Status: this preprint is currently under review for the journal ESSD.
The Standardized Soil Moisture-Temperature Compound Index (SSTCI): Daily scale global data set and event catalogue for compound dry–hot extremes (1961–2023)
Abstract. 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).
Received: 24 Apr 2026 – Discussion started: 29 Jun 2026
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
Review of “The Standardized Soil Moisture-Temperature Compound Index (SSTCI): Daily scale global data set and event catalogue for compound dry–hot extremes (1961–2023)” by Aftab et al.
The manuscript by Aftab et al. deals with the quantification of compound heat-drought extremes. Given that a large share of climate change impact is believed to happen via increasing occurrence of compound events, this is a highly relevant topic. The manuscript present a new global dataset on the Standardized Soil Moisture-Temperature Compound Index (SSTCI). While a standard dataset on compound heat-drought events is potentially relevant, and the manuscript is generally well-written and illustrated, I am not convinced that the current manuscript provides the major contribution to the field and therefor recommend not to accept the manuscript for final publication in ESSD. My recommendation is based on the following arguments:
In the review criteria, ESSD mentions significance as the most important aspect. With regard to uniqueness, it is stated that “it should not be possible to replicate the experiment or observation on a routine basis”. The current manuscript, in my view, fails to clear this hurdle representing a more-or-less straightforward application of a standardized index to openly available reanalysis data, with poorly motivated choices that strongly impact the applicability of the dataset (see also below).
In their approach, the authors use soil moisture averaged over the top 7 cm of the soil profile. This seems rather arbitrary, as there is no physical reason why the top 7 cm soil moisture would influence air temperatures more than the top 2 cm or 10 cm, or even deeper. In many more humid climates, soil moisture averaged over the root zone would be the best representation of soil moisture impacts on T through land-atmosphere interaction, since plant transpiration (of root water uptake) is the largest component of terrestrial ET during dry conditions. Deeper soil moisture would have considerably longer e-folding timescales that more closely follow timescales involved in soil moisture-temperature coupling. The authors do not provide a physical justification of this arbitrary choice, nor do they provide a sensitivity analysis. Any other arbitrary choice here would have resulted in different values of the index. The fact that the authors show a (weak) positive correlation with other indices around most of the globe is not convincing, as almost any other choice would likely do the same because of the strong impact of P.
The authors calculate the soil moisture part of their index based on SASMI which is using an e-folding timescale. The added value of this approach is not made clear. What is the benefit of using this method over using any other possibility, including using SSMI calculated using soil moisture from ERA5-Land directly? The choice again feels arbitrary, and in my opinion results in less realistic values than alternative choices based on available data or model output.
The authors claim that “Yet, most existing compound indices are provided at monthly or seasonal scales”. This does not really do justice to the large body of literature on multivariate indices for heat-drought extremes. I refer here to Miralles et al, 2012 (doi:10.1029/2012GL053703) and Shan et al. 2024 (https://doi.org/10.5194/hess-28-2065-2024) as examples of earlier and recent studies, but many other studies exist. The novelty of the study should be motivated better based on a more thorough literature review.
The authors claim that a main novel aspect in their work is the catalogue of event timing and magnitude per location. I do not consider this particularly novel, since it is rather straightforward to do once the index has been defined and calculated. A more novel aspect would be to define unique spatio-temporal clusters of heat-drought events, and catalogue these rather than the just the temporal dynamics for each grid cell.
Given that many different indices exist, I would see potential value in a large ensemble of heat-drought indices, which would also allow quantification of some of the uncertainties involved through the ensemble spread. Such dataset would, in my view, classify as significant.
This study provides a daily global compound dry–hot index and a companion event catalogue that records individual events, covering 1961 to 2023 at 0.1° resolution. Based on soil moisture and temperature, these datasets reveal that compound dry–hot extremes have become more frequent and longer lasting in many regions, especially in recent decades. This work improves global monitoring of climate risks and their possible impacts on water, ecosystems, and agriculture.
This study provides a daily global compound dry–hot index and a companion event catalogue that...
Review of “The Standardized Soil Moisture-Temperature Compound Index (SSTCI): Daily scale global data set and event catalogue for compound dry–hot extremes (1961–2023)” by Aftab et al.
The manuscript by Aftab et al. deals with the quantification of compound heat-drought extremes. Given that a large share of climate change impact is believed to happen via increasing occurrence of compound events, this is a highly relevant topic. The manuscript present a new global dataset on the Standardized Soil Moisture-Temperature Compound Index (SSTCI). While a standard dataset on compound heat-drought events is potentially relevant, and the manuscript is generally well-written and illustrated, I am not convinced that the current manuscript provides the major contribution to the field and therefor recommend not to accept the manuscript for final publication in ESSD. My recommendation is based on the following arguments: