This dataset contains modeled daily lake area, volume, constituent mass, and biogeochemical rates for 3,692 lakes in the Northern Highlands Lake District (NHLD) for one retrospective model run (1986-2010) and 12 model runs under future climate scenarios. This dataset was created using published tools developed to simulate detailed hydrological and biogeochemical fluxes for thousands of lakes and reservoirs over large spatiotemporal scales. The lake hydrology model utilized a computationally-efficient integrated surface water and groundwater modeling framework that informed a lake water budget model incorporating daily hydrologic inputs and exports from individual lakes within the modeling domain. The lake biogeochemical model was informed by the hydrologic information and was built upon a simple lake energy budget, constituent loading, and lake biogeochemical model to track carbon storage and processing for all lakes within the NHLD modeling domain. Our one retrospective model run was driven by historic meteorological data and the projected model runs were driven by projected future climate scenario periods that are representative through the year 2100. For more details on the historic and projected driver data and model set up, please see Zwart et al. (year and DOI to be entered once MS is published).

Climate change has been shown to influence lake temperatures globally. To better understand the diversity of lake responses to climate change and give managers tools to manage individual lakes, we modelled daily water temperature profiles for 10,774 lakes in Michigan, Minnesota and Wisconsin for contemporary (1979-2015) and future (2020-2040 and 2080-2100) time periods with climate models based on the Representative Concentration Pathway 8.5, the worst-case emission scenario. From simulated temperatures, we derived commonly used, ecologically relevant annual metrics of thermal conditions for each lake. We included all available supporting metadata including satellite and in-situ observations of water clarity, maximum observed lake depth, land-cover based estimates of surrounding canopy height and observed water temperature profiles (used here for validation). This unique dataset offers landscape-level insight into the future impact of climate change on lakes. This data set contains the following parameters: Thermal metrics, Spatial data, Temperature data, Model drivers, Model configuration, which are defined below.

Climate change has been shown to influence lake temperatures globally. To better understand the diversity of lake responses to climate change and give managers tools to manage individual lakes, we modelled daily water temperature profiles for 10,774 lakes in Michigan, Minnesota and Wisconsin for contemporary (1979-2015) and future (2020-2040 and 2080-2100) time periods with climate models based on the Representative Concentration Pathway 8.5, the worst-case emission scenario. From simulated temperatures, we derived commonly used, ecologically relevant annual metrics of thermal conditions for each lake. We included all available supporting metadata including satellite and in-situ observations of water clarity, maximum observed lake depth, land-cover based estimates of surrounding canopy height and observed water temperature profiles (used here for validation). This unique dataset offers landscape-level insight into the future impact of climate change on lakes. This data set contains the following parameters: Thermal metrics, Spatial data, Temperature data, Model drivers, Model configuration, which are defined below.

Climate change has been shown to influence lake temperatures globally. To better understand the diversity of lake responses to climate change and give managers tools to manage individual lakes, we modelled daily water temperature profiles for 10,774 lakes in Michigan, Minnesota and Wisconsin for contemporary (1979-2015) and future (2020-2040 and 2080-2100) time periods with climate models based on the Representative Concentration Pathway 8.5, the worst-case emission scenario. From simulated temperatures, we derived commonly used, ecologically relevant annual metrics of thermal conditions for each lake. We included all available supporting metadata including satellite and in-situ observations of water clarity, maximum observed lake depth, land-cover based estimates of surrounding canopy height and observed water temperature profiles (used here for validation). This unique dataset offers landscape-level insight into the future impact of climate change on lakes. This data set contains the following parameters: glm_setup, morphometry, time, output, init_profiles, meteorology, bird_model, inflow, outflow, snowice, which are defined below.

Climate change has been shown to influence lake temperatures globally. To better understand the diversity of lake responses to climate change and give managers tools to manage individual lakes, we modelled daily water temperature profiles for 10,774 lakes in Michigan, Minnesota and Wisconsin for contemporary (1979-2015) and future (2020-2040 and 2080-2100) time periods with climate models based on the Representative Concentration Pathway 8.5, the worst-case emission scenario. From simulated temperatures, we derived commonly used, ecologically relevant annual metrics of thermal conditions for each lake. We included all available supporting metadata including satellite and in-situ observations of water clarity, maximum observed lake depth, land-cover based estimates of surrounding canopy height and observed water temperature profiles (used here for validation). This unique dataset offers landscape-level insight into the future impact of climate change on lakes. This data set contains the following parameters: time, wtr_{z}, which are defined below.

Climate change has been shown to influence lake temperatures globally. To better understand the diversity of lake responses to climate change and give managers tools to manage individual lakes, we modelled daily water temperature profiles for 10,774 lakes in Michigan, Minnesota and Wisconsin for contemporary (1979-2015) and future (2020-2040 and 2080-2100) time periods with climate models based on the Representative Concentration Pathway 8.5, the worst-case emission scenario. From simulated temperatures, we derived commonly used, ecologically relevant annual metrics of thermal conditions for each lake. We included all available supporting metadata including satellite and in-situ observations of water clarity, maximum observed lake depth, land-cover based estimates of surrounding canopy height and observed water temperature profiles (used here for validation). This unique dataset offers landscape-level insight into the future impact of climate change on lakes. This data set contains the following parameters: site_id, Prmnn_I, GNIS_ID, GNIS_Nm, ReachCd, FType, FCode, which are defined below.

Climate change has been shown to influence lake temperatures globally. To better understand the diversity of lake responses to climate change and give managers tools to manage individual lakes, we modelled daily water temperature profiles for 10,774 lakes in Michigan, Minnesota and Wisconsin for contemporary (1979-2015) and future (2020-2040 and 2080-2100) time periods with climate models based on the Representative Concentration Pathway 8.5, the worst-case emission scenario. From simulated temperatures, we derived commonly used, ecologically relevant annual metrics of thermal conditions for each lake. We included all available supporting metadata including satellite and in-situ observations of water clarity, maximum observed lake depth, land-cover based estimates of surrounding canopy height and observed water temperature profiles (used here for validation). This unique dataset offers landscape-level insight into the future impact of climate change on lakes. This data set contains the following parameters: site_id, Prmnn_I, GNIS_ID, GNIS_Nm, ReachCd, FType, FCode, which are defined below.

,Climate change has been shown to influence lake temperatures in different ways. To better understand the diversity of lake responses to climate change and give managers tools to manage individual lakes, we focused on improving prediction accuracy for daily water temperature profiles in 7,150 lakes in Minnesota and Wisconsin during 1980-2019. The data are organized into these items: