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contributor authorEric P. James
contributor authorCurtis R. Alexander
contributor authorDavid C. Dowell
contributor authorStephen S. Weygandt
contributor authorStanley G. Benjamin
contributor authorGeoffrey S. Manikin
contributor authorJohn M. Brown
contributor authorJoseph B. Olson
contributor authorMing Hu
contributor authorTatiana G. Smirnova
contributor authorTerra Ladwig
contributor authorJaymes S. Kenyon
contributor authorDavid D. Turner
date accessioned2023-04-12T18:53:09Z
date available2023-04-12T18:53:09Z
date copyright2022/08/01
date issued2022
identifier otherWAF-D-21-0130.1.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4290416
description abstractThe High-Resolution Rapid Refresh (HRRR) is a convection-allowing implementation of the Advanced Research version of the Weather Research and Forecast (WRF-ARW) Model that covers the conterminous United States and Alaska and runs hourly (for CONUS; every 3 h for Alaska) in real time at the National Centers for Environmental Prediction. The high-resolution forecasts support a variety of user applications including aviation, renewable energy, and prediction of many forms of severe weather. In this second of two articles, forecast performance is documented for a wide variety of forecast variables and across HRRR versions. HRRR performance varies across geographical domain, season, and time of day depending on both prevalence of particular meteorological phenomena and the availability of both conventional and nonconventional observations. Station-based verification of surface weather forecasts (2-m temperature and dewpoint temperature, 10-m winds, visibility, and cloud ceiling) highlights the ability of the HRRR to represent daily planetary boundary layer evolution and the development of convective and stratiform cloud systems, while gridded verification of simulated composite radar reflectivity and quantitative precipitation forecasts reveals HRRR predictive skill for summer and winter precipitation systems. Significant improvements in performance for specific forecast problems are documented for the upgrade versions of the HRRR (HRRRv2, v3, and v4) implemented in 2016, 2018, and 2020, respectively. Development of the HRRR model data assimilation and physics paves the way for future progress with operational convective-scale modeling.
publisherAmerican Meteorological Society
titleThe High-Resolution Rapid Refresh (HRRR): An Hourly Updating Convection-Allowing Forecast Model. Part II: Forecast Performance
typeJournal Paper
journal volume37
journal issue8
journal titleWeather and Forecasting
identifier doi10.1175/WAF-D-21-0130.1
journal fristpage1397
journal lastpage1417
page1397–1417
treeWeather and Forecasting:;2022:;volume( 037 ):;issue: 008
contenttypeFulltext


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