Christa D. Peters-Lidard

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• 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

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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
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LIS-WRF Testbed for Studying Land-Atmosphere
Coupling
Coupled or Forecast Mode
Uncoupled or Analysis Mode
WRF
Station Data
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.
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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
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LIS Software Structure
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IHOP 2002 Case Study
Central US, Southern Great Plains
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LIS vs. WPS/NARR
Soils
Vegetation
NARR
WRF-Noah WRF-LIS
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LIS vs. WPS/NARR Initial Soil Moisture
Initial Soil Moisture Differences 00Z June 12,
2002
NARR
WRF-Noah WRF-LIS
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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 _at_ 1.25GHz each)

Spin-up Time Wall Clock Hours CPU Hours
6-month 2.1 65.8
1-year 4.15 148.6
2-year 8.1 296.8
3-year 12.2 409.3
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IHOP LIS Spin-Ups

• NLDAS/Stage 2/4 STATSGO Noah LSM gt NSN
• NLDAS/Stage 2/4 FAO Noah LSM gt NFN
• GDAS STATSGO Noah LSM gt GSN
• GDAS FAO Noah LSM gt GFN

199710
200201
NLDAS STG2
STG4
199710
200201
STG4
NLDAS STG2
199710
200001
BERG
GDAS
199710
200001
BERG
GDAS
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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 gt 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

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IHOP Verification Data
Multiple networks were used to validate of the
output of LIS/WRF simulations
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Fair Weather Test Case
June 6, 2002 Case

• Trough axis passing to east, anticyclonic
  vorticity advection -gt subsidence
• Light surface winds -gt good for examining
  impacts of land surface

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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

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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)

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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

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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

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Convective Test Case Results
Precipitation Verification
Used Stage II/IV analyses from NCEP
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Convective Test Case Results
Precipitation Verification
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IHOP 2002 PBL vs. EF Stratified by Soil Moisture

• MRF
• YSU
• MYJ

Dry Soil Moistures
Intermediate Soil Moistures
Wet Soil Moistures
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IHOP 2002 PBL vs. EF Stratified by GVF
x 30 Veg ? 60 Veg o 90 Veg

• MRF
• YSU
• MYJ

30
90
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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)