Research Tools: Forecast


Forecasting a Continuum of Environmental Threats (FACETs) serves as a broad-based framework and strategy to help focus and direct efforts related to next-generation science, technology and tools for forecasting environmental hazards. FACETS will address grid-based probabilistic threats, storm-scale observations and guidance, the forecaster, threat grid tools, useful output, effective response, and verification.


The Warn-on-Forecast (WoF) research project will deliver a set of enabling technologies for FACETs on a variety of space and time scales. WoF aims to create computer-model projections that accurately predict storm-scale phenomena such as tornadoes, large hail, and extremely localized rainfall. If Warn-on-Forecast is successful, forecasters will be provided with reliable guidance for issuing tornado, severe thunderstorm, and flash flood warnings up to an hour before they strike.


Recent advances in computing technology have enabled the use of numerical weather prediction models with high enough resolution to adequately depict individual thunderstorms across very large areas such as the entire continental United States. These models, which are known as convection-allowing models, or CAMs, are extremely valuable to forecasters because they provide information on storm types, which are strongly related to expected hazards. Despite the scientific advances enabled by CAMs, many unresolved research questions need to be addressed to fully exploit the information from CAMs and provide reliable probabilistic information to forecasters. A large amount of NSSL research is devoted to these areas.

View real-time data from CAMS →


The Weather Research and Forecast (WRF), a precursor to CAMS, was the product of a unique collaboration between the meteorological research and forecasting communities. Its level of sophistication wass appropriate for cutting edge research, yet it operated efficiently enough to produce high resolution guidance for front-line forecasters in a timely manner. Working at the interface between research and operations, NSSL scientists were major contributors to WRF development efforts and provided leadership in the operational implementation and testing of WRF. The NSSL WRF generated daily, real-time 1–36 hour experimental forecasts at a 4km resolution of precipitation, lightning threat, and more.

WoF Tornado Threat Prediction

WoF Tornado Threat Prediction (WoF-TTP) is a research project to develop a 0–1 hour, 1-km resolution suite of highly detailed computer models to forecast individual convective storms and their potential tornadoes. Target future average lead-time for tornado warnings via WoF-TTP is 40–60 minutes. The technology and science developed to achieve the WoF-TTP goal will likely improve the prediction of other convective weather threats such as large hail and damaging winds.


NSSL developed and implemented the real-time Multi-Radar Multi-Sensor system in 2004, integrating data from multiple radar networks, surface and upper air observations, lightning detection systems, satellite and numerical weather prediction models. The data is used to estimate and forecast precipitation locations, amounts, and types.

MRMS was transitioned into operations at the National Center for Environmental Prediction in 2014 and provided severe weather and precipitation products for improved decision-making capability within NOAA. The operational MRMS QPE products have high resolution and rapid updating capabilities. The products are also used for verification of satellite rain products and for verification of quantitative rain forecasts from numerical weather prediction models. MRMS serves as a powerful tool for the creation and evaluation of new techniques, strategies and applications to better QPE. As new concepts are developed, they can be tested by easily plugged in and out of MRMS. This process facilitates a rapid science-to-operations transition of new MRMS applications and products for flood and flash flood predictions and water resources management.


NSSL’s Mesoscale Ensemble (NME) is an experimental analysis and short-range ensemble forecast system. These forecasts are designed to be used by forecasters as a 3-D hourly analysis of the environment, a very important tool in the severe weather forecasting process.