Analyzing the heavy rainfall event of July 2011 in Niigata using ground, satellite and radar rainfalls

Authors

  • Narayan Prasad Gautam Department of Meteorology, Trbhuvan University, Kathmandu, Nepal
  • Susumu Fujioka Japan Water Agency, Japan
  • Kazuhiko Fukami ICHARM/PWRI, Japan

DOI:

https://doi.org/10.54302/mausam.v75i4.3566

Keywords:

GSMaP_NRT, Shinano River, ground, satellite, radar, rainfall

Abstract

In recent years the application of radar and satellite precipitation observations has become increasingly useful in poorly gauged areas. However, understanding the relationships between these data sources and ground observations is vital to correct the datasets and improve their application in hydrological studies. In this study we analyzed the spatial and temporal relationships between Global Satellite Mapping of Precipitation-Near Real Time (GSMaP_NRT) data set with radar and ground observations at downstream of Shinano River, Japan.  GSMap_NRT observation showed better relationship with ground observations for longer-duration observations (eg. 3, 6, 12 and 18 hours) than hourly observations. The GSMap_NRT showed excellent relationship with ground rainfall at satellite observation time compared to non-observation time. Comparison of radar observations at various time scales and spatial resolutions showed that radar estimates at smaller-time-interval ratio and lower-spatial-scale ratio are better than longer-time-interval ratio and higher-spatial-scale ratio. We also observed that radar precipitation estimate well-represent the areal averaged precipitation of ground observations. Results from this study showed that radar precipitation estimates could serve as very important input to improve merging of ground and satellite precipitation as well satellite rainfall improvement systems.

 

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Published

01-10-2024

How to Cite

[1]
N. P. Gautam, S. . Fujioka, and K. Fukami, “Analyzing the heavy rainfall event of July 2011 in Niigata using ground, satellite and radar rainfalls ”, MAUSAM, vol. 75, no. 4, pp. 1117–1124, Oct. 2024.

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Section

Shorter Contribution