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1,2Jeffrey P. Walker and 2Paul
R. Houser |
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1Universities Space Research
Association |
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2NASA/Goddard Space Flight Center |
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Accurate soil moisture forecasts are necessary
for accurate predictions of precipitation. |
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LSM spin-up does not guarantee correct soil
moisture initialization. |
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Errors in soil moisture forecasts result from: |
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The memory of errors in LSM soil moisture
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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The process of finding the model representation
which is most consistent with the observations. |
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Forecasting Equations |
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States: |
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Covariances: |
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Observation Equation |
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Surface Moisture: |
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Updating Equations |
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States: |
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Covariances: |
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srfexc = srfexc – es – srflow + i + a |
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rzexc
= rzexc – ev + srflow – rzflow
+ b |
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catdef = catdef + et – rzflow + baseflow
+ c |
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where a, b and c are correction terms to
ensure mass
balance |
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Using a first-order Taylor series
expansion: |
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“Truth” Data Set |
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Spin-up catchment-based LSM for 1987 using
ISLSCP forcing data. |
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Run the simulation for 1987 using ISLSCP forcing
data and output surface moisture data as “observations”. |
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Open Loop Data Set |
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Degrade the soil moisture prognostic variable
spin-up states to make the catchments artificially wet. |
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Run the simulation for 1987 using ISLSCP forcing
data. |
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Assimilated Data Set |
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Degrade the soil moisture prognostic variable
spin-up states to make the catchments artificially wet (as for the open
loop). |
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Run the simulation for 1987 using ISLSCP forcing
data. |
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Assimilate the surface “observations” once every
3 days using the Kalman-filter. |
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Full covariance forecasting |
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Partial covariance forecasting |
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Full covariance forecasting |
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Partial covariance forecasting |
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Identify why the correct soil moisture is
retrieved more quickly for some catchments compared to others. |
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Identify the maximum level of error which
surface observations can have before the assimilation is no longer useful. |
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Identify the minimum frequency of surface
observations before there is a significant degradation of the assimilation
results. |
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Assimilate Manfred’s surface soil moisture data
over North America and evaluate. |
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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 1978 to 1994. |
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How does NSIPP plan to evaluate the soil
moisture assimilation? |
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Soil moisture - ideal but data not available. |
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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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