Research: Winter Weather

Just like any other storm at other times of the year, the right combination of ingredients is necessary for a winter storm to develop. Small variations in temperature determine whether precipitation will fall as sleet, snow, or freezing rain, making forecasting these events very difficult.

Winter Weather Research Areas

Dual Polarization Radar

NSSL was a pioneer in dual-polarization radar technology, now installed on NWS radars across the U.S. Forecasters use dual-polarization technology to clearly identify rain, hail, snow or ice pellets. This gives forecasters more confidence to accurately assess weather events because they will have more information to forecast what kind of precipitation there will be and how much to expect.


NSSL's Q2 is a suite of automated algorithms that uses multiple sensors to detect mixed precipitation. Enhanced reflectivity from the melting of frozen precipitation, called a “brightband” can cause severe overestimation of surface rainfall. Q2 also has a brightband identification algorithm to search for the brightband and report its height. The brightband height also reflects melting and therefore the height of the rain-snow line.

Numerical Forecasts of Snow and Mixed Precipitation Types

Forecasting the amount, location, and type of precipitation associated with winter storms can be quite challenging. Tests ongoing at NSSL show improved forecast accuracy of the location and timing of heavy snow when satellite and radar data are incorporated into the forecast models. Additional work shows promise for including observations from experimental ground-based observation systems in the numerical models. These results will be useful for forecasters to better anticipate when and where hazardous winter weather will occur so that municipalities can be better prepared for snow removal and de-icing efforts.

Detecting different Types of Precipitation

Detecting and forecasting different types of winter precipitation (freezing rain, sleet, snow, and rain) is difficult. We are developing an algorithm—the Winter Hydrometeor Classification Algorithm (HCA)— that uses radar data to sort winter precipitation into categories. The winter HCA combines polarimetric radar data with thermodynamic output from numerical models to produce a surface-based winter precipitation type. This will help the forecaster quickly assess the precipitation event and better forecast how much will fall.

Due to the lack of high quality surface observations of precipitation type, it is often difficult to evaluate algorithm performance. NSSL has two different projects to collect precipitation observations from the public:

  • The mostly student-run NSSL/CIMMS Severe Hazards Analysis and Verification Experiment (SHAVE) now collects winter weather precipitation reports through phone surveys. SHAVE reports, when combined with the voluntary reports collected by the NWS, creates a unique and comprehensive database of winter weather weather events used to evaluate algorithm performance.
  • NSSL's Meteorological Phenomena Identification Near the Ground (mPING) collects weather information from the public through their smart phone or mobile device.  Researchers compare the reports of precipitation with what is detected by the dual-polarized radar data to refine the HCA.

Southwest Colorado Radar Project

NSSL deploys the NOAA X-Pol (NOXP) mobile radar in southwestern Colorado as part of the Southwest Colorado Radar Project to collect data on snowfall in the area. NOXP is equipped with dual-polarization technology, which provides detailed information about the water content of snow, providing better estimates of precipitation amounts. Data from NOXP is being processed through NSSL's NMQ/Q2 multi-sensor precipitation estimation system. Forecasters will use the information to enrich their winter weather forecasts. Local data users include county search and rescue and airport operations.

Past Winter Weather Research

Winter Thunderstorms

NSSL researchers have studied winter thunderstorms. They found that there is some evidence that snowfall is heavier during reports of thunder and lighting at the same place and time. They also learned that these winter thunderstorms, although rare, occur most often in the central United States, Great Lakes, the east coast of the U.S. and Canada, and northern Canada during the winter and spring.

Freezing Rain Climatology

NSSL developed freezing rain climatology for local and national forecasting centers to help forecasters better understand regional and temporal susceptibility to freezing rain. They found that over New York and Pennsylvania, cold-air outbreaks interact with coastal cyclones, making the area more susceptible to freezing rain. Another area experiencing higher reports of freezing rain is in the Pacific Northwest, where storm systems generate precipitation and interact with cold air trapped in the Basin. A third area is located in the lee of the Appalachian Mountains. In this region, cold air damming is a common occurrence during the winter months, contributing to significant ice storms. Precipitation systems, often originating in the Gulf of Mexico or forming along the coastal front, interact with the subfreezing air in the damming region to produce freezing rain.

Radar observations of Lake-Effect snowstorms

NSSL studied the NWS radar monitoring of shallow lake-effect snowstorms over and around Lake Ontario, and made simulations of how detection could improve if the radar was operated using lower elevation angles. Currently, WSR-88D radars do not operate below +0.5 degrees. Shallow lake-effect snowstorms over and around lake Ontario pose a detection and warning challenge for the Buffalo, NY NWS Forecast Office. Limited measurements in the lower portions of the storms limit reliable quantitative precipitation estimation in much of the coverage area. Simulations showed when the elevation angle of the radar beam is lowered, shallow lake-effect storms would be detected over the entire lake and surrounding coastal regions and reliable QPE information would be available for the entire region.


The Intermountain Precipitation Experiment (IPEX) studied winter weather across northern Utah to develop a better understanding of the structure and evolution of winter storms. During January and February 2000, scientists made detailed observations of several large storms including one that produced three feet of snow. They also made unprecedented measurements of electrification and lightning in winter storms and the first dual-Doppler radar analysis of a cold front interacting with the Great Salt Lake and surrounding mountains. Researchers used data gathered to validate precipitation estimates from Doppler weather radars located at high elevations, to improve computer-based forecast models used in mountainous regions, and to study terrain-induced precipitation events and interactions that produce lake-effect snow bands.


Shannon, Ireland, was the base of field operations for the Fronts and Atlantic Storm Tracks Experiment (FASTEX), a multinational program that intensely documented and studied the life cycles of cyclones originating over the data-sparse North Atlantic during January and February 1997. During FASTEX, observations were made using up to seven research aircraft and four research ships. NSSL scientists played a lead role in the design and execution of FASTEX as principal investigators, aircraft chief scientists and members of the P-3 aircraft crew. FASTEX provided the first data sets to document the evolution of rapidly developing cyclones over the ocean. FASTEX was also the first project to target observations where numerical models indicated there would be a benefit to forecasts of cyclone development. Using data collected during FASTEX, scientists are making numerical simulations of cyclone structure and dynamics. Researchers expect results to apply to storm tracks over both the Pacific and Atlantic oceans.