% Berkeley Earth High-Resolution Temperature Data - Beta Release % % README file for the high-resolution gridded data % %%%%%%% % % These files are based on the new high-resolution Berkeley Earth global temperature % data set. It expands upon the previous Berkeley Earth temperature data set by % including predictive structures based on historical weather patterns and % increasing the underlying resolution to 0.25° x 0.25° latitude-longitude. % The methods are described in a paper that is currently under review at Earth % System Science Data. Revisions to the data set remain possible during review. % Please cite this data set as: % % Rohde, R. A., Calvert, B., and Hausfather, Z.: Berkeley Earth Surface % Temperature - High-Resolution (BEST-HR): a 0.25° Global Gridded Temperature % Data Set for Climate Monitoring, Earth Syst. Sci. Data Discuss. [preprint], % https://doi.org/10.5194/essd-2026-412, in review, 2026. % % The data are released under the Creative Commons BY-NC 4.0 International % license, https://creativecommons.org/licenses/by-nc/4.0/ % %%%%%%% % % This file describes the gridded temperature fields of the high-resolution % data set. They hold monthly temperature anomaly values reconstructed by % the Berkeley Earth averaging method. % % All gridded data is provided in the NetCDF format (version 4). Tools for % reading NetCDF are available in most programming languages, including % Python, Matlab, R and C++. % % Products % % Global Land and ocean. Land-surface air temperature merged with a % reinterpolated version of the HadSST4 ocean temperature field. % Average temperature (TAVG) only, monthly from 1850. % % Land Land surface only. Average temperature (TAVG) monthly from % 1750, and the averages of daily maximum (TMAX) and daily % minimum (TMIN) temperature monthly from 1850. % % The global product merges land-surface air temperatures with ocean sea % surface water temperatures. For most of the ocean, sea surface temperatures % are similar to near-surface air temperatures; however, air temperatures % above sea ice can differ substantially from the water below the sea ice. In % sea ice regions, temperature anomalies are extrapolated from the land-surface % air temperatures when ice is present, and from the ocean temperatures when % ice is absent. The percent coverage of sea ice is taken from HadISST2 % (Titcher and Rayner 2014, https://doi.org/10.1002/2013JD020316) and the NSIDC % Sea Ice Index (https://nsidc.org/data/g02135/versions/3), and varies by month % and location. % % File Naming Convention % % The global files are named: % % __Gridded_.nc % __Gridded__s.nc % __Gridded_Ensemble-_.nc % % is Global (land and ocean) or Land (land only). % % is TAVG for average temperature, TMAX for the average of daily % maximum temperature, or TMIN for the average of daily minimum temperature. % TMAX and TMIN are land only. % % is 0p25deg, 1deg or 5deg, indicating 0.25° x 0.25°, 1° x 1° % and 5° x 5° latitude-longitude grids respectively. The 0.25° grid is the % native resolution of the analysis; the coarser grids are derived from it. % % is the first year of a decade, for example 1890s. The 0.25° files % are large, so the same data is also provided split into one file per % decade. % % is 1 through 10 for the individual members of the analysis % ensemble, or All for a file holding all ten. Ensemble files are provided % on the 1° grid. The spread between members indicates the uncertainty of % the field. % % Regional subsets of the 0.25° and 1° fields are provided for smaller % downloads, named: % % __Gridded_.nc (land and ocean) % _Land__Gridded_.nc (land only) % % and its bounds, in degrees of longitude and latitude: % % North_America 169W to 53W, 7N to 84N % CONUS 126W to 66W, 24N to 50N (contiguous United States) % South_America 82W to 34W, 56S to 13N % Europe 11W to 42E, 35N to 72N % Africa 18W to 52E, 35S to 38N % Asia 28E to 180E, 5N to 82N % South_Asia 66E to 150E, 5N to 54N % Australasia 105E to 180E, 50S to 12N % Antarctica 180W to 180E, 90S to 60S % % File Contents % % Each file holds the following variables. Dimensions are listed in the % order NetCDF stores them; Matlab reports them in reverse order. % % longitude (longitude) % latitude (latitude) % time (time) % land_mask (latitude, longitude) % areal_weight (latitude, longitude) % temperature (time, latitude, longitude) % climatology (month_number, latitude, longitude) % % In the ensemble files temperature and climatology have a leading % ensemble_index dimension. % % longitude, latitude: The centers of the grid cells, in degrees. Positive % values are east of Greenwich and north of the equator. % % time: The time of each field, as a decimal year at the middle of the month. % For example, 1981.125 indicates February 1981. % % land_mask: For each grid cell, the fraction of the cell which is land, as % opposed to ocean or other large water bodies. % % areal_weight: For each grid cell, its relative area, used to weight cells % when averaging over a region. % % temperature: The surface air temperature anomaly, in degrees C, relative to % the January 1951 to December 1980 average for that cell and calendar % month. Missing values are reported as NaN. % % climatology: For each grid cell, an estimate of the true surface % temperature for each calendar month during the period January 1951 to % December 1980, in degrees C. month_number has length 12, January through % December. Adding the climatology of the calendar month to an anomaly % gives an estimate of the absolute temperature. % % Uncertainty information is provided by the ensemble files. The other % gridded files contain no uncertainty field.