the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 04 Mar 2026
Increasing heat stress across Southeast Asia driven by compound warming and moistening
Abstract. Heat stress is intensifying across Southeast Asia under global warming, yet the relative influences of atmospheric warming and moistening across timescales remain insufficiently quantified. This study investigates the thermodynamic drivers of warm-season (April–October) heat-stress intensity, measured by the daily maximum wet-bulb globe temperature (WBGTmax), and frequency, defined as the annual number of extreme heat-stress days (Nxday), across Southeast Asia and its 20 climatic sub-regions. Using observations together with dynamically downscaled CORDEX–SEA simulations, we apply a unified attribution framework to separate the effects of air temperature, specific humidity, and residual nonlinear processes on historical (1985–2014) trends, interannual variability, and projected late-century changes (2071–2100 relative to 1985–2014) under SSP5–8.5. Historical increases in WBGTmax and Nxday are dominated by temperature across much of the region. However, humidity already provides important amplification in monsoon-influenced lowlands, including Indochina, the Philippines, and parts of the Malay Peninsula. Future projections indicate a coherent basin-wide shift toward compound warm–humid conditions. In many monsoon regions, rising moisture contributes roughly 30–50 % of the increase, consistent with enhanced atmospheric water-holding capacity in a warmer climate. In contrast, interannual variability, particularly over the Maritime Continent, is strongly governed by nonlinear temperature–humidity interactions, which generate substantial unexplained components. Because Nxday depends on threshold exceedance, it shows a stronger amplification of future change than WBGTmax, even though its long-term evolution remains primarily temperature controlled. Overall, the results demonstrate that heat-stress escalation in Southeast Asia increasingly reflects rising atmospheric moist enthalpy rather than dry-bulb warming alone, underscoring the need for adaptation strategies that explicitly consider both temperature and humidity.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2026-829', Anonymous Referee #1, 29 Mar 2026
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AC1: 'Reply on RC1', Dzung Nguyen-Le, 21 Apr 2026
We sincerely thank the reviewer for the careful reading of our manuscript and for the constructive comments. These comments were very helpful and led to substantial revisions of the manuscript.
(1) On the nonlinear nature of the attribution framework:
We agree that the original presentation did not sufficiently clarify the nonlinear character of WBGT and could give the impression of a purely linear additive decomposition. In the revised manuscript, we have clarified that the framework is based on deterministic factor separation applied directly to the nonlinear WBGT heat-balance equations. We also revised the interpretation of the synergy and unexplained terms to avoid overstating their physical separability.(2) On percentage contributions and uncertainty:
We agree that presenting regional results only as percentages may give a false sense of precision. In the revised manuscript, regional attribution results are now presented in absolute physical units rather than percentages, and 95% confidence intervals are provided using spatial bootstrap resampling.(3) On the omission of wind speed and radiation in the attribution:
We agree that this was an important limitation of the original manuscript. In response, we have expanded the attribution framework to explicitly include wind speed and downwelling solar radiation, in addition to temperature and specific humidity. The Methods, Results, and figures have been revised accordingly.We are grateful for these comments, which helped us improve the clarity and physical consistency of the manuscript. A detailed point-by-point response is provided in the revised submission.
Citation: https://doi.org/10.5194/egusphere-2026-829-AC1
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AC1: 'Reply on RC1', Dzung Nguyen-Le, 21 Apr 2026
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RC2: 'Comment on egusphere-2026-829', Anonymous Referee #2, 23 May 2026
This manuscript investigates the thermodynamic drivers of heat stress across Southeast Asia, focusing on warm-season daily maximum wet-bulb globe temperature, WBGTmax, and the annual number of extreme heat-stress days, Nxday, defined using a WBGTmax threshold of 30 °C. The study uses ERA5 reanalysis for 1985–2014 and dynamically downscaled CORDEX–SEA simulations for late-century projections under SSP5–8.5. The authors apply a unified attribution framework to separate the contributions of near-surface air temperature, specific humidity, and an unexplained residual component to historical trends, interannual variability, and future mean-state changes.
The topic is timely and relevant, and the manuscript has a clear regional focus. The distinction between heat-stress intensity and threshold-exceedance frequency is useful, and the attempt to compare drivers across trends, interannual variability, and future changes is potentially valuable. However, several methodological and presentation issues should be addressed before the conclusions can be considered robust.
Major comments
1. Validation of CORDEX-SEA: The manuscript states that CORDEX–SEA regional climate simulations are bias-corrected using the MBCn multivariate bias-correction method before WBGT calculation. The correction is applied to temperature, specific humidity, wind speed, surface pressure, and shortwave radiation, and the ensemble mean of two simulations is then used to derive WBGT and related heat-stress metrics.
However, the manuscript does not provide a clear validation of the historical CORDEX–SEA simulations against ERA5 or independent observations. Because the main conclusions depend on the relative contributions of temperature and humidity, it is important to demonstrate whether the raw and bias-corrected simulations can reproduce the historical climatology, seasonal cycle, interannual variability, spatial gradients, and threshold exceedance frequency of WBGTmax and Nxday.
2. Only two GCM-RCM results?
Only two are used, which is understandable. The manuscript currently presents the ensemble mean, but the uncertainty associated with the small model sample is not sufficiently discussed. The authors should show whether both simulations produce consistent spatial patterns and similar T/q contribution ratios. At minimum, model-by-model results or uncertainty ranges should be included in the main text or supplementary material. Without this, it is difficult to assess whether the projected humidity contribution and regional contrasts are robust or dependent on one model realization.
3. ENSO/MJO
I don't see much of supporting analysis on the argument on these two. A useful addition would be to correlate regional WBGTmax/Nxday anomalies and the attributed T/q components with ENSO, IOD, and possibly MJO metrics. If such analysis is beyond the scope of the study, the manuscript should present ENSO/MJO only as a possible mechanism rather than a confirmed driver.
4. Residual term
A major result of the paper is that the unexplained residual component is large for interannual variability, particularly over the Maritime Continent and for Nxday. In some sub-regions, the residual reportedly accounts for 40–60% of total Nxday variability. The manuscript interprets this residual mainly as evidence of nonlinear temperature–humidity interactions and compound anomalies. However, the residual may include much more than nonlinear T–q interaction. One has to be quite careful in discussing something not known, like residual term.
5. Figures and text require substantial overhaul:
The figures and captions need significant improvement for clarity and consistency. Figures are generally in percent change. I'm not sure what is the base for that. The text also requires careful editing. For example, a missing author name in the WBGT method citation, where the text says “model of (2008)”.
Citation: https://doi.org/10.5194/egusphere-2026-829-RC2 -
AC2: 'Reply on RC2', Dzung Nguyen-Le, 25 May 2026
We sincerely thank Reviewer #2 for the careful and constructive assessment of our manuscript. We agree that additional validation and clearer presentation are needed to support the robustness of the conclusions.
In the revised manuscript, we will add new validation analyses comparing raw and MBCn-corrected CORDEX–SEA simulations against ERA5 for historical WBGTmax and Nxday, including spatial bias maps and subregional summaries of climatological bias and interannual variability.
We will also add model-by-model analyses for the two CORDEX–SEA simulations to examine whether the projected changes and the relative temperature and humidity contributions are consistent across model realizations.
We also agree that the residual term should be interpreted more cautiously. We will revise the text to clarify that the residual includes not only nonlinear interactions, but also unresolved variability, model-fit limitations, threshold effects, and other processes not explicitly captured by the attribution framework.
Statements referring to ENSO/MJO will be softened unless supported by additional analysis, and we will present them as possible sources of variability rather than confirmed drivers. Finally, we will revise the figures and captions to present contributions in absolute physical units with uncertainty information where appropriate, and we will correct the citation and wording issues noted by the reviewer.
We appreciate these comments, which will help us substantially improve the methodological clarity and robustness of the manuscript. A detailed point-by-point response and a revised manuscript will be provided after completing these additional analyses.
Citation: https://doi.org/10.5194/egusphere-2026-829-AC2
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AC2: 'Reply on RC2', Dzung Nguyen-Le, 25 May 2026
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The author used three different types of attribution methods, namely trend decomposition, variability attribution, and mean-state change attribution, to quantify the relative contributions of air temperature and specific humidity to historical and projected heat stress across Southeast Asia. An interesting study, but there are a few substantial concerns that need to be addressed before acceptance.
1. The manuscript's entire attribution framework relies on an assumption that the contributions of air temperature (T) and specific humidity (Q) to wet-bulb globe temperature (WBGT) can be treated as linearly separable, additive components. This assumption fundamentally misunderstands the thermodynamic relationship between the two variables. In reality, the relationship between T, Q and moist thermodynamic quantities (WBGT in this context) is inherently non-additive. The physical relationship between WBGT and its drivers is nonlinear due to the saturation of evaporative cooling at high humidity and the nonlinear dependence of wet-bulb temperature on T and Q.
T and Q to WBGT is not as analogous to adiabatic and diabatic warming to the total warming, because adiabatic and diabatic contributions are genuinely additive science they both operate on the same variable (T) through physically distinct. See https://doi.org/10.1038/s41561-023-01126-1 and https://doi.org/10.1038/s41612-024-00797-w for details.
Therefore, a substantial portion of interannual variability is attributed to an "unexplained (residual)" term. The manuscript attributes this residual to "nonlinear temperature-humidity interactions" and "compound anomalies" without further analysis. Actually, the high residual fractions in interannual variability indicate that linear models are inadequate for capturing the true dynamics.
2. The author’s attempt to express contributions as percentages gives a false sense of precision in Figures 4, 7 and 10. If the author insists on empirical attribution, uncertainty levels and confidence intervals should be provided. The contributions depend on the specific model specifications and could change with alternative methodological choices (e.g., different regression models, inclusion of interaction terms, or alternative bias-correction methods).
3. The study explicitly states that wind speed and radiation are included in the WBGT calculation but are not attributed.