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<p>This study presents a comprehensive analysis of the climate trends, variability, and short-term climatology of Arunachal Pradesh (ARP), leveraging data from a network of Automatic Weather Stations (AWS) and manual observations. Important meteorological variables such as air temperature (<i>T</i>), relative humidity (RH), wind speed (WS), wind direction (WD), pressure (P), and rainfall (RF) have been assessed. A very good correspondence is seen between two rainfall estimates (correlation coefficient value <i>R</i> = 0.77) for the study region, whilst during the monsoon season 10–20% higher <i>R-</i>values were registered. The plain regions of ARP experienced hot, humid conditions with gusty winds, while the hilly regions were cooler, and hazier conditions with lower wind speeds. Predominantly westerly winds during cooler seasons, while the warmer seasons saw a shift to south-westerly to westerly winds, consistent with the broader monsoonal wind patterns in the region. Rainfall analysis suggested that during the winter (64% isolated, 21% scattered), pre-monsoon (33% isolated, 37% scattered), monsoon (41% scattered, 32% fairly widespread), and post-monsoon season (67% isolated, 18% scattered) rainfall days were recorded. Overall, 70% of the region’s rainfall comes from light-to-moderate rain while 30% is from heavy-to-extremely heavy rainfall, however, the contribution of heavy rainfall increased to 45% during the monsoon season. The study region has a significant long-term negative trend in annual rainfall with a slope rate of − 0.11&#xa0;mm/year for the period from 1976 to 2022. Interestingly, the data shows a positive trend in recent years (2016–2022), with a slope rate of 0.405&#xa0;mm/year. The frequency of heavy rainfall events has also increased, with a slope rate of 0.22/year, highlighting a growing trend towards more frequent intense rainfall. Overall, this study provides the current state of the climate for the study area, but the erratic trends point towards strengthening of the observational network.</p>

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An Observational Study on the Variability and Climatology of Arunachal Pradesh

  • 期刊论文

  • 发表日期：

    2025年2月26日

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  • A. Sandeep,
  • Sunit Das,
  • V. H. Arun

摘要

This study presents a comprehensive analysis of the climate trends, variability, and short-term climatology of Arunachal Pradesh (ARP), leveraging data from a network of Automatic Weather Stations (AWS) and manual observations. Important meteorological variables such as air temperature (T), relative humidity (RH), wind speed (WS), wind direction (WD), pressure (P), and rainfall (RF) have been assessed. A very good correspondence is seen between two rainfall estimates (correlation coefficient value R = 0.77) for the study region, whilst during the monsoon season 10–20% higher R-values were registered. The plain regions of ARP experienced hot, humid conditions with gusty winds, while the hilly regions were cooler, and hazier conditions with lower wind speeds. Predominantly westerly winds during cooler seasons, while the warmer seasons saw a shift to south-westerly to westerly winds, consistent with the broader monsoonal wind patterns in the region. Rainfall analysis suggested that during the winter (64% isolated, 21% scattered), pre-monsoon (33% isolated, 37% scattered), monsoon (41% scattered, 32% fairly widespread), and post-monsoon season (67% isolated, 18% scattered) rainfall days were recorded. Overall, 70% of the region’s rainfall comes from light-to-moderate rain while 30% is from heavy-to-extremely heavy rainfall, however, the contribution of heavy rainfall increased to 45% during the monsoon season. The study region has a significant long-term negative trend in annual rainfall with a slope rate of − 0.11 mm/year for the period from 1976 to 2022. Interestingly, the data shows a positive trend in recent years (2016–2022), with a slope rate of 0.405 mm/year. The frequency of heavy rainfall events has also increased, with a slope rate of 0.22/year, highlighting a growing trend towards more frequent intense rainfall. Overall, this study provides the current state of the climate for the study area, but the erratic trends point towards strengthening of the observational network.