Warn on Forecast


History of Warn-on-Forecast concept and its development at NSSL

“Warn-on-Forecast” is a long arc concept requiring the efforts of dozens of research scientists and participation of a spectrum of groups who have an interest in creating and/or receiving probabilistic forecast guidance for severe weather decision making, including warnings. The publications in this section capture the big picture story of this multi-decade effort.

(1990) Numerical Prediction of Thunderstorms - Has its Time Come? - Doug Lilly

(2009) Convective-scale Warn-on-Forecast System: A Vision for 2020 - David Stensrud and others

(2013) Progress and Challenges with Warn-on-Forecast - David Stensrud and others

(2021) An article is planned which will again discuss progress, and a vision for 2030.

Early development of a WoF System (2009-2015) focusing on data assimilation and illustrated using case studies

WoF is attempting to generate very detailed, explicit (or at least nearly explicit) model and ensemble forecasts of individual thunderstorms. These forecasts will improve the lead time and specificity of warnings for things like tornadoes, large hail, and flash floods. This goal requires using operational and experimental meteorological data, and using it in a way that is computationally efficient so that forecasts can be delivered from the computer in a timely manner. Early tests sought to identify data assimilation methods that would deliver promising forecast results.

(2009) Additive Noise for Storm-scale Ensemble Data Assimilation - David Dowell and Lou Wicker

(2012) Impact of the Environmental Low-level Wind Profile on Forecasts of the 4 May 2007 Greensburg, Kansas, Tornadic Storm and Associated Mesocyclones - Daniel Dawson and others

(2011) Ensemble Kalman Filter Assimilation of Radar Observations of the 8 May 2003 Oklahoma City Supercell: Influences of Reflectivity Observations on Storm-scale Analyses - David Dowell and others

(2013) The Ensemble Kalman Filter Analyses and Forecasts of the 8 May 2003 Oklahoma City Tornadic Supercell Storm Using Single- and Double-Moment Microphysics Schemes - Nusrat Yussouf and others

(2014) Ensemble Kalman Filter Analyses and Forecasts of a Severe Mesoscale Convective System Using Different Choices of Microphysics Schemes - Dustan Wheatley and others

(2015) Storm-Scale Data Assimilation and Ensemble Forecasts for the 27 April 2011 Severe Weather Outbreak in Alabama - Nusrat Yussouf and others

(2018) Assimilation of GOES-13 Imager Clear-Sky Water Vapor (6.5μm) Radiances into a Warn-on-Forecast System - Thomas Jones and others

(2020) Assimilation of GOES-16 Radiances and Retrievals into the Warn-on-Forecast System - Thomas Jones and others

Predictability considerations

Predictability is strongly tied to resolution. What kind of phenomena can a model resolve depending on its resolution? Will the radar-range of a storm make a difference during data assimilation? Are storms in some meteorological environments more or less predictable than others? These and many other related questions were addressed in some of the early “research runs” of WoF.

(2013) A Real-Time Weather-Adaptive 3DVAR Analysis System for Severe Weather Detections and Warnings - Jidong Gao and others

(2013) Assessing Ensemble Forecasts of Low-Level Supercell Rotation within an OSSE Framework - Corey Potvin and Lou Wicker

(2015) Sensitivity of Idealized Supercell Simulations to Horizontal Grid Spacing: Implications for Warn-on-Forecast - Corey Potvin and Monte Flora

(2017) Sensitivity of Superell Simulations to Initial-Condition Resolution - Corey Potvin and others

(2015) Storm-Scale Data Assimilation and Ensemble Forecasting with the NSSL Experimental Warn-on-Forecast System. Part I: Radar Data Experiments - Dustan Wheatley and others

(2016) Storm-Scale Data Assimilation and Ensemble Forecasting with the NSSL Experimental Warn-on-Forecast System. Part II: Combined Radar and Satellite Data Experiments - Thomas Jones and others

(2019) Test of a Weather-Adaptive Dual-Resolution Hybrid Warn-on-Forecast Analysis and Forecast System for Several Severe Weather Events - Yunheng Wang and others

WoF for heavy rainfall

Though initial motivation for WoF was to improve the lead time for Tornado Warnings, the system has a myriad of other potential applications. One area of growth has been in flash flood prediction, including partnership with the Weather Prediction Center and the Hydrometeorological Testbed. Researchers are also testing the idea of using the WoFS in tandem with hydrologic models like NSSL’s FLASH to predict water behavior along rivers and streams.

(2016) Short-Term Probabilistic Forecasts of the 31 May 2013 Oklahoma Tornado and Flash Flood Event Using a Continuous-Update-Cycle Storm-Scale Ensemble System - Nusrat Yussouf and others

(2019) Application of the Warn-on-Forecast System for Flash-Flood Producing Heavy Convective Rainfall Events - Nusrat Yussouf and Kent Knopfmeier

(2020) The Coupling of NSSL Warn-on-Forecast and FLASH Systems for Probabilistic Flash Flood Prediction - Nusrat Yussouf and others


Objective study of verification data is essential to weighing different developmental versions of the WoFS, understanding how the output might be used in forecast operations, and identifying strengths to be maintained or weaknesses to be improved.

(2016) Application of Two Spatial Verification Methods to Ensemble Forecasts of Low-Level Rotation - Patrick Skinner and others

(2018) Object-Based Verification of a Prototype Warn-on-Forecast System - Patrick Skinner and others

(2018) Advancing from Convection-Allowing NWP to Warn-on-Forecast: Evidence of Progress - John Lawson and others

(2019) Object-Based Verification of Short-Term, Storm-Scale Probabilistic Mesocyclone Guidance from an Experimental Warn-on-Forecast System - Monte Flora and others

(2020) Assessing Systematic Impacts of PBL Schemes on Storm Evolution in the NOAA Warn-on-Forecast System - Corey Potvin and others

(2020) Effects of Horizontal Grid Spacing and Inflow Environment on Forecasts of Cyclic Mesocyclogenesis in NSSL’s Warn-on-Forecast System (WoFS) - Kelsey Britt and others

End user research

Ultimately a model system is a very powerful tool, and its value is best demonstrated by examining whether it helps end users such as NWS forecasters to deal with severe weather more swiftly and confidently. As WoFS begins to reach maturity and is used across a greater spectrum of events, NSSL will continue to assess its value with end users.

(2019) Meteorologists’ Interpretations of Storm-Scale Ensemble-Based Forecast Guidance - Katie Wilson and others