Publication: Cloud computing-based estimation of Peninsular India?s long-term climate change impacts on rainfall, surface temperature, and geospatial indices
Date
2024
Authors
Halder B.
Rana B.
Juneng L.
Pande C.B.
Alshehery S.
Elsahabi M.
Yadav K.K.
Sammen S.S.
Naganna S.R.
Journal Title
Journal ISSN
Volume Title
Publisher
Taylor and Francis Ltd.
Abstract
Realizing the intricate relationships between drought, vegetation dynamics, and climate change is essential for sustainable resource management. Although temperature and rainfall patterns are the primary determinants of these fluctuations, human activity also plays a significant role. Recent decades have witnessed significant climate change events, particularly in peninsular India. Analyzing these year-by-year variations in rainfall and temperature is essential for informed decision-making. This knowledge can guide the development of innovative adaptation strategies to ensure sustainable livelihoods in the region. This study utilizes the Google Earth Engine platform to analyze yearly climate data and relevant geographical indices from 2003 to 2023 across Peninsular India. The analysis reveals a statistically significant increase in mean annual rainfall (0.262 mm/year) alongside a slight rise in regional land surface temperature (LST) trends (0.102 �C/year). However, yearly average anomaly values for LST also show an upward trend, rising from 2.56 in 2003 to 3.23 in 2023. This suggests a potential shift in rainfall patterns, with potential consequences for water availability. Rising temperatures coupled with altered rainfall patterns can lead to water scarcity, especially in regions reliant on rain-fed agriculture. This has a direct impact on crop yields and overall agricultural productivity. Despite rising temperatures, the analysis using drought indices suggests a decline in average annual drought severity across Peninsular India, with values decreasing from 0.33 in 2003 to 2.70 in 2023. Interestingly, we found a strong positive association between rainfall and vegetation indices, while rainfall and LST exhibited a negative correlation. Interestingly, while rainfall and LST exhibited a negative correlation, a strong positive association was found between rainfall and vegetation indices. These comprehensive findings hold significant potential for informing future climate projections and promoting sustainable development in peninsular India through evidence-based applications. ? 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
Description
Keywords
Agriculture , Atmospheric temperature , Decision making , Drought , Engines , Land surface temperature , Rain , Surface measurement , Surface properties , Vegetation , Google earth engine , Google earths , Land surface temperature , Peninsular india , Rainfall anomaly , Rainfall index , Rainfall patterns , Rising temperatures , Vegetation condition , Vegetation index , Climate change