2024
DOI: 10.1002/lno.12527
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Nonlinear responses in interannual variability of lake ice to climate change

David C. Richardson,
Alessandro Filazzola,
R. Iestyn Woolway
et al.

Abstract: Climate change is contributing to rapid changes in lake ice cover across the Northern Hemisphere, thereby impacting local communities and ecosystems. Using lake ice cover time‐series spanning over 87 yr for 43 lakes across the Northern Hemisphere, we found that the interannual variability in ice duration, measured as standard deviation, significantly increased in only half of our studied lakes. We observed that the interannual variability in ice duration peaked when lakes were, on average, covered by ice for a… Show more

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Cited by 2 publications
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“…Third, the interannual variability of lake ice phenology, which is significantly influenced by Journal of Geophysical Research: Atmospheres 10.1029/2023JD039935 weather-climate anomalies and large-scale teleconnection patterns, for example, the El Niño-Southern Oscillation, Arctic Oscillation, and North Atlantic Oscillation (Bai et al, 2012;Fujisaki et al, 2013;Imrit & Sharma, 2021), is not accurately captured by the offline WRF-Lake. The model's poor predictability primarily arises from lake ice phenology's highly sensitive and nonlinear response to the complex variability of climate forcings (Benson et al, 2012;Richardson et al, 2024). This issue is underscored by Wang et al (2012), who, using satellite observations of the Laurentian Great Lakes from 1973 to 2010, observed that the standard deviations in annual ice cover were comparable or sometimes even larger than the climatological means for all five lakes.…”
Section: Summary Discussion and Future Recommendationsmentioning
confidence: 99%
“…Third, the interannual variability of lake ice phenology, which is significantly influenced by Journal of Geophysical Research: Atmospheres 10.1029/2023JD039935 weather-climate anomalies and large-scale teleconnection patterns, for example, the El Niño-Southern Oscillation, Arctic Oscillation, and North Atlantic Oscillation (Bai et al, 2012;Fujisaki et al, 2013;Imrit & Sharma, 2021), is not accurately captured by the offline WRF-Lake. The model's poor predictability primarily arises from lake ice phenology's highly sensitive and nonlinear response to the complex variability of climate forcings (Benson et al, 2012;Richardson et al, 2024). This issue is underscored by Wang et al (2012), who, using satellite observations of the Laurentian Great Lakes from 1973 to 2010, observed that the standard deviations in annual ice cover were comparable or sometimes even larger than the climatological means for all five lakes.…”
Section: Summary Discussion and Future Recommendationsmentioning
confidence: 99%