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Upcoming JCSDA Seminars
About JCSDA's Seminar Series
The JCSDA seminar series includes presentations on satellite observing
instruments, radiative transfer models for use in satellite data
assimilation, algorithms for deriving information on the Earth's
atmosphere, oceans, and land surface from satellite observations,
advances in data assimilation techniques, preparations for
assimilation of data from new satellite instruments, and impacts of
satellite data on weather and climate predictions. The seminars are
about 1 hour in duration (including discussion period) and are held
monthly, usually on the 3rd Wednesday of each month at 2 PM, and are
open to the public.
The audience for the seminars generally consists of remote sensing
researchers from NOAA/NESDIS, data assimilation experts and modelers
from NOAA/NCEP and NASA/Goddard Space Flight Center Global Modeling
and Assimilation Office, and students/faculty from the University of Maryland.
Slides for each presentation should be available for download in PDF
format on this page, the day before each talk.
Unless specifically noted otherwise, the contact for
the JCSDA seminar series is Kevin Garrett.
Uncertainties in forward passive microwave brightness temperatures and what to do about them.
Presentation file posted here when available.
UCLA, Joint Institute for Regional Earth System Science and Engineering
Tuesday, May 6, 2014 1:30 p.m. - 2:30 p.m. Conference Center, NOAA Center for Weather and Climate Prediction,5830 University Research Court, College Park, MD
Forward simulations of cloudy satellite radiances are fraught with uncertainty especially in the microwave regime. The scattering parameters that determine satellite brightness temperatures critically depend on complex, unknown size and shape distributions of liquid and solid hydrometeors. These uncertainties can lead to differences of 50 K or more in forward calculations alone, and therefore this issue must be addressed before attempting to assimilate this data into operational models. In this talk, I will quantify some of the various sources of uncertainty in passive microwave radiances (e.g. TRMM/TMI). I will also present an elegant method we have developed at UCLA and JPL to assimilate these uncertain observations. This method is based upon statistical inference using the directions of the most certain correlations. The uncertain directions can be neglected, thus reducing the order of the problem as well as regularizing the mapping. The observation error covariance formulation also becomes straightforward and elegant. We present the encouraging results of our microwave brightness temperatures simulation in both 1D-Var and Ensemble Kalman Filter frameworks.
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