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|Title:||<span style="font-size:11.0pt;font-family: "Times New Roman";mso-fareast-font-family:"Times New Roman";mso-bidi-font-family: Mangal;mso-ansi-language:EN-GB;mso-fareast-language:EN-US;mso-bidi-language: HI" lang="EN-GB">Concepts and principles of rainfall estimation from radar: Multi sensor environment and data fusion</span>|
|Keywords:||Radar rain estimation|
Quantitative precipitation estimation (QPE)
|Abstract:||Rainfall estimation has been pursued nearly since the dawn of civilization. It is also one of the most commonly used applications of modern, meteorological radars in most operational systems. Multi sensor approaches have made great strides in addressing the rainfall estimation problem through better sensor calibration and improved integration of observations at scales spanning many orders of magnitude such as radar, satellite and rain gauges. Data fusion techniques have demonstrated advantages in precipitation retrievals, especially for radar observations at attenuated frequencies. Data fusion has also shown benefits in merging data from multiple radars, as well as radars and satellites. This paper describes essential concepts of multi sensor rainfall estimation with a radar focus. Validation concepts for remote estimation of rainfall are also presented. Examples of data fusion and validation are illustrated through rainfall estimate comparisons between gauge and radar networks. |
|ISSN:||0975-105X (Online); 0367-8393 (Print)|
|Appears in Collections:||IJRSP Vol.41(4) [August 2012]|
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