Climate Change is Contributing to Faster Rates of Lake Ice Loss in Lakes Around the Northern Hemisphere
Bibliographic record
Abstract
Abstract Lake ice phenology has been recorded for decades, providing us with long‐term records to investigate the impact of climate change in lakes since the Industrial Revolution. Here, we examine the trends and drivers of 18 lakes across the Northern Hemisphere, with 156–204 years of data, starting in the 1810s. We show that: (a) trends in ice phenology are faster than found by previous studies. Ice‐on is 11 days later per century, ice‐off is 9 days earlier per century, and ice cover duration is 19 days shorter per century; (b) there are significant breakpoints in the 1850s, 1870s, mid‐1890s, and mid‐1990s, after which trends in ice phenology are even faster, and associated with changing weather and climate; and (c) local air temperatures explain the most variation in ice phenology, on average 36.5%, followed by progressive climate change explaining around 17.5% on average, with teleconnection patterns explaining the least variation. Our findings support the assertion that broad‐scale climatic changes have led to more rapid lake ice loss in lakes distributed across the Northern Hemisphere, with potential widespread impacts on critical ecosystem services that lake ice provides.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".