Food security for the growing global population is closely associated with the variations in agricultural yield at the regional scale. Based on this perspective, the current study was designed to determine the impacts of drought on wheat production in the Punjab province, which is the agricultural hub of Pakistan. Wheat is a staple food in Pakistan, and Punjab provides a major contribution to the total wheat production of the country. Therefore, Punjab is vital to scientific concerns regarding the evaluation of climatic impacts on the annual wheat yield. The current study offers a better understanding of the drought impacts on wheat in Punjab during 2001–2019. The Standardized Precipitation Index was used to assess the impact of drought stress on the wheat yield. Its temporal evolution indicates the recurrent appearance of drought episodes during the wheat cropping season. Furthermore, meteorological drought was noticed in all study years except for 2019. The results reveal that 2002 experienced severe drought conditions. The frequency of drought was calculated as 29% for SPI-12. The relationships between soil moisture, the Standardized Yield Residual Series (SYRS), and the detrended SPI at lags of 1–12 months indicate that zones 1 and 2 are more sensitive to dry conditions. The results presented in this study provide evidence to authorities responsible for developing policies in the context of natural hazards, particularly droughts, and for preparing drought mitigation plans and implementing the adaptation strategies to minimize the effects of drought on wheat yields.

Compound dry–hot extremes (CDHEs) are among the most damaging climate hazards. Most metrics used to diagnose them are estimated at monthly or seasonal resolution or rely on precipitation-based drought proxies that can miss fast soil moisture-driven land–atmosphere feedbacks. This paper delivers two tightly linked products for global CDHE monitoring over land (excluding Antarctica) at 0.1° resolution for 1961–2023: (i) a continuous, daily severity index, i.e. the Standardized Soil Moisture–Temperature Compound Index (SSTCI), and (ii) a companion, event-based CDHE catalogue derived from SSTCI. SSTCI is constructed by first quantifying grid specific soil moisture memory using dry-down events, fitting an exponential decay to estimate a characteristic dry-down timescale (τ). This memory is used to compute a Standardized Antecedent Soil Moisture Index (SASMI), which is paired with a daily Standardized Temperature Index (STI). SASMI and STI are then integrated using a Frank copula to represent their joint probability, which is transformed to a standardized normal variate to yield SSTCI, providing a spatially comparable daily measure of compound dry–hot stress. To move from daily index values to physically interpretable hazards, we apply removal–merging refinement to threshold based SSTCI spells, minimizing fragmented detection and producing a coherent event catalogue with event timing and magnitude descriptors suitable for event-based statistics. Our evaluation shows broad agreement between SASMI (SSTCI) and established drought (compound) metrics and vegetation stress. Moreover, SSTCI captures the timing and evolution of well documented CDHEs across multiple regions and timescales when applied to case studies. Together, the resulting SSTCI fields and event catalogue provide a consistent, daily scale foundation for global monitoring, process attribution of land–atmosphere feedback, and early-warning applications for compound dry–hot hazards. Data introduced in this paper are openly accessible from https://doi.org/10.5281/zenodo.18280747 (SSTCI) (Aftab et al., 2026c) and https://doi.org/10.5281/zenodo.20826759 (CDHE event catalogue) (Aftab et al., 2026b).

Compound dry–hot extremes (CDHEs) are among the most damaging climate hazards. Most metrics used to diagnose them are estimated at monthly or seasonal resolution or rely on precipitation-based drought proxies that can miss fast soil moisture-driven land–atmosphere feedbacks. This paper delivers two tightly linked products for global CDHE monitoring over land (excluding Antarctica) at 0.1° resolution for 1961–2023: (i) a continuous, daily severity index, i.e. the Standardized Soil Moisture–Temperature Compound Index (SSTCI), and (ii) a companion, event-based CDHE catalogue derived from SSTCI. SSTCI is constructed by first quantifying grid specific soil moisture memory using dry-down events, fitting an exponential decay to estimate a characteristic dry-down timescale (τ). This memory is used to compute a Standardized Antecedent Soil Moisture Index (SASMI), which is paired with a daily Standardized Temperature Index (STI). SASMI and STI are then integrated using a Frank copula to represent their joint probability, which is transformed to a standardized normal variate to yield SSTCI, providing a spatially comparable daily measure of compound dry–hot stress. To move from daily index values to physically interpretable hazards, we apply removal–merging refinement to threshold based SSTCI spells, minimizing fragmented detection and producing a coherent event catalogue with event timing and magnitude descriptors suitable for event-based statistics. Our evaluation shows broad agreement between SASMI (SSTCI) and established drought (compound) metrics and vegetation stress. Moreover, SSTCI captures the timing and evolution of well documented CDHEs across multiple regions and timescales when applied to case studies. Together, the resulting SSTCI fields and event catalogue provide a consistent, daily scale foundation for global monitoring, process attribution of land–atmosphere feedback, and early-warning applications for compound dry–hot hazards. Data introduced in this paper are openly accessible from https://doi.org/10.5281/zenodo.18280747 (SSTCI) (Aftab et al., 2026c) and https://doi.org/10.5281/zenodo.20826759 (CDHE event catalogue) (Aftab et al., 2026b).