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  1. Home
  3. Research Domains
  5. Earth Sciences
  7. Atmospheric Sciences
  9. Atmospheric Dynamics
  11. Spatial Datasets Of 30-year (1991-2020) Average Monthly Total Precipitation And Minimum/maximum Temperature For Canada And The United States.
  1. Home
  3. Research Domains
  5. Earth Sciences
  7. Atmospheric Sciences
  9. Atmospheric Dynamics
  11. Spatial Datasets Of 30-year (1991-2020) Average Monthly Total Precipitation And Minimum/maximum Temperature For Canada And The United States.

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In Situ Soil Moisture Sensors in Undisturbed Soils
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Spatial datasets of 30-year (1991-2020) average monthly total precipitation and minimum/maximum temperature for Canada and the United States.

Heather MacDonald1, Daniel W McKenney1, John Pedlar1

  • 1Great Lakes Forestry Centre, Canadian Forest Service, Natural Resources Canada, P6A 2E5 1219 Queen Street East, Sault Ste. Marie, Ontario, Canada.

Data in Brief
|July 5, 2024

View abstract on PubMed

Summary
This summary is machine-generated.

New gridded climate datasets for North America (1991-2020) offer high-resolution temperature and precipitation data. Developed using ANUSPLIN, these datasets provide accurate climate modeling for environmental research.

Keywords:
GridsHistoricalPrecipitationRaster

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Area of Science:

  • Environmental Science
  • Climatology
  • Geospatial Analysis

Background:

  • Accurate climate data is crucial for understanding environmental changes.
  • Existing datasets may lack sufficient resolution or temporal coverage for North America.
  • The North American continent presents unique challenges for climate data due to varying geographic and network densities.

Purpose of the Study:

  • To develop high-resolution, 30-year gridded datasets for monthly mean maximum and minimum temperature and precipitation across Canada and the continental United States.
  • To assess the accuracy and bias of the developed climate models.
  • To make these valuable climate datasets publicly available.

Main Methods:

  • Utilized thin plate smoothing spline models with the ANUSPLIN software.
Spatial datasets
Spline
Temperature
  • Employed monthly weather station data from the National Oceanic and Atmospheric Administration's (NOAA) National Centers for Environmental Information (NCEI) North American dataset.
  • Developed models for the 30-year period from 1991 to 2020, covering Canada and the continental United States.

    • Main Results:

    • Maximum temperature mean absolute errors (MAEs) were between 0.54 °C and 0.64 °C; minimum temperature MAEs ranged from 0.87 °C to 1.0 °C.
    • Precipitation estimates were accurate to within approximately 10% of total precipitation, with seasonal variations (9.0% in summer to 12.2% in winter).
    • Error rates were higher in Canada (14.7% MAE for precipitation) than in the United States (9.7% MAE), linked to station network density.

    Conclusions:

    • The developed 30-year gridded climate datasets provide a valuable resource for environmental research at approximately 2 km resolution.
    • The models demonstrated minimal overall bias for temperature and precipitation, with slight seasonal variations noted.
    • The findings highlight the impact of station network density on data accuracy, particularly between Canada and the United States.