Dataset
GMCP: A Global Multisource Merging-and-Calibration Precipitation Dataset
Abstract
Highly accurate global gridded precipitation datasets for precipitation occurrences and volumes are essential for understanding the water, energy, and carbon cycles on Earth in the context of a changing climate. This study aimed to introduce a new fully global multisource merged precipitation dataset with high quality and resolutions of 1-hourly and 0.1° from 2000 to the present. This dataset integrated the advantages of ground gauge-, satellite-, and model-based precipitation estimates, particularly regarding precipitation occurrence, which can benefit scientific research communities and societal applications worldwide, including hydrological, climatological, meteorological, and water resource management.
Details
| Previous Info: |
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| Access rules: |
Please contact the data centre for details on how to access these data.
For data use licensing information please contact: support@ceda.ac.uk |
| Data lineage: |
The Global Multisource Merged and Calibration Precipitation (GMCP) dataset was generated by integrating gauge-, satellite-, and reanalysis/model-based precipitation estimates through a merging-and-calibration framework. The primary input datasets include ERA5-Land, GSMaP-MVK, and GPM IMERG-Late, which provide complementary information on precipitation occurrence and intensity. The framework combines these datasets to exploit their respective strengths while mitigating individual limitations, with a particular emphasis on improving precipitation occurrence detection. Calibration and quality-control procedures were applied during the merging process to produce a consistent global precipitation product at 0.1° spatial resolution and 1-hourly temporal resolution. The resulting dataset covers the global land surface from 2000 to the present and was generated using standardized processing workflows before being archived at the data centre. |
| Data Quality: |
The quality of the GMCP dataset was assessed through comprehensive validation against independent rain gauge observations and by comparison with existing global precipitation products across multiple spatial and temporal scales. Performance was evaluated using standard statistical metrics, including the correlation coefficient (CC), root-mean-square error (RMSE), and Heidke skill score (HSS), with particular emphasis on precipitation occurrence and intensity. Results demonstrate that GMCP generally outperforms the input datasets (ERA5-Land, GSMaP-MVK, and IMERG-Late) as well as widely used multisource precipitation products, including IMERG-Final, MSWEP V2, and CHIRPS, in representing precipitation variability and occurrence. Validation was conducted over diverse regions, including the contiguous United States and mainland China, indicating that the dataset provides reliable high-resolution global precipitation estimates for hydrological, climatological, meteorological, and water resou
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| File Format: |
Not defined
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Process overview
No variables found.
Temporal Range
2000-01-01T00:00:00
Ongoing
Geographic Extent
90.0000° |
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-180.0000° |
180.0000° |
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-90.0000° |