NASA Daymet Project: Annual Climate Summaries for North America at 1 km Resolution
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Description
Annual climate summaries derived from Daymet Version 4 R1 daily data at a 1 km x 1 km spatial resolution for five variables: minimum and maximum temperature, precipitation, vapor pressure, and snow water equivalent. The dataset covers North America, Hawaii, and Puerto Rico, with data for continental North America and Hawaii starting in 1980 and Puerto Rico data available from 1950. Data are provided in netCDF and Cloud Optimized GeoTIFF formats.
Use Cases
Modeling climate change impacts based on annual temperature and precipitation summaries.
Analyzing regional water resource availability based on snow water equivalent and precipitation totals.
Studying long-term vapor pressure trends for ecological and agricultural research.
Calibrating and validating other climate models using high-resolution gridded data.
Strengths
Provides data at a high 1 km x 1 km spatial resolution.
Covers a long temporal record, starting from 1980 for most regions and 1950 for Puerto Rico.
Data for 2020 and 2021 were specifically updated to correct missing readings from Canadian weather stations.
Offers data in standardized, interoperable netCDF and Cloud Optimized GeoTIFF formats.
Limitations
Column-level documentation is absent; field semantics must be inferred after download.
Row count and total file size are unknown, which may limit suitability assessment.
Provenance
Source
NASA Daymet Project, derived from Daymet Version 4 R1 daily data.
Collection Method
Gridded estimates derived from daily weather parameters, with inputs from sources like GHCNd and Environment Canada.
Time Range
1980 to the most recent full calendar year for continental North America and Hawaii; 1950 onward for Puerto Rico.
Freshness
Data is processed individually at the close of each calendar year, but the last update date for this specific listing is unknown.
Geography
North America (Canada, United States, Mexico), Hawaii, and Puerto Rico.
Data is hosted on S3. Users must be familiar with netCDF or GeoTIFF formats and geospatial analysis tools.