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The 2014 Warn-on-Forecast and High-Impact Weather Workshop

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1 The 2014 Warn-on-Forecast and High-Impact Weather Workshop
RAP GSI 3DVAR-Ensemble Hybrid Data Assimilation with Global and Regional Ensembles Ming Hu1,2, David Dowell2, Steve Weygandt2, Stan Benjamin2, Jeff Whitaker3, Curtis Alxander1,2 1CIRES, University of Colorado at Boulder, CO, USA, 2 NOAA/ESRL/GSD/AMB, Boulder, CO, USA 3 NOAA/ESRL/PSD, Boulder, CO, USA 1st April 2014 National Weather Center, Norman OK

2 Introduction to RAP The Rapid Refresh (RAP) is an operational hourly updated regional numerical weather prediction system for aviation and severe weather forecasting. Configuration: 13 km horizontal North American grid Twice daily partial cycles from GFS atmospheric fields Hourly continue cycled land-surface fields Model: WRF-ARW dynamic core Data Assimilation: GSI 3D-VAR/GFS-ensemble hybrid data assimilation GSI non-variational cloud/precipitation hydrometeor (HM) analysis Diabatic Digital Filter Initialization (DDFI) using hourly radar reflectivity observation RAP version 1 operational implementation: 01 May 2012 RAP version 2 operational implementation: 24 February 2014

3 RAPv2 Data Assimilation
13 km RAP Cycle 13z 14z 15z 80-member GFS EnKF Ensemble forecast valid at 15Z (9-hr fcst from 6Z) GFS EnKF 80-member ensemble Available four times per day valid at 03z, 09z, 15z, 21z Obs Obs Obs GSI Hybrid GSI Hybrid GSI Hybrid 1 hr fcst HM Obs 1 hr fcst HM Obs HM Obs GSI HM Anx GSI HM Anx GSI HM Anx Refl Obs Refl Obs Refl Obs Digital Filter Digital Filter Digital Filter 18 hr fcst 18 hr fcst 18 hr fcst

4 RAP GSI 3DVar/Ensemble hybrid
RAPv2 hybrid configurations: With half Ensemble BE and half Static BE Ensemble forecasts are used on 3 times coarser resolution Analysis is on 2 time coarser analysis grid Ensemble forecasts are available every 6-hour Horizontal localization scale is 110 km Vertical localization scale is 3 grid level No vertical changes in localization scale Baseline retrospective tests May 28th to June 4th, 2012 Only difference are analysis: 3DVar versus Hybrid

5 RAPv2 baseline test results
RMSE Vertical Profiles: Soundings from mb RAP Hybrid RAP No Hybrid (3D-VAR) Upper Air RMS Vertical Profile for 6 hour forecast Wind RH T Upper Air RMS Time Series for 6 hour forecast Wind RH T Consistent Improved upper-air environment little impact to the ceiling forecast, surface forecast, precip forecast

6 Tuning for RAPv2 implementation
GFS/EnKF Ensemble forecast resolution used in the RAP GSI GSI Hybrid using Ensemble with 1X, 3X coarser grid GFS EnKF ensemble forecast available frequency GSI hybrid using ensemble forecast available hourly versus 6-hourly

7 Ensemble Resolution Test
RMSE Vertical Profiles: Soundings from mb Hybrid, 3X coarser GFS/EnKF Fcst Hybrid, 1X GFS/EnKF Fcst Upper Air RMS Vertical Profile for 6 hour forecast Wind RH T Summary: The GSI hybrid using coarser GFS/EnKF ensembles produces the same quality forecast as one using original resolution GFS/EnKF

8 GFS EnKF Ensemble forecast available frequency
Upper Air RMS Vertical Profile for 3 hour forecast Wind RH T Upper Air RMS Vertical Profile for 6 hour forecast Wind RH T Red - Hybrid with 6-hourly GFS/EnKF ensemble Forecast Blue - Hybrid with hourly GFS/EnKF ensemble Forecast

9 Further tests based on RAPv2
Ensemble BE and Static BE ratio GSI Hybrid with 50%, 75%, and 100% Ensemble BE Horizontal localization scale GSI hybrid with horizontal localization scale set to 110 km, 160 km, 220 km, and 330km Vertical localization scale GSI hybrid with vertical localization scale set to 3 levels, 9 levels, and (about 100hPa)

10 Ratio of Ensemble and Static BE
Upper Air RMS Vertical Profile for 3 hour forecast Wind RH T Upper Air RMS Vertical Profile for 6 hour forecast Wind RH T Red - Hybrid with 50% Ensemble BE and 50% Static BE Blue - Hybrid with 75% Ensemble BE and 25% Static BE Black - Hybrid with 100% Ensemble BE and 0% Static BE

11 Horizontal Localization Tests – Single T obs
s_ens_h = 550 km s_ens_h = 330 km Temperature analysis increments: Horizontal cross section Single temperature observation at 500 hPa Hybrid with 50% ensemble BE and 50% static BE Vertical localization scale is 3 levels s_ens_h = 220 km s_ens_h = 110 km

12 Horizontal Localization Test Results
Upper Air RMS Vertical Profile for 6 hour forecast Wind RH T Upper Air RMS Vertical Profile for 12 hour forecast Wind RH T Red Hybrid with s_ens_h=110 km Blue – Hybrid with s_ens_h=160 km Orange - Hybrid with s_ens_h=220 km Black – Hybrid with s_ens_h=330 km

13 Vertical Localization Test – Single obs
s_ens_v = 3 s_ens_v = 9 s_ens_v = -0.15 Single T obs at 500 hPa s_ens_v = 3 s_ens_v = 9 s_ens_v = -0.15 Single T obs at 1000 hPa Vertical cross section Hybrid with 75% ensemble BE and 25% static BE horizontal localization scale is 330 km Temperature analysis increments:

14 Vertical Localization Test Results
Upper Air RMS Vertical Profile for 00 hour forecast Wind RH T Upper Air RMS Vertical Profile for 06 hour forecast Wind RH T Red - hybrid with vertical localization scale = 3 Blue - hybrid with vertical localization scale = 9

15 Vertical Localization Test results
Upper Air RMS Vertical Profile for 00 hour forecast Wind RH T Upper Air RMS Vertical Profile for 06 hour forecast Wind RH T Red - hybrid with vertical localization scale = 3 Blue - hybrid with vertical localization scale = -0.15

16 Summary The RAP GSI 3DVar-Ensemble hybrid improved mid- to upper-tropospheric wind and moisture forecast up to 12-h The RAP GSI hybrid with ensemble forecast valid at each hourly analysis time gives a very slight benefit over one with 6h available ensemble forecast. 75% Ensemble BE in hybrid assimilation can further consistent improve wind and RH forecast, but results for 100% Ensemble BE are mixed Localization scales set to 110 horizontal and 3 levels vertical give the best short-term(0-9h) forecast Current GFS EnKF ensemble BE mainly improves larger scale features of the RAP forecast RAP GSI hybrid assim clearly improves RAP 6h forecasts for all upper air fields. Improvement consistent in time (only 6h shown) and at different vertical levels. Wind forecast is improved most, next is moisture, temperature is improved least among three fields Middle to upper-air levels show stronger improvement; low level and surface forecast impact is nearly neutral. Precipitation forecast impact is neutral except in US West CSI over 0.5 inch. Successful ensemble forecasts used by GSI hybrid is key of a successful GSI hybrid analysis The GFS/EnKF ensemble forecast low level spread is insufficient for RAP hybrid assimilation to make improvement at those levels Potential Benefits Situational awareness NWP through hourly updated high-resolution assimilation cycles can be improved from flow dependent analysis Lower troposphere and frontal structures for cold- and warm-season (largely convective) systems are highly anisotropic, and benefit from flow dependence in bkg error covariance Cloud/hydrometeor variables are also anisotropically distributed in these systems, needing situation-dependent balance among T, Qv, and cloud variables in analysis Challenges High-resolution hourly update cycles require huge computation cost and short cut-off time Ensemble forecasts need to be completed very quickly Ensemble forecasts tends to converge in hourly updated assimilation cycle (poor spread, especially for surface / lower trop.) For cloud analysis and severe weather, ensemble requires special physical configuration suitable for cloud and severe weather analysis

17 Future Work Need Regional Ensemble forecast BE: Near future:
Increase spread in low levels to improve surface data assimilation Create covariances for multi-species hydrometeor fields to improve cloud and storm assimilation Near future: Conduct regional ensemble forecasts initialized from GFS/EnKF ensemble forecasts Build and test RAP EnKF/Ensemble forecast system Build and test North American Rapid Refresh Ensemble (NARRE) by 2016, co-development between ESRL and NCEP/EMC Further tune hybrid parameters, such as localization, ratio of ensemble BE and static BE, vertical variance of this ratio Test RAP GSI hybrid using regional ensemble forecasts initialized from GFS/EnKF ensemble forecast to increase spread in low levels and create covariances for multi-species hydrometeor fields as used in RAP and HRRR Build and test RAP EnKF system Test North American Rapid Refresh Ensemble (NARRE) by 2016, co-development between ESRL and NCEP/EMC

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