The NOAA National Severe Storms Laboratory will host the fifth annual Warn-on-Forecast Workshop April 1-3, 2014 at the National Weather Center in Norman, Okla. NSSL’s Warn-on-Forecast research project aims to increase accuracy and lead times for warnings of storm-specific hazards through high-resolution weather prediction models.
The three-day event gives researchers an opportunity to share progress reports on a variety of operational and experimental models, techniques, and decision-making tools in support of the Warn-on-Forecast project.
Researchers will share results from models that attempt to use satellite, lightning, targeted observations, and radar data, including phased array radar data to predict individual thunderstorms. They will report on how these data impact the model by using case studies of past events, and show comparisons with what actually happened. The group will also address the challenge of how to predict the birth of a storm, and share results using various new techniques.
Warn-on-Forecast collaborators include NOAA National Severe Storms Laboratory and Earth System Research Laboratory’s Global Systems Division, NOAA National Weather Service and Storm Prediction Center, and The University of Oklahoma’s Center for the Analysis and Prediction of Storms.
NSSL scientists Jidong Gao, David Stensrud, and Louis Wicker were among five invited guest editors for a special issue of Advances in Meteorology, an open access international journal. This special issue focuses on high-resolution storm-scale computer models that ingest or assimilate radar data.
With the steady increase in computing power, operational centers throughout the world are preparing to run their weather computer models at resolutions high enough to predict individual thunderstorms. To do this, the models will be required to ingest observations.
This opportunity increases the demand for using radar data in storm-scale data assimilation in order to insert storm structures into model initial conditions.
The potential for successfully assimilating radar data into storm-scale numerical weather prediction (NWP) models is challenged by data quality control, proper estimation of the background error statistics, and the estimation of atmospheric state variables that are not directly observed by radar.
This special issue focuses on progress in some of these important areas. There are 12 papers published in this special issue, including seven papers from NSSL and five papers from other institutions. This special issue can be found at: http://www.hindawi.com/journals/amete/si/567170/