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| Titel |
US NOAA HRRR/RAP Model/Assimilation System 2016-17 Improvements for Aviation Weather Applications |
| VerfasserIn |
Stan Benjamin, Curtis Alexander, Stephen Weygandt, Ming Hu, Tanya Smirnova, Joseph Olson, John Brown, Jaymes Kenyon, Eric James, Isidora Jankov, Terra Ladwig |
| Konferenz |
EGU General Assembly 2017
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 19 (2017) |
| Datensatznummer |
250147032
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| Publikation (Nr.) |
 EGU/EGU2017-11126.pdf |
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| Zusammenfassung |
| To improve US short-range forecast guidance for aviation (and severe weather and energy applications), an operational upgrade of the Rapid Refresh (RAP, 13km) and High-Resolution Rapid Refresh (HRRR, 3km) model systems at NOAA’s NCEP occurred in August 2016. This coordinated upgrade (RAP version 3 and HRRR version 2, RAPv3/HRRRv2) includes enhancements to the data assimilation, model, and post-processing formulations that result in significant improvements to aviation forecasts for upper-air, surface, cloud and precipitation, and thunderstorms. Key changes will be described toward the next NCEP operational implementation (RAPv4/HRRRv3), planned for early 2018. Additional work is focused testing and refinement in related areas, including a real-time prototype High Resolution Rapid Refresh Ensemble (HRRRE), a post-processing-based HRRR-time-lagged ensemble (HRRR-TLE), and a HRRR domain covering Alaska (HRRR-AK).
In this presentation, a recap of the RAPv3/HRRRv2 upgrade and forecast improvements will be provided, followed by a description of the planned improvements for RAPv4/HRRRv3 and impacts for aviation guidance for winds (turbulence), clouds (ceiling and visibility) and near-surface (terminal) forecasts. ESRL is now showing strong further improvements from model and assimilation improvements from the new RAPv4/HRRRv3 including further enhancements to the model physics components (aerosol-aware Thompson microphysics, MYNN PBL scheme, Smirnova land-surface model), and testing of a new vertical coordinate). The interaction of the various physics modules has been a particular research focus area, with modifications in place that further reduce various physics-related model biases. HRRRv3/RAPv4 data assimilation enhancements include improved radar and cloud assimilation, addition of data from TAMDAR aircraft, radar radial velocity data, and GOES cloud-top cooling rate data).
HRRR time-lagged ensemble products are now being produced in real-time for many variables, with grids being transferred to the US Aviation Weather Center and other operational centers to estimate hourly-updating likelihood probabilities of various weather hazards for aviation over the CONUS out to 24 hours. These weather hazards include both convection (intensity and radar echo-top heights) and low ceiling/visibility (including flight rules). In addition, a full 3-km HRRR ensemble with 40-member data assimilation was tested in real-time during the spring of 2016, with additional real-time testing scheduled to resume in March 2017. A brief overview of these efforts will be presented. |
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