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On the Limitations of Variational Bias CorrectionSatellite radiances are the largest dataset assimilated into Numerical Weather Prediction (NWP) models, however the data are subject to errors and uncertainties that need to be accounted for before assimilating into the NWP models. Variational bias correction uses the time series of observation minus background to estimate the observations bias. This technique does not distinguish between the background error, forward operator error, and observations error so that all these errors are summed up together and counted as observation error. We identify some sources of observations errors (e.g., antenna emissivity, non-linearity in the calibration, and antenna pattern) and show the limitations of variational bias corrections on estimating these errors.
Document ID
20180000532
Acquisition Source
Goddard Space Flight Center
Document Type
Presentation
Authors
Moradi, Isaac
(Maryland Univ. College Park, MD, United States)
Mccarty, Will
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Gelaro, Ronald
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Date Acquired
January 17, 2018
Publication Date
January 10, 2018
Subject Category
Geosciences (General)
Earth Resources And Remote Sensing
Report/Patent Number
GSFC-E-DAA-TN51334
Meeting Information
Meeting: American Meteorological Society (AMS) Annual Meeting
Location: Austin,TX
Country: United States
Start Date: January 7, 2018
End Date: January 11, 2018
Sponsors: American Meteorological Society
Funding Number(s)
CONTRACT_GRANT: NNX17AE79A
Distribution Limits
Public
Copyright
Public Use Permitted.
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