The Climate Change Knowledge Portal provides global data on historical and future climate, vulnerabilities, and impacts.
The data on historical temperature and rainfall data included in this compilation comes from the historical CRU dataset. The CRU TS version 4.04 gridded historical dataset is derived from observational data and provides quality-controlled temperature and rainfall values from thousands of weather stations worldwide, as well as derivative products including monthly climatologies and long-term historical climatologies. The dataset is produced by the Climatic Research Unit (CRU) of the University of East Anglia (UEA) CRU-(Gridded Product).
In order to present historical climate conditions, the World Bank Group's Climate Change Knowledge Portal (CCKP) uses the globally available observational datasets derived from CRU to quantify changes in mean annual temperature and mean annual precipitation for the period 1901-2019 per country.
Dataset type:
Time-Series
Dataset level:
Country
Citation:
When using this dataset, please cite as:
(The World Bank Group,
2021)
(Harris et al.,
2020)
• Harris, I., Osborn, T. J., Jones, P., &
Lister, D. (2020). Version 4 of the CRU TS monthly
high-resolution gridded multivariate climate dataset.
Scientific Data, 7(1), 109. https://doi.org/10.1038/s41597-020-0453-3
@misc{cckp1,
author = {{The World Bank Group}},
note = {Date accessed 2 June 2021},
publisher = {The World Bank Washington DC},
title = {Climate Change Knowledge Portal},
url = {https://climateknowledgeportal.worldbank.org},
year = {2021}
}
@article{cru1,
abstract = {CRU TS (Climatic Research Unit gridded Time Series) is a widely used climate dataset on a 0.5° latitude by 0.5° longitude grid over all land domains of the world except Antarctica. It is derived by the interpolation of monthly climate anomalies from extensive networks of weather station observations. Here we describe the construction of a major new version, CRU TS v4. It is updated to span 1901–2018 by the inclusion of additional station observations, and it will be updated annually. The interpolation process has been changed to use angular-distance weighting (ADW), and the production of secondary variables has been revised to better suit this approach. This implementation of ADW provides improved traceability between each gridded value and the input observations, and allows more informative diagnostics that dataset users can utilise to assess how dataset quality might vary geographically.},
author = {Harris, Ian and Osborn, Timothy J and Jones, Phil and Lister, David},
doi = {10.1038/s41597-020-0453-3},
issn = {2052-4463},
journal = {Scientific Data},
number = {1},
pages = {109},
title = {{Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset}},
url = {https://doi.org/10.1038/s41597-020-0453-3},
volume = {7},
year = {2020}
}