Global evaluation of process-based models with in situ observations to detect long-term change in lake ice

Abstract

Abstract. Lake ice phenology has been used extensively to study the impacts of anthropogenic climate change, owing to the widespread occurrence of lake ice and the length of time series available for such studies. The proliferation of process-based lake models and gridded climate data have enabled the modeling of ice phenology across broad spatial scales, for example where lakes are not sampled. In this study, we used ice phenology outputs from an ensemble of lake-climate model projections to directly compare their performance with in situ data. Generally, we found that the lake models captured the range of variability of observational records (RMSE ice on = 22.9 days [4.7, 95.4]; RMSE ice off = 17.4 days [6.1, 76.5]), and particularly the long-term trends in temperate regions. However, the models performed poorly in extremely warm years or when there were rapid short-term changes in ice phenology. The location of the lakes, such as latitude and longitude, as well as lake morphology, such as lake depth and surface area, significantly influenced model performance. For example, the models performed best in shallow small lakes and worst in deep larger lakes. Our analysis suggests that the lake models tested can reliably estimate long-term trends in lake ice cover, particularly when averaged across large spatial scales, but widespread in situ observations are critical to capture extreme events.

Lake Ice From Historical Records to Contemporary Science

“…A combination of meteorological variables, including air temperatures, wind, snowfall, winter precipitation, and solar radiation, are important drivers of ice thickness (Brown & Duguay, 2010;Cheng et al, 2014;Imrit et al, 2022;Leppäranta, 2010;Nõges & Nõges, 2014). Winter air temperatures have often been observed to be the most important factor influencing ice thickness (Gao & Stefan, 1999;Imrit et al, 2022;Murfitt et al, 2018;Todd & Mackay, 2003). For example, Imrit et al (2022) calculated that 81% of the variation in ice thickness for 27 lakes and rivers in North America could be explained by winter air temperatures.…”

“…Winter air temperatures have often been observed to be the most important factor influencing ice thickness (Gao & Stefan, 1999;Imrit et al, 2022;Murfitt et al, 2018;Todd & Mackay, 2003). For example, Imrit et al (2022) calculated that 81% of the variation in ice thickness for 27 lakes and rivers in North America could be explained by winter air temperatures. Warmer winter air temperatures correlate with diminished ice thickness, with correlations as high as r = 0.91 in MacDonald Lake in central Ontario (Murfitt et al, 2018).…”

“…Ice thickness and ice growth have long been of interest to researchers, although consistent long‐term trends of ice thickness are not yet apparent, with large variation amongst years (Cheng et al., 2014; Imrit et al., 2022; Li et al., 2021; Murfitt et al., 2018; Vuglinsky & Valatin, 2018). To our knowledge, the earliest study evaluating ice formation and ice growth is from Lake Baikal, where Shostakovich and Drizhenko (1908) observed an association between snow depth and ice thickness, such that increased snow depth inhibited ice growth (Shostakovich & Drizhenko, 1908).…”

“…To our knowledge, the earliest study evaluating ice formation and ice growth is from Lake Baikal, where Shostakovich and Drizhenko (1908) observed an association between snow depth and ice thickness, such that increased snow depth inhibited ice growth (Shostakovich & Drizhenko, 1908). Ice thickness in lakes is not consistently increasing or decreasing across the Northern Hemisphere or even within a continent or country (Imrit et al., 2022; Korhonen, 2006; Li et al., 2021). For example, across North America and the Northern Hemisphere, lakes found at high latitudes and altitudes often with the thickest ice cover were generally thinning the fastest (Li et al., 2021).…”

“…For example, Imrit et al. (2022) calculated that 81% of the variation in ice thickness for 27 lakes and rivers in North America could be explained by winter air temperatures. Warmer winter air temperatures correlate with diminished ice thickness, with correlations as high as r = −0.91 in MacDonald Lake in central Ontario (Murfitt et al., 2018).…”