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The High-Resolution Rapid Refresh (HRRR): An Hourly Updating Convection-Allowing Forecast Model. Part II: Forecast Performance
by
Dowell, David C.
, Ladwig, Terra
, Alexander, Curtis R.
, Weygandt, Stephen S.
, James, Eric P.
, Smirnova, Tatiana G.
, Kenyon, Jaymes S.
, Benjamin, Stanley G.
, Olson, Joseph B.
, Turner, David D.
, Manikin, Geoffrey S.
, Brown, John M.
, Hu, Ming
in
Atmosphere
/ Aviation
/ Boundary layer evolution
/ Boundary layers
/ Ceiling and visibility
/ Ceilings (meteorology)
/ Cloud systems
/ Clouds
/ Convection
/ Data assimilation
/ Data collection
/ Diurnal cycle
/ Diurnal variations
/ Experiments
/ High resolution
/ Hypotheses
/ Mathematical models
/ Modelling
/ Physics
/ Planetary boundary layer
/ Plumes
/ Precipitation
/ Precipitation forecasting
/ Precipitation systems
/ Predictions
/ R&D
/ Radar
/ Radar reflectivity
/ Reflectance
/ Renewable energy
/ Research & development
/ Resolution
/ Seasons
/ Severe weather
/ Situational awareness
/ Smoke plumes
/ Storms
/ Stratiform clouds
/ Surface temperature
/ Time of use
/ Verification
/ Visibility
/ Weather forecasting
/ Wildfires
/ Winds
/ Winter precipitation
2022
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The High-Resolution Rapid Refresh (HRRR): An Hourly Updating Convection-Allowing Forecast Model. Part II: Forecast Performance
by
Dowell, David C.
, Ladwig, Terra
, Alexander, Curtis R.
, Weygandt, Stephen S.
, James, Eric P.
, Smirnova, Tatiana G.
, Kenyon, Jaymes S.
, Benjamin, Stanley G.
, Olson, Joseph B.
, Turner, David D.
, Manikin, Geoffrey S.
, Brown, John M.
, Hu, Ming
in
Atmosphere
/ Aviation
/ Boundary layer evolution
/ Boundary layers
/ Ceiling and visibility
/ Ceilings (meteorology)
/ Cloud systems
/ Clouds
/ Convection
/ Data assimilation
/ Data collection
/ Diurnal cycle
/ Diurnal variations
/ Experiments
/ High resolution
/ Hypotheses
/ Mathematical models
/ Modelling
/ Physics
/ Planetary boundary layer
/ Plumes
/ Precipitation
/ Precipitation forecasting
/ Precipitation systems
/ Predictions
/ R&D
/ Radar
/ Radar reflectivity
/ Reflectance
/ Renewable energy
/ Research & development
/ Resolution
/ Seasons
/ Severe weather
/ Situational awareness
/ Smoke plumes
/ Storms
/ Stratiform clouds
/ Surface temperature
/ Time of use
/ Verification
/ Visibility
/ Weather forecasting
/ Wildfires
/ Winds
/ Winter precipitation
2022
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Do you wish to request the book?
The High-Resolution Rapid Refresh (HRRR): An Hourly Updating Convection-Allowing Forecast Model. Part II: Forecast Performance
by
Dowell, David C.
, Ladwig, Terra
, Alexander, Curtis R.
, Weygandt, Stephen S.
, James, Eric P.
, Smirnova, Tatiana G.
, Kenyon, Jaymes S.
, Benjamin, Stanley G.
, Olson, Joseph B.
, Turner, David D.
, Manikin, Geoffrey S.
, Brown, John M.
, Hu, Ming
in
Atmosphere
/ Aviation
/ Boundary layer evolution
/ Boundary layers
/ Ceiling and visibility
/ Ceilings (meteorology)
/ Cloud systems
/ Clouds
/ Convection
/ Data assimilation
/ Data collection
/ Diurnal cycle
/ Diurnal variations
/ Experiments
/ High resolution
/ Hypotheses
/ Mathematical models
/ Modelling
/ Physics
/ Planetary boundary layer
/ Plumes
/ Precipitation
/ Precipitation forecasting
/ Precipitation systems
/ Predictions
/ R&D
/ Radar
/ Radar reflectivity
/ Reflectance
/ Renewable energy
/ Research & development
/ Resolution
/ Seasons
/ Severe weather
/ Situational awareness
/ Smoke plumes
/ Storms
/ Stratiform clouds
/ Surface temperature
/ Time of use
/ Verification
/ Visibility
/ Weather forecasting
/ Wildfires
/ Winds
/ Winter precipitation
2022
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The High-Resolution Rapid Refresh (HRRR): An Hourly Updating Convection-Allowing Forecast Model. Part II: Forecast Performance
Journal Article
The High-Resolution Rapid Refresh (HRRR): An Hourly Updating Convection-Allowing Forecast Model. Part II: Forecast Performance
2022
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Overview
The 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.
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