{
    "identifier": "gov.noaa.nodc:0303534",
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    "title": "Daily air temperature data for the North American Great Lakes based on the coastal weather station data from 18970101 to 20231022 (NCEI Accession 0303534)",
    "description": "Daily maximum and minimum air temperature data were obtained from the Global Historical Climatology Network daily (GHCNd, Menne, et al. 2012) and the Great Lakes Air Temperature\/Degree Day Climatology, 1897-1983 (Assel et al. 1995). Daily air temperature was calculated by taking a simple average of daily maximum and minimum air temperature. To accurately capture climate trends and variability, it is critical to ensure data consistency across the historical record, such as spatial coverage, a number of representative weather stations, and measurement details (e.g., sensor types and heights, measurement protocols) as any inconsistencies could result in apparent climate change in the data record. Bearing this in consideration and following Cohn et al. (2021), a total of 24 coastal locations along the Great Lakes were selected (see Figure 1 in the Method Document). These 24 locations had relatively consistent station data records since the 1890s while data from other locations had large gaps in time, or had inconsistencies among data from neighboring stations. Each of the selected locations had multiple weather stations in their proximity covering the historical period from 1890s to 2023, representing the weather conditions around the location. Only a couple of stations covered the whole historical period (e.g., Green Bay, WI). Therefore, for most of the locations, datasets from multiple stations in the proximity of each location were combined to create a continuous data record from the 1890s to 2023 (see Table 1 in the Method Document for station information and periods for which the station data was used). When doing so, data consistency was verified by comparing the data during the period when station datasets overlap. This procedure resulted in almost continuous timeseries, except for a few locations that still had temporal gaps of one to several days (e.g., Escanaba, MI). Therefore, any temporal data gap less than 10 days in the combined timeseries were filled based on the linear interpolation. This resulted in completely continuous timeseries for all the locations.\nAverage daily air temperature was calculated from January 1, 1897 to  October 22, 2023 by simply making an average of timeseries data from corresponding locations around each lake. This resulted in daily air temperature records for all five Great Lakes (Lake Superior, Lake Huron, Lake Michigan, Lake Erie, and Lake Ontario).\n\nThe cumulative freezing degree days (CFDDs) and the net melting degree days (NMDDs) were also added to this version of the dataset. The description of the calculation methods for CFDD and NMDD can be found in the method document included in this dataset.",
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    "bureauCode": [
        "010:04"
    ],
    "modified": "2025-04-20T23:11:32.506Z",
    "publisher": {
        "@type": "org:Organization",
        "name": "Your Publisher"
    },
    "theme": "",
    "keyword": [
        "0303534",
        "AIR TEMPERATURE",
        "Freezing Degree Days",
        "thermometer",
        "in situ",
        "model output",
        "weather stations",
        "University of Michigan Cooperative Institute for Great Lakes Research",
        "Great Lakes",
        "oceanography",
        "Advancing understanding of interannual variability and extreme events in the thermal structure of large lakes under historical and future climate scenarios",
        "Great Lakes Earth System Modeling",
        "EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATURE",
        "Cumulative Freezing Degree Days",
        "Net Melting Degree Days",
        "THERMOMETERS > THERMOMETERS",
        "WEATHER STATIONS > WEATHER STATIONS",
        "CONTINENT > NORTH AMERICA > CANADA > GREAT LAKES, CANADA",
        "CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > GREAT LAKES",
        "The North American Great Lakes",
        "153WR3",
        "environment",
        "oceans",
        "climatologyMeteorologyAtmosphere"
    ]
}