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Validation of TMPA and GPCP 1DD against the ground truth rain-gauge data for Indian region

Authors

  • Manish K. Joshi,

    Corresponding author
    • K. Banerjee Centre of Atmospheric & Ocean Studies, Institute of Interdisciplinary Studies, University of Allahabad, Allahabad, U.P., India
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  • Archana Rai,

    1. K. Banerjee Centre of Atmospheric & Ocean Studies, Institute of Interdisciplinary Studies, University of Allahabad, Allahabad, U.P., India
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  • A. C. Pandey

    Corresponding author
    • K. Banerjee Centre of Atmospheric & Ocean Studies, Institute of Interdisciplinary Studies, University of Allahabad, Allahabad, U.P., India
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Correspondence to: Manish K. Joshi and A. C. Pandey, K. Banerjee Centre of Atmospheric & Ocean Studies, Institute of Interdisciplinary Studies, University of Allahabad, Allahabad 211002, U.P., India. E-mail: manishkumarjoshi@gmail.com; prof.avinashcpandey@gmail.com

ABSTRACT

The satellite datasets, namely, the Tropical Rainfall Measuring Mission (TRMM) MultiSatellite Precipitation Analysis (TMPA) product, 3B42 version 6 and Global Precipitation Climatology Project (GPCP) one-degree-daily (1DD) from NASA Goddard Space Flight Center, have been validated against the ‘ground truth’ rain-gauge data from the India Meteorological Department for all-India during the period 1998–2007. The comparisons reveal that both the satellite datasets are good enough in representing the spatial rainfall distribution over India. The categorical statistics provides an insight in evaluating the satellite's ability and its accuracy in estimating the precipitation. The average bias along the heavy-rainfall regions (e.g. Western coast, Arunachal Pradesh, Sub-Himalayan West Bengal, Sikkim, and east Uttaranchal) for the TMPA (GPCP 1DD) is −8.03 (−8.29) mm d−1, whereas the mean is 7.47 (6.97) mm d−1, which signifies that the satellite datasets underestimate the Indian summer monsoon rainfall in sharp rainfall regions. Albeit, the TMPA excels over GPCP 1DD where the rainfall is mainly attributed to orography, yet both fail in capturing the extreme rainfall year, 2005. The satellite datasets do capture the intraseasonal oscillations as is evident from spectral analysis, whereas the empirical orthogonal function analysis of standardized daily and seasonal anomalies exemplifies that the satellite datasets also capture the dominant modes. Additionally, the active and the break spells calculated for the months of July and August for the satellite datasets are in agreement with the ones obtained for the rain-gauge.

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