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dc.contributor.authorDavid C. Dowell
dc.contributor.authorCurtis R. Alexander
dc.contributor.authorEric P. James
dc.contributor.authorStephen S. Weygandt
dc.contributor.authorStanley G. Benjamin
dc.contributor.authorGeoffrey S. Manikin
dc.contributor.authorBenjamin T. Blake
dc.contributor.authorJohn M. Brown
dc.contributor.authorJoseph B. Olson
dc.contributor.authorMing Hu
dc.contributor.authorTatiana G. Smirnova
dc.contributor.authorTerra Ladwig
dc.contributor.authorJaymes S. Kenyon
dc.contributor.authorRavan Ahmadov
dc.contributor.authorDavid D. Tu
dc.date.accessioned2023-04-12T18:52:52Z
dc.date.available2023-04-12T18:52:52Z
dc.date.copyright2022/08/01
dc.date.issued2022
dc.identifier.otherWAF-D-21-0151.1.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4290409
dc.description.abstractThe High-Resolution Rapid Refresh (HRRR) is a convection-allowing implementation of the Advanced Research version of the Weather Research and Forecasting (WRF-ARW) Model with hourly data assimilation that covers the conterminous United States and Alaska and runs in real time at the NOAA/National Centers for Environmental Prediction (NCEP). Implemented operationally at NOAA/NCEP in 2014, the HRRR features 3-km horizontal grid spacing and frequent forecasts (hourly for CONUS and 3-hourly for Alaska). HRRR initialization is designed for optimal short-range forecast skill with a particular focus on the evolution of precipitating systems. Key components of the initialization are radar-reflectivity data assimilation, hybrid ensemble-variational assimilation of conventional weather observations, and a cloud analysis to initialize stratiform cloud layers. From this initial state, HRRR forecasts are produced out to 18 h every hour, and out to 48 h every 6 h, with boundary conditions provided by the Rapid Refresh system. Between 2014 and 2020, HRRR development was focused on reducing model bias errors and improving forecast realism and accuracy. Improved representation of the planetary boundary layer, subgrid-scale clouds, and land surface contributed extensively to overall HRRR improvements. The final version of the HRRR (HRRRv4), implemented in late 2020, also features hybrid data assimilation using flow-dependent covariances from a 3-km, 36-member ensemble (“HRRRDAS”) with explicit convective storms. HRRRv4 also includes prediction of wildfire smoke plumes. The HRRR provides a baseline capability for evaluating NOAA’s next-generation Rapid Refresh Forecast System, now under development.
dc.publisherAmerican Meteorological Society
dc.titleThe High-Resolution Rapid Refresh (HRRR): An Hourly Updating Convection-Allowing Forecast Model. Part I: Motivation and System Description
dc.typeJournal Paper
dc.journal.volume37
dc.journal.issue8
dc.journal.titleWeather and Forecasting
dc.identifier.doi10.1175/WAF-D-21-0151.1
dc.journal.fristpage1371
dc.journal.lastpage1395
dc.page1371–1395
dc.treeWeather and Forecasting:;2022:;volume( 037 ):;issue: 008
dc.contenttypeFulltext


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