Luke A. Winslow Gretchen J.A. Hansen Jordan S. Read 2017 text files http://dx.doi.org/10.5066/F7DV1H10 Luke A. Winslow Gretchen J.A. Hansen Jordan S. Read Michael Notaro 2017 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. Fisheries biology, limnological research, and climate science. 19790101 20991231 model estimates Complete none planned -96.8589114267623 -83.0573307815185 41.7553570685206 48.7289513243629 none water temperate lakes reservoirs modeling climate change thermal profiles ISO 19115 Topic Category environment inlandWaters 007 012 USGS Metadata Identifier USGS:57d30e7ee4b0571647d113e2 Department of Commerce, 1995, Countries, Dependencies, Areas of Special Sovereignty, and Their Principal Administrative Divisions, Federal Information Processing Standard (FIPS) 10-4, Washington, D.C., National Institute of Standards and Technology United States US U.S. Department of Commerce, 1987, Codes for the identification of the States, the District of Columbia and the outlying areas of the United States, and associated areas (Federal Information Processing Standard 5-2): Washington, D. C., NIST Illinois IL U.S. Department of Commerce, 1987, Codes for the identification of the States, the District of Columbia and the outlying areas of the United States, and associated areas (Federal Information Processing Standard 5-2): Washington, D. C., NIST Indiana IN U.S. Department of Commerce, 1987, Codes for the identification of the States, the District of Columbia and the outlying areas of the United States, and associated areas (Federal Information Processing Standard 5-2): Washington, D. C., NIST Iowa IA U.S. Department of Commerce, 1987, Codes for the identification of the States, the District of Columbia and the outlying areas of the United States, and associated areas (Federal Information Processing Standard 5-2): Washington, D. C., NIST Michigan MI U.S. Department of Commerce, 1987, Codes for the identification of the States, the District of Columbia and the outlying areas of the United States, and associated areas (Federal Information Processing Standard 5-2): Washington, D. C., NIST Minnesota MN U.S. Department of Commerce, 1987, Codes for the identification of the States, the District of Columbia and the outlying areas of the United States, and associated areas (Federal Information Processing Standard 5-2): Washington, D. C., NIST South Dakota SD U.S. Department of Commerce, 1987, Codes for the identification of the States, the District of Columbia and the outlying areas of the United States, and associated areas (Federal Information Processing Standard 5-2): Washington, D. C., NIST Wisconsin WI none Illinois none Indiana none Iowa none Michigan none Minnesota none South Dakota none Wisconsin none These data are subject to change and are not citable until reviewed and approved for official publication by the USGS Jordan S. Read U.S. Geological Survey Mailing and Physical

8551 Research Way

Middleton WI 53562 U.S.A. 608 821-3922 jread@usgs.gov This study was funded by the Department of the Interior Northeast Climate Science Center, the United States Geological Survey National Climate Change and Wildlife Science Center grant 10909172 to the University of Wisconsin–Madison, and the WDNR Federal Aid in Sport Fish Restoration (Project F-95-P, study SSBW). This research used resources of the Core Science Analytics and Synthesis Advanced Research Computing program at the U.S. Geological Survey. Multiple computer systems were used to generate these data, including linux, OSX. The open source language R was used on all systems, as well as the open-source model GLM. Matthey R. Hipsey Louise C. Bruce David P. Hamilton 2013 http://aed.see.uwa.edu.au/research/models/GLM/index.html Michael Notaro Val Bennington Steve Vavrus 2015 http://dx.doi.org/10.1175/JCLI-D-14-00467.1 Kenneth E. Mitchell Dag Lohmann Paul R. Houser Eric F. Wood John C. Schaake Alan Robock Brian A. Cosgrove Justin Sheffield Qingyun Duan Lifeng Luo R. Wayne Higgins Rachel T. Pinker J. Dan Tarpley Dennis P. Lettenmaier Curtis H. Marshall Jared K. Entin Ming Pan Wei Shi Victor Koren Jesse Meng Bruce H. Ramsay Andrew A. Bailey 2004 http://dx.doi.org/10.1029/2003JD003823 No formal attribute accuracy tests were conducted. not applicable not applicable A formal accuracy assessment of the horizontal positional information in the data set has not been conducted. A formal accuracy assessment of the vertical positional information in the data set has either not been conducted, or is not applicable. At the core of the modeling framework is a lake hydrodynamic model that uses inputs of lake-specific properties and local meteorology to estimate water temperature. Our chosen model is the open source, General Lake Model (GLM) version 2.2.0. GLM is a one-dimensional dynamical model which simplifies lakes using a vertical approximation, where horizontal variability is ignored. GLM uses a Lagrangian approach to layer structure where layers can split and combine based on changing vertical gradients. GLM is a modern, implementation of other one-dimensional models. We used GLM to run individual lake simulations according to the processes described in Winslow et al. 2017. Outputs for water temperature were extracted at various depths and written or summarized to the files included in this set of data. The glmtools R package was used for this processing. 20160624 U.S.A. Point G-polygon 10774 0.1 0.1 Decimal degrees North American Datum of 1983 Geodetic Reference System 80 6378137.0 298.257 Model configuration details Model configurations for running the General Lake Model (Hipsey et al. 2013) for each lake, for each driver type. There are seven files that share identical formatting. Six files correspond to downscaled Global Circulation Models (Notaro et al. 2016), and one (NLDAS) are results from contemporary (1979-2015) meterology. Each file contains the same attributes (described above). NLDAS drivers (NLDAS_model_config.json) are described in Mitchell et al. 2004. The remaining six files are driven with models described in Notaro et al. 2015. The value for "lake_name" in the "morphometry" field is the mapping for "site_id" for the other datasets included in this release. Producer Defined glm_setup parameters for setting up the General Lake Model and defining constants Hipsey et al. 2013 NA NA NA morphometry parameters describing the depth/area relationship of the lake for the General Lake Model Hipsey et al. 2013 NA NA NA time parameters describing the time period and frequency of model runs for the General Lake Model Hipsey et al. 2013 NA NA NA output parameters describing how the outputs of model runs from the General Lake Model are written Hipsey et al. 2013 NA NA NA init_profiles parameters describing General Lake Model initial conditions Hipsey et al. 2013 NA NA NA meteorology parameters describing time series drivers of General Lake Model runs Hipsey et al. 2013 NA NA NA bird_model parameters describing the use (if applicable) of the Bird model for General Lake Model runs Hipsey et al. 2013 NA NA NA inflow parameters describing inflows to the General Lake Model Hipsey et al. 2013 NA NA NA outflow parameters describing outflows from the General Lake Model Hipsey et al. 2013 NA NA NA snowice parameters describing how snow and ice dynamics are calculated by the General Lake Model Hipsey et al. 2013 NA NA NA Jordan S. Read U.S. Geological Survey - ScienceBase Mailing and Physical

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Denver CO 80255 U.S.A. 1-888-275-8747 sciencebase@usgs.gov Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. JSON (JavaScript Object Notation) formatted text files none http://dx.doi.org/10.5066/F7DV1H10 None 20200814 Jordan S. Read U.S. Geological Survey Data Chief Mailing and Physical

8505 Research Way

Middleton WI 53562 U.S.A. 608 821-3922 608 821-3817 jread@usgs.gov FGDC Biological Data Profile of the Content Standard for Digital Geospatial Metadata FGDC-STD-001.1-1999