GSB 7.1 Standardlösung

Global precipitation product

A global precipitation product is a major building block of the CM SAF vision to enable climate monitoring of the energy and water cycle. Thus far, CM SAF provided a precipitation product over the ice-free ocean (HOAPS, see below) only. Consequently a TCDR global precipitation product is under development within CM SAF’s CDOP 3 phase and consists in 1°x1° daily accumulated rainfall estimates as well as associated uncertainty information over the globe for the period 2002-2019.

GIRAFE_Comparison_MonthlyMean_FullConstellation GIRAFE GIRAFE_Comparison_MonthlyMean_FullConstellation

The accumulated precipitation is the product of the conditional rain rate, the precipitation fraction and the duration of the day. Poleward of 55°N and S both the rain fraction and the conditional rain rate are computed using the microwave imagers and sounders Level 2 rain products. Over a transition zone, these data are blended with the GEO IR/MW merged rainfall estimates. Indeed, from 55°S to 55°N, the algorithm consists in using the microwave imagers and sounders instantaneous observations collocated with infrared geostationary observations trained for rain detection. The daily accumulation is then built using the trained full geostationary data record derived rain fraction and the microwave based mean rain rate.

The uncertainty estimate comes in the form of a standard error and depends on the standard deviation, scaled by the number of independent observations obtained from variogram computations (Roca et al., 2010). This term of the daily accumulation error budget corresponds to the sampling uncertainty and is completed by a IR-MW data fusion uncertainty estimate and an algorithm uncertainty propagated from the level 2 instantaneous rain rates (Chambon et al., 2012).

The final step of the product realization is the application of a bias correction scheme. This ensures some consistency between the satellite derived products mentioned above with respect to selected other products. This step is often, although improperly, called the calibration step.

The TCDR global precipitation product will be released in 2021.

Precipitation from HOAPS (ice-free ocean)

The Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite data record (HOAPS) is a completely satellite based climatology of various parameters, among them precipitation, over the global ice free oceans. The product is derived from recalibrated and intercalibrated measurements from SSM/I and SSMIS passive microwave radiometers and utilises the CM SAF SSM/I and SSMIS FCDR. The precipitation retrieval algorithm is described in Andersson et al. (2010). The HOAPS precipitation product has global coverage, i.e., within ±180° longitude and ±80° latitude, is only defined over the ice-free ocean surface and covers the period from July 1987 until December 2014. The product is available as monthly averages and 6-hourly composites on a regular latitude/longitude grid with a spatial resolution of 0.5° x 0.5° degrees. The HOAPS product suite also includes evaporation E and the freshwater budget, i.e., E-P. Further details on the products in general, on retrieval details and physical basis as well as on quality can be found in the Product User Manuals (PUM), the Algorithm theoretical basis Documents (ATBD) and the Validation Report (ValRep). The products can be ordered via the Web User Interface.


  • Andersson, A., Fennig, K., Klepp, C., Bakan, S., Graßl, H., and Schulz, J., 2010: The Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data - HOAPS-3, Earth Syst. Sci. Data, 2, 215-234.
  • Chambon P, Jobard I, Roca R, Viltard N. 2012, An investigation of the error budget of tropical rainfall accumulation derived from merged passive microwave and infrared satellite measurements. Q. J. R. Meteorol. Soc. 138:000.000. DOI:10.1002/qj.1907.
  • Roca R., P Chambon, Jobard I, P-E Kirstetter, M Gosset, JC Bergès, 2010, Comparing Satellite and Surface Rainfall Products over West Africa at Meteorologically Relevant Scales during the AMMA Campaign Using Error Estimates, J. App. Met. Clim. Volume 49, Issue 4 , pp. 715-731.

MS / Aug2018

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