Assessing the performance of multi-sources gridded data to estimate long-term rainfall change over north-central region of India
DOI:
https://doi.org/10.54302/mausam.v71i2.21Keywords:
Gridded analysis datasets, North-central-India, Seasonal rainfall, Trend analysis, Skill metricsAbstract
As station data quality and availability is not adequate to reliably estimate observed climate change over many parts of the country, multi sources observational gridded datasets have been employed in the present study. The performances of multi-observational gridded datasets, e.g., IMD gridded data, CRU, APHRODITE, GPCC, NCAR/NCEP reanalysis have been compared with the reference rainfall data from IITM over North central India (NCI), a region of subtropical monsoon climate, during four main seasons (MAM,JJAS,ON and DJF) as well as in annual scale for the period 1951-2003. All the gridded data except CRU and NCEP have secured good skill scores in all seasons as well as at annual scale. APHRODITE and NCEP reanalysis have shown large wet bias in all seasons. The reference rainfall data over NCI has shown 6.3 mm, 4.2 mm, 1.9 mm and 11.2 mm increase per decade for MAM, JJAS, DJF seasons and annual rainfall respectively whereas 2.2 mm decrease per decade has been found for ON season. Only GPCC dataset have been able to capture similar trend for all seasons. Performance of NCEP reanalysis has been worse in compared to others. GPCC and IMD high resolution data has shown smallest bias among all the datasets and also obtain superior skill scores than others. Therefore based on visual inspection and the results from different conventional measures, GPCC high resolution gridded data and high resolution IMD gridded data may be reliably used for climatic analysis of this region.
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