ABSTRACT Hot temperature extremes (HTEs) in the atmosphere can also affect lake surface water temperature, but how this impact changes with global warming is not well understood. Here we use

numerical modelling and satellite observations to quantify the contribution of HTEs to variations in summer lake surface water temperature and lake heatwaves in 1,260 water bodies worldwide

between 1979 and 2022. Over this time period, HTE duration and cumulative intensity over the studied lakes increased significantly, at average rates of 1.4 days per decade and 0.92 °C days

per decade, respectively. Despite only accounting for 7% of the total summer days, HTEs are responsible for 24% of lake surface summer warming trends, with the most pronounced effect

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subscriptions * Read our FAQs * Contact customer support SIMILAR CONTENT BEING VIEWED BY OTHERS CLIMATE CHANGE-INDUCED AMPLIFICATION OF EXTREME TEMPERATURES IN LARGE LAKES Article Open

access 15 May 2025 THE IMPACT OF EXTREME HEAT ON LAKE WARMING IN CHINA Article Open access 02 January 2024 GLOBAL LAKES ARE WARMING SLOWER THAN SURFACE AIR TEMPERATURE DUE TO ACCELERATED

EVAPORATION Article 23 October 2023 DATA AVAILABILITY ERA5-Land reanalysis is available to download from https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-land?tab=overview.

Lakes_cci is available to download from https://data.ceda.ac.uk/neodc/esacci/lakes/data/lake_products/L3S/v2.0. GloboLakes is available to download from

https://catalogue.ceda.ac.uk/uuid/76a29c5b55204b66a40308fc2ba9cdb3. GLTC is available to download from https://doi.org/10.6073/pasta/89bacfc9dfcabce545ae11b353a8e5fd. Daily LSWT in the CTL

and CFT experiments and a table of lake characteristics are provided at https://doi.org/10.11888/Terre.tpdc.301309 (ref. 51). Data used to create figures are available via Zenodo at

https://doi.org/10.5281/zenodo.13189351 (ref. 52). Source data are provided with this paper. CODE AVAILABILITY The source code of the FLake model can be found at

http://www.flake.igb-berlin.de. Codes used to generate figures in the manuscript are available via Zenodo at https://doi.org/10.5281/zenodo.13189351 (ref. 52). CHANGE HISTORY * _ 25

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_Zenodo_ https://doi.org/10.5281/zenodo.13189351 (2024). Download references ACKNOWLEDGEMENTS This work was supported by the National Natural Science Foundation of China (U22A20561 and

42425102), the Tibetan Plateau Scientific Expedition and Research Program (2019QZKK0202), the NIGLAS foundation (E1SL002) and the Water Resource Science and Technology Project in Jiangsu

Province (2020057). R.I.W. was supported by a UKRI Natural Environment Research Council (NERC) Independent Research Fellowship (grant number NE/T011246/1) and NERC grant reference number

NE/X019071/1, ‘UK EO Climate Information Service’. AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of

Geography and Limnology, Chinese Academy of Sciences, Nanjing, China Xiwen Wang, Kun Shi, Boqiang Qin & Yunlin Zhang * School of Geography and Ocean Science, Nanjing University, Nanjing,

China Xiwen Wang & Boqiang Qin * University of Chinese Academy of Sciences, Beijing, China Kun Shi & Yunlin Zhang * College of Nanjing, University of Chinese Academy of Sciences,

Nanjing, China Yunlin Zhang * School of Ocean Sciences, Bangor University, Menai Bridge, UK R. Iestyn Woolway Authors * Xiwen Wang View author publications You can also search for this

author inPubMed Google Scholar * Kun Shi View author publications You can also search for this author inPubMed Google Scholar * Boqiang Qin View author publications You can also search for

this author inPubMed Google Scholar * Yunlin Zhang View author publications You can also search for this author inPubMed Google Scholar * R. Iestyn Woolway View author publications You can

also search for this author inPubMed Google Scholar CONTRIBUTIONS X.W. conceived the work, performed the numerical modelling, completed the data analysis and wrote the manuscript. K.S.

conceived the work and revised the manuscript. B.Q., Y.Z. and R.I.W. revised the manuscript. CORRESPONDING AUTHOR Correspondence to Kun Shi. ETHICS DECLARATIONS COMPETING INTERESTS The

authors declare no competing interests. PEER REVIEW PEER REVIEW INFORMATION _Nature Climate Change_ thanks the anonymous reviewers for their contribution to the peer review of this work.

ADDITIONAL INFORMATION PUBLISHER’S NOTE Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. EXTENDED DATA EXTENDED DATA

FIG. 1 CHARACTERISTICS AND DISTRIBUTION OF THE 1260 STUDIED LAKES. A-C Histogram of the average depth (log10[m], A), surface area (log10[km2], B), and elevation (m, C). D Spatial

distribution of studied lakes. Source data EXTENDED DATA FIG. 2 MODELLED VS. LAKES_CCI LSWT DURING 2000–2020. A-B Number of available Lakes_cci data from 2000 to 2020 across all seasons (A)

and in summer (B). Each range of the amount of validation data is presented on the x-axis, while the number of lakes falling into each category is depicted on the y-axis. C-F Correlation

coefficients between FLake, CSFLake, and Lakes_cci throughout the year (C, E) and summer (D, F). G-J RMSEs (°C) between FLake, CSFLake, and Lakes_cci throughout the year (G, I) and summer

(H, J). Note that there are four lakes not shown in FLake results (C, D) because they stayed frozen throughout the year. Source data EXTENDED DATA FIG. 3 MODELLED VS. OBSERVED LSWT. A

CSFLake vs. GloboLakes. B CSFLake vs. GLTC satellite data. C CSFLake vs. GLTC in situ data. D CSFLake vs. in situ data for seven Chinese lakes. The paired modelled and observed LSWT are

daily means in A and D, and summer means in B and C. Each point represents the values of a paired CSFLake-observation data. The density of data is the normalized kernel density and is

represented by the colour of points. Source data EXTENDED DATA FIG. 4 VALIDATION OF SIMULATED LHW METRICS FROM 2000 TO 2020. A-B The mean absolute errors (MAEs) between LHW cumulative

intensity calculated from Lakes_cci and modelled LSWT. C-D MAEs between LHW duration calculated from Lakes_cci and modelled LSWT. All the metrics were averaged over 2000–2020. In B and D,

each point represents a lake; the density of data is the normalized kernel density and is represented by the colour of points. Source data EXTENDED DATA FIG. 5 THE IMPACT OF HTES ON THE

INTRA-ANNUAL VARIABILITY OF LSWT. A Interannual variations of the intra-annual variability in CTL and CFT averaged over all studied lakes. The _p_ values of trends were calculated using a

two-tailed test. B-C Intra-annual variability trends (decade−1) for each lake in CTL (B) and CFT (C). Source data EXTENDED DATA FIG. 6 CHANGES OF LHW METRICS FROM 1979 TO 2022. A-B Annual

trends in LHW duration (A; days decade−1) and LHW cumulative intensity (B; °C days decade−1). C-D Summer trends in LHW duration (C; days decade−1) and LHW cumulative intensity (D; °C days

decade−1). Source data EXTENDED DATA FIG. 7 RELATIONSHIPS BETWEEN AIR TEMPERATURE, HTE METRICS, AND LHW METRICS IN SUMMER. LHW duration trend vs. air temperature trend (A). LHW duration

trend vs. HTE cumulative intensity trend (B). LHW duration trend vs. HTE duration trend (C). LHW cumulative intensity trend vs. air temperature trend (D). LHW cumulative intensity trend vs.

HTE cumulative intensity trend (E). LHW cumulative intensity trend vs. HTE duration trend (F). Only lakes with non-zero trends in LHW metrics are shown in A-F. Mean LHW duration vs. mean air

temperature (G). Mean LHW duration vs. mean HTE cumulative intensity (H). Mean LHW cumulative intensity vs. mean air temperature (I). Mean LHW cumulative intensity vs. mean HTE cumulative

intensity (J). Pearson correlation coefficients (_r_) are shown in the upper corner. Source data EXTENDED DATA FIG. 8 HTES CONTRIBUTIONS TO TRENDS IN SUMMER LHW METRICS FOR ALL STUDIED

LAKES. A Interannual variations of LHW duration (days) averaged across all studied lakes in CTL and CFT from 1979 to 2022. B Same as A but for LHW cumulative intensity (°C days). The _p_

values were calculated using a two-tailed test. Source data SUPPLEMENTARY INFORMATION SUPPLEMENTARY INFORMATION Supplementary Fig. 1 and Table 1. REPORTING SUMMARY SOURCE DATA SOURCE DATA

FIG. 1 Statistical source data. SOURCE DATA FIG. 2 Statistical source data. SOURCE DATA FIG. 3 Statistical source data. SOURCE DATA FIG. 4 Statistical source data. SOURCE DATA EXTENDED DATA

FIG. 1 Statistical source data. SOURCE DATA EXTENDED DATA FIG. 2 Statistical source data. SOURCE DATA EXTENDED DATA FIG. 3 Statistical source data. SOURCE DATA EXTENDED DATA FIG. 4

Statistical source data. SOURCE DATA EXTENDED DATA FIG. 5 Statistical source data. SOURCE DATA EXTENDED DATA FIG. 6 Statistical source data. SOURCE DATA EXTENDED DATA FIG. 7 Statistical

source data. SOURCE DATA EXTENDED DATA FIG. 8 Statistical source data. RIGHTS AND PERMISSIONS Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this

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such publishing agreement and applicable law. Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Wang, X., Shi, K., Qin, B. _et al._ Disproportionate impact of atmospheric heat

events on lake surface water temperature increases. _Nat. Clim. Chang._ 14, 1172–1177 (2024). https://doi.org/10.1038/s41558-024-02122-y Download citation * Received: 28 September 2023 *

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