Dr. Curtis Alexander (right) and Stan Benjamin (left) analyze a High Resolution Rapid Refresh weather model.
February 15, 2018
GSD’s Dr. Curtis Alexander was honored with the American Meteorological Society (AMS) Weather Analysis and Forecasting Committee Early Career Award at the AMS Annual Meeting in January 2018. The award is given to an individual who has made significant contributions to the weather forecasting enterprise and is on a path to becoming a science leader in the community.
Dr. Curtis Alexander leads the research organization that created NOAA’s High-Resolution Rapid Refresh (HRRR) weather model. The HRRR is the only hourly-updating, radar-initialized, storm-resolving weather forecast model running over the U.S., and to the best of our knowledge, the only one in the world. The innovative HRRR has demonstrated improved forecasts and warnings for high-impact, severe weather events across the U.S. since it was transitioned into NOAA National Weather Service office in 2014.
Dr. Alexander first developed the capability to run the 3km HRRR and companion 13km Rapid Refresh (RAP model, which provides the boundary conditions for the HRRR) forecast model systems in a non-operational, experimental mode to accelerate their development. He personally helped with all the transitions of the RAP and HRRR models into the operational model forecast system at the NWS National Centers for Environmental Prediction (NCEP). The experimental HRRR (aka. HRRRX) runs continuously at NOAA’s Earth System Research Laboratory’s Global System Division (GSD), which has provided the basis for two additional major upgrades of the operational HRRR that have been developed and transitioned into NWS since 2014. These upgrades have included significant improvements to summer and winter storm environments, advanced physics, data assimilation, and improved model initial conditions.
In 2013, Dr. Alexander established the first radar-reflectivity data assimilation technique for the 3-km HRRR. In addition, he developed and tested the first probabilistic thunderstorm product using time-lagged ensembles from the HRRR model, which subsequently led to aviation, severe weather and renewable energy diagnostic forecast products. He also established monitoring, diagnostic, and failover capabilities for RAP and HRRR model workflows on multiple high-performance computer systems and provides technical support to users of RAP and HRRR forecasts at the National Weather Service and in the academic and private sectors. Most recently, he helped guide a version of the HRRR to predict the impacts of the 2017 eclipse, and has produced rapid-response images of HRRRX runs covering hurricanes Harvey, Irma, and Maria for public outreach.
For more information contact: Susan Cobb 303-497-5093