Monthly rain rate over global oceans from IRS-P4 MSMR

Monthly rain rate over global oceans from IRS-P4 MSMR

SHARE

A. K. Varma, R. M. Gairola, B. S. Gohil and V. K. Agarwal
Oceanic Sciences Division, Space Applications Centre (ISRO), Ahmedabad – 380 015

IRS-P4 launched on 26 May, 1999 in a sun synchronous orbit. Satellite carried onboard Multichannel Scanning Microwave Radiometer (MSMR) and an Ocean Colour Monitor (OCM). MSMR provides measurements of brightness temperatures at 6.6, 10, 18 and 21 GHz frequencies in both horizontal and vertical polarisations. Varma et al. (2000a) compared MSMR derived integrated water vapour, wind speed, sea surface temperature and cloud liquid water with similar products from SSM/I and TMI and NOAA – AVHRR and found a good comparison between MSMR derived products and those from the other satellite sensors. Varma et al. (2000b) explored rain estimation capability of MSMR. The MSMR brightness temperature data of 6 channels corresponding to three frequencies of 10, 18 and 21 GHz are collocated with the TRMM Microwave Imager derived rain rates to find a new empirical algorithm for rain rate by regression. Due to high variability of rainfall over space and time, data from two sensor is collocated within 10 min. on temporal scale and 0.25o on spatial scale. Various combinations of channels in linear and non-linear forms are studied to correlate with rain rate and the best combination for rain estimation from MSMR has been obtained. The best algorithm involved brightness temperature observations at 10 and 18 GHz with both V and H polarizations. This algorithm is found to have about 82% correlation with rain rate, and 1.61 mm/h of error of estimation.

In this paper, using above algorithm with MSMR brightness temperature data, global monthly averaged rain rate maps in 1o x 1o grid are generated and presented. MSMR derived monthly averaged rain rates are compared with similar estimates from TMI and SSM/I. It is found that MSMR derived rain rates match well with those from TMI and SSM/I, both quantitatively and qualitatively, and most of the features of the global rain are very nicely picked up by MSMR derived rain rate maps

References:

  • Varma, A. K., Gairola, R. M., Mathur, A. K., Gohil, B. S. and Agarwal, V.K., 2000 a, Intercomparison of IRS-P4-MSMR derived geophysical products with DMSP-SSM/I, TRMM-TMI and NOAA-AVHRR finished products, To appear in the Proceedings of Pacific Ocean Remote Sensing Conference (PORSEC-2000), 5-8 December, 2000, NIO, Goa.
  • Varma, A. K., Gairola, R. M., Mathur, A. K., Gohil, B. S. and Agarwal, V. K., 2000 b, Rain Rate Measurements from IRS-P4 MSMR, To appear in the proceedings of Pacific Ocean Remote Sensing Conference (PORSEC-2000), 5-8 December, 2000, NIO, Goa.