CRU TS

CRU TS
Name	CRU TS
Producer	Climatic Research Unit
Country	United Kingdom
Discipline	Climate science
Start date	1901
Temporal resolution	Monthly
Spatial resolution	0.5° latitude/longitude
Format	Gridded time series

CRU TS CRU TS is a gridded climate dataset produced by the Climatic Research Unit that provides long-term monthly time series of land-surface climate variables. It is widely used by researchers at institutions such as University of East Anglia, Met Office, National Aeronautics and Space Administration, National Oceanic and Atmospheric Administration, and Intergovernmental Panel on Climate Change for climate analysis, impact assessment, and model evaluation.

Overview

CRU TS covers multi-decadal records useful for studies involving Hadley Centre, European Centre for Medium-Range Weather Forecasts, World Meteorological Organization, United Nations Environment Programme, and International Energy Agency stakeholders. The dataset is structured to support comparisons with outputs from centers like NASA Goddard Institute for Space Studies, NOAA Geophysical Fluid Dynamics Laboratory, Max Planck Institute for Meteorology, National Center for Atmospheric Research, and Commonwealth Scientific and Industrial Research Organisation. CRU TS informs reports by entities such as Royal Society, American Meteorological Society, European Commission, and Food and Agriculture Organization of the United Nations.

Data Contents and Variables

CRU TS provides monthly grids of variables including near-surface temperature, precipitation, diurnal temperature range, and cloud cover relevant to analyses by Princeton University, Columbia University, Massachusetts Institute of Technology, California Institute of Technology, and University of Oxford. Specific variables align with parameters used in studies at Stanford University, Yale University, Harvard University, Imperial College London, and Potsdam Institute for Climate Impact Research. The dataset includes metadata conventions familiar to teams at European Space Agency, Japan Meteorological Agency, China Meteorological Administration, Indian Institute of Tropical Meteorology, and Australian Bureau of Meteorology.

Development and Methodology

Development of the dataset involved station data collated from national services like Met Éireann, Météo-France, Deutscher Wetterdienst, Servicio Meteorológico Nacional (Argentina), and Instituto Nacional de Meteorología e Hidrología (Venezuela). Statistical methods incorporate approaches similar to those used by groups at University of Washington, University of Cambridge, University of Leeds, University of Manchester, and University of Bristol. Quality control and homogenization draw on techniques referenced in publications from Scripps Institution of Oceanography, Georgetown University, University of Chicago, University of Tokyo, and Seoul National University. Comparisons and cross-validation have been conducted against reanalyses and products from ECMWF Reanalysis, NCEP/NCAR Reanalysis, ERA5, JRA-55, and MERRA teams.

Applications and Use Cases

CRU TS underpins impact studies in sectors overseen by World Health Organization, World Bank, Asian Development Bank, Inter-American Development Bank, and European Investment Bank. It is used in agricultural assessments by CIMMYT, CGIAR, International Maize and Wheat Improvement Center, International Rice Research Institute, and Food and Agriculture Organization of the United Nations programs. Hydrological modeling efforts at US Geological Survey, British Geological Survey, German Federal Institute of Hydrology, Chinese Academy of Sciences, and Norwegian Water Resources and Energy Directorate rely on CRU TS inputs. Urban climate and infrastructure analyses by UN-Habitat, City of London Corporation, Greater London Authority, New York City Department of Buildings, and Tokyo Metropolitan Government have incorporated the dataset. Energy-sector modeling at Shell plc, BP, Siemens, General Electric, Iberdrola and climate risk assessments by firms such as Munich Re, Swiss Re, Allianz, Willis Towers Watson, and Aon also use the data.

Limitations and Uncertainties

Users should consider limitations documented by researchers at Princeton and Columbia, including station density issues noted for regions monitored by National Institute of Meteorology (Brazil), Kenya Meteorological Department, Ethiopian National Meteorological Agency, and Pakistan Meteorological Department. Uncertainties arise in comparisons with satellite-derived products from MODIS, TRMM, GPM, Landsat, and Sentinel missions, and with paleoclimate reconstructions by groups at University of Bern, Lamont–Doherty Earth Observatory, Swiss Federal Institute for Forest, Snow and Landscape Research, and GFZ German Research Centre for Geosciences. Methodological caveats reflect debates in literature from Nature Climate Change, Science Advances, Journal of Climate, Geophysical Research Letters, and Climate Dynamics authors affiliated with ETH Zurich, University College London, Duke University, and McGill University.

Access and Licensing

CRU TS is distributed under terms coordinated by University of East Anglia and linked with data portals used by UK Research and Innovation, Copernicus Programme, Global Change Data Lab, PANGAEA Data Publisher, and World Data Center infrastructures. Access routes are similar to those provided by DataCite, Zenodo, Dryad, Figshare, and national archives like UK Data Service and National Centers for Environmental Information. Licensing considerations have been discussed in forums involving Creative Commons, European Open Science Cloud, Open Data Institute, Research Councils UK, and Organisation for Economic Co-operation and Development.

Category:Climate datasets