Christa D. Peters-Lidard Head, Hydrological Sciences Branch NASA Goddard Space Flight Center

1. Christa D. Peters-Lidard • Head, Hydrological Sciences Branch • NASA Goddard Space Flight Center • Workshop Objectives • Describe the LIS-WRF Coupled System • Present example case studies using LIS-WRF • Understand WRF-CHEM status and plans • Discuss how GSFC and UMD can collaborate on WRF

2. The LIS-WRF Coupled Testbed • Christa D. Peters-Lidard1, Sujay V. Kumar2,1, Charles J. Alonge3,1, • Joseph A. Santanello, Jr.4,1, Joseph L. Eastman2,1, Wei-Kuo Tao4 • 1NASA Goddard Space Flight Center • Hydrological Sciences Branch, Code 614.3 • 2University of Maryland at Baltimore County • Goddard Earth Sciences Technology Center • 3SAIC • 4University of Maryland at College Park • Earth System Science Interdisciplinary Center • 5NASA Goddard Space Flight Center • Mesoscale Atmospheric Processes Branch, Code 613.1 • Acknowledgements: NASA ESTO, NASA NEWS, AFWA

3. LSM Initial Conditions LIS-WRF Testbed for Studying Land-Atmosphere Coupling Uncoupled or Analysis Mode Coupled or Forecast Mode Station Data WRF Global, Regional Forecasts and (Re-)Analyses ESMF MYJ, YSU, MRF PBL Schemes LSM Physics (Noah, Mosaic, CLM2, Catchment, VIC, HySSiB) Satellite Products GCE, LIN, WSM Microphysics Schemes Kumar, Peters-Lidard et al, EMS, 2006; 2007.

4. LIS Overview Inputs Physics Outputs Topography, Soils Land Surface Models Soil Moisture & Temperature Land Cover, Vegetation Properties Evaporation, Sensible Heat Flux Meteorology Runoff Data Assimilation Modules Snow Soil Moisture Temperature Snowpack Properties

5. LIS Software Structure

6. IHOP 2002 Case Study Central US, Southern Great Plains

7. LIS vs. WPS/NARR Soils Vegetation NARR WRF-Noah WRF-LIS

8. LIS vs. WPS/NARR Initial Soil Moisture Initial Soil Moisture Differences 00Z June 12, 2002 NARR WRF-Noah WRF-LIS

14. Offline LIS/Noah Spin-Up Results • Near-surface fields spin up quickly (about 1.5 years), however, longer spin-ups are needed it can take longer than 2 years for layers 3 and 4 to spin up • The 2 year spin-up removes most of anomalies introduced by initialization with the NARR land surface states. Although, a three year simulation is recommended in semi-arid to arid regions where anomalies can persist much longer • A noteworthy benefit of using LIS for offline spin-ups is the execution time for offline spin-ups (all simulations executed over 64 processors @ 1.25GHz each)

15. IHOP LIS Spin-Ups • NLDAS/Stage 2/4 + STATSGO + Noah LSM => NSN • NLDAS/Stage 2/4 + FAO + Noah LSM => NFN • GDAS + STATSGO + Noah LSM => GSN • GDAS + FAO + Noah LSM => GFN 199710 NLDAS + STG2 200201 STG4 199710 200201 STG4 NLDAS + STG2 199710 BERG 200001 GDAS 199710 BERG 200001 GDAS

16. LIS-WRF Configuration • LIS/WRF configuration: • Goddard Shortwave Radiation Scheme • RRTM Longwave Radiation • Ferrier Microphysics • Mellor-Yamada-Janic PBL Scheme (TKE based) • Monin-Obukov Surface Layer (Janic) • No cumulus parameterization • 1km horizontal grid spacing –> 6 second time step • 44 Vertical Levels • Radiation packages called every 60 seconds • LIS invoked at every time step • All simulation were initialized at 00Z and integrated out to 36 hours

17. IHOP Verification Data Multiple networks were used to validate of the output of LIS/WRF simulations

18. Fair Weather Test Case June 6, 2002 Case • Trough axis passing to east, anticyclonic vorticity advection -> subsidence • Light surface winds -> good for examining impacts of land surface

19. Fair Weather Test Case Results Soil Moisture Evaluation • NSN and GSN runs best for top two soil moisture layers • GDAS runs validate best in the third soil moisture layer of Noah • NARR good at 10cm, too dry below

20. Fair Weather Test Case Results Downward Radiation Fluxes • Goddard Shortwave Radiation scheme exhibiting a high bias in SWDN • RRTM Longwave performs well with respect to LWDN (small high bias during the day and into the evening)

21. Convective Test Case June 12, 2002 Case • Light winds at the surface, southwesterly and westerly flow aloft • Weak synoptic forcing • Small Capping Inversion • Difficult to forecast convective intiation

22. Convective Test Case Results Soil Moisture Evaluation • NLDAS land analyses exhibiting more of a dry bias than the GDAS based runs • NARR initial conditions too dry • GDAS provides better initial soil moisture conditions for all three layers validated

23. Convective Test Case Results Precipitation Verification Used Stage II/IV analyses from NCEP

24. Convective Test Case Results Precipitation Verification

25. IHOP 2002 PBL vs. EF Stratified by Soil Moisture • = MRF • = YSU • = MYJ Dry Soil Moistures Intermediate Soil Moistures Wet Soil Moistures

26. IHOP 2002 PBL vs. EF Stratified by GVF x = 30% Veg ▪ = 60% Veg o = 90% Veg • = MRF • = YSU • = MYJ 30% 90%

27. Conclusions and Future Work • LIS-WRF coupled system is a testbed for studying mesoscale land-atmosphere interactions • Choice of parameters and spin-up data can have significant impacts on results • In general, the GDAS runs outperformed the NLDAS runs (better fluxes and 2m temperature/dewpoint, and heaviest total precipitation amounts), which indicates spin-up forcing may be more important than the parameter datasets • Interactions between various parameterizations (LSM, PBL, Radiation, Microphysics) complex and probably tuned. • Currently working to add CLM2 runs to the series of experiments and NARR runs to the analysis • Possibly need to explore object-based verification methods (Ebert and McBride 2002, Davis et al. 2006) • Need to further examine the quality of each offline simulation (verify more than just the initial conditions)