The SMAP mission is one of the first satellites being developed
by NASA in response to the National Research Council’s Decadal
Survey. SMAP will make global measurements of surface soil
moisture its freeze/thaw state. The measurements should enable
science and applications users to: 1) Understand processes that
link the terrestrial water, energy and carbon cycles, 2) Estimate
global water and energy fluxes at the land surface, 3) Quantify
net carbon flux in boreal landscapes, 4) Enhance weather and
climate forecast skill, 5) Develop improved flood prediction and
drought monitoring capability. The SMAP mission concept would
utilize L-band radar and radiometry. The SMAP project also
includes model value-added data assimilation products on deeper
profile soil moisture (rootzone) and net ecosystem exchange of
carbon. In this presentation a description of the data
assimilation product and a few representative soil moisture data-
denial and control experiments with atmospheric models will be
presented.
Dial-In
JCSDA now offers online streaming presentation access for remote seminar attendees!
The difference between observations and a model simulation can
be decomposed into instrument error, model forecast error, and
representation error. A major challenge for data assimilation is
accurate characterization of these errors. We have developed a
technique which identifies the information content of a model. We
use a long simulation to formulate a basis for a reduced state
space of the model as determined by our metric for the information
content. The projection of a sequence of model-data misfits into
the reduced model state space can be used to estimate the model
forecast errors. The estimate, so obtained, is analogous to the
estimate obtained by ensemble methods. The remainder of the
misfits, which have no projection on the model state space, can be
assigned to the model representation error and instrument error.
Work has begun on construction of a system to test the
consequences of incorporating our error estimates into the
operational climate forecast system.
Dial-In
JCSDA now offers online streaming presentation access for remote seminar attendees!