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The GEOS-5 Neural Network Retrieval (NNR) for AOD
NTRS Full-Text: Click to View  [PDF Size: 31.6 MB]
Author and Affiliation:
Castellanos, Patricia(Universities Space Research Association, Goddard Earth Sciences Technology and Research, Greenbelt, MD, United States)
Da Silva, Arlindo(NASA Goddard Space Flight Center, Greenbelt, MD, United States)
Abstract: One of the difficulties in data assimilation is the need for multi-sensor data merging that can account for temporal and spatial biases between satellite sensors. In the Goddard Earth Observing System Model Version 5 (GEOS-5) aerosol data assimilation system, a neural network retrieval (NNR) is used as a mapping between satellite observed top of the atmosphere (TOA) reflectance and AOD, which is the target variable that is assimilated in the model. By training observations of TOA reflectance from multiple sensors to map to a common AOD dataset (in this case AOD observed by the ground based Aerosol Robotic Network, AERONET), we are able to create a global, homogenous, satellite data record of AOD from MODIS observations on board the Terra and Aqua satellites. In this talk, I will present the implementation of and recent updates to the GEOS-5 NNR for MODIS collection 6 data.
Publication Date: Dec 13, 2017
Document ID:
20170012197
(Acquired Dec 19, 2017)
Subject Category: EARTH RESOURCES AND REMOTE SENSING; METEOROLOGY AND CLIMATOLOGY
Report/Patent Number: GSFC-E-DAA-TN50487
Document Type: Oral/Visual Presentation
Meeting Information: AGU Fall Meeting: H34F: Machine Learning Applications in Earth Science and Remote Sensing II; 11-15 Dec. 2017; New Orleans, LA; United States
Meeting Sponsor: American Geophysical Union; Washington, DC, United States
Contract/Grant/Task Num: NNG11HP16A
Financial Sponsor: NASA Goddard Space Flight Center; Greenbelt, MD, United States
Organization Source: NASA Goddard Space Flight Center; Greenbelt, MD, United States
Description: 22p; In English
Distribution Limits: Unclassified; Publicly available; Unlimited
Rights: Copyright; Public use permitted
NASA Terms: EARTH OBSERVING SYSTEM (EOS); NEURAL NETS; AEROSOLS; OPTICAL THICKNESS; ASSIMILATION; MODIS (RADIOMETRY); MULTISENSOR APPLICATIONS; DATA BASES; MACHINE LEARNING; DATA INTEGRATION; SATELLITE OBSERVATION; SPATIAL DISTRIBUTION; TEMPORAL DISTRIBUTION; REFLECTANCE; METEOROLOGICAL SATELLITES
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