraint substantially improves the vertical velocity retrievals in our experiments, particularly for volume scan times smaller than 2 min.

Qiu, C., A. Shao, Q. Xu, L. Wei, 2007: An Ensemble-Based 4DVar Approach Based on SVD Technique. Extended Abstracts, 18th Conference on Numerical Weather Prediction, park City, UT, USA, Amer. Meteor. Soc., P2.2.

Available online at http://ams.confex.com/ams/22WAF18NWP/techprogram/paper_123933.htm.

Qiu, C., A. Shao, Q. Xu, L. Wei, 2007: Fitting model fields to observations by using singular value decomposition – An ensemble-based 4DVar approach. Journal of Geophysical Research - D: Atmospheres., 112, .

Reeves, H. D., R. Rotunno, 2008: Orographic Flow Response to Variations in Upstream Humidity. Journal of the Atmospheric Sciences, 65, 3557-3570.

The effects of upstream relative humidity, RH , on low-level wind and precipitation patterns for low-speed, statically stable flows over a mountain are investigated using idealized two- and three-dimensional numerical-simulation experiments wherein RH is increased from 0 to 100%. For RH less than some critical threshold, the flow upstream becomes less decelerated as RH is increased; for RH greater than this threshold, the flow upstream becomes more decelerated as RH is increased. This increasing deceleration with RH is due to locally enhanced static stability owing to enhanced condensation near the freezing level. Analyses from the simulations indicate that the lifted condensation level and the height of the freezing level are significant control parameters for the upstream-flow deceleration in the steady-state solutions. Dimensional analysis using these control parameters (as well as others) brings forth new nondimensional parameters that are shown to enter into analytic formulas for the orographic upstream-flow deceleration in a moist atmosphere.

Reeves, H. D., D. J. Stensrud, 2009: Synoptic-scale flow and valley cold pool evolution in the Western United States. Weather and Forecasting, 24, 1625-1643.

Valley cold pools (VCPs), which are trapped, cold layers of air at the bottoms of basins or valleys, pose a significant problem for forecasters because they can lead to several forms of difficult-to-forecast and hazardous weather such as fog, freezing rain, or poor air quality. Numerical models have historically failed to routinely provide accurate guidance on the formation and demise of VCPs, making the forecast problem more challenging. In some case studies of persistent wintertime VCPs, there is a connection between the movement of upper-level waves and the timing of VCP formation and decay. Herein, a 3-yr climatology of persistent wintertime VCPs for five valleys and basins in the western United States is performed to see how often VCP formation and decay coincides with synoptic-scale (~200-2000 km) wave motions. Valley cold pools are found to form most frequently as an upper-level ridge approaches the western United States and in response to strong midlevel warming. The VCPs usually last as long as the ridge is over the area and usually only end when a trough, and its associated midlevel cooling, move over the western United States. In fact, VCP strength appears to be almost entirely dictated by midlevel temperature changes, which suggests large-scale forcing is dominant for this type of VCP most of the time.

Reeves, H. D., K. L. Elmore, G. S. Manikin, D. J. Stensrud, 2011: Assessment of forecasts during persistent valley cold pools in the Bonneville Basin by the North American Mesoscale model. Weather and Forecasting, 26, 447-467.

The North American Mesoscale (NAM) model forecasts of low-level temperature and dewpoint during persistent valley cold pools in the Bonneville Basin of Utah are assessed. Stations near the east sidewall have a daytime cold and nighttime warm bias. This is due to a poor representation of the steep slopes on this side of the basin. Basin stations where the terrain is better represented by the model have a distinct warm, moist bias at night.
Stations in snow-covered areas have a cold bias for both day and night. Biases are not dependent on forecast lead or validation time. Several potential causes for the various errors are considered in a series of sensitivity experiments. An experiment with 4-km grid spacing, which better resolves the gradient of the slopes on the east side of the basin, yields smaller
errors along the east corridor of the basin. The NAM model assumes all soil water freezes at a temperature of 273 K. This is likely not representative of the freezing temperature in the salt flats in the western part of the basin, since salt reduces the freezing point of water. An experiment testing this hypothesis shows that reducing the freezing point of soil water in the salt flats leads to an average error reduction between 1.5 and 4 K, depending on the station and time of day. Using a planetary boundary layer scheme that has greater mixing alleviates the cold bias over snow somewhat, but the exact source of this bias could not be determined.

Reeves, H. D., K. L. Elmore, G. S. Manikin, D. J. Stensrud, 2011: Assessment of forecasts during persistent valley cold pools in the Bonneville basin by the North American Mesoscale Model.. Weather and Forecasting, 26, 447-467.

North American Mesoscale Model (NAM) forecasts of low-level temperature and dewpoint during persistent valley cold pools in the Bonneville Basin of Utah are assessed. Stations near the east sidewall have a daytime cold and nighttime warm bias. This is due to a poor representation of the steep slopes on this side of the basin. Basin stations where the terrain is better represented by the model have a distinct warm, moist bias at night. Stations in snow-covered areas have a cold bias for both day and night. Biases are not dependent on forecast lead or validation time. Several potential causes for the various errors are considered in a series of sensitivity experiments. An experiment with 4-km grid spacing, which better resolves the gradient of the slopes on the east side of the basin, yields smaller errors along the east corridor of the basin. The NAM assumes all soil water freezes at a temperature of 273 K. This is likely not representative of the freezing temperature in the salt flats in the western part of the basin, since salt reduces the freezing point of water. An experiment testing this hypothesis shows that reducing the freezing point of soil water in the salt flats leads to an average error reduction between 1.5 and 4 K, depending on the station and time of day. Using a planetary boundary layer scheme that has greater mixing alleviates the cold bias over snow somewhat, but the exact source of this bias could not be determined.

Schenkman, A. D., M. Xue, A. Shapiro, K. Brewster, J. Gao, 2011: The Analysis and Prediction of the 8–9 May 2007 Oklahoma Tornadic Mesoscale Convective System by Assimilating WSR-88D and CASA Radar Data Using 3DVAR. Monthly Weather Review, 139, 224-246.

The Advanced Regional Prediction System (ARPS) model is employed to perform high-resolution numerical simulations of a mesoscale convective system and associated cyclonic line-end vortex (LEV) that spawned several tornadoes in central Oklahoma on 8–9 May 2007. The simulation uses a 1000 km × 1000 km domain with 2-km horizontal grid spacing. The ARPS three-dimensional variational data assimilation (3DVAR) is used to assimilate a variety of data types. All experiments assimilate routine surface and upper-air observations as well as wind profiler and Oklahoma Mesonet data over a 1-h assimilation window. A subset of experiments assimilates radar data. Cloud and hydrometeor fields as well as in-cloud temperature are adjusted based on radar reflectivity data through the ARPS complex cloud analysis procedure. Radar data are assimilated from the Weather Surveillance Radar-1988 Doppler (WSR-88D) network as well as from the Engineering Research Center for Collaborative and Adaptive Sensing of the Atmosphere (CASA) network of four X-band Doppler radars. Three-hour forecasts are launched at the end of the assimilation window. The structure and evolution of the forecast MCS and LEV are markedly better throughout the forecast period in experiments in which radar data are assimilated. The assimilation of CASA radar data in addition to WSR-88D data increases the structural detail of the modeled squall line and MCS at the end of the assimilation window, which appears to yield a slightly better forecast track of the LEV.

Schenkman, A. D., M. Xue, A. Shapiro, K. Brewster, J. Gao, 2011: Impact of CASA Radar and Oklahoma Mesonet Data Assimilation on the Analysis and Prediction of Tornadic Mesovortices in an MCS. Monthly Weather Review, 139, 3422-3445.

The impact of radar and Oklahoma Mesonet data assimilation on the prediction of mesovortices in a tornadic mesoscale convective system (MCS) is examined. The radar data come from the operational Weather Surveillance Radar-1988 Doppler (WSR-88D) and the Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere’s (CASA) IP-1 radar network. The Advanced Regional Prediction System (ARPS) model is employed to perform high-resolution predictions of an MCS and the associated cyclonic line-end vortex that spawned several tornadoes in central Oklahoman 8–9 May 2007, while the ARPS three-dimensional variational data assimilation (3DVAR) system in combination with a complex cloud analysis package is used for the data analysis. A set of data assimilation and prediction experiments are performed on a 400-m resolution grid nested inside a 2-km grid, to examine the impact of radar data on the prediction of meso-g-scale vortices (mesovortices). An 80-min assimilation window is used in radar data assimilation experiments. An additional set of experiments examines the impact of assimilating 5-min data from the Oklahoma Mesonet in addition to the radar data. Qualitative comparison with observations shows highly accurate forecasts of mesovortices up to 80 min in advance of their genesis are obtained when the low-level shear in advance of the gust front is effectively analyzed. Accurate analysis of the low-level shear profile relies on assimilating high resolution low-level wind information. The most accurate analysis (and resulting prediction) is obtained in experiments that assimilate low-level radial velocity data from the CASA radars. Assimilation of 5-min observations from the Oklahoma Mesonet has a substantial positive impact on the analysis and forecast when high-resolution low-level wind observations from CASA are absent; when the low-level CASA wind data are assimilated, the impact of Mesonet data is smaller. Experiments that do not assimilate low-level wind data from CASA radars are unable to accurately resolve the low-level shear profile and gust front structure, precluding accurate prediction of mesovortex development.

Available online at http://journals.ametsoc.org/toc/mwre/139/11.

Schuur, T. J., H. S. Park, A. V. Ryzhkov, H. D. Reeves, 2012: Classification of precipitation types during transitional winter weather using the RUC model and polarimetric radar retrievals. Journal of Applied Meteorology and Climatology, 51, 763-779.

A new hydrometeor classification algorithm that combines thermodynamic output from the Rapid Update Cycle (RUC) model with polarimetric radar observations is introduced. The algorithm improves upon existing classification techniques that rely solely on polarimetric radar observations by using thermodynamic information to help to diagnose microphysical processes (such as melting or refreezing) that might occur aloft. This added information is especially important for transitional weather events for which past studies have shown radar-only techniques to be deficient. The algorithm first uses vertical profiles of wet-bulb temperature derived from the RUC model output to provide a background precipitation classification type. According to a set of empirical rules, polarimetric radar data are then used to refine precipitation-type categories when the observations are found to be inconsistent with the background classification. Using data from the polarimetric KOUN Weather Surveillance Radar-1988 Doppler (WSR-88D) located in Norman, Oklahoma, the algorithm is tested on a transitional winter-storm event that produced a combination of rain, freezing rain, ice pellets, and snow as it passed over central Oklahoma on 30 November 2006. Examples are presented in which the presence of a radar bright band (suggesting an elevated warm layer) is observed immediately above a background classification of dry snow (suggesting the absence of an elevated warm layer in the model output). Overall, the results demonstrate the potential benefits of combining polarimetric radar data with thermodynamic information from numerical models, with model output providing widespread coverage and polarimetric radar data providing an observation-based modification of the derived precipitation type at closer ranges.

Schwartz, C. S., J. S. Kain, S. J. Weiss, M. Xue, D. R. Bright, F. Kong, K. W. Thomas, J. J. Levit, M. C. Coniglio, 2009: Next-day convection-allowing WRF model guidance: A second look at 2 vs. 4 km grid spacing. Monthly Weather Review, 137, 3351-3372.

During the 2007 NOAA Hazardous Weather Testbed (HWT) Spring Experiment, the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma produced convection-allowing forecasts from a single deterministic 2 km model and a 10-member 4 km resolution ensemble. In this study, the 2 km deterministic output was compared with forecasts from the 4 km ensemble control member. Other than the difference in horizontal resolution, the two sets of forecasts featured identical WRFARW configurations, including vertical resolution, forecast domain, initial and lateral boundary conditions, and physical parameterizations. Therefore, forecast disparities were attributed solely to differences in horizontal grid spacing.

This study is a follow-up to similar work that was based on results from the 2005 Spring Experiment. Unlike the 2005 Experiment, however, model configurations were more rigorously controlled in the present study, providing a more robust dataset and a cleaner isolation of the dependence on horizontal resolution. Additionally, in this study, the 2 and 4 km output were compared to 12 km forecasts from the North American Mesoscale (NAM) model.

Model forecasts were analyzed using objective verification of mean hourly precipitation and visual comparison of individual events, primarily during the 21- to 33-hour forecast period to examine the utility of the models as next-day guidance. On average, both the 2 and 4 km model forecasts showed substantial improvement over the 12 km NAM. However, although the 2 km forecasts produced more detailed structures on the smallest resolvable scales, the patterns of convective initiation, evolution, and organization were remarkably similar to the 4 km output. Moreover, on average, metrics such as equitable threat score, frequency bias, and fractions skill score revealed no statistical improvement of the 2 km forecasts compared to the 4 km forecasts. These results, based on the 2007 dataset, corroborate previous findings, suggesting that decreasing horizontal grid spacing from 4 to 2 km provides little added value as next-day guidance for severe convective storm and heavy rain forecasters in the United States.

Schwartz, C. S., J. S. Kain, S. J. Weiss, D. R. Bright, M. Xue, F. Kong, K. W. Thomas, J. J. Levit, M. C. Coniglio, 2008: Next-day convection-allowing WRF model guidance: A second look at 2- vs. 4-km grid spacing. Preprints, 24th Conference on Severe Local Storms, Savannah, GA, USA, Amer. Meteor. Soc., CD-ROM, P10.3. [Available from Jack Kain, NSSL, 120 David L. Boren Blvd, Norman, OK, USA, 73072.]

Available online at http://ams.confex.com/ams/24SLS/techprogram/paper_142052.htm.

Schwartz, C. S., J. S. Kain, D. R. Bright, S. J. Weiss, M. Xue, F. Kong, J. J. Levit, M. C. Coniglio, M. S. Wandishin, 2008: Toward improved convection-allowing ensembles: Model physics sensitivities and optimizing probabilistic guidance with small ensemble membership. Preprints, 24th Conference on Severe Local Storms, Savannah, GA, USA, Amer. Meteor. Soc., CD-ROM, 13A.6. [Available from Jack Kain, NSSL, 120 David L. Boren Blvd, Norman, OK, USA, 73072.]

Available online at http://ams.confex.com/ams/24SLS/techprogram/paper_142048.htm.

Schwartz, C. S., J. S. Kain, D. R. Bright, S. J. Weiss, M. Xue, F. Kong, J. J. Levit, M. C. Coniglio, M. S. Wandishin, 2009: Optimizing probabilistic high resolution ensemble guidance for hydrologic prediction. Preprints, 23rd Conference on Hydrology, Phoenix, AZ, USA, Amer. Meteor. Soc., CD-ROM, 9.4.

Available online at http://ams.confex.com/ams/89annual/techprogram/paper_147171.htm.

Schwartz, C. S., J. S. Kain, M. C. Coniglio, S. J. Weiss, D. R. Bright, M. Xue, F. Kong, K. W. Thomas, M. S. Wandishin, 2010: Toward Improved Convection-Allowing Ensembles: Model Physics Sensitivities and Optimizing Probabilistic Guidance with Small Ensemble Membership. Weather and Forecasting, 25, 263-280.

During the 2007 NOAA Hazardous Weather Testbed Spring Experiment, the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma produced a daily 10-member 4-km horizontal resolution ensemble forecast covering approximately three-fourths of the continental United States. Each member used the Advanced Research version of the Weather Research and Forecasting (WRF-ARW) model core, which was initialized at 2100 UTC, ran for 33 h, and resolved convection explicitly. Different initial condition (IC), lateral boundary condition (LBC), and physics perturbations were introduced in 4 of the 10 ensemble members, while the remaining 6 members used identical ICs and LBCs, differing only in terms of microphysics (MP) and planetary boundary layer (PBL) parameterizations. This study focuses on precipitation forecasts from the ensemble.

The ensemble forecasts reveal WRF-ARW sensitivity to MP and PBL schemes. For example, over the 7-week experiment, the Mellor–Yamada–Janjić PBL and Ferrier MP parameterizations were associated with relatively high precipitation totals, while members configured with the Thompson MP or Yonsei University PBL scheme produced comparatively less precipitation. Additionally, different approaches for generating probabilistic ensemble guidance are explored. Specifically, a “neighborhood” approach is described and shown to considerably enhance the skill of probabilistic forecasts for precipitation when combined with a traditional technique of producing ensemble probability fields.

Shao, A., S. Xi, C. Qiu, Q. Xu, 2009: A hybrid-space approach for ensemble-based 4DVar. Journal of Geophysical Research - D: Atmospheres, 114, .

A new scheme is developed to improve the ensemble-based 4D variational data assimilation (En4DVar). In this scheme, leading singular vectors are extracted from 4D ensemble perturbations in a hybrid space and then used to construct the analysis increment to fit the 4D innovation (observation minus background) data. The hybrid space combines the 4D observation space with only a gridded 3D subspace at the end of each assimilation cycle, so its dimension can be much smaller than the dimension of the fully gridded 4D space used in the original En4DVar. This improves the computational efficiency. With this hybrid-space approach, the analysis increment can fit the 4D innovation data in the observation space directly and also provide the necessary initial condition in the gridded 3D subspace exclusively for the model integration into the next assimilation cycle, so the background covariance matrix can be and only needs to be constructed by the ensemble perturbations in the 3D subspace. This reduces the rank deficiency of the ensemble-constructed covariance matrix and improves analysis accuracy as long as the observations are not too sparse. The potential merits of the new scheme are demonstrated by assimilation experiments performed with an imperfect shallow-water equation model and simulated observations.

Stensrud, D. J., N. Yussouf, M. E. Baldwin, J. T. McQueen, J. Du, B. Zhou, B. Ferrier, G. Manikin, F. M. Ralph, J. M. Wilczak, A. B. White, I. Djlalova, J. W. Bao, R. J. Zamora, S. G. Benjamin, P. A. Miller, T. L. Smith, T. Smirnova, M. F. Barth, 2006: The New England High-Resolution Temperature Program. Bulletin of the American Meteorological Society, 87, 491-498.

The New England High-Resolution Temperature Program seeks to improve the accuracy of summertime 2-m temperature and dewpoint temperature forecasts in the New England region through a collaborative effort between the research and operational components of the National Oceanic and Atmospheric Administration (NOAA). The four main components of this program are 1) improved surface and boundary layer observations for model initialization, 2) special observations for the assessment and improvement of model physical process parameterization schemes, 3) using model forecast ensemble data to improve upon the operational forecasts for near surface variables, and 4) transfering knowledge gained to commercial weather services and end users. Since 2002 this program has enhanced surface temperature observations by adding 70 new automated Cooperative Observer Program (COOP) sites, identified and collected data from over 1000 non-NOAA mesonet sites, and deployed boundary layer profilers and other special instrumentation throughout the New England region to better observe the surface energy budget. Comparisons of these special data sets with numerical model forecasts indicate that near surface temperature errors are strongly correlated to errors in the model predicted radiation fields. The attenuation of solar radiation by aerosols is one potential source of the model radiation bias. However, even with these model errors, results from bias-corrected ensemble forecasts are more accurate than the operational model output statistics (MOS) forecasts for 2-m temperature and dewpoint temperature, while also providing reliable forecast probabilities. Discussions with commerical weather vendors and end users have emphasized the potential economic value of these probabilistic ensemble-generated forecasts.

Stensrud, D. J., N. Yussouf, 2007: Reliable probabilistic quantitative precipitation forecasts from a short-range ensemble forecasting system. Weather and Forecasting, 22, 3-17.

A simple binning technique is developed to produce reliable 3-h probabilistic quantitative precipitation forecasts (PQPFs) from the National Centers for Environmental Prediction (NCEP) multimodel shortrange ensemble forecasting system obtained during the summer of 2004. The past 12 days’ worth of forecast 3-h accumulated precipitation amounts and observed 3-h accumulated precipitation amounts from the NCEP stage-II multisensor analyses are used to adjust today’s 3-h precipitation forecasts. These adjustments are done individually to each of ensemble members for the 95 days studied. Performance of the adjusted ensemble precipitation forecasts is compared with the raw (original) ensemble predictions. Results show that the simple binning technique provides significantly more skillful and reliable PQPFs of rainfall events than the raw forecast probabilities. This is true for the base 3-h accumulation period as well as for accumulation periods up to 48 h. Brier skill scores and the area under the relative operating characteristics curve also indicate that this technique yields skillful probabilistic forecasts. The performance of the adjusted forecasts also progressively improves with the increased accumulation period. In addition, the adjusted ensemble mean QPFs are very similar to the raw ensemble mean QPFs, suggesting that the method does not significantly alter the ensemble mean forecast. Therefore, this simple postprocessing scheme is very promising as a method to provide reliable PQPFs for rainfall events without degrading the ensemble mean forecast.

Stensrud, D. J., N. Yussouf, D. C. Dowell, M. C. Coniglio, 2009: Assimilating surface data into a mesoscale model ensemble: Cold pool analyses from spring 2007. Atmos. Res., 93, 207-220.

Hourly mesoscale analyses are created through an ensemble Kalman filter assimilation of 2-m potential temperature, 2-m dewpoint temperature, and 10-m wind observations into the Weather Research and Forecast (WRF-ARW) model using the Data Assimilation Research Testbed (DART) framework. Hourly analyses are created from 1300 UTC to 0600 UTC each day from 15 March through 30 June 2007. Two cases in which a distinct isolated mesoscale convective system is seen in observations are selected for further examination. Results indicate that the ensemble mean surface analyses reproduce the surface mesoscale features associated with cold pools underneath these precipitating systems in agreement with available observations. However, the ensemble Kalman filter also is able to produce vertical motion fields and vertical structures within and above the boundary layer that are consistent with these observed surface features. In particular, a rear inflow jet is produced at roughly 1 km above ground level behind the main convective line along with an “onion” sounding along the back edge of the trailing stratiform precipitation region near a surface mesolow. Both of these structures are known to be associated with MCSs and the ability of the ensemble Kalman filter assimilation to produce these important mesoscale features is encouraging.

Stensrud, D. J., M. Xue, L. J. Wicker, K. E. Kelleher, M. P. Foster, J. T. Schaefer, R. S. Schneider, S. G. Benjamin, S. S. Weygandt, J. T. Ferree, J. P. Tuell, 2009: Convective-scale warn on forecast: A vision for 2020. Bulletin of the American Meteorological Society, 90, 1487-1499.

The National Oceanic and Atmospheric Administration’s (NOAA’s) National Weather Service (NWS) issues warnings for severe thunderstorms, tornadoes, and flash floods since these phenomena are a threat to life and property. These warnings are presently based upon either visual confirmation of the phenomena or the observational detection of proxy signatures that are largely based upon radar observations. Convective-scale weather warnings are unique in the NWS by having little reliance on direct numerical forecast guidance. Since increasing severe thunderstorm, tornado, and flash flood warning lead times is a key NOAA strategic mission goal designed to reduce the loss of life, injury, and economic costs of these high impact weather phenomena, a new warning paradigm is needed in which numerical model forecasts play a larger role in convective-scale warnings. This new paradigm shifts the warning process from warn-on-detection to warn-on-forecast and has the potential to dramatically increase warning lead times.

A warn-on-forecast system is envisioned as a probabilistic convective-scale ensemble analysis and forecast system that assimilates in-storm observations into a high-resolution convection-resolving model ensemble. The building blocks needed for such a system are presently available and initial research results clearly illustrate the value of radar observations to the production of accurate analyses of convective weather systems and improved forecasts. While a number of scientific and cultural challenges still need to be overcome, the potential benefits are significant. A probabilistic convective-scale warn-on-forecast system is a vision worth pursuing.

Straka, J., E. Mansell, D. MacGorman, E. Bruning, C. L. Ziegler, 2007: Comparison of modeled and observed electrical charging and lightning in a low-precipitation supercell storm during TELEX. Preprints, 13th International Conference on Atmospheric Electricity, Beijing, China, International Commission on Atmospheric Electricity, 272-275.

Stuart, N. A., P. S. Market, B. Telfeyan, G. M. Lackmann, K. Carey, H. E. Brooks, B. C. Motta, K. Reeves, 2006: The future of humans in an increasingly automated forecast process. Bulletin of the American Meteorological Society, 87, 1-6.

The meteorological community is considering new roles for forecasters as increased accuracy in computer-generated weather forecasts continues to reduce the need for human intervention.

Available online at http://www.nssl.noaa.gov/users/brooks/public_html/papers/stuart.pdf.

Suarez, A., H. D. Reeves, D. Wheatley, M. Coniglio, 2012: Comparison of Ensemble Kalman Filter–Based Forecasts to Traditional Ensemble and Deterministic Forecasts for a Case Study of Banded Snow. Weather and Forecasting, 27, 85-105.

The ensemble Kalman filter (EnKF) technique is compared to other modeling approaches for a case study of banded snow. The forecasts include a 12- and 3-km grid-spaced deterministic forecast (D12 and D3), a 12-km 30-member ensemble (E12), and a 12-km 30-member ensemble with EnKF-based four- dimensional data assimilation (EKF12). In D12 and D3, flow patterns are not ideal for banded snow, but they have similar precipitation accumulations in the correct location. The increased resolution did not improve the quantitative precipitation forecast. The E12 ensemble mean has a flow pattern favorable for banding and precipitation in the approximate correct location, although the magnitudes and probabilities of relevant features are quite low. Six members produced good forecasts of the flow patterns and the precipitation structure. The EKF12 ensemble mean has an ideal flow pattern for banded snow and the mean produces banded precipitation, but relevant features are about 100 km too far north. The EKF12 has a much lower spread than does E12, a consequence of their different initial conditions. Comparison of the initial ensemble means shows that EKF12 has a closed surface low and a region of high low- to midlevel humidity that are not present in E12. These features act in concert to produce a stronger ensemble-mean cyclonic system with heavier precipitation at the time of banding.

Available online at http://dx.doi.org/10.1175/WAF-D-11-00030.1.

Wang, B., J. Zhang, W. Xia, K. Howard, X. Xu, 2008: Analysis of radar and gauge rainfall during the warm season in Oklahoma. Preprints, The 22nd Conf. on Hydrology, New Orleans, LA, USA, Amer. Meteor. Soc., CD-ROM, P2.1.

Weiss, S. J., J. S. Kain, D. R. Bright, J. J. Levit, M. Pyle, Z. I. Janjic, B. Ferrier, J. Du, M. L. Weisman, M. Xue, 2007: The NOAA Hazardous Weather Testbed: Collaborative testing of ensemble and convection-allowing WRF models and subsequent transfer to operations at the Storm Prediction Center.. Preprints, 22th Conference on Weather Analysis and Forecasting/18th Conference on Numerical Weather Prediction, Park City, UT, USA, Amer. Meteor. Soc., CD-ROM, 6B.4.

Weiss, S. J., J. S. Kain, D. R. Bright, J. J. Levit, M. Pyle, Z. I. Janjic, B. S. Ferrier, J. Du, M. L. Weisman, M. Xue, 2007: The NOAA Hazardous Weather Testbed: Collaborative testing of ensemble and convection-allowing WRF models and subsequent transfer to operations at the Storm Prediction Center. Preprints, 22th Conference on Weather Analysis and Forecasting/18th Conference on Numerical Weather Prediction, Park City, UT, USA, Amer. Meteor. Soc., CD-ROM, Amer. Mete. [Available from S. J. Weiss, SPC, 120 David L. Boren Blvd, Norman, OK, USA, 73072.]

Since 2003, the Storm Prediction Center (SPC) has played a leading role in testing various configurations of Short-Range Ensemble Forecast (SREF) systems and high resolution WRF models for their operational utility. These test and evaluation activities have occurred during organized collaborative activities in the NOAA Hazardous Weather Testbed (HWT) in Norman. The HWT is designed to bring research scientists, model developers, and forecasters together to work on issues of mutual interest, facilitating the rapid transfer of research to operations. This organizational framework helps researchers and model developers to better understand the operational challenges and requirements of forecasters, educates forecasters on new science and technological advances, and has accelerated the application of new modeling approaches to severe weather forecasting. This paper focuses on the use of the operational NCEP SREF and two experimental high resolution convection-allowing WRF models as complementary sources of information for SPC forecasters.

NCEP is running a 21 member multi-model, multi-analysis SREF system with enhanced physics diversity four times daily with output through 87 hours. SPC processes the grids from all SREF members and produces a large variety of products for severe weather forecasting, including standard spaghetti, mean and spread, probability, and max/min charts, as well as specialized multi-parameter convective fields and post-processed calibrated probabilities for the occurrence of thunderstorms, dry thunderstorms, and severe thunderstorms.

NCEP has also been running an experimental high resolution WRF-Non-hydrostatic Mesoscale Model (WRF-NMM4) for the SPC since April 2004; this model was recently upgraded to a 4 km grid length. And starting in November 2006, SPC forecasters have had access to output from a 4 km Advanced Research WRF (WRF-ARW4) developed by NCAR and run at the National Severe Storms Laboratory. Both WRF models are initialized from a cold start once daily at 0000 UTC using initial and lateral boundary conditions from the operational North American Mesoscale model, and provide forecasts through a 36 hour period over a domain covering approximately three-fourths of the U.S. Several unique WRF products have been developed for use by severe weather forecasters, including simulated reflectivity and measures of updraft rotation in model-generated storms.

The incorporation of SREF and high resolution WRF guidance into an operational severe weather forecasting environment already dealing with high volumes of observational and model data requires careful assessment of the unique strengths of each modeling system, and knowledge of the specific needs of SPC forecasters. Since the SPC severe weather forecast mission focuses on phenomena smaller than that predicted by mesoscale models, such as tornadoes and severe thunderstorms, the traditional forecast methodology has focused on first predicting the evolution of the mesoscale environment and then determining the spectrum of convective storms a particular environment may support. SREF output has been found to be particularly useful in quantifying the likelihood that the environment will occupy specific parts of convective parameter space, as well as the likelihood and timing for thunderstorms and severe thunderstorms to develop over Outlook-scale regions. While this can be extremely helpful to SPC forecasters, more detailed information about the intensity and mode of storms is also needed, since the type of severe weather (e.g., tornadoes, damaging wind) is often strongly related to convective mode. The value of the high resolution WRF guidance is most evident here, as it has capability to resolve near storm-scale convective characteristics, such as the development of discrete cells ahead of a line of storms, and the development of model storms with rotating updrafts.

We will examine the complementary role of SREF and high resolution WRF output during several strongly-forced and weakly-forced severe weather days during the winter and spring severe weather period and illustrate the operational application of these model datasets in the SPC decision-making process for both Convective Outlooks and Watches.

Available online at http://ams.confex.com/ams/pdfpapers/124772.pdf.

Wheatley, D. M., D. J. Stensrud, 2010: The Impact of Assimilating Surface Pressure Observations on Severe Weather Events in a WRF Mesoscale Ensemble System. Monthly Weather Review, 138, 1673-1694.

Surface pressure observations are assimilated into a Weather Research and Forecast ensemble using an ensemble Kalman filter (EnKF) approach and the results are compared with observations for two severe weather events. Several EnKF experiments are performed to evaluate the relative impacts of two very different pressure observations: altimeter setting (a total pressure field) and 1-h surface pressure tendency. The primary objective of this study is to determine the surface pressure observation that is most successful in producing realistic mesoscale features, such as convectively driven cold pools, which often play an important role in future convective development. Results show that ensemble-mean pressure analyses produced from the assimilation of surface temperature, moisture, and winds possess significant errors in regard to mesohigh strength and location. The addition of surface pressure tendency observations within the assimilation yields limited ability to constrain such errors, while the assimilation of altimeter setting yields accurate depictions of the mesoscale pressure patterns associated with mesoscale convective systems. The mesoscale temperature patterns produced by all the ensembles are quite similar and tend to reproduce the observed features. Results suggest that even though surface pressure observations can have large cross covariances with temperature and the wind components, the resulting analyses fail to improve upon the EnKF temperature and wind analyses that exclude the surface pressure observations. Ensemble forecasts following the assimilation period show the potential to improve short-range forecasting of surface pressure.

Wheatley, D. M., D. J. Stensrud, D. C. Dowell, N. Yussouf, 2012: Application of a WRF Mesoscale Data Assimilation System to Springtime Severe Weather Events 2007-09. Monthly Weather Review, 140, 1539-1557.

An ensemble-based data assimilation system using the Weather Research and Forecasting (WRF) model has been used to initialize forecasts of prolific severe weather events from springs 2007-2009. These experiments build on previous work that has shown the ability of ensemble Kalman filter (EnKF) data assimilation to produce realistic mesoscale features, such as drylines and convectively driven cold pools, which often play an important role in future convective development. For each event in this study, severe weather parameters are calculated from an experimental ensemble forecast started from EnKF analyses, and then compared to a control ensemble forecast in which no ensemble-based data assimilation is performed. Root mean square errors for surface observations averaged across all events are generally smaller for the experimental ensemble over the 0-6 h forecast period. At model grid points nearest tornado reports, the ensemble-mean significant tornado parameter (STP) and the probability of STP > 1 are often greater in the experimental 0-6 h ensemble forecasts than in the control forecasts. Likewise, the probability of MCS Maintenance Probability (MMP) is often greater with the experimental ensemble at model grid points nearest wind reports. Severe weather forecasts can be sharpened by coupling the respective severe weather parameter with the probability of measurable rainfall at model grid points. The differences between the two ensembles are found to be significant at the 95% level, suggesting that even a short period of ensemble data assimilation can yield improved forecast guidance for severe weather events.

Xu, Q., L. Wei, H. Lu, K. Nai, Q. Zhao, 2006: Phased-array radar data assimilation at the National Weather Radar Testbed -- Theoretical issues and practical solutions. Preprints, Fourth European Conference on Radar Meteorology, Barcelona, Spain, ERAD multiple Sponsors. See http://www.grahi.upc.edu/ERAD2006/i, 515-518.

Available online at http://www.grahi.upc.edu/ERAD2006/index.php.

Xu, Q., S. Liu, M. Xue, 2006: Background error covariance functions for vector wind analyses using Doppler radar radial-velocity observations. Quart. J. Roy. Meteor. Soc., 132, 2887-2904.

Xu, Q., K. Nai, L. Wei, 2007: An innovation method for estimating radar radial-velocity observation error and background wind error covariances. Quart. J. Roy. Meteor. Soc., 133, 407-415.

Xu, Q., 2007: Measuring information content from observations for data assimilation: Relative entropy versus Shannon entropy difference. Tellus, 59A, 198-209.

Xu, Q., 2007: Modal and non-modal symmetric perturbations. Part 1. Modal solutions and partial orthogonality. Journal of the Atmospheric Sciences, 64, 1745-1763.

Xu, Q., T. Lei, S. Gao, 2007: Modal and non-modal symmetric perturbations. Part 2. Non-modal growths measured by total perturbation energy. Journal of the Atmospheric Sciences, 64, 1764-1781.

Xu, Q., K. Nai, L. Wei, H. Lu, P. Zhang, S. Liu, D. Parrish, 2007: Estimating radar wind observation error and NCEP WRF background wind error covariances from radar radial-velocity innovations. Extended Abstracts, 18th Conference on Numerical Weather Prediction, Park City, UT, USA, Amer. Meteor. Soc., 1B.3.

Available online at http://ams.confex.com/ams/pdfpapers/123419.pdf.

Xu, Q., L. Wei, H. Lu, Q. Zhao, C. Qiu, 2007: Time-expanded sampling for ensemble-based filter with covariance localization: assimilation experiments with a shallow-water equation model. Preprints, 18th Conference on Numerical Weather Prediction, Park City, UT, USA, Amer. Meteor. Soc., 6B.1A.

Available online at http://ams.confex.com/ams/pdfpapers/123409.pdf.

Xu, Q., H. Lu, L. Wei, Q. Zhao, 2007: Studies of phased-array scan strategies for radar data assimilation. Extended Abstracts, 33rd Conference on Radar Meteorology, Cairns, Australia, Amer. Meteor. Soc., 4A.3.

Available online at http://ams.confex.com/ams/pdfpapers/122972.pdf.

Xu, Q., L. Wei, H. Lu, C. Qiu, Q. Zhao, 2008: Time-expanded sampling for ensemble-based filters: Assimilation experiments with a shallow-water equation model. Journal of Geophysical Research - D: Atmospheres, 113, .

Xu, Q., H. Lu, L. Wei, S. Gao, M. Xue, M. Tong, 2008: Time-expanded sampling for ensemble Kalman filter: Assimilation experiments with simulated Radar observations. Monthly Weather Review, 136, 2651-2667.

Xu, X., K. Howard, J. Zhang, 2008: An Automated Radar Technique for the Identification of Tropical Precipitation. Journal of Hydrometeorology, 9, 885-902.

Xu, Q., L. Wei, S. Healy, 2009: Measuring information content from observations for data assimilations: connection between different measures and application to radar scan design. Tellus, 61A, 144-153.

The previously derived formulations for using the relative entropy and Shannon entropy difference to measure information content from observations are revisited in connection with another known information measure – degrees of freedom for signal, which is defined as the statistical average of the signal part of the relative entropy. For a linear assimilation system, the statistical average of the relative entropy reduces to the Shannon entropy difference. The formulations are extended for four-dimensional variational data assimilation (4DVar). The extended formulations reveal that the information content increases (or decreases) as the model error increase (or decrease) and/or become strongly (or weakly) correlated in 4D space. These properties are also highlighted by illustrative examples, and the extended formulations are shown to be potential useful for designing optimum phased-array radar scan configurations to maximize the extractable information contents from radar observations by a 4DVar analysis system.

Xu, Q., K. Nai, L. Wei, P. Zhang, Q. Zhao, P. Harasti, 2009: A real-time radar wind data quality control and analysis system for nowcast application. Extended Abstracts, International Symposium on Nowcasting and Very Short Range Forecasting (WSN09), Whistler, Canada, WMO, CD-ROM, 3.5.

A real-time radar wind analysis system has been developed for monitoring low-level wind conditions at high spatial and temporal resolution. By ingesting real-time wind observations from KTLX radar, Oklahoma Mesonet data and NOAA Profiler Network, this system produces and displays real-time vector wind field at each selected vertical level or on each conical surface of radar scans superimposed on radar reflectivity or radial-velocity image. The products are made available to NWS Norman Forecast Office. The early system has been evaluated and used to provide real-time winds to drive high-resolution emergency response dispersion models. The key technical elements developed in the system for the radar data quality control and wind analysis are presented with illustrative examples.

Xu, Q., K. Nai, L. Wei, Q. Zhao, 2009: An unconventional approach for assimilating aliased radar radial velocities. Tellus, 61A, 621-630.

An aliasing operator is introduced to mimic the effect of aliasing that causes discontinuities in radial-velocity observations, and to modify the observation term in the costfunction for direct assimilations of aliased radar radial-velocity observations into numerical models. It is found that if the aliasing operator is treated as a part of the observation operator and applied to the analysed radial velocity in a conventional way, then the analysis is not ensured to be aliased (or not aliased) in consistency with the aliased (or not aliased) observation at every observation point. Thus, the analysis-minus-observation term contains a large alias error whenever an inconsistency occurs at an observation point. This causes fine-structure discontinuities in the costfunction. An unconventional approach is thus introduced to apply the aliasing operator to the entire analysis-minus-observation term at each observation point in the observation term of the costfunction. With this approach, the costfunction becomes smooth and concave upwards in the vicinity of the global minimum. The usefulness of this approach for directly assimilating aliased radar radial-velocity observations under certain conditions is demonstrated by illustrative examples.

Available online at http://ejournals.ebsco.com/direct.asp?ArticleID=448381488B6BEA676451.

Xu, Q., 2009: Bayesian perspective of the unconventional approach for assimilating aliased radar radial velocities. Tellus, 61A, 631-634.

The global minimization problem for directly assimilating aliased radial velocities is derived in terms of Bayesian estimation by folding the domain of the original Gaussian non-aliased observation probability density function (pdf) into the Nyquist interval. By truncating the folded tails of the observation pdf, the observation term in the costfunction recovers the aliased observation term formulated previously by an unconventional approach. This establishes the theoretical basis for the unconventional approach and quantifies the involved approximation. The alias-robust radar wind analysis developed based on the unconventional approach is also revisited from the Bayesian perspective.

Available online at http://ejournals.ebsco.com/direct.asp?ArticleID=44A7933F6CED60B8DF35.

Xu, Q., K. Nai, L. Wei, 2010: Fitting VAD wind to aliased Doppler radial-velocity observations – A minimization problem with multiple minima. Quart. J. Roy. Meteor. Soc., 136, 451-461.

When the horizontal vector wind is estimated by the traditional velocity azimuth display (VAD) analysis from radar radial-velocity observations on a selected range circle, the observations should be thoroughly de-aliased first. When the effect of aliasing is formulated into the cost function, the VAD analysis can be applied to raw aliased radial-velocity observations, but the minimization problem for the VAD fitting is complicated by the multiple local minima caused by the zigzag-discontinuities of the aliasing operator. An efficient two-step VAD algorithm is thus developed in this paper to find the global minimum in properly transformed subspaces of the VAD wind parameters. The algorithm is then extended into a three-step volume velocity processing (VVP) method to estimate the vertical profile of horizontal winds from each volume of radar radial-velocity scans. Examples are presented to illustrate the capability and robustness of the method.

Xu, Q., L. Wei, W. Gu, J. Gong, Q. Zhao, 2010: A 3.5-Dimensional Variational Method for Doppler Radar Data Assimilation and Its Application to Phased-Array Radar Observations. Advances in Meteorology, 2010, 61-74.

A 3.5-dimensional variational method is developed for Doppler radar data assimilation. In this method, incremental analyses are performed in three steps to update the model state upon the background state provided by the model prediction. First, radar radial-velocity observations from three consecutive volume scans are analyzed on the model grid. The analyzed radial-velocity fields are then used in step 2 to produce incremental analyses for the vector velocity fields at two time levels between the three volume scans. The analyzed vector velocity fields are used in step 3 to produce incremental analyses for the thermodynamic fields at the central time level accompanied by the adjustments in water vapor and hydrometeor mixing ratios based on radar reflectivity observations. The finite element B-spline representations and recursive filter are used to reduce the dimension of the analysis space and enhance the computational efficiency. The method is applied to a squall line case observed by the phased-array radar with rapid volume scans at the National Weather Radar Testbed and is shown to be effective in assimilating the phased-array radar observations and improve the prediction of the subsequent evolution of the squall line.

Xu, Q., 2010: Modal and Nonmodal Growths of Symmetric Perturbations in Unbounded Domain. Journal of the Atmospheric Sciences, 67, 1996-2017.

Xu, Q., K. Nai, P. Zhang, S. Liu, D. Parrish, 2009: A new dealiasing method for Doppler velocity data quality control. Preprints, 34rd Conference on Radar Meteorology, Williamsburg, VA, USA, Amer. Meteor. Soc., CD-ROM, P9.6.

Available online at http://ams.confex.com/ams/34Radar/techprogram/paper_155947.htm.

Xu, Q., K. Nai, L. Wei, P. Zhang, S. Liu, D. Parrish, 2011: A VAD-based dealiasing method for radar velocity data quality control. Journal of Atmospheric and Oceanic Technology, 28, 50-62.

This paper describes a new VAD-based dealiasing method developed for automated radar radial-velocity data quality control to satisfy the high quality standard and efficiency required by operational radar data assimilation. The method is built on an alias-robust velocity azimuth display (AR-VAD) analysis. It upgrades and simplifies the previous three-step dealiasing method in three major aspects. First, the AR-VAD is used with sufficiently stringent threshold conditions in place of the original modified VAD for the preliminary reference check to produce alias-free seed data in the first step. Second, the AR-VAD is more accurate than the traditional VAD for the refined reference check in the original second step, so the original second step becomes unnecessary and is removed. Third, a block-to-point continuity check procedure is developed, in place of the point-to-point continuity check in the original third step, to enhance the use of available seed data in a properly enlarged block area around each flagged data point that is being checked with multiple threshold conditions to avoid false dealiasing. The new method has been tested extensively with aliased radial-velocity data collected under various weather conditions, including hurricane high-wind conditions. The robustness of the new method is exemplified by the result tested with a hurricane case. The limitations of the new method and possible improvements are discussed.

Xu, Q., 2011: Measuring information content from observations for data assimilation: Spectral formulations and their implications to observational data compression. Tellus, 63A, 793-804.

The previous singular-value formulations for measuring information content from observations are transformed into spectral forms in the wavenumber space for univariate analyses of uniformly distributed observations. The transformed spectral formulations exhibit the following advantages over their counterpart singular-value formulations: (i) The information contents from densely distributed observations can be calculated very efficiently even if the background and observation space dimensions become both too large to compute by using the singular-value formulations. (ii) The information contents and their asymptotic properties can be analyzed explicitly for each wavenumber. (iii) Super-observations can be not only constructed by a truncated spectral expansion of the original observations with zero or minimum loss of information but also explicitly related to the original observations in the physical space. The spectral formulations reveal that (i) uniformly thinning densely distributed observations will always cause a loss of information and (ii) compressing densely distributed observations into properly coarsened super-observations by local averaging may cause no loss of information under certain circumstances.

Xu, Q., 2011: Completeness of Normal Modes for Symmetric Perturbations in Vertically Bounded Domain. J. Met. Soc. Japan, 89, 389-397.

Perturbations generated by symmetric instability can be characterized, in terms of growing normal modes, by slantwise vertical motion bands similar to those observed in frontal rainbands. Nonmodal growths of symmetric perturbations, characterized also by slantwise vertical motion bands, can be produced by linear combinations of normal modes even before the basic state becomes symmetrically unstable to generate growing modes. In this paper, normal modes for nonhydrostatic symmetric perturbations in a vertically bounded domain are revisited and constructed by free modes obtained in unbounded domain. The constructed modes form a complete set in the full-solution space and thus can construct any admissible solutions to further explore nonmodal growths of symmetric perturbations in the vertically bounded domain beyond previous studies.

Xu, Q., J. Cao, S. Gao, 2011: Computing streamfunction and velocity potential in a limited domain. Part I: Theory and integral formulae. Adv. Atmos. Sci., 28, 1433-1444.

The non-uniqueness of solution and compatibility between the coupled boundary conditions in computing velocity potential and streamfunction from horizontal velocity in a limited domain of arbitrary shape are revisited theoretically with rigorous mathematic treatments. Classic integral formulas and their variants are used to formulate solutions for the coupled problems.
In the absence of data holes, the total solution is the sum of two integral solutions. One is the internally induced solution produced purely and uniquely by the domain internal divergence and vorticity, and its two components (velocity potential and streamfunction) can be constructed by applying Green's function for Poisson equation in unbounded domain to the divergence and vorticity inside the domain. The other is the externally induced solution produced purely but non-uniquely by the domain external divergence and vorticity, and the non-uniqueness is caused by the harmonic nature of the solution and the unknown divergence and vorticity distributions outside the domain. By setting either the velocity potential (or streamfunction) component to zero, the other component of the externally induced solution can be expressed by the imaginary (or real) part of the Cauchy integral constructed using the coupled boundary conditions and solvability conditions that exclude the internally induced solution. The streamfunction (or velocity potential) for the externally induced solution can also be expressed by the boundary integral of a double-layer (or single-layer) density function. In the presence of data holes, the total solution includes a data-hole--induced solution in addition to the above internally and externally induced solutions.

Xu, Q., L. Wei, 2011: Measuring information content from observations for data assimilation: Utilities of spectral formulations for radar data compression. Tellus, 63A, 1014-1027.

Utilities of the spectral formulations for measuring information content from observations are explored and demonstrated with real radar data. It is shown that the spectral formulations can be used (i) to precisely compute the information contents from one-dimensional radar data uniformly distributed along the radar beam, (ii) to approximately estimate the information contents from two-dimensional radar observations non-uniformly distributed on the conical surface of radar scan, and thus (iii) to estimate the information losses caused by super-observations generated by local averaging with a series of successively coarsened resolutions to find an optimally coarsened resolution for radar data compression with zero or near-zero minimal loss of information. The results obtained from the spectral formulations are verified against the results computed accurately but costly from the singular-value formulations. As the background and observation error power spectra can be derived analytically for the above utilities, the spectral formulations are computationally much more efficient and affordable than the singular-value formulations, even and especially when the background space and observation space are both extremely large and too large to be computed by the singular-value formulations.

Yeary, M., R. Palmer, M. Xue, T. Y. Yu, G. Zhang, A. Zahrai, J. Crain, Y. Zhang, R. Doviak, Q. Xu, P. Chilson, 2008: Introduction to multi-channel receiver development for the realization of multi-mission capabilities at the National Weather Radar Testbed. Extended Abstracts, 24rd Conference on Interactive Information Processing Systems (IIPS), New Orleans, LA, USA, AMS, 9A.3.

Yeary, M., G. E. Crain, A. Zahrai, T. Yu, R. Palmer, G. Zhang, Y. Zhang, R. J. Doviak, P. Chilson, M. Xue, Q. Xu, 2009: An update on multi-channel receiver development for the realization multi-mission capabilities at the national weather radar testbed. Extended Abstracts, 25th Conference on International Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, Phoenix, AZ, USA, AMS, CD-ROM, 8B.5.

Yeary, M., J. Crain, A. Zahrai, R. Kelley, J. Meier, Y. Zhang, I. Ivic, C. Curtis, R. Palmer, T. Y. Yu, G. Zhang, R. J. Doviak, P. B. Chilson, M. Xue, Q. Xu, 2010: A status report on the RF and digital components of the multi-channel receiver development at the National Weather Radar Testbed. Extended Abstracts, 26th Conference on International Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, Atlanta, GA, USA, AMS, CD-ROM, 14B.3.

Available online at http://ams.confex.com/ams/90annual/techprogram/paper_160298.htm.

Yussouf, N., D. J. Stensrud, 2006: Prediction of near surface variables at independent locations from a bias-corrected ensemble forecasting system. Monthly Weather Review, 134, 3415-3424.

The ability of a multimodel short-range bias-corrected ensemble (BCE) forecasting system, created as part of NOAA’s New England High Resolution Temperature Program during the summer of 2004, to obtain accurate predictions of near-surface variables at independent locations within the model domain is explored. The original BCE approach produces bias-corrected forecasts only at National Weather Service (NWS) observing surface station locations. To extend this approach to obtain bias-corrected forecasts at any given location, an extended BCE technique is developed and applied to the independent observations provided by the Oklahoma Mesonet. First, a Cressman weighting scheme is used to interpolate the bias values of 2-m temperature, 2-m dewpoint temperature, and 10-m wind speeds calculated from the original BCE approach at the NWS observation station locations to the Oklahoma Mesonet locations. These bias values are then added to the raw numerical model forecasts bilinearly interpolated to this same specified location. This process is done for each forecast member within the ensemble and at each forecast time. It is found that the performance of the extended BCE is very competitive with the original BCE approach across the state of Oklahoma. Therefore, a simple postprocessing scheme like the extended BCE system can be used as part of an operational forecasting system to provide reasonably accurate predictions of near surface variables at any location within the model domain.

Yussouf, N., D. J. Stensrud, 2007: Bias-Corrected Short-Range Ensemble Forecasts of Near-Surface Variables during the 2005/06 Cool Season. Weather and Forecasting, 22, 1274-1286.

A postprocessing method initially developed to improve near-surface forecasts from a summertime multimodel short-range ensemble forecasting system is evaluated during the cool season of 2005/06. The method, known as the bias-corrected ensemble (BCE) approach, uses the past complete 12 days of model forecasts and surface observations to remove the mean bias of near-surface variables from each ensemble member for each station location and forecast time. In addition, two other performance-based weighted-average BCE schemes, the exponential smoothing method BCE and the minimum variance estimate BCE, are implemented and evaluated. Values of root-mean-squared error from the 2-m temperature and dewpoint temperature forecasts indicate that the BCE approach outperforms the routinely available Global Forecast System (GFS) model output statistics (MOS) forecasts during the cool season by 9% and 8%, respectively. In contrast, the GFS MOS provides more accurate forecasts of 10-m wind speed than any of the BCE methods. The performance-weighted BCE schemes yield no significant improvement in forecast accuracy for 2-m temperature and 2-m dewpoint temperature when compared with the original BCE, although the weighted BCE schemes are found to improve the forecast accuracy of the 10-m wind speed. The probabilistic forecast guidance provided by the BCE system is found to be more reliable than the raw ensemble forecasts. These results parallel those obtained during the summers of 2002–04 and indicate that the BCE method is a promising and inexpensive statistical postprocessing scheme that could be used in all seasons.

Yussouf, N., D. J. Stensrud, 2008: Reliable Probabilistic Quantitative Precipitation Forecasts from a Short-Range Ensemble Forecasting System during the 2005/06 Cool Season. Monthly Weather Review, 136, 2157-2172.

A simple binning technique developed to produce reliable probabilistic quantitative precipitation forecasts (PQPFs) from a multimodel short-range ensemble forecasting system is evaluated during the cool season of 2005/06. The technique uses forecasts and observations of 3-h accumulated precipitation amounts from the past 12 days to adjust the present day’s 3-h quantitative precipitation forecasts from each ensemble member for each 3-h forecast period. Results indicate that the PQPFs obtained from this simple binning technique are significantly more reliable than the raw (original) ensemble forecast probabilities. Brier skill scores and areas under the relative operating characteristic curve also reveal that this technique yields skillful probabilistic forecasts of rainfall amounts during the cool season. This holds true for accumulation periods of up to 48 h. The results obtained from this wintertime experiment parallel those obtained during the summer of 2004. In an attempt to reduce the effects of a small sample size on two-dimensional probability maps, the simple binning technique is modified by implementing 5- and 9-point smoothing schemes on the adjusted precipitation forecasts. Results indicate that the smoothed ensemble probabilities remain an improvement over the raw (original) ensemble forecast probabilities, although the smoothed probabilities are not as reliable as the unsmoothed adjusted probabilities. The skill of the PQPFs also is increased as the ensemble is expanded from 16 to 22 members during the period of study. These results reveal that simple postprocessing techniques have the potential to provide greatly improved probabilistic guidance of rainfall events for all seasons of the year.

Yussouf, N., D. J. Stensrud, 2008: Impact of high temporal frequency radar data assimilation on storm-scale NWP model simulations. Preprints, 24th Conference on Severe Local Storms, Savannah, GA, USA, Amer. Meteor. Soc., 9B.1. [Available from Nusrat Yussouf, 120 David L. Boren Blvd., Norman, OK, USA, 73072.]

Radial-velocity and reflectivity observations from Doppler radars can provide important information for initializing numerical storm-scale prediction models and in diagnosing the evolution of severe weather events like thunderstorms and tornadoes. Recent research indicates that the assimilation of Doppler radar data using the Ensemble Kalman Filter (EnKF) approach generates good estimates of storm structure. While the conventional Doppler radar takes 4-5 minutes to scan a thunderstorm, the new and emerging Phased Array Radar (PAR) rapid and adaptive scanning technology can scan the same storm in less than a minute and can enhance the scanning angles in real time to get a better depiction of the storm top. Thus, in an effort to explore the impact of high temporal frequency PAR observations in storm assimilation, Observing System Simulation Experiments (OSSEs) are designed using the EnKF as a method for initializing storm-scale numerical forecast models.

Several different OSSEs are conducted with radial-velocity and reflectivity observations constructed from simulated supercells in native radar coordinates using a realistic volume averaging technique. Two sets of experiment are run for each OSSE. One experiment assimilates the simulated Doppler radar observations while the other experiment assimilates the high temporal frequency PAR observations. Results obtained are compared to document the value of new PAR observations to the creation of improved storm analyses and short-range ensemble forecasts.

Available online at http://ams.confex.com/ams/pdfpapers/141555.pdf.

Yussouf, N., D. J. Stensrud, 2010: Impact of Phased-Array Radar Observations over a Short Assimilation Period: Observing System Simulation Experiments Using an Ensemble Kalman Filter. Monthly Weather Review, 138, 517-538.

The conventional Weather Surveillance Radar-1988 Doppler (WSR-88D) scans a given weather phenomenon in approximately 5 min, and past results suggest that it takes 30–60 min to establish a storm into a model assimilating these data using an ensemble Kalman filter (EnKF) data assimilation technique. Severe weather events, however, can develop and evolve very rapidly. Therefore, assimilating observations for a 30–60-min period prior to the availability of accurate analyses may not be feasible in an operational setting. A shorter assimilation period also is desired if forecasts are produced to increase the warning lead time. With the advent of the emerging phased-array radar (PAR) technology, it is now possible to scan the same weather phenomenon in less than 1 min. Therefore, it is of interest to see if the faster scanning rate of PAR can yield improvements in storm-scale analyses and forecasts from assimilating over a shorter period of time. Observing system simulation experiments are conducted to evaluate the ability to quickly initialize a storm into a numerical model using PAR data in place of WSR-88D data. Synthetic PAR and WSR-88D observations of a splitting supercell storm are created from a storm-scale model run using a realistic volume-averaging technique in native radar coordinates. These synthetic reflectivity and radial velocity observations are assimilated into the same storm-scale model over a 15-min period using an EnKF data assimilation technique followed by a 50-min ensemble forecast. Results indicate that assimilating PAR observations at 1-min intervals over a short 15-min period yields significantly better analyses and ensemble forecasts than those produced using WSR-88D observations. Additional experiments are conducted in which the adaptive scanning capability of PAR is utilized for thunderstorms that are either very close to or far away from the radar location. Results show that the adaptive scanning capability improves the analyses and forecasts when compared with the nonadaptive PAR data. These results highlight the potential for flexible rapid-scanning PAR observations to help to quickly and accurately initialize storms into numerical models yielding improved storm-scale analyses and very short range forecasts.

Yussouf, N., D. J. Stensrud, 2012: Comparison of Single-Parameter and Multiparameter Ensembles for Assimilation of Radar Observations Using the Ensemble Kalman Filter.. Monthly Weather Review, 140, 562-586.

Observational studies indicate that the densities and intercept parameters of hydrometeor distributions can vary widely among storms and even within a single storm. Therefore, assuming a fixed set of microphysical parameters within a given microphysics scheme can lead to significant errors in the forecasts of storms. To explore the impact of variations in microphysical parameters, Observing System Simulation Experiments are conducted based on both perfect- and imperfect-model assumptions. Two sets of ensembles are designed using either fixed or variable parameters within the same single-moment microphysics scheme. The synthetic radar observations of a splitting supercell thunderstorm are assimilated into the ensembles over a 30-min period using an ensemble Kalman filter data assimilation technique followed by 1-h ensemble forecasts. Results indicate that in the presence of a model error, a multiparameter ensemble with a combination of different hydrometeor density and intercept parameters leads to improved analyses and forecasts and better captures the truth within the forecast envelope compared to single-parameter ensemble experiments with a single, constant, inaccurate hydrometeor intercept and density parameters. This conclusion holds when examining the general storm structure, the intensity of midlevel rotation, surface cold pool strength, and the extreme values of the model fields that are most helpful in determining and identifying potential hazards. Under a perfect-model assumption, the single- and multiparameter ensembles perform similarly as model error does not play a role in these experiments. This study highlights the potential for using a variety of realistic microphysical parameters across the ensemble members in improving the analyses and very short-range forecasts of severe weather events.

Zhang, G., Q. Cao, M. Xue, P. Chilson, M. Morris, R. Palmer, J. Brotzke, T. Schuur, E. Brandes, K. Ikeda, A. Ryzhkov, D. Zrnic, E. Jessup, 2008: A field experiment to study rain microphysics using video disdrometers and polarimetric S and X-band radars. Preprints, Symposium on Recent Developments in Atmospheric Applications of Radar and Lidar, New Orleans, LA, USA, American Meteorological Society, P2.23.

Zhang, J., K. Howard, X. Xu, 2008: A warm season radar QPE algorithm using adaptive Z-R relationships. Proc. World Environmental and Water Resources Congress 2008, Honolulu, HI, USA, Amer. Soc. Civil Engineers, CD-ROM, 420.pdf.

Zhang, G., S. Luchs, A. Ryzhkov, M. Xue, L. Ryzhkova, Q. Cao, 2011: Winter precipitation microphysics characterized by polarimetric radar and video disdrometer observations in central Oklahoma. Journal of Applied Meteorology and Climatology, 50, 1558-1570.

The study of precipitation in different phases is important to understanding the physical processes that occur in storms, as well as to improving their representation in numerical weather prediction models. A 2D video disdrometer was deployed about 30 km from a polarimetric weather radar in Norman, Oklahoma, (KOUN) to observe winter precipitation events during the 2006/07 winter season. These events contained periods of rain, snow, and mixed-phase precipitation. Five-minute particle size distributions were generated from the disdrometer data and fitted to a gamma distribution; polarimetric radar variables were also calculated for comparison with KOUN data. It is found that snow density adjustment improves the comparison substantially, indicating the importance of accounting for the density variability in representing model microphysics.

Zhao, Q., J. Cook, Q. Xu, P. Harasti, 2006: Using radar wind observations to improve mesoscale numerical weather prediction. Weather and Forecasting, 21, 502-522.

Zhao, Q., J. Cook, Q. Xu, P. Harasti, 2008: Improving short-term storm predictions by assimilating both radar radial-wind and reflectivity observations.. Weather and Forecasting, 23, 373-391.

Ziegler, C. L., M. S. Buban, E. N. Rasmussen, 2007: A Lagrangian Objective Analysis Technique for Assimilating In Situ Observations with Multiple-Radar-Derived Airflow. Monthly Weather Review, 135, 2417-2442.

A new Lagrangian analysis technique is developed to assimilate in situ boundary layer measurements using multi-Doppler-derived wind fields, providing output fields of water vapor mixing ratio, potential temperature, and virtual potential temperature from which the lifting condensation level (LCL) and relative humidity (RH) fields are derived. The Lagrangian analysis employs a continuity principle to bidirectionally distribute observed values of conservative variables with the 3D, evolving boundary layer airflow, followed by temporal and spatial interpolation to an analysis grid. Cloud is inferred at any grid point whose height z > zLCL or equivalently where RH ≥ 100%. Lagrangian analysis of the cumulus field is placed in the context of gridded analyses of visible satellite imagery and photogrammetric cloud-base area analyses. Brief illustrative examples of boundary layer morphology derived with the Lagrangian analysis are presented based on data collected during the International H2O Project (IHOP): 1) a dryline on 22 May 2002; 2) a cold-frontal–dryline “triple point” intersection on 24 May 2002. The Lagrangian analysis preserves the sharp thermal gradients across the cold front and drylines and reveals the presence of undulations and plumes of water vapor mixing ratio and virtual potential temperature associated with deep penetrative updraft cells and convective roll circulations. Derived cloud fields are consistent with satellite-inferred cloud cover and cloud-base locations.

Ziegler, C. L., E. N. Rasmussen, M. S. Buban, Y. P. Richardson, L. J. Miller, R. M. Rabin, 2007: The "Triple Point" on 24 May 2002 during IHOP. Part II: Ground-Radar and In Situ Boundary Layer Analysis of Cumulus Development and Convection Initiation. Monthly Weather Review, 135, 2443-2472.

Cumulus formation and convection initiation are examined near a cold front–dryline “triple point” intersection on 24 May 2002 during the International H2O Project (IHOP). A new Lagrangian objective analysis technique assimilates in situ measurements using time-dependent Doppler-derived 3D wind fields, providing output 3D fields of water vapor mixing ratio, virtual potential temperature, and lifted condensation level (LCL) and water-saturated (i.e., cloud) volumes on a subdomain of the radar analysis grid. The radar and Lagrangian analyses reveal the presence of along-wind (i.e., longitudinal) and cross-wind (i.e., transverse) roll circulations in the boundary layer (BL). A remarkable finding of the evolving radar analyses is the apparent persistence of both transverse rolls and individual updraft, vertical vorticity, and reflectivity cores for periods of up to 30 min or more while moving approximately with the local BL wind. Satellite cloud images and single-camera ground photogrammetry imply that clouds tend to develop either over or on the downwind edge of BL updrafts, with a tendency for clouds to elongate and dissipate in the downwind direction relative to cloud layer winds due to weakening updrafts and mixing with drier overlying air. The Lagrangian and radar wind analyses support a parcel continuity principle for cumulus formation, which requires that rising moist air parcels achieve their LCL before moving laterally out of the updraft. Cumuli form within penetrative updrafts in the elevated residual layer (ERL) overlying the moist BL east of the triple point, but remain capped by a convection inhibition (CIN)-bearing layer above the ERL. Dropsonde data suggest the existence of a convergence line about 80 km east of the triple point where deep lifting of BL moisture and locally reduced CIN together support convection initiation.

Ziegler, C. L., E. Mansell, J. Straka, D. MacGorman, D. Burgess, 2007: Impact of varying inversion strength on the electrification, lightning, kinematics, and microphysics in a simulated supercell storm. Preprints, 13th International Conference on Atmospheric Electricity, Beijing, China, International Commission on Atmospheric Electricity, 225-228.

Ziegler, C. L., E. R. Mansell, J. M. Straka, D. R. MacGorman, D. W. Burgess, 2008: Impact of Spatially Varying Inversion Strength on the Evolution of a Simulated Supercell Storm.. Extended Abstracts, 24th Conference on Severe Local Storms, Savannah, GA, USA, American Meteorological Society, P10.10.

Ziegler, C. L., K. Kuhlman, M. Biggerstaff, D. Betten, L. Wicker, E. Mansell, D. MacGorman, 2008: Evolution of low-level rotation in the tornadic 29 May 2004 Geary, Oklahoma supercell storm. Extended Abstracts, 24th Conference on Severe Local Storms, Savannah, GA, USA, AMS, 2.2.

Two mobile C-band Doppler SMART radars sampled a high-precipitation, tornadic supercell storm on 29 May 2004 during its severe, right-moving phase. Bulk parameters of the storm’s near-environment were obtained from approximately hourly, storm-following mobile GPS advanced upper-air sounding system (MGAUS) profiles obtained within the storm’s inflow extending from its initiation stage through the time of maximum low-level rotation in central Oklahoma. Analysis of the high-resolution, dual-Doppler three-dimensional airflow focuses on identifying downdraft source regions and estimating vorticity dynamical processes that contribute to the development of the low-level mesocyclonic and tornado-cyclonic circulations.

During the storm’s most intense phase, a storm-scale rear-flank downdraft boundary (RFDB) intersected the conventional forward flank downdraft boundary (FFDB) within the wrapping inflow to the intensifying low-level mesocyclone. The combined dataset facilitates preliminary testing of the hypothesis that the low-level mesocyclone is intensified via the classical mechanism of solenoidal (horizontal streamwise) vorticity generation followed by tilting and stretching with contributions from both the RFDB and FFDB. The evolution of the low-level angular momentum field will also be examined as a preliminary test of the alternate hypothesis that RFD development combined with strong stratification of horizontal angular momentum may combine to trigger a corner-flow collapse process leading to low-level mesocyclogenesis. This case illustrates the likely hypothesis testing procedures for other supercell storms sampled by the SMART radars during the upcoming VORTEX2 field project.

Ziegler, C. L., E. R. Mansell, E. C. Bruning, 2010: Impact of varying CCN concentration on the precipitation process in a simulated convective storm. Extended Abstracts, 13th Conference on Cloud Physics, Portland, OR, USA, American Meteorological Society, JP3.17.

The effects of the concentration of cloud condensation nuclei (CCN) on cloud microphysics have long been recognized, though the impact of CCN on the precipitation process in convective storms has been relatively unexplored. In the present study, the impact of varying CCN concentration on the microphysical structure and evolution of a small multicell storm is simulated with NSSL's 3-dimensional cloud model (COMMAS). The 2-moment microphysics scheme used for this study predicts the mass mixing ratio and number concentration of cloud droplets, rain, ice crystals, snow, graupel, and hail. CCN concentration is predicted as a single-category, monodisperse size spectrum approximating small aerosols. Bulk graupel and hail particle densities are also predicted as functions of rime layer density. Rime density in turn is a function of droplet size (affected by CCN concentration) and impact speed. Particle density (graupel and hail) is also used as a roughness parameter to scale the drag coefficient in the expression for particle fallspeed. The prediction of hydrometeor number concentration is particularly critical to the resolution of secondary ice nucleation at higher temperatures (-5 < T < -20 C) in the mixed phase updraft region, where ice crystals may be produced both by rime fracturing (Hallett–Mossop process) and by splintering of freezing drops in addition to a range of primary nucleation mechanisms. The prediction of cloud droplet and rain drop concentration and mass and their evolution proceeds through condensation growth, quasi-stochastic coalescence, and vertical transport to force the production of graupel embryos via drop freezing (Bigg freezing and crystal contact nucleation).

Model sensitivity tests with a range of ambient CCN concentrations (50 to 2000 per cubic cm) control the mean droplet size at cloud base, thereby modulating drop growth via condensation-coalescence in environments effectively ranging from maritime to continental. Higher CCN concentrations reduce the collision-coalescence formation of rain/drizzle, gradually increasing the proportion of precipitation mass produced by a graupel-based, cold-cloud riming process relative to the warm rain process. Even at the highest CCN concentrations, the primary process of simulated graupel initiation is via drop freezing. Even in the event of high CCN, the vapor supply in the updraft remains sufficient for droplets to eventually grow large enough via condensation to accelerate drop coalescence growth. The time-integrated volume containing graupel at heights above the freezing level increases monotonically with increasing CCN according to a power law relationship.

Precipitation in the simulated storm initiates as raindrops via stochastic collision-coalescence in regions of high cloud water content just below the freezing level. However as expected, formation of significant rain mixing ratios and simulated radar echo are delayed to later times and higher altitudes as CCN concentration is increased. Raindrops lifted in updraft begin freezing at temperatures around -10 deg. C to form graupel. The simulated time-height reflectivity, graupel mass, rain mass, and updraft volume all show systematic variations in their evolutions as base CCN concentration increases. Updraft volume tends to show three maxima at increasing altitudes of 2-3 km, 6-7 km, and 8-11 km at times of about 25-30 min, 40-55 min and 55-65 min in the simulation. Peak integrated rain mass above the freezing level is maximized at CCN concentration of about 500 cm-3, whereas maximum integrated graupel mass tends to increase monotonically with increasing CCN concentration. Average graupel density tends to decrease with increasing CCN concentration above 500 cm-3, as smaller droplets and lower graupel fall speeds lead to lower-density rime formation. As a by-product of the variation of simulated cloud and precipitation content with CCN, additional cloud simulations in which optional electrification mechanisms are activated manifest a sensitivity of microphysically-based charge separation and lightning production to CCN changes.

Available online at http://ams.confex.com/ams/13CldPhy13AtRad/techprogram/paper_171866.htm.

Ziegler, C. L., E. R. Mansell, J. M. Straka, D. R. MacGorman, D. W. Burgess, 2010: The impact of spatial variations of low-level stability on the life cycle of a simulated supercell storm. Monthly Weather Review, 138, 1738-1766.

This study reports on the dynamical evolution of simulated, long-lived right-moving supercell storms in a high-CAPE, strongly sheared mesoscale environment, which initiate in a weakly capped region and subsequently move into a cold boundary layer (BL) and inversion region before dissipating. The storm simulations realistically approximate the main morphological features and evolution of the 22 May 1981 Binger, Oklahoma, supercell storm by employing time-varying inflow lateral boundary conditions for the storm relative moving grid, which in turn are prescribed from a parent, fixed steady-state mesoscale analysis to approximate the observed inversion region to the east of the dryline on that day. A series of full life cycle storm simulations have been performed in which the magnitude of boundary layer coldness and the convective inhibition are varied to examine the ability of the storm to regenerate and sustain its main updraft as it moves into environments with increasing convective stability. The analysis of the simulations employs an empirical expression for the theoretical speed of the right-forward-flank outflow boundary relative to the ambient, low-level storm inflow that is consistent with simulated cold-pool boundary movement. The theoretical outflow boundary speed in the direction opposite to the ambient flow increases with an increasing cold-pool temperature deficit relative to the ambient BL temperature, and it decreases as ambient wind speed increases. The right-moving, classic (CL) phase of the simulated supercells is supported by increasing precipitation content and a stronger cold pool, which increases the right-moving cold-pool boundary speed against the constant ambient BL winds. The subsequent decrease of the ambient BL temperature with eastward storm movement decreases the cold-pool temperature deficit and reduces the outflow boundary speed against the ambient winds, progressing through a state of stagnation to an ultimate retrogression of the outflow boundary in the direction of the ambient flow. Onset of a transient, left-moving low-precipitation (LP) phase is initiated as the storm redevelops on the retrograding outflow boundary. The left-moving LP storm induces compensating downward motions in the inversion layer that desiccates the inflow, elevates the cloudy updraft parcel level of free convection (LFC), and leads to the final storm decay. The results demonstrate that inversion-region simulations support isolated, long-lived supercells. Both the degree of stratification and the coldness of the ambient BL regulate the cold-pool intensity and the strength and capacity of the outflow boundary to lift BL air through the LFC and thus regenerate convection, resulting in variation of supercell duration in the inversion region of approximately 1–2 h. In contrast, horizontally homogeneous conditions lacking an inversion region result in the development of secondary convection from the initial isolated supercell, followed by rapid upscale growth after 3 h to form a long-lived mesoscale convective system.

Ziegler, C., L. Wicker, D. Betten, M. Biggerstaff, E. Mansell, K. Kulman, D. MacGorman, 2009: Evolution of Downdraft thermodynamics and low-level rotation in the 29 May 2004 Geary, OK USA Supercell Storm.. Preprints, 5th European Conference on Severe Storms, Landshut, Germany, European Severe Storm Laboratory (ESSL), 29-30.

Available online at http://www.essl.org/ECSS/2009/preprints/O02-6-ziegler.pdf.

Ziegler, C. L., M. I. Biggerstaff, L. J. Wicker, D. W. Burgess, E. R. Mansell, C. S. Schwarz, P. Markowski, Y. P. Richardson, C. C. Weiss, 2010: Storm structure and decay process of the 9 June 2009 Greensburg, KS supercell during VORTEX2. Extended Abstracts, 25th Conference on Severe Local Storms, Denver, CO, USA, AMS, 7A.2.