CSU machine learning model helps forecasters improve confidence in storm prediction

Over the last several years, Russ Schumacher, professor in the Department of Atmospheric Science and Colorado State Climatologist, has led a team developing a sophisticated machine learning model for advancing skillful prediction of hazardous weather across the continental United States. First trained on historical records of excessive rainfall, the model is now smart enough to make accurate predictions of events like tornadoes and hail four to eight days in advance – the crucial sweet spot for forecasters to get information out to the public so they can prepare. The model is called CSU-MLP, or Colorado State University-Machine Learning Probabilities. 

People on a zoom call through a laptop

Webinar: FY23 Notice of Funding Opportunity

WPO recently held a webinar hosted by the NOAA Central Library on the FY23 Notice of Funding Opportunity. Our Program Managers spoke in detail about about this year’s competitions for Observations, Social and Behavioral Sciences, Innovations for Community Modeling, and VORTEX-USA. We also shared tips on how to write a compelling proposal, how to successfully…

Dropsonde Profile

Improving the use of Dropsondes in NOAA Operations with HWRF (Sippel FY17)

This project implements an algorithm to estimate drift of the dropsondes in the data assimilation system of the operational Hurricane Weather Research and Forecasting model. With the help of JTTI funds this dropsonde drift algorithm was operational tested and implemented in the National Weather Service (NWS) operations.  NWS is now able to assimilate more dropsonde observations…

RiVorS deployment (Photo by Matthew Mahalik/OU CIMMS)

Implications of Inconsistent Visuals

On end user uncertainty, risk perception, and behavioral intentions (Grundstein FY18) Within the last decade, operational meteorologists have raised concerns that the availability of weather information from a variety of sources may contribute to a perception that weather risk messages are inconsistent and result in negative consequences among end users. The challenge, however, is that…