Volume XLII-5
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-5, 383-388, 2018
https://doi.org/10.5194/isprs-archives-XLII-5-383-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-5, 383-388, 2018
https://doi.org/10.5194/isprs-archives-XLII-5-383-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  19 Nov 2018

19 Nov 2018

STUDY OF GPM-IMERG RAINFALL DATA PRODUCT FOR GANGOTRI GLACIER

P. Verma and S. K. Ghosh P. Verma and S. K. Ghosh
  • Geomatics Engineering Group, Department of Civil Engineering, IIT Roorkee, India

Keywords: GPM constellation satellites, IMERG data, Gangotri glacier, Satellite precipitation estimates, Remote Sensing

Abstract. 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.