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      Permanent link:
      https://www.ias.ac.in/article/fulltext/jess/111/03/0257-0266

    • Keywords

       

      IRS-P4; MSMR; TRMM; TMI; PR

    • Abstract

       

      In this paper rain estimation capability of MSMR is explored. MSMR brightness temperature data of six channels corresponding to three frequencies of 10, 18 and 21 GHz are colocated with the TRMM Microwave Imager (TMI) derived rain rates to find a new empirical algorithm for rain rate by multiple regression. Multiple correlation analysis involving various combinations of channels in linear and non-linear forms and rain rate from TMI is carried out, and thus the best possible algorithm for rain rate measurement was identified which involved V and H polarized brightness temperature measurements at 10 and 18 GHz channels. This algorithm explained about 82 per cent correlation (r) with rain rate, and 1.61 mm h-1 of error of estimation.

      Further, this algorithm is used for generating global average rain rate map for two contrasting months of August (2000) and January (2001) of northern and southern hemispheric summers, respectively. MSMR derived monthly averaged rain rates are compared with similar estimates from TRMM Precipitation Radar (PR), and it was found that MSMR derived rain rates match well, quantitatively and qualitatively, with that from PR.

    • Author Affiliations

       

      A K Varma1 R M Gairola1 Samir Pokhrel1 B S Gohil1 A K Mathur1 Vijay K Agarwal1

      1. Oceanic Sciences Division, Space Applications Centre (ISRO), Ahmedabad - 380 015, India
    • Dates

       
  • Journal of Earth System Science | News

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