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Volume 12, issue 3 | Copyright

Special issue: Forecast and projection in climate scenario of Mediterranean...

Nat. Hazards Earth Syst. Sci., 12, 785-798, 2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 23 Mar 2012

Research article | 23 Mar 2012

A high resolution climatology of precipitation and deep convection over the Mediterranean region from operational satellite microwave data: development and application to the evaluation of model uncertainties

C. Claud1, B. Alhammoud1, B. M. Funatsu1, C. Lebeaupin Brossier3,1, J.-P. Chaboureau2, K. Béranger3, and P. Drobinski1 C. Claud et al.
  • 1Laboratoire de Météorologie Dynamique/IPSL, CNRS, UMR8539, Ecole Polytechnique, Palaiseau, France
  • 2Laboratoire d'Aérologie, University of Toulouse and CNRS, Toulouse, France
  • 3Ecole Nationale Supérieure de Techniques Avancées (ENSTA) – ParisTech, Unité de Mécanique, Palaiseau, France

Abstract. A new precipitation and convection dataset for the Mediterranean Basin, derived from operational satellite microwave data is documented. The dataset is derived from diagnostics that rely on brightness temperatures measured since 1999 in the water vapour absorption line (183–191 GHz). The dataset consists of twice-daily (a.m. and p.m.) and monthly maps of precipitation and convection occurrences on a 0.2° lat × 0.2° long grid for the area 25°–60° N, 10° W–50° E. The instruments used so far are the AMSU-B sensor on the NOAA-15 to -17 satellites, and the MHS sensor on the NOAA-18 and -19 and METOP-2 satellites, with precipitation and convection available separately for the different sensors. The slightly different radiometric characteristics of MHS compared to AMSU-B do not affect significantly the continuity of the dataset. Precipitation and convection data from different sensors on different satellites are remarkably consistent, with generally small biases between the instruments. When larger biases appear, they can be explained either by the drifts in the satellite orbit, scan asymmetry, or temporal aliasing from insufficiently resolving the diurnal cycle of precipitation and convection. After a description of climatological aspects of rain and deep convection occurrence, the interest of this dataset to evaluate model uncertainties for simulating a high-impact weather event and for climatic regional runs over this area is illustrated.

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