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Description

This dataset provides annual climate summaries derived from Daymet Version 4 daily data at a 1 km x 1 km spatial resolution for five Daymet variables: minimum and maximum temperature, precipitation, vapor pressure, and snow water equivalent. Annual averages are provided for minimum and maximum temperature, vapor pressure, and snow water equivalent, and annual totals are provided for the precipitation variable. Each data file is provided as a single year by variable and covers the same period of record as the Daymet V4 daily data. The annual climatology files are derived from the larger datasets of daily weather parameters produced on a 1 km x 1 km grid for North America (including Canada, the United States, and Mexico), Hawaii, and Puerto Rico. Separate annual files are provided for the land areas of continental North America, Hawaii, and Puerto Rico. Data are distributed in standardized Climate and Forecast (CF)-compliant netCDF (.nc) and Cloud-Optimized GeoTIFF (.tif) file formats.

Product Summary

Platforms
MODELS
Instruments
Computer
Projects
Daymet
Spatial Extent

N: 82.9143 S: 14.0749 E: -52.6667 W: -178.133

Location
PUERTO RICO ,
HAWAII ,
NORTH AMERICA
Coordinate System
CARTESIAN
Granule Spatial Representation
CARTESIAN
Temporal Extent
1950-01-01 to 2021-12-31
Data Partner
THE OAK RIDGE NATIONAL LABORATORY (ORNL) DISTRIBUTED ACTIVE ARCHIVE CENTER (DAAC) (ORNL_DAAC)
Concept ID
C4290764759-ORNL_CLOUD
Data State
DEPRECATED
Number of Files/Granules
0
Processing Level
4
Published
Updated
Science Keywords
Vapor Pressure ,
Shortwave Radiation ,
Snow Water Equivalent ,
Precipitation Amount ,
Maximum/Minimum Temperature

Citation

Citation is critically important for dataset documentation and discovery. This dataset is openly shared, without restriction, in accordance with the EOSDIS Data Use and Citation Guidance.

Copy Citation

Thornton, M. M., Shrestha, R., Wei, Y., Thornton, P. E., & Kao, S.-C. (2020). Daymet: Annual Climate Summaries on a 1-km Grid for North America, Version 4 (Version 4). ORNL Distributed Active Archive Center. https://doi.org/10.3334/ORNLDAAC/1852 Date Accessed: 2026-09-26

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Publications Citing This Dataset

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Contribution of anthropogenic and hydroclimatic factors on the variation
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A new approach to evaluate the risk of bark beetle outbreaks using multi-step machine learning methods
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Climatic and Topographic Variables Improve Estimation Accuracy of Patula
  • Nava-Nava, Adan, Santiago-Garcia, Wenceslao, Quinonez-Barraza, Geronimo, Santos-Posadas, Hector Manuel de los, Valdez-Lazalde, Jose Rene, Angeles-Perez, Gregorio
Fire Effects on Evapotranspiration in the Upper Rio Grande Basin using Landsat-based SSEBop
  • Mankin, Kyle R., Patel, Rhythm
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