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Wenge Ni-Meister |
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Jeff Walker |
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Paul Houser |
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Extended 1-D Kalman filter (EKF) has been
implemented into the catchment model and
was validated using identical twin experiment in North America by
Jeff Walker |
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Ensemble Kalman filter (EnKF) has been
implemented into the catchchment
model and was validated using identical twin experiement in North America by Rolf Reichle |
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Currently we are assimilating the soil moisture
data from SMMR into the the catchement model and validate the above two
data assimilation methods using in-situ measurements in Eurasia and using
the new catchment definitions |
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Run the catchment model without data
assimilation (case I) |
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Run the catchment model with data assimilation
(case II) |
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Compare modeled soil moisture from the above two
cases with the in situ SM measurements |
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New catchment definitions, soil parameters, and topographic
information are from Sarith Mahanama. |
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Vegetation parameters: |
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Use Max Suarez’s SIB vegetation types + 9 year
AVHRR greenness and LAI datasets from Pierre |
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Generate
MOSAIC vegetation parameters based
on the code given by Randy Koster |
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Convert to catchment-based vegetation parameters
by choosing the dominant vegetation types |
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Compare the histograms of the land cover types
both from the new and old catchment
definitions to validate our
algorithm |
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Forcings: ISLSCP forcings for the period of
1987-1988 |
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Model predictions |
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Moisture
content at the surface layer (2cm), root zone layer (1m) and the whole soil
profile |
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Period : 1987-1988 |
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SMMR |
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at the very thin top surface (1cm), period:
1979-87 |
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In-situ measurements |
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Plant-available SM: originally recorded as
percent wetness by mass of dry soil->volumetric SM –> subtract volumetric SM at wilting level ->
Plant-available SM |
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Different datasets (Russia (130 stations, 1978-85, Mongolia
(42 stations, 1964-93), China (43 stations, 1981-91) cover different years |
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Three datasets with different soil moisture
definitions, how will we compare them? |
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Use the ECMWF forcings from Jay’s group |
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Use the new snow model |
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Reprocess the in-situ data to check the
seasonality of in-situ measurements |
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Run the data assimilation |
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