STUDY OF GPM-IMERG RAINFALL DATA PRODUCT FOR GANGOTRI GLACIER

This study presents a comparison of new generation weather observatory satellites Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG) rainfall products with field data collected for Gangotri glacier in India. The meteorological analysis of rainfall estimates...

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Main Authors: P. Verma, S. K. Ghosh
Format: Article
Language:English
Published: Copernicus Publications 2018-11-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-5/383/2018/isprs-archives-XLII-5-383-2018.pdf
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spelling doaj-855906b02ae74c2f99a117f9a3c225af2020-11-24T21:47:11ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342018-11-01XLII-538338810.5194/isprs-archives-XLII-5-383-2018STUDY OF GPM-IMERG RAINFALL DATA PRODUCT FOR GANGOTRI GLACIERP. Verma0S. K. Ghosh1Geomatics Engineering Group, Department of Civil Engineering, IIT Roorkee, IndiaGeomatics Engineering Group, Department of Civil Engineering, IIT Roorkee, IndiaThis study presents a comparison of new generation weather observatory satellites Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG) rainfall products with field data collected for Gangotri glacier in India. The meteorological analysis of rainfall estimates has been performed on GPM IMERG Final, Late and Early precipitation products available at daily scale with a spatial resolution of 0.1° × 0.1° for melting season from May to September for the year 2014 and 2015 respectively. The comparison of satellite products with field data was done using correlation coefficient and standard anomaly. The Late run curve showed a high degree of similarity with final run curve while early run showed variation from them. The satellite meteorological data correctly identified non-rainy days with an average of ∼86.7%, ∼67.5% and ∼95% for pre-monsoon, monsoon and post-monsoon season respectively. The rmse for final run data product for 2014 and 2015 are 4.5, 1.23, 1.55, 1.24, 0.8 and 1.14, 7.1, 1.82, 1.15, 1.52 from May to September respectively. Overall, it has been observed that for medium to heavy rainfall final run estimates are close to field data and for light to medium rainfall late run estimates are close. Similar results have been obtained from both datasets for non-rainy days in the study area.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-5/383/2018/isprs-archives-XLII-5-383-2018.pdf
collection DOAJ
language English
format Article
sources DOAJ
author P. Verma
S. K. Ghosh
spellingShingle P. Verma
S. K. Ghosh
STUDY OF GPM-IMERG RAINFALL DATA PRODUCT FOR GANGOTRI GLACIER
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
author_facet P. Verma
S. K. Ghosh
author_sort P. Verma
title STUDY OF GPM-IMERG RAINFALL DATA PRODUCT FOR GANGOTRI GLACIER
title_short STUDY OF GPM-IMERG RAINFALL DATA PRODUCT FOR GANGOTRI GLACIER
title_full STUDY OF GPM-IMERG RAINFALL DATA PRODUCT FOR GANGOTRI GLACIER
title_fullStr STUDY OF GPM-IMERG RAINFALL DATA PRODUCT FOR GANGOTRI GLACIER
title_full_unstemmed STUDY OF GPM-IMERG RAINFALL DATA PRODUCT FOR GANGOTRI GLACIER
title_sort study of gpm-imerg rainfall data product for gangotri glacier
publisher Copernicus Publications
series The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
issn 1682-1750
2194-9034
publishDate 2018-11-01
description This study presents a comparison of new generation weather observatory satellites Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG) rainfall products with field data collected for Gangotri glacier in India. The meteorological analysis of rainfall estimates has been performed on GPM IMERG Final, Late and Early precipitation products available at daily scale with a spatial resolution of 0.1° × 0.1° for melting season from May to September for the year 2014 and 2015 respectively. The comparison of satellite products with field data was done using correlation coefficient and standard anomaly. The Late run curve showed a high degree of similarity with final run curve while early run showed variation from them. The satellite meteorological data correctly identified non-rainy days with an average of ∼86.7%, ∼67.5% and ∼95% for pre-monsoon, monsoon and post-monsoon season respectively. The rmse for final run data product for 2014 and 2015 are 4.5, 1.23, 1.55, 1.24, 0.8 and 1.14, 7.1, 1.82, 1.15, 1.52 from May to September respectively. Overall, it has been observed that for medium to heavy rainfall final run estimates are close to field data and for light to medium rainfall late run estimates are close. Similar results have been obtained from both datasets for non-rainy days in the study area.
url https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-5/383/2018/isprs-archives-XLII-5-383-2018.pdf
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