More than one-third of Earth’s landmass is drained by rivers that seasonally freeze over. Ice transforms the hydrologic1,2, ecologic3,4, climatic5 and socio-economic6,7,8 functions of river corridors. Although river ice extent has been shown to be declining in many regions of the world1, the seasonality, historical change and predicted future changes in river ice extent and duration have not yet been quantified globally. Previous studies of river ice, which suggested that declines in extent and duration could be attributed to warming temperatures9,10, were based on data from sparse locations. Furthermore, existing projections of future ice extent are based solely on the location of the 0-°C isotherm11. Here, using satellite observations, we show that the global extent of river ice is declining, and we project a mean decrease in seasonal ice duration of 6.10 ± 0.08 days per 1-°C increase in global mean surface air temperature. We tracked the extent of river ice using over 400,000 clear-sky Landsat images spanning 1984–2018 and observed a mean decline of 2.5 percentage points globally in the past three decades. To project future changes in river ice extent, we developed an observationally calibrated and validated model, based on temperature and season, which reduced the mean bias by 87 per cent compared with the 0-degree-Celsius isotherm approach. We applied this model to future climate projections for 2080–2100: compared with 2009–2029, the average river ice duration declines by 16.7 days under Representative Concentration Pathway (RCP) 8.5, whereas under RCP 4.5 it declines on average by 7.3 days. Our results show that, globally, river ice is measurably declining and will continue to decline linearly with projected increases in surface air temperature towards the end of this century.
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The code used to acquire, analyse and visualize the dataset can be accessed online at the project’s GitHub page (https://github.com/seanyx/global-river-ice-dataset-from-Landsat). The river ice model and all figures in the paper (including the extended data figures) were made using R statistical software (http://www.R-project.org/).
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Funding was provided to T.M.P. by a subcontract from the SWOT Project Office at the NASA/Caltech Jet Propulsion Laboratory. We thank S. Lindsey at the Alaska-Pacific River Forecast Center for providing us with the NWS Alaska river break-up and freeze-up records, and W. Dolan for help with geolocating Alaskan river ice records.
The authors declare no competing interests.
Peer review information Nature thanks John Kimball, Gerhard Krinner and Homa Kheyrollah Pour for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data figures and tables
a, Data availability map for the decades 1984–1994 and 2008–2018 based on the river ice extent dataset. Black indicates no data or no studied river. b, Percentage of successful river ice observations for each month of each decade. The percentage was calculated by taking the ratio between the number of observations used in the historical analysis and the total number of Landsat river observations when no filters (cloud, topographic shadow and river length) were applied.
Extended Data Fig. 2 Monthly maps of the changes in river ice extent between 1984–1994 and 2008–2018.
Black indicates no data or no studied river.
Extended Data Fig. 3 Modelled average monthly river ice difference between 2009–2029 and 2080–2100 using CESM SAT output (RCP 4.5).
The percentage point change over the Northern Hemisphere is listed under the month, with the percentage change in parentheses.
Extended Data Fig. 4 Modelled average monthly river ice difference between 2009–2029 and 2080–2100 using CESM SAT.
a, Model output under RCP 8.5. b, Model output under RCP 4.5. Only the months that showed obvious changes in percentage points (June, July and and August) were mapped. The percentage point changes and percentage changes over the Southern Hemisphere are listed in the tables on the right.
Extended Data Fig. 5 Modelled ice duration zones between 2009–2029 and 2080–2100 using CESM modelled SAT.
a, The Northern Hemisphere under RCP 4.5. b, c, The Southern Hemisphere under RCP 8.5 (b) and RCP 4.5 (c). Areas showing obvious changes are marked by red rectangles.
Extended Data Fig. 6 Sensitivity of the changes in annual maximum river ice extent to the changes in global mean SAT.
The sensitivity was assessed for three models (CESM1-BGC, GFDL-ESM2M and MIROC-ESM).
Extended Data Fig. 7 Landsat sampling difference between the historical period 1984–1994 and 2008–2018.
a, Distribution of the temporal sampling difference within each month. b, Temporal sampling difference and its relationship with the difference in the ice extent. c, Distribution of the spatial sampling difference within the 5° × 5° tiles. d, Spatial sampling difference and its relationship with the difference in the ice extent.
Extended Data Fig. 8 Summary of river ice duration decline based on temperature outputs from three CMIP5 models.
a, Difference in the global mean SAT across 21 CMIP5 models between 2006–2036 and 2069–2099. The three models used to assess future river ice change are marked with red rectangles. b, Decline in global mean river ice duration between 2009–2029 and 2080–2100 for the three selected models.
Extended Data Fig. 9 Evaluating Landsat-derived river ice conditions against in situ river ice records.
a, The accuracy of Landsat-derived river ice extents when evaluated against in situ reports of river ice condition. b, Monthly evaluation of Landsat-derived river ice estimates. c, Examples of differences in definition between remotely sensed and ground-based ice conditions. The GRWL centrelines are shown in images c2 and c4 to indicate the river. Satellite images courtesy of the US Geological Survey.
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Yang, X., Pavelsky, T.M. & Allen, G.H. The past and future of global river ice. Nature 577, 69–73 (2020). https://doi.org/10.1038/s41586-019-1848-1
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Remote Sensing of Environment (2020)
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