HR: 0830h
AN: NG51A-0824    [PDF]
TI: Multifractal downscaling of a GCM rainfield
AU: * Biaou, A
EM: Angelbert.Biaou@ensmp.fr
AF: Ecole des Mines de Paris, 35 rue Saint Honor\'{e}, Fontainebleau, 77305 France
AU: Hubert, P
EM: Angelbert.Biaou@ensmp.fr
AF: Ecole des Mines de Paris, 35 rue Saint Honor\'{e}, Fontainebleau, 77305 France
AU: Schertzer, D
EM: Daniel.Schertzer@cereve.enpc.fr
AF: CEREVE Ecole Nationale des Ponts et Chauss‚es, 6-8, avenue Blaise Pascal Cit\'{e} Descartes, Marne-la-vall\'{e}e, 77455Cedex France
AU: Schertzer, D
EM: Daniel.Schertzer@cereve.enpc.fr
AF: M\'{e}t\'{e}o-France, 1 Quai Branly, Paris, 75007 France
AU: Hendrickx, F
EM: Frederic.Hendrickx@edf.fr
AF: EDF Division Recherche et Developpement, 6 Quai Watier, Chatou, 78041Cedex France
AU: Tchiguirinskaia, I
EM: Tchiguir@ccr.jussieu.fr
AF: UMR Sysiphe,Laboratoire de G\'{e}ologie Appliqu\'{e}e Universit\'{e} Pierre et Marie Curie, 4 place Jussieu, Paris, 75252Cedex France
AB: In order to get a more efficient production management of reservoirs, it would be helpful to apply long-term meteorological forecasts to hydrological models. Unfortunately, the explicit scales of present GCM's are quite larger (e.g. 243kmx243kmx32 days) than those of hydrological models (e.g. 1 kmx1kmx1day). Therefore it is indispensable to proceed to a downscaling of the output of the former in order to obtain an input for the latter. In this paper, we present a multifractal downscaling procedure. The site of the study is the area of Doubs river, with the help of a dense local hydrological network, but in order to get a larger spatial scale ratio we extend our multifractal analysis to France, with the help of M\'{e}t\'{e}o-France PRECIP data base. We first argue that it is indispensable to consider a multifractal downscaling procedure in order to respect the scaling properties of the hydro-meteorological fields. We performed time, scale and time-space multifractal analysis of the available data and evaluate the corresponding universal exponents, as well as the anisotropy/dynamical exponent of the time-space generalized scale. We show that these exponents are quite robust. We compare our analysis to similar works, but restricted to the use of Log-Poison cascade and space-time isotropy. We show both theoretically and empirically that these restrictions are untenable, in particular with respect to the extremes. We also show simulations should be done with the help of continuous (in scale) and causal cascade models, not with ad-hoc time-space cascades, and present the corresponding numerical simulations. of space-time downscaling of (meso-scale) GCM data down to (micro-scale) hydrological scales. We greatly acknowledge the financial support from Electricit‚ de France, as well as M‚t‚o-France for providing access to its PRECIP data base.
UR: http://www.multifractal.jussieu.fr
DE: 1800 HYDROLOGY
DE: 3220 Nonlinear dynamics
DE: 3250 Fractals and multifractals
DE: 5445 Meteorology (3346)
SC: Nonlinear Geophysics [NG]
MN: 2003 Fall Meeting