10.4 Improvements in the RAP/HRRR Modeling Systems for Renewable Energy Forecast Applications

Wednesday, 15 January 2020: 11:00 AM
256 (Boston Convention and Exhibition Center)
Jaymes S. Kenyon, CIRES, Univ. of Colorado, and NOAA/ESRL, Boulder, CO; and J. Olson, S. G. Benjamin, D. D. Turner, M. Marquis, W. M. Angevine, E. P. James, R. Ahmadov, T. T. Ladwig, D. C. Dowell, J. M. Brown, M. D. Toy, C. Alexander, and G. A. Grell

NOAA's Rapid Refresh (RAP) and High-Resolution Rapid Refresh (HRRR) are hourly updating forecast models that support short-range forecast interests within the contiguous United States, to include renewable-energy applications. In May 2020, these models will be upgraded to RAPv5 and HRRRv4, and with this upgrade, numerous improvements in RAP/HRRR data assimilation and model physics will be installed into real-time operational production.

This presentation will describe the key advancements in RAPv5 and HRRRv4 that will benefit solar and wind forecasting on hourly to day-ahead timescales. Most notably, HRRRv4 will be initialized from the 36-member HRRR Data Assimilation System (HRRRDAS), which will provide the HRRR with improved initial conditions through better use of observations and model background. RAPv5 and HRRRv4 will predict smoke transport and its impact on radiation, providing improved forecasts of solar irradiance in the presence of wildfire smoke. Additionally, the representation of boundary-layer processes and subgrid-scale cloudiness are further refined in RAPv5/HRRRv4, with corresponding improvements in solar irradiance forecasts in the presence of partial cloudiness. Lastly, with future RAP/HRRR development shifting from the WRF–ARW to the FV3 modeling framework (but with similar physics and assimilation), we will provide perspective on the forecast improvements accrued by the RAP and HRRR models since their inception, as well as the development priorities moving forward.

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