Hot season gets hotter due to rainfall delay over tropical land in a warming climate

Domain: earth_science
Published: 2025-03-04
Editorial outcome: minor_revision

Abstract
Tropical land generally experiences the hottest period (spring) in a year just before the onset of wet season. Previous studies suggested that in a warming climate, the wet season would come later, but its origin is debated and its impact on temperature remains unknown. Here, we find that the warming of hot season would be amplified under global warming, and refer to it as “hot-season-gets-hotter” phenomenon. The amplified hot season warming is closely tied to the amplified warming of hot temperature percentiles. The hot-season-gets-hotter phenomenon is mainly due to the rainfall delay and most evident in the Amazon, where spring is warming by almost 1 K more than the annual mean and the 99th percentile temperatures are warming ~30% more than the mean by the end of 21st century in a high emission scenario. Comparing experiments with and without land-atmosphere coupling, it is further found that the rainfall delay is initially driven by the enhanced effective atmospheric heat capacity and then substantially amplified by positive soil moisture-atmosphere feedback. In the satellite period, observations consistently show that the hot-season-gets-hotter phenomenon has already emerged along with the rainfall delay in the Amazon. Intensified hot and dry spring climate can enhance risks of drought, heatwaves and wildfires, threatening the Amazon forest and habitats in the tropics.

Introduction
The tropics are home to ~40% of the world’s population and 80% of global biodiversity1,2. By 2050, tropical land is predicted to host most of the world’s people and two-third of its children2. As the tropics are already warmer than any other region in the world, any further warming may significantly affect its habitability. This could especially affect low-income and lower-middle-income countries as these are mostly located in the tropics. Although the human-induced warming rate in the tropics is generally smaller than the higher latitudes, the anthropogenically forced signal may emerge earlier from the observation3–5 considering the weaker inter-annual variability in the tropics. These motivate an examination of how the tropical climate responds to global warming and whether the forced signal has already emerged in the historical period.

Influenced by the seasonal cycle of solar radiation, precipitation and temperature are closely linked over tropical land throughout the year. As the sun crosses the Equator, the hemisphere experiencing spring heats up rapidly, causing the temperature to rise until the onset of monsoon rainfall, which helps to mitigate the summer heat. Hence, spring is usually the hottest season over tropical land and the timing of the monsoon onset has large impacts on how hot the land can get. At the inter-annual time scale, there is a tight relationship between the monsoon onset and spring temperature over the Indian monsoon region6,7. That is, a monsoon onset delay is accompanied by a warmer spring. This tight relationship between precipitation and temperature is also found in South America8–10. Hence, the future change in the monsoon onset is important for the temperature change during spring. In a warming climate, previous studies have identified a significant seasonal delay of tropical rainfall11,12, mainly over tropical land monsoon regions13–16. If the tight relationship between precipitation and temperature still holds under global warming, we may expect higher-than-the-annual mean warming in spring, which is already the hottest season over tropical land. This will be one of the focuses of this study.

Regarding the seasonal delay of tropical rainfall, two views have prevailed17. The first one argues that under global warming, the effective atmospheric heat capacity is enhanced due to the nonlinear dependence of moisture on temperature under the Clausius–Clapeyron relation, which delays the response of tropical rainfall to the seasonal solar forcing as the atmosphere needs more time to accumulate the energy for the monsoon onset. This view emphasizes the role of enhanced moisture demand in the wet season onset under global warming12,13,15,16,18, which can be met via either local evaporation or remote transport. The remote transport would involve large-scale circulation as discussed in many previous studies11,19,20. The other view argues that under global warming, as the dry season gets drier11,21, the soil moisture in the following spring would decrease, so more time is needed for the soil moisture to replenish to support evapotranspiration that enhances the low-level moist static energy (MSE) to meet the convection threshold, thus delaying the onset of wet season22–24. This “enhanced convective barrier” mechanism emphasizes the role of reduced moisture sources in the wet season onset under global warming. It is important to note that moisture will be required for the wet season onset in the two views, which can either be provided locally through evapotranspiration or from remote regions. The relative importance of the two views on the rainfall delay remains to be reconciled, which is crucial for understanding the temperature changes over tropical land. This will be the second focus of this study.

A recent study developed a quantitative theory based on convection coupling to explain the amplified warming over tropical land25. It concluded the amplified warming in the hot days over tropical land is linked to the concurrent dry condition of the high-percentile temperature and decreased humidity changes under global warming25. This provides important guidance for understanding the temperature changes over tropical land. Following this, here we aim to examine seasonal warming over tropical land and how it links to seasonal delay of rainfall under global warming. Since there is a higher chance for spring to experience the high-percentile temperature over tropical land, it is pertinent to examine whether the amplified warming of the high-percentile temperature is tied to the seasonal changes in the temperature and precipitation. Here, by combining the climate simulations from the Coupled Model Intercomparison Project Phases 526 and 627 (CMIP5 and CMIP6, see “Modelsimulations” in Methods), we find that the amplified high-percentile temperature over tropical land is closely linked to the amplified spring warming. We refer to the amplified spring warming as a hot-season-gets-hotter regime. As an evident phenomenon over tropical land under global warming, this hot-season-gets-hotter phenomenon is found to be associated with the seasonal delay of rainfall, i.e., decreased rainfall in spring. Model experiments with fixed soil moisture further reveal that rainfall delay under global warming is initially driven by the enhanced atmospheric heat capacity, then substantially amplified by the soil moisture-atmosphere feedback. During the satellite period, the hot-season-gets-hotter phenomenon has already emerged in the Amazon and Southern Africa, with far-reaching implications for human society and the ecosystems.

Results
Here, we utilize the historical and high radiative forcing scenarios (RCP8.5 for CMIP5 and SSP585 for CMIP6) from 30 CMIP5 models and 27 CMIP6 models to represent current and future climates and their differences as the changes under global warming (see “Modelsimulations” in Methods). Figure 1 shows the annual cycle changes of rainfall and daily-maximum surface air temperature (TX) over tropical land under global warming. Here, TX, defined as the highest temperature recorded at a height of 2 meters across a day, is used as it is more influenced by the changes in the solar radiation, but the results from surface air temperature are consistent with TX (Supplementary Fig. 1). Climatologically, rainfall peaks in the local summer in both hemispheres (Fig. 1a, b), while temperature peaks in the local spring before the onset of wet season and once the wet season starts, temperature decreases (Fig. 1d, e). Under global warming, the local spring receives less rainfall but the local autumn receives more rainfall (Fig. 1a, b), featuring an evident seasonal delay of tropical rainfall as previously noted11–13. It is found that there are high inter-model correlations between phase changes of rainfall annual cycle and local spring rainfall changes (0.89 and 0.78 in the northern and southern tropical land, respectively, Supplementary Fig. 2), suggesting the local spring rainfall change is a good indicator of the rainfall delay. Corresponding to the seasonal delay of tropical rainfall, the local spring sees the maximum temperature increases across the year in both hemispheres under global warming (Fig. 1d, e). As the local spring is the hottest season, the increase in the temperature would make the hot season even hotter, which we refer to as the “hot-season-gets-hotter” regime. Regionally, the seasonal delay of rainfall and hot-season-gets-hotter phenomena are evident in almost all tropical land monsoon regions (except northern Australia and northern South America) and are most evident in the Amazon (Fig. 1c, f). This suggests this is a common feature in the tropical land monsoon regions, also consistent with a recent finding of a widespread seasonal delay of rainfall across different monsoons under global warming16. There is also a high spatial correspondence between the seasonal delay of rainfall and hot-season-gets-hotter phenomena, with a pattern correlation of −0.68 (Fig. 1c vs. f). Moreover, there exists a significant inter-model relationship between local spring precipitation changes and temperature changes, with correlations of −0.64 and −0.70 in the northern and southern tropical land respectively (Fig. 1g, h). That is when one model exhibits a stronger rainfall delay under global warming, it would also project a stronger hot-season-gets-hotter phenomenon.

To illustrate how the seasonal delay of tropical rainfall leads to the hot-season-gets-hotter phenomenon, the detailed physical processes are examined through surface energy flux analysis. It is found that surface energy fluxes are closely tied to the seasonal delay of tropical rainfall (Supplementary Fig. 3): the reduced rainfall in the local spring is tied to the reduced cloud cover, which allows more incoming solar radiation (Supplementary Fig. 4a, c, d). Meanwhile, the reduced rainfall also decreases soil moisture, which reduces latent heat flux (Supplementary Fig. 4b, e, f). Hence, the more incoming shortwave radiation can only be balanced by the more upward longwave radiation and sensible heat flux, both associated with more spring warming. The related mechanisms are also consistent with previous findings20,21. The conclusion still holds when the absolute changes in these variables are considered. Hence, the seasonal delay of tropical rainfall produces the hot-season-gets-hotter phenomenon mainly by increasing the incoming solar radiation due to fewer clouds and decreasing the latent heat flux due to lower soil moisture.

Along with the hot-season-gets-hotter, we would expect the higher percentile temperature to warm more under global warming, which would favor more occurrences of extreme heat events. To confirm this, we also plot the future changes of different percentiles of temperature (Fig. 2). Clearly, the climatological higher percentile temperatures generally warm more in both hemispheres under global warming (Fig. 2a, b), i.e., “hot-percentile-gets-hotter”. For example, the 99th percentile temperature (TX99p) would warm 14% and 25% more than the 1st percentile temperature in the northern and southern tropical land, respectively. Compared to the mean warming, there is 7.4% and 18.5% more warming for TX99p in the northern and southern tropical lands, respectively. As expected, the enhanced TX99p warming is closely linked to the larger warming in the local spring in both hemispheres (Fig. 2c, d), with inter-model correlations of 0.61 and 0.88 for the northern and southern tropical land, respectively. The regional features of this “hot-percentile-gets-hotter” phenomenon are also examined (Supplementary Fig. 5). The enhanced high-percentile warming is evident in almost all the tropical land, including Mexico, Sahel, India, Indochina Peninsula, Amazon, and Southern Africa. The most evident signal occurs in the Amazon, where the local spring warms by 0.93 K more than the annual mean, and the 99th percentile warms by 29% more than the mean temperature. The hot-percentile-gets-hotter phenomenon is also pronounced in the mid- and long-term from the middle and high emission scenarios over tropical land (Supplementary Fig. 6). The enhanced high-percentile temperature warming is consistent with a previous study25, and here we clearly link it to the seasonal temperature changes, which is found to be caused by the seasonal delay of rainfall as examined above.

As the hot-season-gets-hotter phenomenon is mainly due to the seasonal delay of tropical rainfall under global warming, it is important to reconcile the two views mentioned above on the causes of the delay. To compare the relative importance of the two mechanisms, we employ two experiments from a subset of models that participated in the CMIP6 LS3MIP (the Land Surface, Snow and Soil Moisture Model Intercomparison Project)28: one featuring land-atmosphere interactions in fully coupled simulations and the other with soil moisture fixed so that the land-atmosphere coupling through interactive soil moisture is disabled (see “Soil moisture-atmosphere coupling experiments” in Methods). By comparing the two experiments, we can examine the relative importance of the enhanced convective barrier mechanism versus the enhanced effective atmospheric heat capacity in causing the rainfall delay. The former would be present in the fully coupled experiments, whereas the latter would be expected in both experiments. Figure 3 shows precipitation and TX annual cycle changes in these two experiments and their differences. Both the seasonal delay of tropical rainfall and hot-season-gets-hotter phenomena are evident in the fully coupled runs, suggesting these two phenomena are robust, regardless of only a subset of models used here. Interestingly, in the fixed soil moisture experiment, the seasonal delay of tropical rainfall and hot-season-gets-hotter phenomena are still evident, albeit with reduced magnitude. However, the local evaporation is even enhanced in the local spring under global warming due to the enhanced humidity difference between air and land in the fixed soil moisture experiment (Supplementary Fig. 7). Hence, the convective barrier mechanism does not work here. These results are consistent with ref. 18, which found the seasonal delay of rainfall is still evident under global warming in aquaplanet model simulations without the soil moisture-atmosphere feedback. Hence, we conclude that the convective barrier mechanism is not fundamental to the rainfall delay and hot-season-gets-hotter phenomena, but it can amplify the initial signal via positive feedback. Instead, the effective atmospheric heat capacity is largely enhanced in both the fully coupled and fixed soil moisture runs (Supplementary Fig. 8; see “Effective atmospheric heat capacity” in Methods). The enhanced effective atmospheric heat capacity would make the atmosphere more sluggish to the seasonal solar forcing. In other words, the atmosphere needs more time to accumulate the MSE, mostly the latent energy, to meet the monsoon onset criterion12,13. There is also a significant relationship between the changes in the inter-seasonal differences between latent energy tendency and precipitation (Supplementary Fig. 9), suggesting a more fundamental role of the effective atmospheric heat capacity mechanism12,13,15,16 in driving the seasonal delay of rainfall, which induces the hot-season-gets-hotter phenomenon. The difference between the two experiments suggests that the soil moisture-atmosphere coupling can amplify the seasonal delay of rainfall and the hot-season-gets-hotter phenomenon by 54% and 46%, respectively, over northern tropical land. Over southern tropical land, the corresponding values are 44% and 52%. In most tropical land regions, the effective atmospheric heat capacity and the convective barrier mechanism contribute almost equally, including Amazon, Southern Africa, and Sahel (Supplementary Fig. 10). In conclusion, the tropical rainfall delay is initially driven by the enhanced atmospheric heat capacity as suggested by refs. 12, 15, while substantially amplified by the enhanced convective barrier mechanism, which nearly doubles the initial response. Here, we mainly focus on two prevailing views on the seasonal delay of tropical rainfall. Other factors, such as moisture transport due to local circulation response may also play a role in rainfall over some locations, particularly for islands29–31. This warrants further investigation in the future.

The above investigation into the hot-season-gets-hotter phenomenon and the seasonal delay of rainfall is based on a future warming scenario. It is important to examine whether they have emerged in the historical period, which is challenging due to the short record of good-quality observations, the relatively weak external forcings, and large internal variability. A previous study suggested the seasonal delay of tropical rainfall has already emerged in the satellite period15, so it is natural to inquire whether the hot-season-gets-hotter phenomenon has also emerged, given their causal relationship. To examine this, we employ all available precipitation and temperature observational datasets (see “Observational data” in Methods) and find that enhanced spring warming has already emerged in the Amazon and Southern Africa (Fig. 4), where the response projected under global warming is also the strongest (Fig. 1f). Over the Amazon, the observations show that spring has warmed by 0.47 K more than the annual mean and precipitated −0.14 mm day−1 fewer than the annual mean. Most of the observed changes are accounted for by the multimodel ensemble mean of CMIP (0.37 K and −0.24 mm day−1, respectively, Fig. 4a), which represents the external forcings (including GHGs, aerosols, solar radiation, and volcanic eruptions). This suggests the dominant role of external forces. Over Southern Africa, the external forcing accounts for less of the observed changes: about half of the precipitation changes and one-third of the temperature changes can be attributed to the external forcings. Moreover, the enhanced spring warming is closely tied to the reduced rainfall in spring, with inter-model correlations of −0.69 and −0.68 in the Amazon and Southern Africa, respectively. The reduced rainfall in spring over the recent decades over the Amazon is consistent with previous studies32,33, but here we highlight it is closely tied to the enhanced spring warming and both of them are mainly accounted for by the external forcing.

The delayed rainfall and hot-season-gets-hotter phenomena would make the future spring drier and hotter, which poses a heightened challenge for local residents’ daily lives and creates more favorable conditions for wildfires. The Standardized Dry and Hot Index (SDHI)34, broadly used to represent the hot and dry climate as an indicator of the weather and climate conditions for the wildfire, is calculated and shown in Supplementary Fig. 11 (see “Standardized Dry and Hot Index” in Methods). The lower SDHI indicates a higher risk for wildfire. One can see that the SDHI becomes significantly lower during spring in the satellite period in the southern tropical land, corresponding to the hotter and drier spring. The SDHI change is well correlated with the decreased rainfall in spring over the southern tropical land, with an inter-model correlation of 0.75 (Supplementary Fig. 11a). Regionally, the SDHI changes are also evident over the Amazon and Southern Africa, which are also closely tied to the rainfall delay (Supplementary Fig. 11b-c). Along with the future amplified rainfall delay and hot-season-gets-hotter phenomena, we would expect harsher living conditions for the populations in the tropics and an enhanced likelihood of wildfire over tropical land.

Methods
Modelsimulations
To detect seasonal delay of tropical rainfall and hot-season-gets-hotter phenomena, we analyze monthly outputs of precipitation and daily-maximum surface air TX from 30 CMIP5 models and 27 CMIP6 models26,27, as listed in Supplementary Table 1. We include most of the available model datasets to enlarge sample sizes. Given the various variables used in our study, some models are not included due to the lack of necessary outputs. We use one realization from each model to compose multimodel ensembles, which contain both CMIP5 models and CMIP6 models. Our results are not sensitive to the number of realizations. All model outputs are interpolated onto a common 2.5°×2.5° grid.

We use 1986–2005 of historical simulation to represent the current climate, 2080–2099 of the high radiative forcing scenarios (RCP8.5 for CMIP5 and SSP585 for CMIP6) simulation to define the future climate and the difference between the latter and the former to represent the future changes in a warming climate. The RCP8.5 simulations from CMIP5 and SSP585 simulations from CMIP6 have additional radiative forcing of 8.5 Wm−2 by 2100, representing the high range of emission scenarios of CMIP5 and CMIP6, respectively. SSP585 additionally encompasses factors like non-CO2 greenhouse gases, aerosols, and land use changes based on socio-economic development pathways39, but CMIP5 and CMIP6 simulations show very similar results. Furthermore, the RCP4.5 simulations from CMIP5 and SSP245 simulations from CMIP6 are used to examine our results in middle emission scenarios. To estimate the hot-season-gets-hotter phenomenon during the satellite period (1979–2022), we combine historical simulation and high radiative forcing scenarios simulation for each model to compute trends in the recent four decades.

In addition to the monthly TX, daily mean TX from both CMIP5 and CMIP6 models are also utilized to estimate enhanced high-percentile warming. Percentiles in current and future climate are computed by all daily TX averaged over the corresponding tropical land during 1986–2005 and 2080–2099, respectively, consistent with ref. 25. Ninety-nine percentiles of TX between 1st and 99th percentiles are computed for each model. The difference between the xth percentile of TX (TXxp) in the future and that in the current is defined as the future changes of TXxp.

Observational data
To estimate seasonal delay of tropical rainfall in the satellite period (1979–2022), we use the following five precipitation datasets: (1) the Climate Prediction Center (CPC) merged analysis of precipitation dataset (CMAP) with a 2.5° grid40; (2) the Global Precipitation Climatology Project dataset (GPCP) with a 2.5° grid41; (3) CPC global unified gauge-based analysis of daily precipitation (CPC)42; (4) Climatic Research Unit gridded Time Series version 4.07 (CRUv. 4.07) with a 0.5° grid43; (5) the Precipitation Reconstruction over Land dataset with a 2.5° grid44. We also use three observational datasets to detect the observed hot-season-gets-hotter phenomenon, including the monthly-mean TX from (1) the Climate Prediction Center global daily surface air temperature dataset (CPC) with a 0.5° grid45; (2) Berkeley Earth monthly temperature dataset (BEST) with a 1° grid46, as well as (3) CRU v. 4.0743. Monthly CPC datasets are obtained by averaging daily values. To compute observational Standardized Dry and Hot Index, we use five precipitation datasets described and following three near-surface air temperature: (1) CRU v. 4.0743; (2) BEST46; (3) HadCRUT5 data with a 5° grid47. All observation datasets used in this study are interpolated onto a 2.5°×2.5° grid to form observation ensembles.

Soil moisture-atmosphere coupling experiments
We use the Land Feedback Model Intercomparison Project with prescribed Land Conditions (LFMIP-pdLC) experiment (1980–2099) in the Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) to analyze the impact of soil moisture-atmosphere feedback28. LS3MIP simulations are only available from seven CMIP6 models (CESM2, CMCC-ESM2, CNRM-CM6-1, EC-Earth3, IPSL-CM6A-LR, MIROC6, MPI-ESM1-2-LR) so far. Meanwhile, not all the models provide the necessary variables, but we use all the models with the needed data in the corresponding analyses. See Supplementary Table 1 for the details. The LFMIP-pdLC experiment is performed by fixing the soil moisture based on the climatological annual cycle for the period 1980–2014 derived from historical simulation outputs of the corresponding CMIP6 model. In this study, we use the r1i1p1f2 member in the LFMIP-pdLC experiment, in which the external forcings are consistent with the historical (1980–2014) and the SSP585 (2015–2099) simulations except for fixing the soil moisture. Therefore, the difference between the fully coupled experiments (historical and SSP585 simulations) and the fixed soil moisture experiment (LFMIP-pdLC experiment) represents the soil moisture-atmosphere coupling effects. This experiment has been widely used in recent studies to diagnose the role of land-atmosphere feedback on air temperature response in climate change48–50.

Effective atmospheric heat capacity
Increased effective atmospheric heat capacity (CA) contributes to the seasonal delay of tropical rainfall. To determine the CA increases in both fully coupled and fixed soil moisture experiments, following refs. 13, 51, we calculate CA as:
CA = ∂<h> / ∂<T> / ∂t (1)
where the angle bracket denotes vertical integration between surface and top of the atmosphere. h = cpT + gz + Lvq is MSE, cp is specific heat of dry air at constant pressure, T is air temperature, g is gravity acceleration, z is geopotemtial height, Lv is latent heat of vaporization, q is specific humidity and t is time.

Standardized dry and hot index
The precipitation delay and hot-season-gets-hotter phenomenon may induce compound dry and hot events over tropical land in a warming climate. To evaluate the severity of compound dry and hot conditions, we use the SDHI34, which can be expressed as:
SDHI = Φ−1(F(G1(P), G2(T))) (2)
where Φ is the standard normal distribution, F is the marginal cumulative distribution, which transforms the joint probability into the uniform distribution, G1(P) and G2(T) are the marginal probabilities of precipitation and near-surface air temperature, respectively. Marginal distribution functions (F, G1, G2) can be fitted based on the Gringorten plotting position formula52: G = (i − 0.44) / (n + 0.12), where i is the rank of the data in the series sorted from the smallest to the largest values, n is the length of the series.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "\"Hot gets hotter due to rainfall delay over tropical land in a warming climate\" by Song et al examines climatic changes in\nspring temperature – and high percentiles of temperature – over tropical land in CMIP5/6 models. Amplified warming of\nthese temperatures is found, consistent with earlier work. The authors argue that the amplified warming can be related to a\ndelay in seasonal rainfall in a warmer climate.\nThis is an interesting manuscript that is generally well written and well presented. The science is broadly sound, but I am not\nconvinced by the arguments explaining the hot-get-hotter mechanism and the physical interpretations made. I would like to\nsee this study published, but in my opinion the scientific argument first needs to be strengthened significantly and better\nplaced in the context of previous work.\nSpecific comments:\n- Line 25: \"but its origin is on debate\" -> \"but its origin is debated\"\n- Line 26: \"both the hot season and its extreme hot events get hotter in a warming climate\" -> this is not surprising in a\nwarming climate! Suggest tweaking to highlight that the warming in those cases is amplified.\n- Line 31: \"proved\" -> this word is conventionally used when something is proven mathematically (not the case here). I\nsuggest rephrasing.\n- Line 45: From my understanding, the earlier emergence of forced trends in the tropics is due to smaller inter-annual\nvariability, rather than weaker synoptic activity.\n- Lines 60,61: Held & Soden (2006) is not an appropriate reference here; they do not discuss seasonal aspects of the water\ncycle response to warming.\n- Lines 72-75: The Byrne (2021) study developed a quantitative theory based on convective coupling to explain the amplified\nwarming over tropical land. This theory showed that the amplified warming is largely explained by climatological humidity\nover land, but humidity changes are also important. This theory was verified using CMIP6 simulations, where it can explain\nboth the multi-model mean response and the spread in temperature changes across models. With this success of the Byrne\n(2021) theory, it is not accurate to state that \"the detailed physical mechanisms remain elusive\". Given that Byrne (2021)\nboth demonstrated the amplified tropical land warming that is the focus of this study, and derived a quantitative physical to\nexplain the model behaviour, more discussion of that paper is needed to more clearly place this manuscript in the context of\nrecent work.\n- Line 83: \"caused by\" -> in my opinion, this causality has not been shown convincingly. What has been shown is a\ncorrelation between springtime precip changes and Tx changes, but this does not automatically imply causality.\n- Lines 118-120: The surface energy budget is approximately balanced over land on monthly+ timescales, and therefore\nboils down to a balance of fluxes. Using this framework to quantify \"contributions to the enhanced spring warming\" is not\nstraightforward, as temperature is a state variable and not a flux. The authors should revise this section of the manuscript to\nbetter communicate that a change in a given surface flux cannot be directly interpreted as a contribution to a temperature\nchange signal.\n- Lines 124-126: Same point as directly above – surface energy balance alone cannot explain the land temperature\nresponse.\n- Lines 178-181: Do these experiments isolate these two mechanisms cleanly? Rainfall seasonality depends on a lot of\nfactors in addition to effective heat capacity, even for fixed SM – more explanation needed. Also fixed SM runs do not\nconserve water, which is an issue given the hot-get-hotter argument is based on changes in rainfall.\n- Lines 192,193: I agree that the effective heat capacity increases with warming, but more evidence/explanation needed for\nwhy this drives the seasonal delay in rainfall. How about a scatterplot of changes in effective heat capacity vs changes in\nrainfall phase across models? This would be more convincing than Extended Data Fig. 6, which simply shows that the\neffective heat capacity increases with warming but tells us nothing directly about the change in rainfall.\n- Line 263: \"implies a compelling causal link\" -> correlation does not imply causation; this sentence should be revised.\n- Line 265: \"reducing evapotranspiration due to drier soil\" -> does the rainfall delay lead to an absolute reduction in spring\nrainfall and drier soils? Please include plots of the absolute changes in precip and SM to better support this conclusion.", "reviewer_2": "This study examines the relationship between delayed wet-season onset and increased maximum daily temperatures\ntowards the end of the dry season (local spring) over tropical land regions. The authors use high-emissions scenarios\nRCP8.5 and SSP5-8.5 from CMIP5 and CMIP6, respectively, to show that a drier and prolonged dry season leads to two\nphenomena:\n1. Increases in maximum daily temperatures during the climatologically warmest season (local spring)\n2. Stronger warming of the hottest days than for the coldest days during local spring\nThese two phenomena are grouped together and referred to as the “hot-get-hotter” phenomenon by the authors.\nFurthermore, the authors compare fully-coupled to fixed soil-moisture experiments to disentangle the impacts of enhanced\natmospheric moisture demand versus reduced moisture supply from the land-surface on this “hot-get-hotter” phenomenon.\nFinally, observations and historical CMIP simulations are used to show that this hot-get-hotter phenomenon has already\nstarted to occur, particularly in the Amazon region.\nRecommendation: The findings of this study will be of interested to the scientific community, the text is clear (albeit some\ncorrections to the language and wording are recommended) and the figures are of high quality. However, a few major\ncomments should be addressed before the paper can be published, and several minor changes are suggested.\nMajor comments:\nL54 – 67: This paragraph introduces two views to explain the delay in wet-season onset under global warming.\n1. I would argue that both of these views take a very localised approach and there is no mention of the importance of the\nlarge-scale circulation (movement of the ITCZ) in the wet-season onset as discussed e.g. by Geen et al. (2020), Biasutti &\nSobel (2009), Li, Fu (2004). This might not be the dominant mechanism, but it should be mentioned here.\n2. Regardless of which of the two outlined views is the dominant one, moisture will be required for the wet season onset.\nThis can either be provided locally through evapotranspiration or from remote regions (i.e. the ocean or other land regions).\nAgain, this is worth mentioning for the reader (see also comments below regarding L170-202).\n3. All of the references provided for the first view involve the lead author of this manuscript, and the references for the\n(opposing) second view are both from a different lead author. Are there more references that could be provided here to make\nthis a bit more of a balanced representation?\nL118 – 126: This paragraph describes how the delay of the wet-season onset leads to higher temperatures by analysing\nsurface energy fluxes and cloud cover changes (Extended Data Figures 3 and 4).\n1. The sign of change of latent and sensible heat fluxes are opposite to what is described in the text/what one would expect.\nThe sensible heat flux should be increasing and the latent heat flux should be decreasing if there is less moisture available\nfrom the soil to evaporate.\n2. The mechanism that the authors describe here has been described in other studies (e.g. Li, Fu (2004) and Li, Fu,\nDickinson (2006) and possibly others) and these should be cited.\nMinor comments:\nL42: “… most tropical countries are underdeveloped”. I would not use the word “underdeveloped”, I am not sure this is\npolitically correct. Instead, “least developed countries” (UN) or “low-income/lower-middle income countries” (e.g. World\nBank, OECD, …) could be used. For both those definitions, the statement is not true as several countries in the tropics do not\nfall in either of those categories. However, it does appear that the majority of LDCs or low-income/lower-middle income\ncountries are located in the tropics.\nL60 – 61: The cited Held and Soden (2006) paper takes a zonal-mean, annual mean approach but does not really discuss a\nseasonal drying. Other references should be included here to support this point (e.g. Li et al 2006, Biasutti & Sobel 2009, …)\nFigure 1: It would be helpful for the reader to show the future seasonal cycle as well (e.g. as a dashed line). Same for Figure\n3, and Extended Data Fig 1.\nL152-154: I am not sure it is helpful to group these two phenomena together as it makes it confusing in the rest of the paper\nwhich of the two is being referred to. For example, in the section “The observed emergence of hot-get-hotter along with\nrainfall delay” only the local-spring TX but not the hot-percentile changes are examined in the observational data, but this is\nstill being referred to as “hot-get-hotter” which should cover both of those effects. I thus suggest referring to the phenomenon\nas “hot-season-gets-hotter” throughout the paper and presenting the finding that the hot percentile also warms more as a\nlinked finding.\nL170 – 202: In this section, the fully-coupled versus fixed-soil moisture simulations are examined in order to determine what\ndrives the wet-season onset delay in a warmer climate: enhanced moisture demand by the atmosphere (“enhanced effective\nheat capacity”) or decrease moisture supply from the surface (“convective barrier mechanism”).\n1. Are there other mechanisms in the fixed soil moisture experiment which might affect\nevapotranspiration, e.g. vegetation? If so, would this affect the conclusion that the enhanced\nmoisture demand of the atmosphere is the dominant driver of rainfall delay?\n2. Due to the different monsoon dynamics over different tropical land regions (see e.g. Geen et al 2020), taking the average\nover all northern hemisphere/southern hemisphere tropical land regions might simplify things too much. Does the same\npicture emerge when averaging over the tropical land regions separately?\n3. Extended Data Figure 7 shows that in the fixed SM experiments, some of the land regions actually receive more rainfall in\na warmer world (e.g. Indonesia, northern hemisphere South America). Particularly for islands, moisture transport from the\nocean could play an important role at least in the annual mean (see e.g. Kooperman et al. 2018, Saint Lu et al 2019,\nPietschnig et al. 2021). The importance of non-local moisture sources is not addressed in the present study\nbut would be expected to play a role in wet-season onset at least over some locations.\nL 179 – 181: “The second experiment can isolate the role of enhanced effective atmospheric heat capacity in the seasonal\ndelay of rainfall.” I would suggest changing L178-181 to: \"By comparing the two experiments, we can examine the relative\nimportance of the enhanced convective barrier mechanism versus the enhanced effective atmospheric heat capacity in\ncausing the rainfall delay. The former would be present in the fully coupled experiments, whereas the latter would be\nexpected in both experiments.” since the second experiment alone cannot isolate this effect, right?\nL227 – 228: It is not clear where these numbers come from and what is meant by “external forcings”.\nFigure 4: The axis tick spacing is a bit difficult to interpret, it would be easier for the reader to have ticks at 0.1, 0.2, 0.3, … (as\nis the case for the y-axis in panel b)\nFigure 4: The region referred to in this paper as “Southern Amazon” actually spans almost all of the Amazon basin and more.\nI would perhaps refer to this region as northern South America or the Amazon (see e.g. Li et al, 2006 for their definition of the\nSouthern Amazon)\nConclusions: I would recommend starting the conclusions with a 1 – 2 sentence summary of what was examined in this\npaper and why, and then move to the findings.\nL 274: The impact on heatwaves has not really been examined in this study, the variables that were examined were\nmaximum daily temperatures and 99th percentile temperatures, but not the duration of these temperature extremes (which is\npart of the definition of a heatwave).\nReferences: It would strengthen the manuscript to include more citations from a diverse set of papers to include different\nviewpoints. Currently, only about 35 sources are cited, five of which the lead author of this manuscript is also an author on.\nSome suggestions have been made in the comments above (but this is not an exhaustive list).\nComments on language (non-exhaustive list):\nL29: “and the 99th percentile temperature is ~30% warming more than” should read as “and the 99th percentile temperatures\nare warming ~30% more than….”\nL39: “The tropics are home to … “ instead of “Tropics is …” - I would always refer to the tropics as plural (also L41)\nL49: I would say “As the Sun crosses the Equator” instead of equinox.\nL52: “how hot the land can get” instead of “reach”\nGenerally, there are some “the” too many in some places, and some “the” missing in other places, e.g. L52, L80, … : “over\nthe tropical land” should be “over tropical land” or L56-58: “. …. nonlinear dependence of moisture on the temperature under\nClausius–Clapeyron relation, which delays the response of tropical rainfall to the seasonal solar forcing as atmosphere ….”\nshould read as “…. nonlinear dependence of moisture on temperature under the Clausius–Clapeyron relation, which delays\nthe response of tropical rainfall to the seasonal solar forcing as the atmosphere ….”\nL65: “The relative importance….” Instead of “Hence, the relative importance” as this part does not really follow from what has\nbeen said above\nL72 : “in the tropical land” should be “over tropical land” (also L76, L82, …)\nL81: “We refer to the amplified spring warming” instead of “We refer the”\nL108: “referring to ‘hot-season-get-hotter’” should be “referred to here as ‘hot-season-gets-hotter’”", "reviewer_3": "The article is well presented, it adequately states the objectives of the study and the methodology used to quantify the\nchanges in the variables is solid and duly supported by the literature. The introduction appropriately describes previous\nstudies, but, a point to highlight in the introduction is the lack of references to studies for the Southern Hemisphere. There is\nabundant literature on extreme events that include changes in temperature and humidity. For example, among some recent\nstudies is that of Olmo et al., 2022 (Compound Events in South America Using the CORDEX-CORE Ensemble: Current\nClimate Conditions and Future Projections in a Global Warming Scenario), who worked throughout South America with\nregional models. More recently, Alvarez et al., 2024 (Projected changes in the frequency of compound hot and dry events\nover Tropical Brazil in CORDEX-CORE simulations), worked in the Amazon region. Also, Collazo et al., 2022 (Hot and dry\ncompound events in South America: present climate and future projections, and their association with the Pacific Ocean),\nstudied extreme events composed of temperature and humidity using a set of CMIP6 models in South America. The\nintroduction is biased towards studies carried out in the Northern Hemisphere, therefore, the inclusion of works that also\nfocus on the Southern Hemisphere is suggested.\nRegarding originality, the authors comment that there are various studies that conclude that in a warmer climate, a significant\ndelay in the start of the rainy season is expected in tropical monsoon regions. Because of the higher chance for spring to\nexperience the high percentile temperature in the tropical land, the authors propose to examine whether the amplified\nwarming of the high percentile temperature is tied to the seasonal changes in the temperature and precipitation.\nVarious databases are used, which is appropriate considering the large area covered by the study.\nThe figures chosen for each analysis contribute greatly to explaining the results obtained; they satisfactorily combine\ndifferent variables without losing the clarity of what is to be explained.\nIn the Methodology section I have some suggestions that should be included to strengthen the work, as detailed below:\n• In the “model simulation” section (line 326) it is mentioned that 30 CMIP5 models and 27 CMIP6 models were chosen.\nWhat is the criteria for selecting all these models?\n• On line 328 it says: “We use one realization from each model to compose multimodel ensembles which contains both\nCMIP5 models and CMIP6 models”. Why is only a single initialization of each model used? The use of only one initial\ncondition limits the understanding of the climate system variability, which is better represented by a set of initial conditions.\n• In the paragraph on line 331, it says that the high radiative forcing scenario “RCP8.5 for CMIP5 and SSP585 for CMIP6” is\nused, but nowhere in the text is it clarified what the difference is between them. It should be justified the use of different\ngenerations of models (CMIP5 and CMIP6) and what the differences are between these scenarios.\n• The study only uses a high emissions scenario, RCP8.5 and SSP585. Although all results are supported by rigorous\nstatistical significance tests, it would be appropriate to include other emissions scenarios, as using only one narrows the\nstudy's conclusions. Another point related to the previous one, why is the scenario only used in the distant future? (end of the\ncentury), so that it is suggested the inclusion of a mid-term scenario.\nConclusion:\nThe study is rigorous in almost all its sections (except for the points mentioned above), and the conclusions are expressed\nclearly. It is recommended to include the suggestions made above to strengthen the results, covering not only various\nemissions scenarios but also various temporal scenarios."}, "author_response": "1 Response to Reviewer #1\n3 manuscript. The comments are all valuable and helpful for revising our paper. Based on these\n4 comments, we provide a point-by-point response. The text in black is the original review\n5 comments, and the text in blue is the authors’ response.\n6 \"Hot gets hotter due to rainfall delay over tropical land in a warming climate\" by Song et al\n7 examines climatic changes in spring temperature – and high percentiles of temperature – over\n8 tropical land in CMIP5/6 models. Amplified warming of these temperatures is found, consistent\n9 with earlier work. The authors argue that the amplified warming can be related to a delay in\n10 seasonal rainfall in a warmer climate.\n12 is broadly sound, but I am not convinced by the arguments explaining the hot-get-hotter\n13 mechanism and the physical interpretations made. I would like to see this study published, but\n14 in my opinion the scientific argument first needs to be strengthened significantly and better\n15 placed in the context of previous work.\n17 arguments by incorporating more model simulations. We have also better placed our study in\n18 the context of previous studies by conducting more comparison with previous studies and\n19 including more references.\n21 1. Line 25: \"but its origin is on debate\" -> \"but its origin is debated\"\n23 2. Line 26: \"both the hot season and its extreme hot events get hotter in a warming climate\" ->\n24 this is not surprising in a warming climate! Suggest tweaking to highlight that the warming in\n25 those cases is amplified.\n27 warming climate, which is referred to as “hot-season-gets-hotter” phenomenon. The amplified\n28 hot season warming is also consistent with the amplified warming of hot temperature\n1\n29 percentiles recently revealed.”\n30 3. Line 31: \"proved\" -> this word is conventionally used when something is proven\n31 mathematically (not the case here). I suggest rephrasing.\n33 4. Line 45: From my understanding, the earlier emergence of forced trends in the tropics is due\n34 to smaller inter-annual variability, rather than weaker synoptic activity.\n36 variability”.\n37 5. Lines 60,61: Held & Soden (2006) is not an appropriate reference here; they do not discuss\n38 seasonal aspects of the water cycle response to warming.\n41 6. Lines 72-75: The Byrne (2021) study developed a quantitative theory based on convective\n42 coupling to explain the amplified warming over tropical land. This theory showed that the\n43 amplified warming is largely explained by climatological humidity over land, but humidity\n44 changes are also important. This theory was verified using CMIP6 simulations, where it can\n45 explain both the multi-model mean response and the spread in temperature changes across\n46 models. With this success of the Byrne (2021) theory, it is not accurate to state that \"the detailed\n47 physical mechanisms remain elusive\". Given that Byrne (2021) both demonstrated the\n48 amplified tropical land warming that is the focus of this study, and derived a quantitative\n49 physical to explain the model behaviour, more discussion of that paper is needed to more\n50 clearly place this manuscript in the context of recent work.\n52 by Byrne (2021), which explains the amplified warming over tropical land very clearly based\n53 on the quantitative theory. They concluded the amplified warming in the hot days over land\n54 under global warming is mainly due to two factors, the lower specific humidity in the current\n55 climate and the decrease in the relative humidity under global warming based on the weak\n2\n56 horizontal temperature gradient and active convection in the tropics. Following this great work,\n57 it is important to illustrate whether this amplified warming in the hot days is related to the\n58 seasonal delay of precipitation we previously found, which is the focus of our work. In addition,\n59 we totally agree with Byrne (2021) that humidity changes are very important, but the reasons\n60 for seasonal humidity changes are not clearly discussed yet. In our study, we highlight the\n61 seasonal delay of tropical rainfall reduces local spring relative humidity, which favors the\n62 amplified warming of hot season and extreme hot events over tropical land. We further examine\n63 the relative contributions of the two main mechanisms on the cause of rainfall delay, namely\n64 the enhanced moisture demand by the atmosphere (“enhanced effective heat capacity”) and\n65 decreased moisture supply from the surface (“convective barrier mechanism”). In the revision,\n66 we have added more descriptions on Byrne (2021) in Lines 81-85 and highlight our innovation\n67 points at Lines 61-63, Lines 78-80 and Lines 85-87.\n68 7. Line 83: \"caused by\" -> in my opinion, this causality has not been shown convincingly. What\n69 has been shown is a correlation between springtime precip changes and Tx changes, but this\n70 does not automatically imply causality.\n72 8. Lines 118-120: The surface energy budget is approximately balanced over land on monthly+\n73 timescales, and therefore boils down to a balance of fluxes. Using this framework to quantify\n74 \"contributions to the enhanced spring warming\" is not straightforward, as temperature is a state\n75 variable and not a flux. The authors should revise this section of the manuscript to better\n76 communicate that a change in a given surface flux cannot be directly interpreted as a\n77 contribution to a temperature change signal.\n79 correspond to spring temperature warming. In the revision, the section about the surface energy\n80 budget analysis has been deleted.\n81 9. Lines 124-126: Same point as directly above – surface energy balance alone cannot\n82 explain the land temperature response.\n3\n84 revision.\n85 10. Lines 178-181: Do these experiments isolate these two mechanisms cleanly? Rainfall\n86 seasonality depends on a lot of factors in addition to effective heat capacity, even for fixed SM\n87 – more explanation needed. Also fixed SM runs do not conserve water, which is an issue\n88 given the hot-get-hotter argument is based on changes in rainfall.\n90 wet season decreases the moisture supply from the surface in a warming climate, which allows\n91 the low-level moist static energy to take more time to reach the convection threshold, thus\n92 delaying the rainfall3,4. LFMIP-pdLC experiment (fixed soil moisture experiment) used in our\n93 study is performed by fixed surface water reservoirs (soil moisture, snow mass) based on the\n94 mean annual cycle in the period 1980-2014 from historical GCM simulations5. In this\n95 experiment, soil moisture would not decrease with global warming, which means sufficient\n96 spring evaporation can still supply enough moisture to the atmosphere. As shown in Figure R2,\n97 spring evaporation significantly decreases in fully coupled experiments (Fig. R2a, d), while\n98 increases in fixed soil moisture experiments (Fig. R2b, e) and the reduction in soil moisture\n99 plays a substantial role in the decrease in spring evaporation (Fig. R2c, f). Consequently, the\n100 enhanced convective barrier mechanism cannot work in fixed soil moisture experiment due to\n101 the sufficient moisture supply from evaporation. Furthermore, we found the rainfall delay is\n102 still evident in fixed soil moisture experiment (Fig. 3b, e of our manuscript). We then consider\n103 the other main view on tropical rainfall delay: “enhanced effective atmospheric heat capacity”,\n104 and found this mechanism works efficiently in both fully coupled and fixed soil moisture\n105 experiments (Extended Data Fig.7 in our manuscript). As you pointed out, in addition to these\n106 two predominant physical mechanisms, other factors such as non-local moisture transport may\n107 also contribute to rainfall delay in a warming climate. In the revision, we have added a\n108 discussion about non-local moisture sources in Lines 225-227 of our manuscript.\n110 understood as one kind of forcing experiments, similar to the setup of AMIP experiments. This\n111 experiment has been widely used in recent studies to diagnose the role of land-atmosphere\n112 feedback on air temperature response in climate change6–8. We only use this experiment to\n4\n113 verify the cause of rainfall delay and the contribution of soil moisture changes to the warming,\n114 which would not be largely affected by the conservation of water. In the revisions, these\n115 references have been added in Lines 371-373.\n116\n118 evaporation annual cycle. a, b, Changes (bars) and current climatology (solid line) of\n119 evaporation in fully coupled experiment (a) and the fixed soil moisture (SM) experiment (b)\n120 over NTL. c, SA influence on seasonal cycle of evaporation. d-f, As in a-c, but over STL. The\n121 hatched bars denote significance at the 95% confidence level based on Student’s t test.\n122 11. Lines 192,193: I agree that the effective heat capacity increases with warming, but more\n123 evidence/explanation needed for why this drives the seasonal delay in rainfall. How about a\n124 scatterplot of changes in effective heat capacity vs changes in rainfall phase across models?\n126 effective heat capacity increases with warming but tells us nothing directly about the change\n127 in rainfall.\n129 drive the seasonal delay of tropical rainfall in our previous studies9,10. Song et al. (2018) found\n130 the cross-equatorial energy transport corresponds well with tropical precipitation delay based\n131 on atmospheric energetic framework. In this framework, a northward cross-equatorial energy\n132 transport corresponds to a southward tropical precipitation and vice versa. This can be dictated\n133 by the atmospheric structure in the tropics: the upper branch of Hadley cell dominates the\n134 direction of energy transport as the moist static energy (MSE) is higher in the upper atmosphere,\n5\n135 while the lower branch of Hadley cell, with an opposite direction to the upper branch, transports\n136 moisture and results in precipitation. According to atmospheric energy equation, the divergence\n137 of atmospheric energy transport (∇𝐴𝐻𝑇 ) can be caused by the net energy input into the\n𝜕<ℎ>\n138 atmosphere (𝐹 ) and the column MSE tendency ( ):\n𝑛𝑒𝑡\n𝜕𝑡\n𝜕 < ℎ >\n139 ∇𝐴𝐻𝑇 = 𝐹 − , (1)\n𝑛𝑒𝑡 𝜕𝑡\n140 where h is MSE, < > represents the vertical integration between surface and top of the model\n141 and t is time. Song et al. (2018) found the changes in ∇𝐴𝐻𝑇 can well explain the seasonal\n𝜕<ℎ> 𝜕<ℎ>\n142 delay of tropical rainfall. For ∇𝐴𝐻𝑇, the changes of − is dominant. Among − , the\n𝜕𝑡 𝜕𝑡\n143 most important one is the latent energy tendency (−\n𝜕<𝐿𝑣𝑞>\n, where 𝐿 is latent heat of\n𝑣\n𝜕𝑡\n144 vaporization and q is specific humidity). Song et al. (2020) established the close relationship\n145 between the effective atmospheric heat capacity and the changes of inter-seasonal differences\n146 of\n𝜕<𝐿𝑣𝑞>\n. Physically, the enhanced effective atmospheric heat capacity makes the seasonally-\n𝜕𝑡\n147 warmed hemisphere need more time to accumulate the latent energy, which is corresponding\n148 to the rainfall delay. Indeed, there is a good relationship between inter-season difference of\n149 −\n𝜕<𝐿𝑣𝑞>\nand precipitation over tropical land (Fig. R3). In the revision, Fig. R3 has been\n𝜕𝑡\n150 included as Extended Data Fig. 8. Meanwhile, we have added some descriptions about how the\n151 enhanced atmospheric heat capacity drives the seasonal delay of tropical rainfall in Lines 210-\n152 216.\n6\n153\n155 model relationship between inter-season difference (SON – AMJ over NTL, MAM – SON over\n157 black line) is shown together with the correlation coefficient R and the corresponding P value.\n158 12. Line 263: \"implies a compelling causal link\" -> correlation does not imply causation; this\n159 sentence should be revised.\n161 link” to “implies a close link”.\n162 13. Line 265: \"reducing evapotranspiration due to drier soil\" -> does the rainfall delay lead to\n163 an absolute reduction in spring rainfall and drier soils? Please include plots of the absolute\n164 changes in precip and SM to better support this conclusion.\n166 to the annual mean changes, as the annual mean changes have relatively been well documented\n167 in many previous studies. To address your concerns, we have plotted the absolute changes in\n168 precipitation and soil moisture in Fig. R4. It can be seen that the absolute spring precipitation\n169 and soil moisture decrease over most tropical land, especially in the southern hemisphere where\n170 the “hot-season-gets-hotter” phenomenon is most pronounced. Hence, our conclusion works\n7\n171 over most tropical land region. In the revision, we have clearly mentioned that this conclusion\n172 also holds when the absolute changes are considered in Lines 136-137.\n173\n175 spatial patterns of absolute changes in precipitation (a) and soil moisture (b) during local spring.\n178 1. Li, W., Fu, R. & Dickinson, R. E. Rainfall and its seasonality over the Amazon in the 21st\n179 century as assessed by the coupled models for the IPCC AR4. J. Geophys. Res. Atmospheres\n180 111, 2005JD006355 (2006).\n181 2. Biasutti, M. & Sobel, A. H. Delayed Sahel rainfall and global seasonal cycle in a warmer\n182 climate. Geophys. Res. Lett. 36, 2009GL041303 (2009).\n183 3. Seth, A., Rauscher, S. A., Rojas, M., Giannini, A. & Camargo, S. J. Enhanced spring\n184 convective barrier for monsoons in a warmer world?: A letter. Clim. Change 104, 403–414\n185 (2011).\n186 4. Seth, A. et al. CMIP5 Projected Changes in the Annual Cycle of Precipitation in Monsoon\n188 5. van den Hurk, B. et al. LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and\n8\n191 6. Qiao, L., Zuo, Z. & Xiao, D. Evaluation of Soil Moisture in CMIP6 Simulations. J. Clim.\n192 35, 779–800 (2022).\n193 7. Qiao, L. et al. Soil moisture–atmosphere coupling accelerates global warming. Nat.\n195 8. Zuo, Z. et al. Importance of soil moisture conservation in mitigating climate change. Sci.\n197 9. Song, F., Leung, L. R., Lu, J. & Dong, L. Seasonally dependent responses of subtropical\n198 highs and tropical rainfall to anthropogenic warming. Nat. Clim. Change 8, 787–792 (2018).\n199 10. Song, F., Lu, J., Leung, L. R. & Liu, F. Contrasting Phase Changes of Precipitation Annual\n201 e2020GL090327 (2020).\n202\n9\n3 manuscript. The comments are all valuable and helpful for revising our paper. Based on these\n4 comments, we provide a point-by-point response. The text in black is the original review\n5 comments, and the text in blue is the authors’ response.\n7 maximum daily temperatures towards the end of the dry season (local spring) over tropical land\n8 regions. The authors use high-emissions scenarios RCP8.5 and SSP5-8.5 from CMIP5 and\n10 1. Increases in maximum daily temperatures during the climatologically warmest season (local\n11 spring)\n12 2. Stronger warming of the hottest days than for the coldest days during local spring\n14 by the authors. Furthermore, the authors compare fully-coupled to fixed soil-moisture\n15 experiments to disentangle the impacts of enhanced atmospheric moisture demand versus\n16 reduced moisture supply from the land-surface on this “hot-get-hotter” phenomenon. Finally,\n17 observations and historical CMIP simulations are used to show that this hot-get-hotter\n18 phenomenon has already started to occur, particularly in the Amazon region.\n20 the text is clear (albeit some corrections to the language and wording are recommended) and\n21 the figures are of high quality. However, a few major comments should be addressed before\n22 the paper can be published, and several minor changes are suggested.\n24 1. L54 – 67: This paragraph introduces two views to explain the delay in wet-season onset\n25 under global warming.\n26 1.1. I would argue that both of these views take a very localised approach and there is no\n27 mention of the importance of the large-scale circulation (movement of the ITCZ) in the wet-\n1\n28 season onset as discussed e.g. by Geen et al. (2020), Biasutti & Sobel (2009), Li, Fu (2004).\n31 mechanism is a localized approach, but we would like to emphasize that the “enhanced\n32 atmospheric heat capacity” mechanism is based on atmospheric energetic framework, which\n33 emphasizes the role of large-scale circulation in transporting energy and locating the tropical\n34 rainfall. The atmospheric energetic framework is initially used to explain the annual-mean\n36 transport corresponds to southward tropical rain band, and vice versa. By extending this\n37 framework to the seasonal cycle, we have found the cross-equatorial energy transport can well\n38 explain the tropical precipitation seasonal delay2, and the key driver is the enhanced\n39 atmospheric effective heat capacity3. We are very sorry for not clearly illustrating this point in\n40 our original manuscript. In the revision, we have added some relevant descriptions and cited\n41 these important three references in Lines 69-71.\n42 1.2. Regardless of which of the two outlined views is the dominant one, moisture will be\n43 required for the wet season onset. This can either be provided locally through\n44 evapotranspiration or from remote regions (i.e. the ocean or other land regions). Again, this is\n45 worth mentioning for the reader (see also comments below regarding L170-202).\n48 season onset in both views, which can either be provided locally through evapotranspiration or\n49 from remote regions.”\n50 1.3. All of the references provided for the first view involve the lead author of this manuscript,\n51 and the references for the (opposing) second view are both from a different lead author. Are\n52 there more references that could be provided here to make this a bit more of a balanced\n53 representation?\n55 respectively. Hui (2022) found seasonal delay of rainfall is driven by enhanced atmospheric\n56 effective heat capacity under global warming based on an aquaplanet model4. Bombardi &\n2\n58 relative moist static energy supporting the convective barrier mechanism5. In the revision, we\n59 have cited these two references.\n60 2. L118 – 126: This paragraph describes how the delay of the wet-season onset leads to higher\n61 temperatures by analysing surface energy fluxes and cloud cover changes (Extended Data\n63 2.1. The sign of change of latent and sensible heat fluxes are opposite to what is described in\n64 the text/what one would expect. The sensible heat flux should be increasing and the latent heat\n65 flux should be decreasing if there is less moisture available from the soil to evaporate.\n67 spring temperature warming. Hence, this section was deleted in the revision.\n68 2.2. The mechanism that the authors describe here has been described in other studies (e.g. Li,\n72 1. L42: “… most tropical countries are underdeveloped”. I would not use the word\n73 “underdeveloped”, I am not sure this is politically correct. Instead, “least developed\n74 countries” (UN) or “low-income/lower-middle income countries” (e.g. World Bank,\n76 countries in the tropics do not fall in either of those categories. However, it does appear that\n77 the majority of LDCs or low-income/lower-middle income countries are located in the tropics.\n79 2. L60 – 61: The cited Held and Soden (2006) paper takes a zonal-mean, annual mean\n80 approach but does not really discuss a seasonal drying. Other references should be included\n81 here to support this point (e.g. Li et al 2006, Biasutti & Sobel 2009, …)\n83 3. Figure 1: It would be helpful for the reader to show the future seasonal cycle as well (e.g. as\n84 a dashed line). Same for Figure 3, and Extended Data Fig 1.\n3\n86 4. L152-154: I am not sure it is helpful to group these two phenomena together as it makes it\n87 confusing in the rest of the paper which of the two is being referred to. For example, in the\n88 section “The observed emergence of hot-get-hotter along with rainfall delay” only the local-\n89 spring TX but not the hot-percentile changes are examined in the observational data, but this is\n90 still being referred to as “hot-get-hotter” which should cover both of those effects. I thus\n91 suggest referring to the phenomenon as “hot-season-gets-hotter” throughout the paper and\n92 presenting the finding that the hot percentile also warms more as a linked finding.\n94 hotter” throughout the paper and presented the finding that hot percentile gets hot as a linked\n95 finding in the revision.\n96 5. L170 – 202: In this section, the fully-coupled versus fixed-soil moisture simulations are\n97 examined in order to determine what drives the wet-season onset delay in a warmer climate:\n98 enhanced moisture demand by the atmosphere “( enhanced effective heat capacity”) or decrease\n99 moisture supply from the surface (“convective barrier mechanism”).\n100 5.1. Are there other mechanisms in the fixed soil moisture experiment which might affect\n101 evapotranspiration, e.g. vegetation? If so, would this affect the conclusion that the enhanced\n102 moisture demand of the atmosphere is the dominant driver of rainfall delay?\n104 and “convective barrier mechanism” are the two main mechanisms previously proposed for the\n105 rainfall seasonal delay. The enhanced effective atmospheric heat capacity increases the\n106 moisture demand, which can be met via either the local evaporation or remote transport. The\n107 convective barrier mechanism emphasizes the role of decreased local evaporation. In the fixed\n108 soil moisture experiments, the local evaporation is even enhanced in the local spring under\n109 global warming due to the enhanced humidity difference between air and land (Fig. R2), but\n110 precipitation is still decreased (Fig. 3). Hence, the convective barrier mechanism doesn’t work\n111 here. Instead, in the fixed soil moisture experiment, the effective atmospheric heat capacity is\n112 still significantly enhanced (Extended Data Fig. 7), well explaining why there is rainfall\n4\n113 decrease when there is more moisture supply from the surface. In the revision, Fig. R2 has been\n114 included as Extended Data Fig. 6 and related descriptions have been added in Lines 201-203.\n115\n117 evaporation annual cycle. a, b, Changes (bars) and current climatology (solid line) of\n118 evaporation in fully coupled experiment (a) and the fixed soil moisture (SM) experiment (b)\n119 over NTL. c, SA influence on seasonal cycle of evaporation. d-f, As in a-c, but over STL. The\n120 hatched bars denote significance at the 95% confidence level based on Student’s t test.\n121 5.2. Due to the different monsoon dynamics over different tropical land regions (see e.g. Geen\n122 et al 2020), taking the average over all northern hemisphere/southern hemisphere tropical land\n123 regions might simplify things too much. Does the same picture emerge when averaging over\n124 the tropical land regions separately?\n126 temperature changes during local spring in the Extended Data Fig. 9 (original Extended Data\n128 the average over all northern/southern tropical land regions. Hence, it is a quite common feature\n129 across different monsoon regions. This is also consistent with Lv et al. (2024)6, which found\n130 that the seasonal delay of rainfall occurs in most tropical land monsoon regions under global\n131 warming. Here, we also take Amazon as an example to show the rainfall delay and hot-season-\n132 gets-hotter under global warming (Fig. R3), which shows a consistent picture as the southern\n133 tropical land average. In the revision, we have clearly stated that this rainfall delay and hot-\n134 season-gets-hotter is quite common across different monsoon regions in Lines 122-124.\n135\n137 seasonal cycle of precipitation and TX over the Amazon. a, b, Multimodel mean changes\n138 (bars), current (solid line) and future climatology (dashed line) of precipitation in the fully\n139 coupled experiment (a) and the fixed soil moisture (SM) experiment (b) over the Amazon. c,\n141 fixed soil moisture experiment from those of the fully coupled experiment. d-f, As in a-b, but\n142 for TX. Error bars represent 25th and 75th percentile of multimodel ensembles. The hatched\n143 bars denote significance at the 95% confidence level based on Student’s t test.\n144 5.3. Extended Data Figure 7 shows that in the fixed SM experiments, some of the land regions\n145 actually receive more rainfall in a warmer world (e.g. Indonesia, northern hemisphere South\n147 role at least in the annual mean (see e.g. Kooperman et al. 2018, Saint Lu et al 2019, Pietschnig\n148 et al. 2021). The importance of non-local moisture sources is not addressed in the present study\n149 but would be expected to play a role in wet-season onset at least over some locations.\n151 significance of moisture transport due to local circulation response which may also play an\n152 important role in precipitation over some regions, particularly for islands. The relative roles of\n153 non-local moisture sources on wet-season onset should be emphasized and discussed in our\n154 study. In the revision, we have cited the three references you mentioned and added a discussion\n6\n155 about the importance of moisture transport in Lines 225-227 of our manuscript.\n156 6. L 179 – 181: “The second experiment can isolate the role of enhanced effective\n157 atmospheric heat capacity in the seasonal delay of rainfall.” I would suggest changing L178-\n158 181 to: \"By comparing the two experiments, we can examine the relative importance of the\n159 enhanced convective barrier mechanism versus the enhanced effective atmospheric heat\n160 capacity in causing the rainfall delay. The former would be present in the fully coupled\n161 experiments, whereas the latter would be expected in both experiments.” since the second\n162 experiment alone cannot isolate this effect, right?\n164 7. L227 – 228: It is not clear where these numbers come from and what is meant by\n165 “external forcings”\n167 in Fig. 4a. Here, “external forcings” represent historical all forcings, which include both\n168 anthropogenic (such as GHGs and aerosols) and natural forcings (solar radiation and volcanic\n169 eruptions). In the revision, we have clearly stated the source of these numbers and the meaning\n170 of external forcings in Lines 252-254.\n171 8. Figure 4: The axis tick spacing is a bit difficult to interpret, it would be easier for the reader\n172 to have ticks at 0.1, 0.2, 0.3, … (as is the case for the y-axis in panel b)\n174 9. Figure 4: The region referred to in this paper as “Southern Amazon” actually spans almost\n175 all of the Amazon basin and more. I would perhaps refer to this region as northern South\n178 10. Conclusions: I would recommend starting the conclusions with a 1 – 2 sentence summary\n179 of what was examined in this paper and why, and then move to the findings.\n7\n181 and amplified warming of extreme temperatures are reported over tropical land, which urges\n182 us to investigate the possible link between the two. Here, it is found that the warming in the\n183 hot season (local spring) would get amplified over the tropical land, referred to as the “hot-\n184 season-gets-hotter” phenomenon under global warming.”\n185 11. L 274: The impact on heatwaves has not really been examined in this study, the variables\n186 that were examined were maximum daily temperatures and 99th percentile temperatures, but\n187 not the duration of these temperature extremes (which is part of the definition of a heatwave).\n189 temperature” in the Line 304 of our manuscript.\n190 12. References: It would strengthen the manuscript to include more citations from a diverse set\n191 of papers to include different viewpoints. Currently, only about 35 sources are cited, five of\n192 which the lead author of this manuscript is also an author on. Some suggestions have been\n193 made in the comments above (but this is not an exhaustive list).\n196 1. L29: “and the 99th percentile temperature is ~30% warming more than” should read as “and\n197 the 99th percentile temperatures are warming ~30% more than….”\n199 2. L39: “The tropics are home to … “ instead of “Tropics is …” - I would always refer to the\n200 tropics as plural (also L41)\n202 3. L49: I would say “As the Sun crosses the Equator” instead of equinox.\n204 4. L52: “how hot the land can get” instead of “reach”\n8\n206 5. Generally, there are some “the” too many in some places, and some “the” missing in other\n207 places, e.g. L52, L80, … : “over the tropical land” should be “over tropical land” or L56-58:\n208 “. …. nonlinear dependence of moisture on the temperature under Clausius–Clapeyron relation,\n209 which delays the response of tropical rainfall to the seasonal solar forcing as atmosphere ….”\n210 should read as “…. nonlinear dependence of moisture on temperature under the Clausius–\n212 as the atmosphere ….”\n214 6. L65: “The relative importance….” Instead of “Hence, the relative importance” as this part\n215 does not really follow from what has been said above\n217 7. L72 : “in the tropical land” should be “over tropical land” (also L76, L82, …)\n219 8. L81: “We refer to the amplified spring warming” instead of “We refer the”\n221 9. L108: “referring to ‘hot-season-get-hotter’” should be “referred to here as ‘hot-season-gets-\n222 hotter’”\n224\n227 warmer climate. Geophysical Research Letters, 36(23).\n228 https://doi.org/10.1029/2009GL041303\n230 the Global Monsoon. In Reviews of Geophysics (Vol. 58, Issue 4). Blackwell Publishing Ltd.\n9\n231 https://doi.org/10.1029/2020RG000700\n234 asymmetric rainfall change over tropical land. Nature Climate Change, 8(5), 434–440.\n235 https://doi.org/10.1038/s41558-018-0144-7\n239 0442(2004)017>2637:TOTLAA<2.0.CO;2\n241 21st century as assessed by the coupled models for the IPCC AR4. Journal of Geophysical\n245 34, 9221–9234. https://doi.org/10.1175/JCLI-D-21\n246\n248 1. Kang, S. M., Held, I. M., Frierson, D. M. W. & Zhao, M. The Response of the ITCZ to\n250 3521–3532 (2008).\n251 2. Song, F., Leung, L. R., Lu, J. & Dong, L. Seasonally dependent responses of subtropical\n252 highs and tropical rainfall to anthropogenic warming. Nat. Clim. Change 8, 787–792 (2018).\n253 3. Song, F., Lu, J., Leung, L. R. & Liu, F. Contrasting Phase Changes of Precipitation Annual\n255 e2020GL090327 (2020).\n10\n256 4. Hui, K. L. Monsoonal Precipitation in a Model Hierarchy: Impact of Continental Geometry\n257 and Global Warming. Dissertation (Ph.D.). California Institute of Technology. (2022).\n259 5. Bombardi, R. J. & Boos, W. R. Explaining Globally Inhomogeneous Future Changes in\n261 6. Lv, S., Song, F., Dong, H. & Wu, L. Phase and Amplitude Changes in Rainfall Annual Cycle\n263 e2024GL108496 (2024).\n264\n11\n3 manuscript. The comments are all valuable and helpful for revising our paper. Based on these\n4 comments, we provide a point-by-point response. The text in black is the original review\n5 comments, and the text in blue is the authors’ response.\n6 1. The article is well presented, it adequately states the objectives of the study and the\n7 methodology used to quantify the changes in the variables is solid and duly supported by the\n8 literature. The introduction appropriately describes previous studies, but, a point to highlight\n9 in the introduction is the lack of references to studies for the Southern Hemisphere. There is\n10 abundant literature on extreme events that include changes in temperature and humidity. For\n11 example, among some recent studies is that of Olmo et al., 2022 (Compound Events in South\n14 regional models. More recently, Alvarez et al., 2024 (Projected changes in the frequency of\n15 compound hot and dry events over Tropical Brazil in CORDEX-CORE simulations), worked\n16 in the Amazon region. Also, Collazo et al., 2022 (Hot and dry compound events in South\n18 studied extreme events composed of temperature and humidity using a set of CMIP6 models\n19 in South America. The introduction is biased towards studies carried out in the Northern\n21 suggested.\n23 revision, we have cited these references and highlighted the increasing compound hot and dry\n24 events over South America in Lines 57-58 of our manuscript.\n26 a warmer climate, a significant delay in the start of the rainy season is expected in tropical\n27 monsoon regions. Because of the higher chance for spring to experience the high percentile\n28 temperature in the tropical land, the authors propose to examine whether the amplified warming\n1\n29 of the high percentile temperature is tied to the seasonal changes in the temperature and\n30 precipitation.\n33 satisfactorily combine different variables without losing the clarity of what is to be explained.\n35 work, as detailed below:\n36 2. In the “model simulation” section (line 326) it is mentioned that 30 CMIP5 models and 27\n39 most of the available model datasets to enlarge sample sizes. Given the various variables used\n40 in our study, some models are not selected due to the lack of necessary outputs. In the revision,\n41 we have clearly stated this in Lines 318-320 in the section of Model simulations in the Methods.\n42 3. On line 328 it says: “We use one realization from each model to compose multimodel\n43 ensembles which contains both CMIP5 models and CMIP6 models”. Why is only a single\n44 initialization of each model used? The use of only one initial condition limits the understanding\n45 of the climate system variability, which is better represented by a set of initial conditions.\n47 models, so there are 57 samples in total to better understand the climate system variability and\n48 also model difference. We only pick up one member from each model to keep the same weight\n49 from each model. To further verify whether our main conclusions are sensitive to the number\n50 of initializations, we utilize the ensemble mean of 50 initializations from MIROC6 to analyze\n51 the seasonal delay of tropical rainfall and hot season-get-hotter phenomenon. As shown in\n53 pronounced as the results in our manuscript. In the revision, we have highlighted our results\n54 are not sensitive to the number of realizations in Lines 321-322 of our manuscript.\n2\n55\n57 annual cycles based on 50 ensembles of MIROC6. a, b, Future changes (bars), current (solid\n58 line) and future climatology (dashed line) of the annual cycle of precipitation with annual-mean\n59 changes removed over the northern tropical land (NTL) (0°-25°N, a) and the southern tropical\n60 land (STL) (0°-25°S, b). c, Spatial distribution of the changes in precipitation during local\n61 spring (April-May-June (AMJ) in the northern hemisphere and September-October-November\n62 (SON) in the southern hemisphere) with annual-mean changes removed. d, e, f, As in a, b, c,\n63 but for TX. Error bars denote the 25th and 75th percentiles of changes among the MIROC6\n64 ensembles. Diagonal lines indicate significance at the 95% confidence level based on a two-\n65 sided Student’s t test. Stippling indicates at least 70% of the models agree on the sign of\n66 changes.\n67 4. In the paragraph on line 331, it says that the high radiative forcing scenario “RCP8.5 for\n69 difference is between them. It should be justified the use of different generations of models\n70 (CMIP5 and CMIP6) and what the differences are between these scenarios.\n72 but SSP585 simulations further encompass other factors like non-CO greenhouse gases,\n2\n73 aerosols and land use changes based on socio-economic development pathways1. To address\n74 your concerns, here we further show the results from CMIP6 and CMIP5 simulations separately.\n3\n76 means combining them together would not affect our conclusions. In the revision, we have\n77 added a description of the difference between these scenarios and emphasize their similar\n78 results in Lines 329-332 of our manuscript.\n79\n81 annual cycles from CMIP6 and CMIP5 models. As in Figure R1, but for multimodel\n82 ensembles of CMIP6 (a-f) and CMIP5 models (g-l).\n83 5. The study only uses a high emissions scenario, RCP8.5 and SSP585. Although all results are\n84 supported by rigorous statistical significance tests, it would be appropriate to include other\n4\n85 emissions scenarios, as using only one narrows the study's conclusions. Another point related\n86 to the previous one, why is the scenario only used in the distant future? (end of the century), so\n87 that it is suggested the inclusion of a mid-term scenario.\n89 term (2050-2069) and middle emission scenarios (RCP4.5 and SSP245). Hot-season-gets-\n90 hotter caused by rainfall delay is also remarkable in mid-term from high emission scenarios\n91 (Fig. R3) as well as long-term and mid-term from middle emission scenarios (Fig. R4). In\n92 addition, hot-percentile-get-hotter is also pronounced in mid- and long-term from middle and\n93 high emission scenarios over tropical land (Fig. R5). In the revision, we have added Fig. R5 as\n95\n97 annual cycles in mid-term from high emission scenarios. As in Figure R1, but for changes\n98 between the mid-term (2050-2069) and the current (1986-2005) from high emission scenarios\n99 of multimodel ensembles.\n5\n100\n102 annual cycles in long-term and mid-term from middle emission scenarios. As in Figure R3,\n103 but for long-term (a-f) and mid-term (g-l) from the middle emission scenario.\n6\n104\n106 emission scenarios. a, b, Mid-term (blue line) and long-term (red line) changes from middle\n107 emission scenario and mid-term changes from high emissions scenarios (black line) of the xth\n108 (1st to 99th) percentile of daily TX averaged over the NTL (a) and the STL (b). Shading\n109 indicates one standard deviation of inter-model spread.\n112 conclusions are expressed clearly. It is recommended to include the suggestions made above to\n113 strengthen the results, covering not only various emissions scenarios but also various temporal\n114 scenarios.\n116 temporal scenarios have been added in our analysis. We have also clearly stated the additional\n117 analysis in our conclusion based on your suggestion: “It should be noted that the seasonal delay\n118 of rainfall and hot-season-gets-hotter are evident across different warming scenarios and\n119 periods.”\n7\n121 1. IPCC. Climate Change 2021: The Physical Science Basis. Contribution of Working Group\n8\n3 manuscript. The comments are all valuable and helpful for revising our paper. Based on these\n4 comments, we provide a point-by-point response. The text in black is the original review\n5 comments, and the text in blue is the authors’ response.\n7 arise due to those reviews, which should be addressed before publication:\n8 1. Something is not quite right with Fig 1. The climatological seasonal cycles are not shifted\n9 relative to each other as you would expect from the changes shown by the bars. For example,\n11 decreases (in autumn – winter) and some increases (in spring). Why is the future climatology\n12 not shifted downwards during autumn-winter? Similarly for Fig 1e for the respective months.\n14 0.2 mm/d but this is not visible in a relative shift of the climatologies. In contrast, the 0.2 mm/d\n15 increase in October and November is visible as a shift between the two climatologies. Why is\n16 this?\n18 by subtracting the annual-mean changes from absolute monthly changes. The annual-mean\n19 changes are relatively well documented in many previous studies, so we pay more attention to\n20 the seasonal changes in this study. This has been clearly stated in the figure caption.\n21 2. Same as above for Figure 3 and Extended Data Figure 1.\n23 seasonal changes by removing the annual-mean changes, which are clearly stated in the figure\n24 caption.\n25 3. L134 – 136: I do not think it makes sense to explain the changes in the surface energy budget\n26 terms and then not show them in a figure. If the surface energy balance changes are the\n27 explanation, then these need to be shown. This finding is central to the paper so it’s important\n1\n28 to logically show to the reader why the changes in temperature occur, or if this is not possible,\n29 discuss why there is no clear mechanism to be found.\n31 upward as positive values) shows enhanced downward shortwave radiation, enhanced upward\n32 longwave radiation, decreased upward latent heat flux and enhanced upward sensible heat flux\n33 during spring. As you pointed out, these results are important for readers to understand detailed\n34 physical processes: the reduced rainfall is tied to reduced cloud cover, which allows more\n35 downward solar radiation; meanwhile, the reduced rainfall also decreases soil moisture, which\n36 reduces upward latent heat flux. Thus, the more incoming shortwave radiation can only be\n37 balanced by the more upward longwave radiation and sensible heat flux, both associated with\n38 more spring warming. In the revision, we have added Figure R1 as Extended Data Fig. 3 and\n39 revised relevant descriptions in Lines 133-139 of our manuscript.\n2\n40\n42 spring changes (annual-mean changes subtracted) of maximum temperature (TX), net surface\n43 shortwave radiation (SW ), net surface longwave radiation (LW ), latent heat flux (LH),\nsfc sfc\n44 sensible heat flux (SH) over the NTL (a) and STL (b). The upward (downward) energy fluxes\n45 are positive (negative). Error bars denote 25th and 75th of changes among multimodel\n46 ensembles. The diagonal lines indicate significance at the 95% confidence level based on a\n47 two-sided Student’s t test.\n48 4. L 155: I would suggest including a new section title “The hot percentile gets hotter due\n49 to ….. ” , to be consistent with L101\n3\n51 gets hotter tied to the amplified spring warming” in Line 158 of our manuscript.\n52 5. L250 – 262: The interpretation of the results here does not make sense to me. CMIP6 cannot\n53 simply be seen as representing the external forcing, and OBS to represent external forcing +\n54 internal variability. Both the CMIP models and OBS will represent both the external forcing\n55 and internal variability (at least to some extent; see e.g. Jain et al. 2023 and references cited\n56 there). A discrepancy between observations and models cannot simply be explained by lack of\n57 representation of internal variability in the models. This needs to be revised or justified in more\n58 detail.\n60 internal variability. Here, we utilize the multi-model ensemble mean of CMIP models,\n61 including 30 CMIP5 models and 27 CMIP6 models, to represent the external forcings in this\n62 study, as the internal variability is largely suppressed in this approach. What is shown in Figure\n63 4 is the multi-model ensemble mean trends in precipitation and TX (black star in Fig. 4). It is\n64 largely consistent with observations (black circle in Fig. 4) over the Amazon. Hence, the\n65 external forcings play a dominant role in observed changes over Amazon. In the revision, this\n66 has been clearly stated in the figure caption and main text.\n67 6. See language/wording suggestions in the annotated pdf\n4"}]

Decision letter