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<p>The steady rise in greenhouse gas concentrations has accelerated global and regional warming, posing serious challenges to agriculture-centric regions like Punjab, India. This study scrutinises historical (1951–2020) and projected (2025–2095) temperature trends across five key locations, i.e., Ludhiana, Ballowal Saunkhri, Amritsar, Patiala, and Bathinda, using IMD gridded datasets and CSIRO-Mk3-6–0 model simulations under RCP2.6, RCP4.5, RCP6.0, and RCP8.5 pathways. Bias correction was performed using the CF<sub>x</sub> method. Trends in maximum (T<sub>max</sub>) and minimum (T<sub>min</sub>) temperatures were evaluated on annual and seasonal scales (<i>kharif</i>, <i>rabi</i>, monsoon, winter) using the Mann–Kendall test and Sen’s slope estimator. Over the past seven decades, T<sub>max</sub> exhibited rising trends during the annual, <i>kharif</i>, and <i>rabi</i> periods, while winter T<sub>max</sub> declined. A consistent warming trend in T<sub>min</sub> was observed across seasons. A highest and statistically significant increase in annual T<sub>min</sub> (@0.009&#xa0;°C/year; Zs: 0.61) was observed in Punjab’s southwest station Bathinda. Future projections indicate further warming, with T<sub>max</sub> and T<sub>min</sub> rising by 0.6–1.19&#xa0;°C and 0.7–0.77&#xa0;°C under RCP2.6, and by 3.57–5.81&#xa0;°C and 3.99–8.33&#xa0;°C under RCP8.5. These findings highlight a need for location-specific adaptation and mitigation stratagems to preserve agricultural productivity under a changing climate.</p>

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Multi-decadal annual and seasonal temperature variability from 1951 to 2095 over Indian Punjab—A non-parametric statistical approach

  • 期刊论文

  • 发表日期：

    2025年10月20日

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  • Agatambidi Bala Krishna,
  • Prabhjyot-Kaur,
  • Samanpreet Kaur,
  • Sandeep Singh Sandhu,
  • Harleen Kaur

摘要

The steady rise in greenhouse gas concentrations has accelerated global and regional warming, posing serious challenges to agriculture-centric regions like Punjab, India. This study scrutinises historical (1951–2020) and projected (2025–2095) temperature trends across five key locations, i.e., Ludhiana, Ballowal Saunkhri, Amritsar, Patiala, and Bathinda, using IMD gridded datasets and CSIRO-Mk3-6–0 model simulations under RCP2.6, RCP4.5, RCP6.0, and RCP8.5 pathways. Bias correction was performed using the CFx method. Trends in maximum (Tmax) and minimum (Tmin) temperatures were evaluated on annual and seasonal scales (kharif, rabi, monsoon, winter) using the Mann–Kendall test and Sen’s slope estimator. Over the past seven decades, Tmax exhibited rising trends during the annual, kharif, and rabi periods, while winter Tmax declined. A consistent warming trend in Tmin was observed across seasons. A highest and statistically significant increase in annual Tmin (@0.009 °C/year; Zs: 0.61) was observed in Punjab’s southwest station Bathinda. Future projections indicate further warming, with Tmax and Tmin rising by 0.6–1.19 °C and 0.7–0.77 °C under RCP2.6, and by 3.57–5.81 °C and 3.99–8.33 °C under RCP8.5. These findings highlight a need for location-specific adaptation and mitigation stratagems to preserve agricultural productivity under a changing climate.