The HadEX-CAM dataset contains four land-based extreme indices (TX90p, TN90p, TX10p, TN10p) for the European region. The original dataset (containing missing values) has been created by the MetOffice by aggregating station data using the Climate Anomaly Method (CAM). The infilled version of this dataset has been created by DKRZ by applying a deep learning (DL) model based on U-Net architecture and trained on CMIP6 data (see https://www.nature.com/articles/s41467-024-53464-2). The original HadEX-CAM dataset is distributed under the Open Government Licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/. The DL-infilled HadEX-CAM dataset is distributed under the Creative Commons Attribution 4.0 International license.
Plésiat, Étienne; Dunn, Robert J. H.; Donat, Markus; Kadow, Christopher (2025). HadEX-CAM dataset: original and deep learning infilled TX90p, TN90p, TX10p, TN10p ETCCDI Indices (CLINT H2020). World Data Center for Climate (WDCC) at DKRZ. https://doi.org/10.26050/WDCC/HadEX-CAM
SQA - Scientific Quality Assurance 'approved by author'
Result Date
2025-06-04
Technical Quality Assurance (TQA)
TQA - Technical Quality Assurance 'approved by WDCC'
Description
1. Number of data sets is correct and > 0: passed; 2. Size of every data set is > 0: passed; 3. The data sets and corresponding metadata are accessible: passed; 4. The data sizes are controlled and correct: passed; 5. The spatial-temporal coverage description (metadata) is consistent to the data: passed; 6. The format is correct: passed; 7. Variable description and data are consistent: passed
Method
WDCC-TQA checklist
Method Description
Checks performed by WDCC. The list of TQA metrics are documented in the 'WDCC User Guide for Data Publication' Chapter 8.1.1
[1] DOIPlésiat, Étienne; Dunn, Robert J. H.; Donat, Markus G.; Kadow, Christopher. (2024). Artificial intelligence reveals past climate extremes by reconstructing historical records. doi:10.1038/s41467-024-53464-2