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Christa D. Peters-Lidard Head, Hydrological Sciences Branch NASA Goddard Space Flight Center Workshop Objectives 1.Describe the LIS-WRF Coupled System.

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Presentation on theme: "Christa D. Peters-Lidard Head, Hydrological Sciences Branch NASA Goddard Space Flight Center Workshop Objectives 1.Describe the LIS-WRF Coupled System."— Presentation transcript:

1 Christa D. Peters-Lidard Head, Hydrological Sciences Branch NASA Goddard Space Flight Center Workshop Objectives 1.Describe the LIS-WRF Coupled System 2.Present example case studies using LIS-WRF 3.Understand WRF-CHEM status and plans 4.Discuss how GSFC and UMD can collaborate on WRF

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

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

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

5 LIS Software Structure

6 Central US, Southern Great Plains IHOP 2002 Case Study

7 LIS vs. WPS/NARR NARR WRF-Noah WRF-LIS SoilsVegetation

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

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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) Spin-up Time Wall Clock Hours CPU Hours 6-month2.165.8 1-year4.15148.6 2-year8.1296.8 3-year12.2409.3

15 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 200201 200001 BERG GDAS NLDAS + STG2 STG4 IHOP LIS Spin-Ups

16 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 LIS-WRF Configuration

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

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 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 Soil Moisture Evaluation

20 Fair Weather Test Case Results 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) Downward Radiation Fluxes

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 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 Soil Moisture Evaluation

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

24 Convective Test Case Results Precipitation Verification

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

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

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)


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