Author:

Andersson, A.

Additional authors:

M. Ziese, F. Dietzsch, M. Schröder, A. Becker, and K. Schamm

DOI:

See Description for DOI of different resolutions of the product

Description:

Citation

For 0.5° grid resolution:
Andersson, Axel; Ziese, Markus; Dietzsch, Felix; Schröder, Marc; Becker, Andreas; Schamm, Kirstin (2016): HOAPS/GPCC European daily precipitation data record with uncertainty estimates using satellite and gauge based observations at 0.5°, dx.doi.org/10.5676/DWD_CDC/HOGP_050/V002  

For 1.0° grid resolution:
Andersson, Axel; Ziese, Markus; Dietzsch, Felix; Schröder, Marc; Becker, Andreas; Schamm, Kirstin (2016): HOAPS/GPCC global daily precipitation data record with uncertainty estimates using satellite and gauge based observations at 1.0°, dx.doi.org/10.5676/DWD_CDC/HOGP_100/V002 

For 2.5° grid resolution:
Andersson, Axel; Ziese, Markus; Dietzsch, Felix; Schröder, Marc; Becker, Andreas; Schamm, Kirstin (2016): HOAPS/GPCC global daily precipitation data record with uncertainty estimates using satellite and gauge based observations at 2.5°, dx.doi.org/10.5676/DWD_CDC/HOGP_250/V002 

Summary

This dataset contains global precipitation observations combined from satellite and rain gauge data over ocean and over land, respectively. It spans the years 1988-2008 and has a spatial resolution of 2.5°×2.5°. Satellite observations are based on SSM/I data of the HOAPS-3.2 dataset of CM SAF (DOI:  10.5676/EUM_SAF_CM/HOAPS/V001 ). These data have been extended with observations from the TMI microwave imager platform. The basic rain rate retrieval is based on a neuronal network approach. The retrieval excludes sea-ice covered regions. Uncertainty estimations are given as standard deviation of pixel values in one grid cells. Precipitation observations over land are included from the GPCC Full Data Daily product (DOI:  10.5676/DWD_GPCC/FD_D_V1_100 ). Relative precipitation anomalies at the stations are interpolated by means of ordinary block kriging. For these data, uncertainty information is included as well. On coastal edges data gaps are interpolated. This dataset is recommended to be used for analyses of extreme events and related statistics at daily resolution as well as for verification and validation purposes of other precipitation products or climate models.
This dataset was created within the DAPACLIP project (Daily Precipitation Analysis for Climate Prediction). The DAPACLIP project was part of the MiKlip project framework (Mittelfristige Klimaprognosen) and funded by the German Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung, BMBF).

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