Scholarlink

<p>Spatio-temporal variability analysis of climate factors provides key information for sustainable development and adaptation to urban risks. This study examines the spatio-temporal variability of climatic factors in urban districts, utilizing statistical trend line data to estimate changes over time. The research analysis of temperature, precipitation, and other key climate indicators identifies patterns and trends crucial for sustainable urban development. The study recognizes the long-term (1992–2022) temporal variations on seasonal and annual scales for climatic variables including temperature, precipitation, relative humidity, and wind speed for the urban district of Bangalore city in Karnataka state of India. The above-mentioned variables were done with non-parametric statistical methods for trend analysis and the Mann–Kendall test with Sen’s slope estimators to obtain the direction (either positive/upward or negative/downward) and magnitude of the trend. The variations in the spatio-temporal scale were assessed with ArcMap 10.8 to visualise significant variations and variations that occurred over time. This study used Google Earth Console for daily data on climate variables for all the stations and Terra Climate for describing annual variations. The results showed substantial rising maximum and minimum temperatures in all urban districts and relative humidity was found to have an increasing significant trend at the rate of 0.18–0.20%/year during the winter season. Some areas exhibited a significant shrinking trend of wind speed due to urban development. The mean daily precipitation rate exhibited a significant increasing trend during the summer season which attributed to the increased moisture-holding capacity of the atmosphere due to increased temperatures in the summer season. The findings offer valuable insights for urban planners and policymakers to enable the integration of climate variability into sustainable development strategies to enhance urban resilience and adaptability to changing environmental conditions. The results will contribute to climate risk assessment for decision-makers, planners, and stakeholders in developing effective mitigation and adaptation strategies to respond to the growing urban risks associated with climate change. </p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Spatio-temporal variability analysis for climatic factors in urban districts with statistical trend line data estimates for sustainable development

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月30日

查看全文
  • Saloni Mangal,
  • Renu Dhupper,
  • Maya Kumari,
  • Vipan Kumar Verma,
  • Deepak Kumar

摘要

Spatio-temporal variability analysis of climate factors provides key information for sustainable development and adaptation to urban risks. This study examines the spatio-temporal variability of climatic factors in urban districts, utilizing statistical trend line data to estimate changes over time. The research analysis of temperature, precipitation, and other key climate indicators identifies patterns and trends crucial for sustainable urban development. The study recognizes the long-term (1992–2022) temporal variations on seasonal and annual scales for climatic variables including temperature, precipitation, relative humidity, and wind speed for the urban district of Bangalore city in Karnataka state of India. The above-mentioned variables were done with non-parametric statistical methods for trend analysis and the Mann–Kendall test with Sen’s slope estimators to obtain the direction (either positive/upward or negative/downward) and magnitude of the trend. The variations in the spatio-temporal scale were assessed with ArcMap 10.8 to visualise significant variations and variations that occurred over time. This study used Google Earth Console for daily data on climate variables for all the stations and Terra Climate for describing annual variations. The results showed substantial rising maximum and minimum temperatures in all urban districts and relative humidity was found to have an increasing significant trend at the rate of 0.18–0.20%/year during the winter season. Some areas exhibited a significant shrinking trend of wind speed due to urban development. The mean daily precipitation rate exhibited a significant increasing trend during the summer season which attributed to the increased moisture-holding capacity of the atmosphere due to increased temperatures in the summer season. The findings offer valuable insights for urban planners and policymakers to enable the integration of climate variability into sustainable development strategies to enhance urban resilience and adaptability to changing environmental conditions. The results will contribute to climate risk assessment for decision-makers, planners, and stakeholders in developing effective mitigation and adaptation strategies to respond to the growing urban risks associated with climate change.