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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

Abstract

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, https://esgf-data.dkrz.de/). 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, https://cds.climate.copernicus.eu/cdsapp#!/search?type=dataset). The Global Lake Temperature Collaboration Dataset lake surface temperatures used for evaluating ERA5-Land can be found here: https://portal.edirepository.org/nis/mapbrowse?packageid=knb-lter-ntl.10001.3. ESA CCI lake products can be found here: https://catalogue.ceda.ac.uk/uuid/3c324bb4ee394d0d876fe2e1db217378. The Global Lake and River Ice Phenology Database is available at https://nsidc.org/data/lake_river_ice/.

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 (https://github.com/VUB-HYDR/2021_Grant_etal).

Change history

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Acknowledgements

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

Authors

Contributions

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). https://doi.org/10.1038/s41561-021-00833-x

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