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Daily lake surface temperatures estimates for 185,549 lakes across the contiguous United States from 1980 to 2020 generated using an entity-aware long short-term memory deep learning model. In-situ measurements used for model training and evaluation are from 12,227 lakes and are included as well as daily meteorological conditions and lake properties. Median per-lake estimated error found through cross validation on lakes with in-situ surface temperature observations was 1.24 °C. The generated dataset will be beneficial for a wide range of applications including estimations of thermal habitats and the impacts of climate change on inland lakes.
Abstract (from Ecosphere): Understanding invasive species spread and projecting how distributions will respond to climate change is a central task for ecologists. Typically, current and projected air temperatures are used to forecast future distributions of invasive species based on climate matching in an ecological niche modeling approach. While this approach was originally developed for terrestrial species, it has also been widely applied to aquatic species even though aquatic species do not experience air temperatures directly. In the case of lakes, species respond to lake thermal regimes, which reflect the interaction of climate and lake attributes such as depth, size, and clarity. The result is that adjacent...
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The dataset described here includes estimates of historical (1980–2020) daily surface water temperature, lake metadata, and daily weather conditions for lakes bigger than 4 ha in the conterminous United States (n = 185,549), and also in situ temperature observations for a subset of lakes (n = 12,227). Estimates were generated using a long short-term memory deep learning model and compared to existing process-based and linear regression models. Model training was optimized for prediction on unmonitored lakes through cross-validation that held out lakes to assess generalizability and estimate error. On the held-out lakes with in situ observations, median lake-specific error was 1.24°C, and the overall root mean squared...
Categories: Publication;
Types: Citation
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