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<p>Climate change is now recognized as one of the most important environmental challenges of the 21st century. Global warming, coupled with a decrease in precipitation, has exacerbated the effects of climate change. Assessing drought severity and distribution within a region and devising strategies to mitigate its impacts constitutes a central component of drought management. Recently, General Circulation Models (GCMs) have been implemented to predict the impacts of climate change (CC) on various systems, including water resources and others. Therefore, this study examines the effects of CC on temperature and precipitation parameters using CMIP6 climate models in southern Kerman Province. The study implements data from the CanESM5 predictor model and the SDSM downscaling model, based on emission scenarios developed for the baseline period (1998–2022), to forecast future atmospheric conditions. The Standardized Precipitation Index (SPI) was used for monitoring temporal and spatial patterns of drought variations under present and future conditions. The SPI was calculated using precipitation data from 24 meteorological stations across time scales of 1, 3, 6, 9, 12, 18, 24, and 48 months during the 1998–2022 statistical period. Climate variables were downscaled and simulated using the Coupled Model Intercomparison Project Phase 6 (CMIP6) framework by applying the Shared Socioeconomic Pathways (SSPs; the optimistic SSP1-2.6 and pessimistic SSP5-8.5) to project a near-future twenty-year period spanning 2040 to 2059. The performance of CMIP6 was evaluated by implementing two model evaluation metrics, as Root Mean Square Error (RMSE) and the coefficient of determination (R<sup>2</sup>). Temporal and spatial patterns of drought were evaluated for the historical baseline and future scenarios. Baseline time series analysis revealed that short-term droughts were more frequent but less persistent than long-term droughts. Spatial analysis indicated that most of the region experienced predominantly normal conditions, with wetter conditions concentrated in the northern and northwestern areas, while southern regions showed higher susceptibility to drought. Rainfall simulations using the SDSM model during the baseline period demonstrated high reliability, with <i>R²</i> values varying from 0.63 to 0.98 across different meteorological stations. Future projections suggest prolonged drought episodes, with drought conditions expected in 42–58% of cases across 3 to 24-month time scales under both scenarios. Southern and southwestern parts of the region are identified as areas with the highest likelihood of future drought occurrence. The results offer critical resources to better manage agriculture and water in the area.</p>

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Forecasting drought characteristics under CMIP6 climate change scenarios in southern Kerman Province

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月15日

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  • Saghi Neshat,
  • Baharak Motamedvaziri,
  • Hadi Kiadaliri,
  • Mahdi Sarai Tabrizi

摘要

Climate change is now recognized as one of the most important environmental challenges of the 21st century. Global warming, coupled with a decrease in precipitation, has exacerbated the effects of climate change. Assessing drought severity and distribution within a region and devising strategies to mitigate its impacts constitutes a central component of drought management. Recently, General Circulation Models (GCMs) have been implemented to predict the impacts of climate change (CC) on various systems, including water resources and others. Therefore, this study examines the effects of CC on temperature and precipitation parameters using CMIP6 climate models in southern Kerman Province. The study implements data from the CanESM5 predictor model and the SDSM downscaling model, based on emission scenarios developed for the baseline period (1998–2022), to forecast future atmospheric conditions. The Standardized Precipitation Index (SPI) was used for monitoring temporal and spatial patterns of drought variations under present and future conditions. The SPI was calculated using precipitation data from 24 meteorological stations across time scales of 1, 3, 6, 9, 12, 18, 24, and 48 months during the 1998–2022 statistical period. Climate variables were downscaled and simulated using the Coupled Model Intercomparison Project Phase 6 (CMIP6) framework by applying the Shared Socioeconomic Pathways (SSPs; the optimistic SSP1-2.6 and pessimistic SSP5-8.5) to project a near-future twenty-year period spanning 2040 to 2059. The performance of CMIP6 was evaluated by implementing two model evaluation metrics, as Root Mean Square Error (RMSE) and the coefficient of determination (R2). Temporal and spatial patterns of drought were evaluated for the historical baseline and future scenarios. Baseline time series analysis revealed that short-term droughts were more frequent but less persistent than long-term droughts. Spatial analysis indicated that most of the region experienced predominantly normal conditions, with wetter conditions concentrated in the northern and northwestern areas, while southern regions showed higher susceptibility to drought. Rainfall simulations using the SDSM model during the baseline period demonstrated high reliability, with R² values varying from 0.63 to 0.98 across different meteorological stations. Future projections suggest prolonged drought episodes, with drought conditions expected in 42–58% of cases across 3 to 24-month time scales under both scenarios. Southern and southwestern parts of the region are identified as areas with the highest likelihood of future drought occurrence. The results offer critical resources to better manage agriculture and water in the area.