NDLI: Global precipitation retrieval algorithm trained for SSMIS using a Numerical Weather Prediction Model: Design and evaluation

Content Provider	IEEE Xplore Digital Library
Author	Surussavadee, C. Staelin, D.H.
Copyright Year	2010
Description	Author affiliation: Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, 02139 USA (Surussavadee, C.; Staelin, D.H.)
Abstract	This paper presents and evaluates a global precipitation retrieval algorithm for the Special Sensor Microwave Imager/Sounder (SSMIS). It is based on those developed earlier for the Advanced Microwave Sounding Unit (AMSU) [1]-[6] and employs neural networks trained with 122 global storms that spanned a year and were simulated using the fifth-generation National Center for Atmospheric Research/Penn State Mesoscale Model (MM5) and a radiative transfer program validated using AMSU observations. Only non-icy surfaces at latitudes less than 50° have been analyzed because their surface effects are more predictable. Sensitivity to surface emissivity variations was reduced by using only more surface-insensitive principal components of brightness temperature. Based on MM5 simulations, retrievals for land are slightly less accurate than those for sea and all are useful for rates above 1 mm/h. F-16 SSMIS, NOAA-15 AMSU, and Global Precipitation Climatology Project (GPCP) annual estimates generally agree. SSMIS retrieves less precipitation for some areas partly due to its higher resolution that resolves precipitation better. SSMIS overestimates precipitation over under-vegetated land requiring the near-surface evaporation correction illustrated earlier for AMSU [6].
Starting Page	2341
Ending Page	2344
File Size	546707
Page Count	4
File Format	PDF
ISBN	9781424495658
ISSN	21537003
e-ISBN	9781424495665
e-ISBN	9781424495641
DOI	10.1109/IGARSS.2010.5649699
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sea surface Ocean temperature Artificial neural networks Land surface Storms Microwave imaging Satellites satellite Special Sensor Microwave Imager/Sounder (SSMIS) microwave precipitation estimation precipitation rain remote sensing
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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