Comparative trend analysis of minimum temperature using daily gridded data of 72 years at 1° and 0.5° resolution over west bengal

Abstract

Climate change is expected to significantly increase the frequency of extreme events, with storm events increasing by 21% for every -16.78 °C increase in ocean temperature, leading to severe consequences such as floods, structural damage, and crop loss. Detecting and understanding climate change through trend analysis is an emerging field, though many uncertainties remain. While many studies have focused on warming trends, studies on the coldest years or decades, particularly regarding minimum temperature (Tmin), are rare. Tmin is an important variable in climate models, influencing human health, agriculture, and biodiversity. This study aims to analyze and compare the trends of gridded Tmin data at two resolutions (1° x 1º observed and 0.5° x 0.5° interpolated) over the Indian state of West Bengal (WB) from 1951 to 2022. Using Innovative Polygon Trend Analysis (IPTA), the study examines seasonal, monthly, and decadal trends to understand past and predict future climatic conditions. The findings reveal that the finer 0.5° resolution data gives more detailed results compared to that of 1º resolution, particularly in the central to southern regions of WB. Although the decadal comparison shows minimal differences. Division-wise statistical analysis indicates that trend length (TL) is more consistent than trend slope (TS), with mean TL yielding more stable outputs. IPTA patterns for monthly and seasonal mean Tmin are identified as nearly identical across divisions, while significant differences are observed in the IPTA of monthly and seasonal standard deviations. This study highlights the persistent Tmin discrepancies between north and south Bengal, with finer resolutions suggesting more advanced fluctuations. Recent trends show a higher magnitude of slope than historical decades, emphasizing the increasing sensitivity to climate change. This research contributes to understanding the spatiotemporal variations of hydroclimatic variables, offering insights for mitigating the impacts of climate change on natural and human resources. Future studies should focus on the broader implications of these changes on water resources, human health, and overall climate resilience.