Released
Dataset

EartH2Observe, WFDEI and ERA-Interim data Merged and Bias-corrected for ISIMIP (EWEMBI)

Cite as:

Lange, Stefan (2016): EartH2Observe, WFDEI and ERA-Interim data Merged and Bias-corrected for ISIMIP (EWEMBI). GFZ Data Services. http://doi.org/10.5880/pik.2016.004

Status

I   N       R   E   V   I   E   W : Lange, Stefan (2016): EartH2Observe, WFDEI and ERA-Interim data Merged and Bias-corrected for ISIMIP (EWEMBI). GFZ Data Services. http://doi.org/10.5880/pik.2016.004

Abstract

The EWEMBI dataset was compiled to support the bias correction of climate input data for the impact assessments carried out in phase 2b of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b; Frieler et al., 2017), which will contribute to the 2018 IPCC special report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways.

The EWEMBI data cover the entire globe at 0.5° horizontal and daily temporal resolution from 1979 to 2013. Data sources of EWEMBI are ERA-Interim reanalysis data (ERAI; Dee et al., 2011), WATCH forcing data methodology applied to ERA-Interim reanalysis data (WFDEI; Weedon et al., 2014), eartH2Observe forcing data (E2OBS; Calton et al., 2016) and NASA/GEWEX Surface Radiation Budget data (SRB; Stackhouse Jr. et al., 2011). The SRB data were used to bias-correct E2OBS shortwave and longwave radiation (Lange, 2018).

Variables included in the EWEMBI dataset are Near Surface Relative Humidity, Near Surface Specific Humidity, Precipitation, Snowfall Flux, Surface Air Pressure, Surface Downwelling Longwave Radiation, Surface Downwelling Shortwave Radiation, Near Surface Wind Speed, Near-Surface Air Temperature, Daily Maximum Near Surface Air Temperature, Daily Minimum Near Surface Air Temperature, Eastward Near-Surface Wind and Northward Near-Surface Wind. For data sources, units and short names of all variables see Frieler et al. (2017, Table 1).

Dataset Contact

Contributors

Dutra, Emanuel; Weedon, Graham

Keywords

Meteorological Forcing Data, Bias Correction, Climate Impact Research, ISIMIP

GCMD Science Keywords

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          • nameIdentifier (nameIdentifierScheme=ORCID): 0000-0003-2102-8873
          • affiliation: Potsdam Institute for Climate Impact Research
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        • title (xml:lang=en): EartH2Observe, WFDEI and ERA-Interim data Merged and Bias-corrected for ISIMIP (EWEMBI)
      • publisher: GFZ Data Services
      • publicationYear: 2016
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        • subject: Bias Correction
        • subject: Climate Impact Research
        • subject: ISIMIP
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          • affiliation: Potsdam Institute for Climate Impact Research
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          • affiliation: Potsdam Institute for Climate Impact Research
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          • affiliation: European Centre for Medium-Range Weather Forecasts
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          • affiliation: Met Office
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      • Entry_Title: EartH2Observe, WFDEI and ERA-Interim data Merged and Bias-corrected for ISIMIP (EWEMBI)
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        • Dataset_Creator: Lange, Stefan
        • Dataset_Title: EartH2Observe, WFDEI and ERA-Interim data Merged and Bias-corrected for ISIMIP (EWEMBI)
        • Dataset_Release_Date: 2016
        • Dataset_Release_Place: Potsdam, Germany
        • Dataset_Publisher: GFZ Data Services
        • Online_Resource: http://dx.doi.org/10.5880/pik.2016.004
      • Parameters
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        • Topic: ATMOSPHERE
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      • Parameters
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        • Topic: DATA ANALYSIS AND VISUALIZATION
        • Term: CALIBRATION/VALIDATION
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      • Keyword: Meteorological Forcing Data
      • Keyword: Bias Correction
      • Keyword: Climate Impact Research
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      • Summary
        • Abstract: The EWEMBI dataset was compiled to support the bias correction of climate input data for the impact assessments carried out in phase 2b of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b; Frieler et al., 2017), which will contribute to the 2018 IPCC special report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways. The EWEMBI data cover the entire globe at 0.5° horizontal and daily temporal resolution from 1979 to 2013. Data sources of EWEMBI are ERA-Interim reanalysis data (ERAI; Dee et al., 2011), WATCH forcing data methodology applied to ERA-Interim reanalysis data (WFDEI; Weedon et al., 2014), eartH2Observe forcing data (E2OBS; Calton et al., 2016) and NASA/GEWEX Surface Radiation Budget data (SRB; Stackhouse Jr. et al., 2011). The SRB data were used to bias-correct E2OBS shortwave and longwave radiation (Lange, 2018). Variables included in the EWEMBI dataset are Near Surface Relative Humidity, Near Surface Specific Humidity, Precipitation, Snowfall Flux, Surface Air Pressure, Surface Downwelling Longwave Radiation, Surface Downwelling Shortwave Radiation, Near Surface Wind Speed, Near-Surface Air Temperature, Daily Maximum Near Surface Air Temperature, Daily Minimum Near Surface Air Temperature, Eastward Near-Surface Wind and Northward Near-Surface Wind. For data sources, units and short names of all variables see Frieler et al. (2017, Table 1).
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      • date (dateType=Created): 2016
      • creator
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        • nameIdentifier (nameIdentifierScheme=ORCID): 0000-0003-2102-8873
        • affiliation: Potsdam Institute for Climate Impact Research

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    License: CC BY 4.0