An appraisal of rainfall estimation over India using remote sensing and in situ measurements
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Title |
An appraisal of rainfall estimation over India using remote sensing and in situ measurements
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Creator |
Dwivedi, Sanjeev
Kumar Thakur, Manoj Lakshmi Kumar, T V Rao, B M Kishtawal, C M Narayanan, M S |
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Subject |
Monsoon rainfall
Tropical Rainfall Monitoring India Meteorological Department (IMD4) gridded data INSAT Mission (TRMM) Global Precipitation Mission (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG) Doppler Weather Radars (DWR) Z–R relation |
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Description |
167-177
The most important meteorological parameter Rainfall, shows high variability in space and time, particularly over Tropics / Monsoon region. Many new observational and analysis methods to observe / analyse them by remote sensing techniques (Satellites, Doppler Weather Radars) have emerged over the decades, besides the dense network of in situ rain gauges, Automatic Weather Stations (AWS) etc on ground. The scales of observations being vastly different for in situ and remote sensing methods, large discrepancies between different techniques are inherent. These problems have been brought out through various validation studies by many groups in the country. Even on the daily all India spatial scale, basically only the peaks and troughs from satellite estimates match reasonably well with in situ data. Results of a case study during an intense and long-lasting rain event over Chennai, from DWR, with different satellite products and ground truth are presented. The importance of DWR rainfall data in significantly improving the integrated products is emphasised. A simple two-way approach to establish Z – R relationship for the DWRs in the country is also suggested. A well-coordinated integrated programme to study the inter comparability of precipitation at various spatio- temporal scales in the context of our water resources, model validation, extreme rainfall events, Climate change, etc., is called for. The desired accuracies from satellite data vis a vis IMD gridded data for different applications have been summarised. |
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Date |
2022-02-14T07:34:00Z
2022-02-14T07:34:00Z 2021-12 |
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Type |
Article
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Identifier |
0975-105X (Online); 0367-8393 (Print)
http://nopr.niscair.res.in/handle/123456789/59120 |
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Language |
en
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Publisher |
NIScPR-CSIR, India
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Source |
IJRSP Vol.50(4) [December 2021]
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