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Attribution of global lake systems change to anthropogenic forcing

An Author Correction to this article was published on 11 November 2021

This article has been updated


Lake ecosystems are jeopardized by the impacts of climate change on ice seasonality and water temperatures. Yet historical simulations have not been used to formally attribute changes in lake ice and temperature to anthropogenic drivers. In addition, future projections of these properties are limited to individual lakes or global simulations from single lake models. Here we uncover the human imprint on lakes worldwide using hindcasts and projections from five lake models. Reanalysed trends in lake temperature and ice cover in recent decades are extremely unlikely to be explained by pre-industrial climate variability alone. Ice-cover trends in reanalysis are consistent with lake model simulations under historical conditions, providing attribution of lake changes to anthropogenic climate change. Moreover, lake temperature, ice thickness and duration scale robustly with global mean air temperature across future climate scenarios (+0.9 °C °Cair–1, –0.033 m °Cair–1 and –9.7 d °Cair–1, respectively). These impacts would profoundly alter the functioning of lake ecosystems and the services they provide.

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Fig. 1: Reanalysed historical lake ice changes.
Fig. 2: Detection and attribution of the human imprint on lake variables.
Fig. 3: End-of-century change in lake temperature and ice onset, break-up and duration according to RCP 8.5.
Fig. 4: Anomalies for lake temperature, ice thickness and ice cover.

Data availability

The ISIMIP2b lake sector simulations presented in this study are available through the Earth System Grid Federation (ESGF, The ERA5-Land lake data used in this study are developed by the European Centre for Medium-Range Weather Forecasts (ECMWF) and are available through the Copernicus Climate Change Service’s Climate Data Store (CDS,!/search?type=dataset). The Global Lake Temperature Collaboration Dataset lake surface temperatures used for evaluating ERA5-Land can be found here: ESA CCI lake products can be found here: The Global Lake and River Ice Phenology Database is available at

Code availability

All code used to generate these analyses are available through the GitHub repository of the Department of Hydrology and Hydraulic Engineering at VUB (

Change history


  1. Mueller, H., Hamilton, D. P. & Doole, G. J. Evaluating services and damage costs of degradation of a major lake ecosystem. Ecosyst. Serv. 22, 370–380 (2016).

    Article  Google Scholar 

  2. Rinke, K., Keller, P. S., Kong, X., Borchardt, D. & Weitere, M. Ecosystem Services from Inland Waters and Their Aquatic Ecosystems (Springer, 2019).

  3. Bonan, G. B. Sensitivity of a GCM simulation to inclusion of inland water surfaces. J. Clim. 8, 2691–2704 (1995).

    Article  Google Scholar 

  4. Subin, Z. M., Murphy, L. N., Li, F., Bonfils, C. & Riley, W. J. Boreal lakes moderate seasonal and diurnal temperature variation and perturb atmospheric circulation: analyses in the Community Earth System Model 1 (CESM1). Tellus A 64, 15639 (2012).

  5. Thiery, W. et al. Understanding the performance of the FLake model over two African Great Lakes. Geosci. Model Dev. 7, 317–337 (2014).

    Article  Google Scholar 

  6. Thiery, W. et al. The impact of the African Great Lakes on the regional climate. J. Clim. 28, 4061–4085 (2015).

    Article  Google Scholar 

  7. Scott, R. W. & Huff, F. A. Impacts of the Great Lakes on regional climate conditions. J. Great Lakes Res. 22, 845–863 (1996).

    Article  Google Scholar 

  8. Griffiths, K., Michelutti, N., Sugar, M., Douglas, M. S. & Smol, J. P. Ice-cover is the principal driver of ecological change in High Arctic lakes and ponds. PLoS ONE 12, e0172989 (2017).

    Article  Google Scholar 

  9. Tan, Z., Yao, H. & Zhuang, Q. A small temperate lake in the 21st century: dynamics of water temperature, ice phenology, dissolved oxygen, and chlorophyll a. Water Resour. Res. 54, 4681–4699 (2018).

    Article  Google Scholar 

  10. Austin, J. A. & Colman, S. M. Lake Superior summer water temperatures are increasing more rapidly than regional temperatures: a positive ice-albedo feedback. Geophys. Res. Lett. 34, L06604 (2007).

    Article  Google Scholar 

  11. Ghanbari, R. N., Bravo, H. R., Magnuson, J. J., Hyzer, W. G. & Benson, B. J. Coherence between lake ice cover, local climate and teleconnections (Lake Mendota, Wisconsin). J. Hydrol. 374, 282–293 (2009).

    Article  Google Scholar 

  12. Duguay, C. R. et al. Recent trends in Canadian lake ice cover. Hydrol. Process. 20, 781–801 (2006).

    Article  Google Scholar 

  13. Sharma, S. et al. Widespread loss of lake ice around the Northern Hemisphere in a warming world. Nat. Clim. Change 9, 227–231 (2019).

    Article  Google Scholar 

  14. O’Reilly, C. M. et al. Rapid and highly variable warming of lake surface waters around the globe. Geophys. Res. Lett. 42, 10773–10781 (2015).

    Google Scholar 

  15. Woolway, R. I. & Merchant, C. J. Worldwide alteration of lake mixing regimes in response to climate change. Nat. Geosci. 12, 271–276 (2019).

    Article  Google Scholar 

  16. O’Reilly, C. M., Alin, S. R., Piisnier, P. D., Cohen, A. S. & McKee, B. A. Climate change decreases aquatic ecosystem productivity of Lake Tanganyika, Africa. Nature 424, 766–768 (2003).

    Article  Google Scholar 

  17. Hansen, G. J., Read, J. S., Hansen, J. F. & Winslow, L. A. Projected shifts in fish species dominance in Wisconsin lakes under climate change. Glob. Change Biol. 23, 1463–1476 (2017).

    Article  Google Scholar 

  18. Lyons, J. et al. Trends in the reproductive phenology of two Great Lakes fishes. Trans. Am. Fish. Soc. 144, 1263–1274 (2015).

    Article  Google Scholar 

  19. Muñoz-Sabater, J. ERA5-Land Hourly Data from 1981 to Present (Copernicus, 2019).

  20. Ribes, A., Azaís, J. M. & Planton, S. Adaptation of the optimal fingerprint method for climate change detection using a well-conditioned covariance matrix estimate. Clim. Dyn. 33, 707–722 (2009).

    Article  Google Scholar 

  21. Allen, M. R. & Stott, P. A. Estimating signal amplitudes in optimal fingerprinting, part I: theory. Clim. Dyn. 21, 477–491 (2003).

    Article  Google Scholar 

  22. Bindoff, N. L. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 867–952 (Cambridge Univ. Press, 2013).

  23. Gillett, N. P. et al. The Detection and Attribution Model Intercomparison Project (DAMIP v1.0) contribution to CMIP6. Geosci. Model Dev. 9, 3685–3697 (2016).

    Article  Google Scholar 

  24. Frieler, K. et al. Assessing the impacts of 1.5 °C global warming—simulation protocol of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b). Geosci. Model Dev. 10, 4321–4345 (2017).

    Article  Google Scholar 

  25. Wan, H., Zhang, X., Zwiers, F. & Min, S. K. Attributing northern high-latitude precipitation change over the period 1966–2005 to human influence. Clim. Dyn. 45, 1713–1726 (2015).

    Article  Google Scholar 

  26. Qian, C. & Zhang, X. Human influences on changes in the temperature seasonality in mid- to high-latitude land areas. J. Clim. 28, 5908–5921 (2015).

    Article  Google Scholar 

  27. Gudmundsson, L., Seneviratne, S. I. & Zhang, X. Anthropogenic climate change detected in European renewable freshwater resources. Nat. Clim. Change 7, 813–816 (2017).

    Article  Google Scholar 

  28. Padrón, R. S. et al. Observed changes in dry-season water availability attributed to human-induced climate change. Nat. Geosci. 13, 477–481 (2020).

    Article  Google Scholar 

  29. Ribes, A., Planton, S. & Terray, L. Application of regularised optimal fingerprinting to attribution. Part I: method, properties and idealised analysis. Clim. Dyn. 41, 2817–2836 (2013).

    Article  Google Scholar 

  30. Myhre, G. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 659–740 (Cambridge Univ. Press, 2013).

  31. Maberly, S. C. et al. Global lake thermal regions shift under climate change. Nat. Commun. 11, 1232 (2020).

    Article  Google Scholar 

  32. Ito, A. et al. Pronounced and unavoidable impacts of low-end global warming on northern high-latitude land ecosystems. Environ. Res. Lett. 15, 044006 (2020).

    Article  Google Scholar 

  33. Dibike, Y., Prowse, T., Saloranta, T. & Ahmed, R. Response of Northern Hemisphere lake-ice cover and lake-water thermal structure patterns to a changing climate. Hydrol. Process. 25, 2942–2953 (2011).

    Google Scholar 

  34. Bonsal, B. R., Prowse, T. D., Duguay, C. R. & Lacroix, M. P. Impacts of large-scale teleconnections on freshwater-ice break/freeze-up dates over Canada. J. Hydrol. 330, 340–353 (2006).

    Article  Google Scholar 

  35. Korhonen, J. Long-term changes in lake ice cover in Finland. Nord. Hydrol. 37, 347–363 (2006).

    Article  Google Scholar 

  36. Bonsal, B. R. & Prowse, T. D. Trends and variability in spring and autumn 0 °C-isotherm dates over Canada. Climatic Change 57, 341–358 (2003).

    Article  Google Scholar 

  37. Giardino, C., Merchant, C. & Simis, S. Preparing for the first Lakes ECV climate data record. Lakes Newsletter (October 2019).

  38. Mastrandrea, M. D. et al. Guidance Note for Lead Authors of the IPCC Fifth Assessment Report on Consistent Treatment of Uncertainties Technical Report (IPCC, 2010).

  39. Frieler, K. et al. Assessing the impacts of 1.5 °C global warming—simulation protocol of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b). Geosci. Model Dev. 10, 4321–4345 (2017).

    Article  Google Scholar 

  40. Lange, S. EartH2Observe, WFDEI and ERA-Interim Data Merged and Bias-corrected for ISIMIP (EWEMBI) (GFZ Data Services, 2016).

  41. Lawrence, D. M. et al. Parameterization improvements and functional and structural advances in Version 4 of the Community Land Model. J. Adv. Model. Earth Syst. 3, M03001 (2011).

    Google Scholar 

  42. Tan, Z. et al. Modeling methane emissions from arctic lakes: Model development and site‐level study. J. Adv. Model. Earth Syst. 6, 513–526 (2015).

    Google Scholar 

  43. Goudsmit, G. H., Burchard, H., Peeters, F. & Wüest, A. Application of k-ϵ turbulence models to enclosed basins: the role of internal seiches. J. Geophys. Res. Oceans 107, 23-1–23-13 (2002).

    Article  Google Scholar 

  44. Bowling, L. C. & Lettenmaier, D. P. Modeling the effects of lakes and wetlands on the water balance of Arctic environments. J. Hydrometeorol. 11, 276–295 (2010).

    Article  Google Scholar 

  45. Stepanenko, V. et al. LAKE 2.0: a model for temperature, methane, carbon dioxide and oxygen dynamics in lakes. Geosci. Model Dev. 9, 1977–2006 (2016).

    Article  Google Scholar 

  46. Kourzeneva, E., Asensio, H., Martin, E. & Faroux, S. Global gridded dataset of lake coverage and lake depth for use in numerical weather prediction and climate modelling. Tellus A 64, 15640 (2012).

    Article  Google Scholar 

  47. Subin, Z. M., Riley, W. J. & Mironov, D. An improved lake model for climate simulations: model structure, evaluation, and sensitivity analyses in CESM1. J. Adv. Model. Earth Syst. 4, M02001 (2012).

    Article  Google Scholar 

  48. Choulga, M., Kourzeneva, E., Zakharova, E. & Doganovsky, A. Estimation of the mean depth of boreal lakes for use in numerical weather prediction and climate modelling. Tellus A 66, 21295 (2014).

    Article  Google Scholar 

  49. Balsamo, G., Dutra, E., Beljaars, A. & Viterbo, P. Evolution of land surface processes in the Integrated Forecast System. ECMWF Newsl. 127, 17–22 (2011).

    Google Scholar 

  50. Ledoit, O. & Wolf, M. A well-conditioned estimator for large-dimensional covariance matrices. J. Multivar. Anal. 88, 365–411 (2004).

    Article  Google Scholar 

  51. Gudmundsson, L., Seneviratne, S. I. & Zhang, X. Anthropogenic climate change detected in European renewable freshwater resources. Nat. Clim. Change 7, 813–816 (2017).

    Article  Google Scholar 

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We are grateful to the Potsdam Institute for Climate Impact Research (PIK) for initiating and coordinating the ISIMIP initiative, with special thanks to M. Büchner for his oversight of ISIMIP data publishing, and to the modelling centres for making their impact simulations publicly available through ESGF. We acknowledge the European Centre for Medium-Range Weather Forecasts (ECMWF) and the Copernicus Climate Change Service for their provision of publicly available ERA5-Land lake data; this paper contains modified Copernicus Climate Change Information [2021]. Furthermore, L.Grant is funded by European Copernicus Climate Change Service (C3S) implemented by the European Centre for Medium-Range Weather Forecasts (ECMWF) under the service contract Independent Assessment on ECVs led by National Research council of Italy (CNR) with the funding number ECMWF/Copernicus/2017/C3S_511_CNR. We owe many thanks to F. Fröb and A. Winkler for sharing their regularized optimal fingerprinting python code and to M. Schmid for the helpful discussions. We also thank the National Center for Atmospheric Research (NCAR) for maintaining CLM and making the source code publicly available. I.V. is a research fellow at the Research Foundation Flanders (FWO) (FWOTM920). W.T. acknowledges the Uniscientia Foundation and the ETH Zurich Foundation for their support to this research. Z.T. is supported by the US DOE’s Earth System Modeling programme through the Energy Exascale Earth System Model (E3SM) project. The computational resources and services used in this work were provided by the VSC (Flemish Supercomputer Center), funded by the Research Foundation Flanders (FWO) and the Flemish Government, department EWI. R.M. participated through the project WATExR of the JPI Climate ERA4CS Program and acknowledges funding from the CERCA programme of the Generalitat de Catalunya. V.M.S. and A.V.D. used the HPC facilities of Lomonosov Moscow State University (‘Lomonosov-2’ supercomputer) and were supported by the Russian Ministry of Science and Higher Education, agreement no. 075-152019-1621. A.B.G.J acknowledges the Talent Programme Veni of the Netherlands Organisation for Scientific Research (NWO) (VI.Veni.194.002).

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Authors and Affiliations



L. Grant, I.V. and W.T. designed the study. L. Grant wrote the manuscript with support from all authors and performed all analyses under the supervision of I.V. and W.T. L. Gudmundsson provided guidance on the detection analysis. Z.T., M.P., V.M.S., A.V.D., B.D., A.B.G.J., S.I.S. and W.T. conducted the global lake model simulations. J.S., F.Z., M.G., D.P., R.M. and W.T. coordinated the ISIMIP lake sector activities. M.C. and G.B. helped validate ERA5-Land reanalysis data as reference products. I.V.d.V. provided oversight for data publishing. L. Grant and I.V. performed additional analyses in response to referee comments and together composed the referee response letter with the help of all authors.

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Correspondence to Luke Grant.

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Peer review information Nature Geoscience thanks Peter Stott, Matthew Hipsey and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Thomas Richardson.

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Supplementary Information

Supplementary Table 1, Figs. 1–39, Notes 1.1–1.5 and references.

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Grant, L., Vanderkelen, I., Gudmundsson, L. et al. Attribution of global lake systems change to anthropogenic forcing. Nat. Geosci. 14, 849–854 (2021).

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