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摘要
Winter (DJF) precipitation over Northwest India (NWI) is very important for the cultivation of Rabi crops. Thus, an accurate estimation of high-resolution observations, evaluation of high-resolution numerical models, and understanding the local variability trends are essential. The objective of this study is to verify the quality of a new high spatial resolution (0.25A degrees A x 0.25A degrees) gridded daily precipitation data set of India Meteorological Department (IMD1) over NWI during winter. An intercomparison with four existing precipitation data sets at 0.5A degrees A x 0.5A degrees of IMD (IMD2), 1A degrees A x 1A degrees of IMD (IMD3), 0.25A degrees A x 0.25A degrees of APHRODITE (APRD1), and 0.5A degrees A x 0.5A degrees of APHRODITE (APRD1) resolution during a common period of 1971-2003 is done. The evaluation of data quality of these five data sets against available 26 station observations is carried out, and the results clearly indicate that all the five data sets reasonably agreed with the station observation. However, the errors are relatively more in all the five data sets over Jammu and Kashmir-related four stations (Srinagar, Drass, Banihal top, and Dawar), while these errors are less in the other stations. It may be due to the lack of station observations over the region. The quality of IMD1 data set over NWI for winter precipitation is reasonably well than the other data sets. The intercomparison analysis suggests that the climatological mean, interannual variability, and coefficient of variation from IMD1 are similar with other data sets. Further, the analysis extended to the India meteorological subdivisions over the region. This analysis indicates overestimation in IMD3 and underestimation in APRD1 and APRD2 over Jammu and Kashmir, Himachal Pradesh, and NWI as a whole, whereas IMD2 is closer to IMD1. Moreover, all the five data sets are highly correlated (> 0.5) among them at 99.9% confidence level for all subdivisions. It is remarkably noticed that multicategorical (light precipitation, moderate precipitation, heavy precipitation, and very heavy precipitation) skill score of accuracy (> 0.8) for the four data sets against IMD1 is good for all the subdivisions as well as NWI and is more in IMD2. IMD1 performs well in capturing the relationships of winter precipitation with climate indices such as Nino 3.4 region sea surface temperature, Southern Oscillation Index, Arctic Oscillation, and North Atlantic Oscillation. The results conclude that IMD1 is useful to understand the variability trends at the local climate scale and its global teleconnections.
- 出版日期2018-4
