Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 5.153
IF 5-year value: 5.460
IF 5-year
CiteScore value: 7.8
SNIP value: 1.623
IPP value: 4.91
SJR value: 2.092
Scimago H <br class='widget-line-break'>index value: 123
Scimago H
h5-index value: 65
Volume 14, issue 1
Hydrol. Earth Syst. Sci., 14, 129–139, 2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 14, 129–139, 2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.

  21 Jan 2010

21 Jan 2010

Characteristics of 2-D convective structures in Catalonia (NE Spain): an analysis using radar data and GIS

M. Barnolas1,2, T. Rigo2, and M. C. Llasat1 M. Barnolas et al.
  • 1GAMA Team, Dept. of Astronomy and Meteorology, Univ. of Barcelona, Avda. Diagonal, 647, 08028 Barcelona, Spain
  • 2Servei Meteorològic de Catalunya, Barcelona, Spain

Abstract. Flood simulation studies use spatial-temporal rainfall data input into distributed hydrological models. A correct description of rainfall in space and in time contributes to improvements on hydrological modelling and design. This work is focused on the analysis of 2-D convective structures (rain cells), whose contribution is especially significant in most flood events. The objective of this paper is to provide statistical descriptors and distribution functions for convective structure characteristics of precipitation systems producing floods in Catalonia (NE Spain). To achieve this purpose heavy rainfall events recorded between 1996 and 2000 have been analysed. By means of weather radar, and applying 2-D radar algorithms a distinction between convective and stratiform precipitation is made. These data are introduced and analyzed with a GIS. In a first step different groups of connected pixels with convective precipitation are identified. Only convective structures with an area greater than 32 km2 are selected. Then, geometric characteristics (area, perimeter, orientation and dimensions of the ellipse), and rainfall statistics (maximum, mean, minimum, range, standard deviation, and sum) of these structures are obtained and stored in a database. Finally, descriptive statistics for selected characteristics are calculated and statistical distributions are fitted to the observed frequency distributions. Statistical analyses reveal that the Generalized Pareto distribution for the area and the Generalized Extreme Value distribution for the perimeter, dimensions, orientation and mean areal precipitation are the statistical distributions that best fit the observed ones of these parameters. The statistical descriptors and the probability distribution functions obtained are of direct use as an input in spatial rainfall generators.

Publications Copernicus