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1,2Jeffrey Walker and 2Paul
Houser |
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1Goddard Earth Sciences and
Technology Center |
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2NASA/Goddard Space Flight Center |
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http://land.gsfc.nasa.gov/~cejpw |
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Goal: Provide global land surface initialization
states for the retrospective period of 1979 to present. |
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A two-tiered approach. |
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Tier 1: Spin-up the land surface model off-line
from the GCM using the best atmospheric forcing data available. Minimizes
forcing bias! |
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Tier 2:Assimilate passive microwave remote
sensing observations of near-surface soil moisture from SMMR and SSM/I. Minimizes
model and forcing bias! |
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Re-Analysis Atmospheric Forcing Data Sets |
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ECMWF Re-analysis Advanced Global Data |
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4x/day,
01/79 - 12/93 |
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1.125 degrees
(Gaussian) |
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NCEP/NCAR Re-analysis |
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4x/day, 01/48 – 12/99 |
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2.5 x 2.5 degrees |
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Bias Correct Using Monthly Mean Observational
Data Sets |
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Observational Data Sets |
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NCAR Northern Hemisphere Sea Level Pressure |
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01/1899
– present; 5 x 5 degrees |
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Climate Research Unit (University of East
Anglia) Temperature and Precipitation |
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01/01 - 12/98; 0.5 x 0.5 degrees |
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Center for Climatic Research (University of
Delaware) Terrestrial Temperature and Precipitation |
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01/50 - 12/96 ; 0.5 x 0.5 degree |
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Global Precipitation Climatology Project (GPCP) |
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01/86 - 03/95; 2.5 x 2.5 degree |
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Langley Eight Year Shortwave and Longwave
Surface Radiation Budget |
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07/83 - 06/91 - in process of being extended;
2.5 x 2.5 degree |
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Accurate initial conditions for the land surface
are necessary for accurate predictions of precipitation. |
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LSM spin-up does not guarantee correct land
surface initialization. |
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Errors in land surface forecasts result from: |
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The memory of errors in LSM initialization. |
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Errors in atmospheric forcing data. |
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Errors in LSM physics. |
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Errors in soil and topographic data. |
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How can we evaluate the soil moisture
assimilation? |
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Soil moisture – ideal but limited data
available. United states has 19 stations in Illinois, 6 stations in Iowa
and transect of 89 points in New Mexico for SMMR period. |
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Analysis increments – only provides check for
systematic biases. |
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Runoff - data available but assumes that soil
moisture is the only reason for poor estimates. |
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Evapotranspiration – data not available and
assumes that soil moisture is the only reason for poor estimates. |
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Precipitation forecasts – assumes soil moisture
is the only reason for poor forecasts. |
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Other ? |
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Move towards a global implementation of the
assimilation. |
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Develop a set of global soil moisture
initialization states for the start of each month from 1979 to 1987 (term
of SMMR data). |
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