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On the Limitations of Variational Bias Correction
NTRS Full-Text: Click to View  [PDF Size: 37.1 MB]
Author and Affiliation:
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)
Abstract: Satellite 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.
Publication Date: Jan 10, 2018
Document ID:
20180000532
(Acquired Feb 13, 2018)
Subject Category: GEOSCIENCES (GENERAL); EARTH RESOURCES AND REMOTE SENSING
Report/Patent Number: GSFC-E-DAA-TN51334
Document Type: Oral/Visual Presentation
Meeting Information: American Meteorological Society (AMS) Annual Meeting; 98th; 7-11 Jan. 2018; Austin,TX; United States
Meeting Sponsor: American Meteorological Society; Washington, DC, United States
Contract/Grant/Task Num: NNX17AE79A
Financial Sponsor: NASA Goddard Space Flight Center; Greenbelt, MD, United States
Organization Source: NASA Goddard Space Flight Center; Greenbelt, MD, United States
Description: 19p; In English
Distribution Limits: Unclassified; Publicly available; Unlimited
Rights: Copyright; Public use permitted
NASA Terms: ANTENNA RADIATION PATTERNS; BIAS; CORRECTION; EMISSIVITY; MATHEMATICAL MODELS; NUMERICAL WEATHER FORECASTING; SPATIAL DISTRIBUTION; TROPOSPHERE; WATER VAPOR; HETERODYNING; NEAR FIELDS; NONLINEARITY; OPTICAL MEASUREMENT; RANDOM ERRORS; TIME SERIES ANALYSIS; UNCERTAIN SYSTEMS
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