gridmet
What is gridmet?
gridMET is a dataset of daily high-spatial resolution (~4-km, 1/24th degree) surface meteorological data covering the contiguous US from 1979-yesterday. We have also extended these data to cover southern British Columbia in our real time products. These data can provide important inputs for ecological, agricultural, and hydrological models. These data are updated daily. gridMET is the preferred naming convention for these data; however, the data are also known as cited as METDATA.
Datasets
Primary Climate Variables: Maximum temperature, minimum temperature, precipitation accumulation, downward surface shortwave radiation, wind-velocity, humidity (maximum and minimum relative humidity and specific humidity
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Derived variables: Reference evapotranspiration (ASCE Penman-Montieth), Energy Release Component*, Burning Index*, 100-hour and 1000-hour dead fuel moisture, mean vapor pressure deficit, 10-day Palmer Drought Severity Index *fuel model G (conifer forest)
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Methods
gridMET blends spatial attributes of gridded climate data from PRISM with desirable temporal attributes (and additional variables) from regional reanalysis (NLDAS-2) using climatically aided interpolation. The resulting product is a spatially and temporally complete, high-resolution (1/24th degree ~4-km) gridded dataset of surface meteorological variables. gridMET is semi-operational product that we provide to the community pro-bono and update daily.
Near Real time updates
Originally developed as a research project, we have made significant efforts to provide a living dataset to multiple communities. As such we implemented (and continue to implement) several changes to minimize latency effects and changing data sources. Namely, NLDAS2 has a latency of 3-5 days which is not suitable for near real time information. Several approaches are outlined below in terms of how we overcome this to create a continuous product
- daily PRISM data for temperature anomalies and precipitation anomalies are used for prior days (except the most recent day). The most recent day's temperature is updated using anomalies from Climate Forecast System version 2 (CFSV2), while we use precipitation from the National Water Prediction Service QPE.
- anomalies of wind speed, humidity, and solar radiation from CFSv2 are used to fill the latency and are replaced with NLDAS2 when those data are available
- Anomalies are superposed to the underlying gridMET fields. In both cases anomalies are taken with respect to the same periods of record to ensure consistency across time (i.e., PRISM data 1981-2010 averages are added (or multiplied) to gridMET 1981-2010; 2011-2017 anomalies are used for CFSv2).
accuracy
Validation of the resulting gridded surface meteorological data was conducted against an extensive network of weather stations including RAWS, AgriMet, AgWeatherNet and USHCN-2. For more information on validation measures see Abatzoglou (2013).
Data limitations
- gridMET will likely not capture microclimates that arise at spatial scales finer than the native resolution of the grid or parent datasets (<4-km). Comparisons to station data should account for differences in spatial scales between gridded products (average over the grid) versus in-situ observations.
- gridMET wind fields and solar radiation are interpolated from NARR/NLDAS-2 which has a 32-km spatial resolution. This will be insufficient for capturing mesoscale influences of terrain on wind fields.
- Solar radiation from gridMET is not adjusted for topographic effects, but instead is provided for a planar surface. Users may wish to terrain correct for solar radiation loading using a digital elevation model.
- gridMET nominally considers a "day" to be midnight-to-midnight Mountain Standard Time (7 UTC)
Frequently asked Data Questions
- gridMET grids correspond to the centroid of the 4-km x 4-km pixel.
- Data for dates within the last 60 days are considered preliminary and subject to change.
COPYRIGHTS
To the extent possible under law,
John Abatzoglou
has waived all copyright and related or neighboring rights to
gridMET.
This work is published from:
United States.
This research was supported by the NSF Idaho EPSCoR Program and by the National Science Foundation under award number EPS-0814387 and the National Institute for Food and Agriculture competitive grant, award number: 2011-68002-30191. This work (METDATA, by John Abatzoglou) is free of known copyright restrictions.
There are several options for acquiring gridMET data. We provide a list of current options below:
Direct file downloads
Data subsets can be accessed using the web tools:
Direct file downloads
- Direct download of NetCDF files
- Create wget script for downloading NetCDF files
- THREDDS Catalog (OPENDAP)
- Aggregated THREDDS Catalog (OPENDAP)
- Elevation data on the same 4-km grid as the Meteorological data.
Data subsets can be accessed using the web tools:
Updates to data products (recalls, new variables) will be highlighted here
September 2024
Data for dates 2023-02-19, 2024-08-16, and 2022-02-27 were reprocessed to correct for missing values in hourly NLDAS2 data. Likewise, gridMET was recomputed from 2022-08-01 to 2024-03-01 incorporating new NLDAS2 hourly data for this time period due to an NLDAS2 bug. See https://ldas.gsfc.nasa.gov/index.php/nldas/news/nldas-2-data-re-processed-2022-08-01-2024-03-01 for more info on the NLDAS2 bug.
February 2021
An update to netCDF software may create problems for users accessing netCDF files from the cloud. A workaround involves adding #fillmismatch at the end of the netcdf file name. For example,
http://thredds.northwestknowledge.net/thredds/dodsC/MET/erc/erc_2012.nc#fillmismatch
Subsequent improvements to the netCDF infrastructure will fix this problem.
July 2020
Over the next several weeks operational gridMET related products may be delayed or not updated as our lab is transitioning to UC Merced. Products will be updated and continue operating as usual once our systems as restored in their new home.
August 2019
File formats have been updated to NETCDF4 format to improve data efficiency. Note that these files will contain a scale_factor and offset that need to be considered upon reading the data in.
May 2018
To improve latency issues, daily gridMET temperature and precipitation data now make use of daily PRISM maximum temperature, minimum temperature and precipitation that have been bias corrected to adhere to the gridMET fields. The same monthly corrections using PRISM have also been updated to reflect the most recent version of PRISM.
We have updated the structure of all netcdf files and made a minor adjustment to the grid. These were made to allow our netcdf files to be compatible with a more diverse set of programming and geospatial software packages.
January 2018
We have added layers of reference alfalfa evapotranspiration and vapor pressure deficit.
NETCDF4 data model, file format HDF5)
September 2024
Data for dates 2023-02-19, 2024-08-16, and 2022-02-27 were reprocessed to correct for missing values in hourly NLDAS2 data. Likewise, gridMET was recomputed from 2022-08-01 to 2024-03-01 incorporating new NLDAS2 hourly data for this time period due to an NLDAS2 bug. See https://ldas.gsfc.nasa.gov/index.php/nldas/news/nldas-2-data-re-processed-2022-08-01-2024-03-01 for more info on the NLDAS2 bug.
February 2021
An update to netCDF software may create problems for users accessing netCDF files from the cloud. A workaround involves adding #fillmismatch at the end of the netcdf file name. For example,
http://thredds.northwestknowledge.net/thredds/dodsC/MET/erc/erc_2012.nc#fillmismatch
Subsequent improvements to the netCDF infrastructure will fix this problem.
July 2020
Over the next several weeks operational gridMET related products may be delayed or not updated as our lab is transitioning to UC Merced. Products will be updated and continue operating as usual once our systems as restored in their new home.
August 2019
File formats have been updated to NETCDF4 format to improve data efficiency. Note that these files will contain a scale_factor and offset that need to be considered upon reading the data in.
May 2018
To improve latency issues, daily gridMET temperature and precipitation data now make use of daily PRISM maximum temperature, minimum temperature and precipitation that have been bias corrected to adhere to the gridMET fields. The same monthly corrections using PRISM have also been updated to reflect the most recent version of PRISM.
We have updated the structure of all netcdf files and made a minor adjustment to the grid. These were made to allow our netcdf files to be compatible with a more diverse set of programming and geospatial software packages.
- The latitude dimension of the data increases monotonically;
- The dimension (or order) of the data has changed;
- There was a very slight ~400m offset in the reported centroid of the grid. This does not influence actual data, but just adjusts the latitude/longitude for the exact location of the cell.
January 2018
We have added layers of reference alfalfa evapotranspiration and vapor pressure deficit.
NETCDF4 data model, file format HDF5)
Abatzoglou, J. T. (2013), Development of gridded surface meteorological data for ecological applications and modelling. Int. J. Climatol., 33: 121–131.
- The primary input dataset for daily precipitation (NLDAS-2) contains inhomogeneities due to changes in data sources through time that are currently entrained into gridMET precipitation. We caution against using gridMET to infer changes in precipitation intensity and frequency.
- Operational data from gridMET (2013-) makes use of anomalies derived from daily PRISM data for temperature and precipitation as well as anomalies from the Climate Forecast System version 2 (CFSV2) analysis fields. PRISM data are differenced from their corresponding 1981-2010 averages and added (or multiplied) to gridMET averages for the corresponding time period. To address latency issues with NLDAS2, CFSV2 data are used to fill the gap over the most recent 3-4 days. CFSV2 anomalies from the 1981-2010 are calculated and applied to get first-estimate fields for wind, radiation, and humidity.
- gridMET uses downward shortwave radiation from NLDAS2. Some studies have shown that NLDAS2 downward shortwave radiation shows a positive bias over much of North America.