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<p>Compound hot–dry extremes are an important climate risk in monsoon-influenced, water-stressed regions, but their diagnosed occurrence can depend strongly on the dryness metric and timescale used. Using daily maximum temperature (T<sub>max</sub>) and precipitation observations from 46 meteorological stations across Pakistan for 1980–2017, we assessed heat extremes, dryness, and compound hot–dry months within a station-based framework. Heat was quantified using TX90p, and dryness was represented using two complementary precipitation-based metrics: (i) an SPI-like standardized monthly precipitation index and (ii) a rapid-drying metric based on standardized anomalies of 30-day running precipitation sums. A hot–dry month was defined as a month with at least three TX90p days and concurrent dryness under either definition. Station-averaged climatology shows peak T<sub>max</sub> in June (37.42&#xa0;°C) and peak precipitation in July (93.01&#xa0;mm month<sup>− 1</sup>, together with strong spatial gradients in baseline climate across the station network. TX90p trends are spatially heterogeneous, ranging from − 0.53 to + 0.68 days year-1. Compound hot–dry frequency is low but strongly definition-dependent, mean frequency is 0.14 months year<sup>− 1</sup> under SPI-like dryness and 0.13 months year<sup>− 1</sup> under rapid drying. At the same time, overlap between the two inventories remains limited (station-level mean Jaccard index = 0.04). Sensitivity analysis further shows that this low agreement persists across plausible alternative thresholds for dryness and heat. Lead–lag analysis indicates organized heat–drying covariability, with temperature anomalies typically preceding increases in drying intensity by several days. However, this timing should be interpreted with caution because the rapid-drying metric uses a 30-day accumulation window. Overall, the results show that compound hot–dry conditions in Pakistan differ markedly between monthly precipitation deficits and shorter-timescale drying diagnostics, highlighting the importance of multi-timescale dryness characterization for compound-risk assessment and climate monitoring.</p>

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Multi-metric assessment of compound hot–dry events in Pakistan

  • 期刊论文

  • 发表日期：

    2026年6月15日

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  • Usama Bin Anjum,
  • Hong Fan,
  • Israr Ahmad,
  • Urooj Fatima,
  • Irfan Ullah

摘要

Compound hot–dry extremes are an important climate risk in monsoon-influenced, water-stressed regions, but their diagnosed occurrence can depend strongly on the dryness metric and timescale used. Using daily maximum temperature (Tmax) and precipitation observations from 46 meteorological stations across Pakistan for 1980–2017, we assessed heat extremes, dryness, and compound hot–dry months within a station-based framework. Heat was quantified using TX90p, and dryness was represented using two complementary precipitation-based metrics: (i) an SPI-like standardized monthly precipitation index and (ii) a rapid-drying metric based on standardized anomalies of 30-day running precipitation sums. A hot–dry month was defined as a month with at least three TX90p days and concurrent dryness under either definition. Station-averaged climatology shows peak Tmax in June (37.42 °C) and peak precipitation in July (93.01 mm month− 1, together with strong spatial gradients in baseline climate across the station network. TX90p trends are spatially heterogeneous, ranging from − 0.53 to + 0.68 days year-1. Compound hot–dry frequency is low but strongly definition-dependent, mean frequency is 0.14 months year− 1 under SPI-like dryness and 0.13 months year− 1 under rapid drying. At the same time, overlap between the two inventories remains limited (station-level mean Jaccard index = 0.04). Sensitivity analysis further shows that this low agreement persists across plausible alternative thresholds for dryness and heat. Lead–lag analysis indicates organized heat–drying covariability, with temperature anomalies typically preceding increases in drying intensity by several days. However, this timing should be interpreted with caution because the rapid-drying metric uses a 30-day accumulation window. Overall, the results show that compound hot–dry conditions in Pakistan differ markedly between monthly precipitation deficits and shorter-timescale drying diagnostics, highlighting the importance of multi-timescale dryness characterization for compound-risk assessment and climate monitoring.