Geoscience Reference
In-Depth Information
Chapter 19
All-Sky Satellite Radiance Data Assimilation:
Methodology and Challenges
Milija Zupanski
Abstract Assimilation of satellite radiances is the backbone of today's operational
data assimilation. Satellites can cover all parts of globe and provide information in
areas not accessible by any other observation type. Of special interest are high-
impact weather areas, such as tropical cyclones and severe weather outbreaks,
which are mostly covered by clouds. Unfortunately, in current operational practice
only clear-sky satellite radiances are assimilated, with only few exceptions. This
effectively filters out a potentially useful information from all-sky radiances related
to clouds and microphysics, and consequently limits the utility of satellite data. In
this paper we will address numerous challenges related to the use of all-sky satellite
radiances.
All-sky satellite radiances present a formidable challenge for data assimila-
tion as they relate to numerous technical aspects of data assimilation such as:
(1) forecast error covariance, (2) correlated observation errors, (3) nonlinearity
and non-differentiability, and (4) non-Gaussian errors. Assimilation of all-sky
radiances is also challenging from a dynamical/physical point of view, since
observing clouds implies a need for better understanding and ultimately sim-
ulation of cloud microphysical processes. Given that a reliable prediction of
clouds requires a high-resolution cloud-resolving model, assimilation of all-sky
radiancesis also a high-dimensional problem that requires addressing computational
challenges.
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