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Reply to: Detecting long-term Arctic surface water changes

Nature Climate Change volume 13, pages 1194–1196 (2023)Cite this article

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The Original Article was published on 05 October 2023

replying to I. Olthof et al. Nature Climate Change https://doi.org/10.1038/s41558-023-01836-9 (2023)

Our pan-Arctic analysis based on the Moderate Resolution Imaging Spectroradiometer (MODIS) superfine water index (SWI) suggested that permafrost thaw is driving widespread surface water declines1. Olthof et al.2 question the reliability of SWI-derived surface water trends because (1) there is a weak relationship between MODIS SWI (at 500 m resolution) and a Landsat-based surface water product3 (30 m resolution) over Canada; (2) the SWI is sensitive to land surface changes other than water area2; and (3) the negative surface water trends we reported contradict trends derived from two Landsat-based products3,4 over Canada2. Here we show that: (1) Landsat-based products have their own uncertainties and limitations that preclude their use as a true reference; (2) decreasing trends in surface water inferred from the SWI are unlikely to be caused by confounding variables (for example, vegetation change or turbidity); and (3) our conclusion of a net decrease in surface water across the Arctic is supported by independent evidence. We also offer a broader view of the uncertainties in analysing Arctic surface water change through remote-sensing techniques, and highlight that this is an unresolved, ongoing field of research.

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Data availability

The analysis in this study relied on datasets from the following sources, all of which are freely available to the public. Webb et al.1 SWI trends are available at: https://arcticdata.io/catalog/view/doi:10.18739/A2NK3665N. Olthof and Rainville3 surface water trends are available at: https://open.canada.ca/data/en/dataset/62de5952-a5eb-4859-b086-22a8ba8024b8. Pickens et al.4 surface water trends are available at: https://glad.umd.edu/dataset/global-surface-water-dynamics. Nitze et al.7 lake area trends are available at: https://doi.pangaea.de/10.1594/PANGAEA.894755. Yao et al.20 lake water storage trends are available at: https://zenodo.org/record/7946043.

Code availability

Google Earth Engine code used to calculate the net changes in surface water in eastern Canada from different data sources is available here: https://code.earthengine.google.com/0edfaa0327c018b68f1ab8aab2e32f98. Google Earth Engine code used to isolate lake water storage trends over Canada and pan-Arctic permafrost zones is available here: https://code.earthengine.google.com/75a7ea6f5b35252e4a55fb4972da1aec.

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Authors and Affiliations

  1. School of Natural Resources and Environment, University of Florida, Gainesville, FL, USA

    Elizabeth E. Webb

  2. Department of Biology, University of Florida, Gainesville, FL, USA

    Elizabeth E. Webb & Jeremy W. Lichstein

  3. Woodwell Climate Research Center, Falmouth, MA, USA

    Anna K. Liljedahl

  4. Department of Geography, Colgate University, Hamilton, NY, USA

    Michael M. Loranty

  5. Department of Natural Resources and the Environment, University of Connecticut, Storrs, CT, USA

    Chandi Witharana

Authors
  1. Elizabeth E. Webb
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  2. Anna K. Liljedahl
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  3. Michael M. Loranty
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  4. Chandi Witharana
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  5. Jeremy W. Lichstein
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Contributions

E.E.W. wrote the manuscript with assistance from J.W.L. and all authors provided feedback.

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Correspondence to Elizabeth E. Webb.

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Nature Climate Change thanks the anonymous reviewers for their contribution to the peer review of this work.

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Webb, E.E., Liljedahl, A.K., Loranty, M.M. et al. Reply to: Detecting long-term Arctic surface water changes. Nat. Clim. Chang. 13, 1194–1196 (2023). https://doi.org/10.1038/s41558-023-01837-8

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