DOI: 10.1002/joc.5359
论文题名: Characterizing Indian meteorological moisture anomaly condition using long-term (1901–2013) gridded data: a multivariate moisture anomaly index approach
作者: Das P.K. ; Midya S.K. ; Das D.K. ; Rao G.S. ; Raj U.
刊名: International Journal of Climatology
ISSN: 8998418
出版年: 2018
卷: 38 起始页码: e144
结束页码: e159
语种: 英语
英文关键词: joint probability distribution
; moisture anomaly
; multivariate moisture anomaly index
; potential evapotranspiration
; rainfall
Scopus关键词: Evapotranspiration
; Precipitation (meteorology)
; Probability
; Probability distributions
; Rain
; Seebeck effect
; Stream flow
; Time series
; Anomaly indexes
; Joint probability distributions
; Log-logistic distribution
; Mann-Kendall test
; Peninsular india
; Potential evapotranspiration
; Probability analysis
; Standardized precipitation index
; Moisture
; atmospheric moisture
; climatology
; evapotranspiration
; multivariate analysis
; spatial distribution
; trend analysis
; Gujarat
; 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. © 2017 Royal Meteorological Society Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/117011
Appears in Collections: 气候减缓与适应
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作者单位: Regional Remote Sensing Centre-East, National Remote Sensing Centre, Kolkata, India; Department of Atmospheric Sciences, University of Calcutta, India; Agricultural Chemistry and Soil Science, University of Calcutta, India; Regional Centres, National Remote Sensing Centre, Hyderabad, India
Recommended Citation:
Das P.K.,Midya S.K.,Das D.K.,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,2018-01-01,38