Exploring the Utility of Machine Learning-Based Passive Microwave Brightness Temperature Data Assimilation over Terrestrial Snow in High Mountain Asia

Exploring the Utility of Machine Learning-Based Passive Microwave Brightness Temperature Data Assimilation over Terrestrial Snow in High Mountain Asia

This study explores the use of a support vector machine (SVM) as the observation operator within a passive microwave brightness temperature data assimilation framework (herein SVM-DA) to enhance the characterization of snow water equivalent (SWE) over High Mountain Asia (HMA). A series of synthetic...

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Bibliographic Details
Main Authors: Yonghwan Kwon, Barton A. Forman, Jawairia A. Ahmad, Sujay V. Kumar, Yeosang Yoon
Format: Article
Language:English
Published: MDPI AG 2019-09-01
Series:Remote Sensing
Subjects:
support vector machine
passive microwave brightness temperature
data assimilation
snow water equivalent
high mountain asia
synthetic twin experiment
nasa land information system
Online Access:https://www.mdpi.com/2072-4292/11/19/2265

Internet

https://www.mdpi.com/2072-4292/11/19/2265

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