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Seasonal and inter-annual variation in surface energy fluxes and forcing parameters in agro-climatic regions of India.

Authors :
Choudhury, Indrani
Source :
International Journal of Remote Sensing; May2015, Vol. 36 Issue 9, p2375-2394, 20p
Publication Year :
2015

Abstract

Understanding changes in monsoon variability over a decade requires thorough knowledge of the seasonal and inter-annual variability in surface energy flux and its forcing parameters (land surface and meteorology) in response to climate change. In the present study, the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua climate model gridded global products (0.05° × 0.05° spatial resolution) of land surface temperature (LST;Ts), normalized difference vegetation index (NDVI), and surface albedo (α) were used to generate seasonal (June–September) and inter-annual (2003–2012) variation in surface energy flux and its forcing parameters over different agro-climatic regions (ACRs) of India. Energy fluxes were retrieved using a single-source surface energy balance model (here vegetation and soil is considered as a single unit). Energy flux observations over different ACRs allowed comparison of the seasonal transition of latent heat flux (LE), net radiation (Rn), soil heat flux (G), available energy (Q = Rn – G), and evaporative fraction (EF) as terrestrial links to the atmosphere. The seasonal and inter-annual variation in EF was investigated by plotting against the soil moisture information retrieved from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) global monthly data product (1° × 1° spatial resolution). Decadal and seasonal analysis showed that energy fluxes vary widely in time and space due to variability in surface radiation parameters (Ts,α), vegetation cover, soil moisture, and air temperature (Ta), which influence the seasonal transition of monsoon through LE and EF. Among the ACRs, LE and EF were found lowest in the Western Dry Region (WDR) and highest in the Western Himalayan Region (WHR). The spatiotemporal depiction of MODIS LE and MODIS EF over a span of 10 years can identify the hotspots and monsoon intensity over different ACRs. Climatic parameters that are susceptible to changes resulting from climate change are thoroughly studied in the present analysis. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01431161
Volume :
36
Issue :
9
Database :
Complementary Index
Journal :
International Journal of Remote Sensing
Publication Type :
Academic Journal
Accession number :
102498133
Full Text :
https://doi.org/10.1080/01431161.2015.1035406