Overview
The gridded Climatic Research Unit (CRU) Time-series (TS) data version 4.05 data are month-by-month variations in climate over the period 1901-2020, provided on high-resolution (0.5 x 0.5 degrees) grids, produced by CRU at the University of East Anglia and funded by the UK National Centre for Atmospheric Science (NCAS), a NERC collaborative centre.
Provider's contact information
University of East Anglia Climatic Research Unit (CRU)
Licensing
Access to these data is available to any registered CEDA user. Users need to register and login for an account to gain access.
Use of these data is covered by the following licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/. When using these data, you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Variable name and units:
Monthly precipitation in mm/month, % for anomalies.
Spatial coverage and resolution:
Spatial coverage: Global.
Spatial resolution: 0.5° x 0.5˚
Temporal coverage and resolution:
Monthly.
Information about observations (number, homogeneity)
Monthly land station observations for precipitation (and six other variables: Mean, Minimum and Maximum Temperatures, Vapour Pressure, Wet Days and Cloud Cover) are updated regularly from several principal monthly sources: CLIMAT messages, exchanged internationally between WMO (World Meteorological Organisation) countries, obtained as quality-controlled files via the UK Met Office; MCDW (Monthly Climatic Data for the World) summaries, obtained from the US National Oceanographic and Atmospheric Administration (NOAA) via its National Climate Data Centre (NCDC); and updates of minimum and maximum temperatures for Australia, obtained from the Bureau of Meteorology (BoM). In addition, ad hoc collections of stations are incorporated (after quality control checks including location, correspondence to existing holdings, and outlier checking) (see Harris et al., 2020)
Methodology
For version 4 of the CRU TS dataset the interpolation process has been changed to use angular-distance weighting (ADW), which delivers full traceability back to station measurements. The ADW method was adopted from New et al. (2000). The station measurements of precipitation are provided as well as the gridded dataset and national averages for each country. Cross-validation was performed at a station level, and the results can be examined in the paper by Harris et al. (2020) as a guide to the accuracy of the interpolation.
The overall process is always being refined and improved, an approach made possible by NCAS funding as part of the NCAS Long-Term Global Change theme.
Information about the technical and scientific quality
CRU TS shows a broad range of outcomes but is dominated by positive cross-validation correlations (95% are >=0.38). Larger errors are found in dry regions with Canada being positively validated. Differences in precipitation when compared to the GPCC dataset are small for the northern Hemisphere (Harris et al., 2020)
Limitations and strengths for application in North Canada
CRU TS compiles station data of multiple variables from numerous data sources into a consistent format. The station data are also used to compute secondary variables such as potential evapotranspiration, diurnal temperature range, and number of frost and rain days. Although many of the input data were homogenized, the data set is not strictly homogenous. Derived trends should be used with caution.
References to documents describing the methodology or/and the dataset
Harris, I., T.J. Osborn, P. Jones, and D. Lister, 2020: Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset. Scientific data, 7(1), 1-18 , https://doi.org/10.1038/s41597-020-0453-3
Link to download the data and format of data:
The data are available in two formats: NetCDF, and space-separated ASCII text.
Data can be accessed via the CEDA Archive: https://archive.ceda.ac.uk/
Version 4.05. is available at: https://catalogue.ceda.ac.uk/uuid/c26a65020a5e4b80b20018f148556681
Publications including dataset evaluation or comparison with other data in northern Canada
Rapaić, M., R. Brown, M. Markovic, and D. Chaumont, 2015: An Evaluation of Temperature and Precipitation Surface-Based and Reanalysis Datasets for the Canadian Arctic, 1950–2010, Atmosphere-Ocean, 53:3, 283-303, https://doi.org/10.1080/07055900.2015.1045825
Lindsay, R., M. Wensnahan, A. Schweiger, and J. Zhang, 2014: Evaluation of Seven Different Atmospheric Reanalysis Products in the Arctic, Journal of Climate, 27(7), 2588-2606. Retrieved Nov 1, 2021, from https://journals.ametsoc.org/view/journals/clim/27/7/jcli-d-13-00014.1.xml (Previous version of CRU)