Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/joc.5359 |
Characterizing Indian meteorological moisture anomaly condition using long-term (1901-2013) gridded data: a multivariate moisture anomaly index approach | |
Das, Prabir Kumar1; Midya, Subrata Kumar2; Das, Dilip Kumar3; Rao, Goru Srinivas1; Raj, Uday4 | |
2018-04-01 | |
发表期刊 | INTERNATIONAL JOURNAL OF CLIMATOLOGY
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ISSN | 0899-8418 |
EISSN | 1097-0088 |
出版年 | 2018 |
卷号 | 38页码:E144-E159 |
文章类型 | Article |
语种 | 英语 |
国家 | India |
英文摘要 | The long-term (1901-2013) gridded rainfall and potential evapotranspiration (PET) data were utilized to develop a new index, multivariate moisture anomaly index (MMAI), for characterizing the meteorological moisture anomaly condition during monsoon season over Indian region. The 6-month timescale standardized precipitation index (SPI) and standardized evapotranspiration index (SEI) were computed using time series rainfall and PET data using gamma and log-logistic distribution, respectively. The long-term seasonal SPI and SEI were converted into moisture anomaly magnitude and duration information, and their trends were analysed using Sen's slope and Mann-Kendall test, respectively. The standardized precipitation evapotranspiration index (SPEI) at 6-month timescale was also analysed to find the impact of rainfall and PET on meteorological moisture anomaly. Both the trends and probability analysis showed that SPEI was mainly representing the trends and pattern of SPI only and was unable to capture the impact of PET. The MMAI was developed by fitting the time series SPI and SEI information into different joint probability distribution and by adapting the best model for each grid. The new index was able to consider the impact of both rainfall and PET. Based on the MMAI trend analysis, it was found that the overall moisture anomaly was decreasing in northwest (NW) India, whereas it was increasing in northeast (NE), central and peninsular India. The trends analysis of SPI and SEI depicted that in NW India the significant decrease in moisture anomaly may be due to both increase in rainfall and decrease in PET, whereas in NE India the significant increase in moisture anomaly may be due to both increase in PET and decrease in rainfall. In eastern and Gujarat coast the increase in moisture anomaly may be attributed to increase in PET whereas the significant increase in rainfall might lead to reduced moisture anomaly over western coast. |
英文关键词 | moisture anomaly rainfall potential evapotranspiration multivariate moisture anomaly index joint probability distribution |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000431999600011 |
WOS关键词 | SEA-SURFACE TEMPERATURES ; SUMMER MONSOON RAINFALL ; EVAPOTRANSPIRATION TRENDS ; SOUTHERN OSCILLATION ; EQUATORIAL PACIFIC ; AIR-TEMPERATURE ; DROUGHT ; PRECIPITATION ; VARIABILITY ; REGION |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/37652 |
专题 | 气候变化 |
作者单位 | 1.Natl Remote Sensing Ctr, Reg Remote Sensing Ctr East, BG 2,AA 1B, Kolkata 700156, India; 2.Univ Calcutta, Dept Atmospher Sci, Kolkata, W Bengal, India; 3.Univ Calcutta, Agr Chem & Soil Sci, Kolkata, W Bengal, India; 4.Natl Remote Sensing Ctr, Reg Ctr, Hyderabad, Andhra Pradesh, India |
推荐引用方式 GB/T 7714 | Das, Prabir Kumar,Midya, Subrata Kumar,Das, Dilip Kumar,et al. Characterizing Indian meteorological moisture anomaly condition using long-term (1901-2013) gridded data: a multivariate moisture anomaly index approach[J]. INTERNATIONAL JOURNAL OF CLIMATOLOGY,2018,38:E144-E159. |
APA | Das, Prabir Kumar,Midya, Subrata Kumar,Das, Dilip Kumar,Rao, Goru Srinivas,&Raj, Uday.(2018).Characterizing Indian meteorological moisture anomaly condition using long-term (1901-2013) gridded data: a multivariate moisture anomaly index approach.INTERNATIONAL JOURNAL OF CLIMATOLOGY,38,E144-E159. |
MLA | Das, Prabir Kumar,et al."Characterizing Indian meteorological moisture anomaly condition using long-term (1901-2013) gridded data: a multivariate moisture anomaly index approach".INTERNATIONAL JOURNAL OF CLIMATOLOGY 38(2018):E144-E159. |
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