Water temperature and ice cover are critical variables for the ecological, biogeochemical, and physical functioning of a lake. However, site-specific observations of water temperature and ice cover are not available for most lakes in the world. Yet this information is crucial to understanding the global role of lakes in the functioning of the bio- and hydrosphere and understanding the (projected) changes induced by global environmental change. Here, we present two datasets which include: 1) lake surface water temperature (LSWT) observations between 2013 and 2021 for ~1.4 million lakes (larger than 0.1 km²) globally, and 2) seasonal LSWT summary statistics as well as predictions of average yearly ice cover derived from dataset 1. The observations were extracted from Landsat-8 thermal radiance imageries, processed and calculated to LSWT from a center point of each lake. We used in-situ LSWT data for validation and compared our data to other satellite-derived LSWT and ice phenology datasets. All data underwent extensive quality control, based on outlier detection, overlapping imagery removal, and the removal of observations taken from dry lake beds. We used an ensemble of computational tools (e.g., Google Earth Engine, ArcGIS, R) to create these datasets, and although we believe that large-scale data retrieval methods are becoming increasingly more accessible, we also acknowledge that there is still a time and resource barrier for many interested in analyzing large-scale data. We therefore make these two datasets openly available and provide them in an analytical-friendly format. We believe that this dataset fills a crucial spatial data gap, especially for the incorporation of small(er) lakes and understudied geographies in large-scale limnological research.

Primary Presenter: Maartje Korver, McGill University (maartjekorver@gmail.com)

Authors:

Bernhard Lehner, McGill University  ()

Jeffrey Cardille, McGill University  ()

Laura Carrea, University of Reading  ()