1 / 26

Hourly Updated NOAA NWP Models

Water-Vapor Analysis Uncertainty and Implications for Storm-Scale Radar-Data Assimilation David Dowell and Curtis Alexander NOAA ESRL GSD AMB, Boulder, CO Acknowledgments: Ming Hu, Steve Weygandt, Tanya Smirnova, Stan Benjamin, John Brown, Eric James, Patrick Hofmann, Jian Zhang.

fionan
Download Presentation

Hourly Updated NOAA NWP Models

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Water-Vapor Analysis Uncertaintyand Implications for Storm-ScaleRadar-Data AssimilationDavid Dowell and Curtis AlexanderNOAA ESRL GSD AMB, Boulder, COAcknowledgments:Ming Hu, Steve Weygandt, Tanya Smirnova, Stan Benjamin, John Brown, Eric James, Patrick Hofmann,Jian Zhang

  2. Hourly Updated NOAA NWP Models Rapid Refresh (RR) replaces RUC at NCEP in 2011 WRF, GSI with RUC features 13km Rapid Refresh (mesoscale) 13km RUC (mesoscale) 3km HRRR (storm-scale) RUC – current oper Model, new 18h fcst every hour High-Resolution Rapid Refresh Experimental 3km nest inside RR, new 15-h fcst every hour

  3. NOAA/ESRL/GSD/AMB Models

  4. HRRR Reflectivity Verification Eastern US, Reflectivity > 25 dBZ 11-20 August 2011 BIAS 03 km CSI 40 km RUC->HRRR Radar RR->HRRR Radar RR->HRRR No Radar RUC->HRRR No Radar Optimal RR->HRRR Radar RR->HRRR No Radar RUC->HRRR Radar RUC->HRRR No Radar Reflectivity DA in RR/RUC increases HRRR forecast skill HRRR bias depends strongly on parent model

  5. NOAA/ESRL/GSD/AMB Models

  6. more accuraterepresentation ofsystem maturity convection develops quickly (RR cycling, DDFI) obs 1-h fcstwithout 3-kmradar DA 1-h fcstwith 3-kmradar cycling 1-h fcstwith 3-kmradar DA CompositeReflectivity2100 UTC11 May 2011

  7. more accurateforecast ofconvective system propagation obs 6-h fcstwithout 3-kmradar DA 6-h fcstwith 3-kmradar DA CompositeReflectivity0200 UTC11 May 2011

  8. spurious convection spurious convection obs 6-h fcstwithout 3-kmradar DA 6-h fcstwith 3-kmradar DA CompositeReflectivity0200 UTC11 May 2011

  9. Impressions from Reflectivity DataAssimilation on HRRR (x=3 km) Grid • Forecast skill from radar DA • Improvement in 00-03 hr forecasts • Little change in 06-12 hr forecasts •  meso-/synoptic-scale forcing quickly dominates forecast? • Model inability to sustain some observed storms • Convective-scale model error • and/or storm-environment analysis error? • Spurious convective storms • Pervasive problem • Unclear solution on convective scale

  10. Back to the Mesoscale • Rapid Refresh (RR) and Rapid Update Cycle (RUC) • Similarities: resolution (Dx=13 km), 3DVar DA, hourly cycling • Differences: resulting HRRR forecasts • How different are the RR and RUC mesoscale analyses? • Two realizations of a mesoscale analysis • Differences representative of analysis uncertainty? RR->HRRR No Radar RUC->HRRR No Radar Optimal BIAS 03 km

  11. RR and RUC Temperature Bias CONUS All 00/12 UTC Raobs 08 July – 08 Sept 2011 00 hr (analysis) 12 hr fcsts RR RUC RR - RUC RR RUC RR - RUC Very small temperature bias in both RR and RUC

  12. RR and RUC Humidity Bias CONUS All 00/12 UTC Raobs 08 July – 08 Sept 2011 00 hr (analysis) 06 hr fcsts RR RUC RR - RUC RR RUC RR - RUC RUC/RR drier/moister below 650 mb, opposite above RR a closer fit to the observations by 6 hrs in lower trop Water vapor is the dominant source of the RH bias

  13. RR and RUC Humidity Bias CONUS All 00/12 UTC Raobs 11-22 August 2011 NO RADAR DA 00 hr (analysis) 06 hr fcsts RR RUC RR - RUC RR RUC RR - RUC Without radar DA, model bias even more pronounced

  14. HRRR Water Vapor Histograms CONUS 11-22 August 2011 NO RADAR DA 0 hr forecasts Surface ~800 mb RUC-> HRRR higher RR-> HRRR higher RUC-> HRRR higher RR-> HRRR higher Differences large enough to affect convective forecasts

  15. HRRR Reflectivity Verification Eastern US, Reflectivity > 25 dBZ 11-20 August 2011 NO RADAR DA 04 hr fcsts BIAS 03 km CSI 40 km Optimal Same Skill No difference RR->HRRR RUC->HRRR RR->HRRR – RUC->HRRR RR->HRRR RUC->HRRR RR->HRRR – RUC->HRRR

  16. HRRR Reflectivity Verification Eastern US, Reflectivity > 25 dBZ 11-20 August 2011 NO RADAR DA 04 hr fcsts BIAS 03 km CSI 40 km Optimal Same Skill No difference RR->HRRR RUC->HRRR RR->HRRR – RUC->HRRR RR->HRRR RUC->HRRR RR->HRRR – RUC->HRRR

  17. CompositeReflectivity0800 UTC13 Aug 2011 obs storm coverage somewhat underforecast (overforecast) in RUC->HRRR (RR->HRRR) 2-h fcstRUC->HRRR 2-h fcstRR->HRRR

  18. Water Vapor Analyses 8 m AGL0600 UTC13 Aug 2011 RR – RUC difference storm coverage somewhat underforecast (overforecast) in RUC->HRRR (RR->HRRR) RUC->HRRR RR->HRRR

  19. Water Vapor Analyses 2600 m AGL0600 UTC13 Aug 2011 RR – RUC difference storm coverage somewhat underforecast (overforecast) in RUC->HRRR (RR->HRRR) RUC->HRRR RR->HRRR

  20. Analysis Vertical Profiles0600 UTC13 Aug 2011 RR->HRRR RUC->HRRR RR->HRRR

  21. CompositeReflectivity1500 UTC14 Aug 2011 obs spurious convection in RR->HRRR 3-h fcstRUC->HRRR 3-h fcstRR->HRRR

  22. Water Vapor Analyses 8 m AGL1200 UTC14 Aug 2011 RR – RUC difference location of spurious convection in RR->HRRR RUC->HRRR RR->HRRR

  23. Water Vapor Analyses 600 m AGL1200 UTC14 Aug 2011 RR – RUC difference differences as much as 10 g/kg ! RUC->HRRR RR->HRRR

  24. Analysis Vertical Profiles1200 UTC14 Aug 2011 RR->HRRR Observed Profile RUC->HRRR RR->HRRR

  25. Water-Vapor Analysis • Small analysis differences near surface • Abundance of surface observations • Large analysis differences (several g/kg) at low levels above surface • Much larger than what is considered important for • convective-storm formation and evolution • Limited potential of storm-scale radar DA in the presence of large water-vapor analysis and forecast errors • Spurious convective storms • Model inability to sustain some observed storms • Reducing analysis uncertainty and bias • Radar and/or satellite data? • DA methods? => 3DVar cloud analysis; flow-dependent b. e. c. • Model improvements? => PBL scheme

More Related