De la méso-échelle à la micro-échelle : désagrégation spatio-temporelle multifractale des précipitations

We present a study performed in the framework of the EDF project on the use of seasonal meteorological forecasts to improve hydro-electrical resources management. Due to the difference of space and time scales, it is indispensable to downscale the (meso-scale) GCM rainfall to the (micro-) scale of the hydrological models. To preserve the scaling properties of the rainfall field, as well as its close interrelation with the dynamics at all scales, we develop a multifractal downscaling algorithm based on the idea that the rain rate cascades from large to small scale in a multiplicative manner: a scale invariant random multiplicative increment determines the rate fraction forwarded from a parent structure to a child one. Firstly, we proceeded to a rather exhaustive space and time analysis of the Météo-France PRECIP data base (about 10 years of high resolution data for 243 rain gages distributed over France territory) in order to estimate the universal multifractal parameters α, C1 as well as the exponent Ht of the scaling anisotropy of time versus space. The latter was empirically estimated to be in full agreement with its theoretical value: Ht=1/3. Secondly, we develop a cascade model defined with these parameters from space-time pixels corresponding to 243km×243km×32days, close to those of the GCM, which are of the order of 250km×250km×30 days, i.e. 35km×35km×25days. This choice is done in agreement with the value of Ht. In conclusion, we discuss how to take into account the orographic effects.Le passage de la méso-échelle, échelle des modèles de circulation générale GCM, de l'anglais "General Circulation Models", à la micro-échelle (échelle hydrologique), pour les précipitations, est un exercice assez complexe. Les champs de précipitations comme la plupart des champs géophysiques turbulents obéissent au concept d'invariance d'échelle, qui est une caractéristique principale des champs multifractals. Par ailleurs, il a été prouvé que le transfert d'énergie des grosses structures aux plus petites structures au sein d'un phénomène géophysique turbulent s'effectue de façon multiplicative (Kolmogorov, 1962; Mandelbrot, 1974 ...): un facteur aléatoire déterminant la fraction de flux transmis d'un gros tourbillon à un plus petit. Le travail que nous présentons ici s'inscrit dans le cadre du projet EDF "Prévisions saisonnières et Hydraulicité" dans la gestion de son parc hydroélectrique et a pour objectif la construction d'un modèle de désagrégation basé sur le principe d'invariance d'échelle des champs de précipitation, donc utilisant les propriétés des champs géophysiques mentionnées ci-dessus. Dans un premier temps, nous conduisons une analyse multifractale (Schertzer et Lovejoy , 1991) sur des séries pluviométriques de la France (243 séries pluviométriques au pas de temps de six minutes, constituées sur une dizaine d'années distribuées sur la France métropolitaine), ce qui nous permet de déduire les paramètres multifractals, dans le temps, dans l'espace ou dans le cas spatio-temporel. La seconde étape consiste à construire des cascades multifractales, à partir des valeurs saisonnières de pluies avec les paramètres déterminés dans la première étape. Le principe de cette deuxième partie consiste, à partir d'une prévision mensuelle sur des mailles de dimensions 243km×243km×32jours (correspondant à une anisotropie espace-temps de l'ordre de H=2/3 :x=y=t (3/2) ) voisines de celles des modèles de circulation générale (dimensions de l'ordre de 250km×250km×30jours) et à conduire la cascade multifractale, avec les paramètres multifractals préalablement déterminés, pour atteindre des valeurs de prévision sur des mailles de l'ordre de 1km×1km×1j. Les résultats obtenus devront faire l'objet d'un conditionnement orographique avant d'être comparés avec les valeurs réelles obtenues

De la méso-échelle à la micro-échelle (désagrégation spatio-temporelle multifractale des précipitations)

PARIS-MINES ParisTech (751062310) / SudocPARIS-BIUSJ-Sci.Terre recherche (751052114) / SudocSudocFranceF

Multifractal analysis of the evolution of simulated precipitation over France in a climate scenario

National audienceMultifractal techniques are applied to the study of rainfall daily time series over France simulated by the climate model CNRM-CM3 of Meteo France in a coupled climate scenario A2 over the period 1860-2100. We quantify the scaling variability of the simulated rainfall with the help of a few relevant multifractal exponents characterizing the intermittency and multifractality of the field. These multifractal exponents are determined by the Double Trace Moment (DTM), which shows a scaling range from one day to about 16 days. The opposite trends found in the evolution of the intermittency and multifractality exponents have contradictory effects on the evolution of the extremes. However, a refined analysis shows that due to the dominant effect of intermittency increase, we may expect an effective increase of rainfall extremes for the next hundred years

Statistical Analysis of Recent and Future Rainfall and Temperature Variability in the Mono River Watershed (Benin, Togo)

This paper assessed the current and mid-century trends in rainfall and temperature over the Mono River watershed. It considered observation data for the period 1981–2010 and projection data from the regional climate model (RCM), REMO, for the period 2018–2050 under emission scenarios RCP4.5 and RCP8.5. Rainfall data were interpolated using ordinary kriging. Mann-Kendall, Pettitt and Standardized Normal Homogeneity (SNH) tests were used for trends and break-points detection. Rainfall interannual variability analysis was based on standardized precipitation index (SPI), whereas anomalies indices were considered for temperature. Results revealed that on an annual scale and all over the watershed, temperature and rainfall showed an increasing trend during the observation period. By 2050, both scenarios projected an increase in temperature compared to the baseline period 1981–2010, whereas annual rainfall will be characterized by high variabilities. Rainfall seasonal cycle is expected to change in the watershed: In the south, the second rainfall peak, which usually occurs in September, will be extended to October with a higher value. In the central and northern parts, rainfall regime is projected to be characterized by late onsets, a peak in September and lower precipitation until June and higher thereafter. The highest increase and decrease in monthly precipitation are expected in the northern part of the watershed. Therefore, identifying relevant adaptation strategies is recommended

Climate Variability and Groundwater Response: A Case Study in Burkina Faso (West Africa)

West Africa experiences great climate variability, as shown by the long-lasting drought since the 1970s. The impacts of the drought on surface water resources are well documented but remain less studied regarding groundwater resources. The nexus between climate variability and groundwater level fluctuations is poorly documented in this area. The present study focuses on the large reserve of groundwater held by the Kou catchment, a tributary of Mouhoun river (formerly the Black Volta) in the southwest of Burkina Faso, in the Sudanian region. Analyses were undertaken using climatic time series (1961–2014), two rivers’ hydrometric data (1961–2014), and 21 piezometers’ time series (1995–2014) applying statistical trend (Mann–Kendall) and break (Pettitt) tests, correlation analysis, and principal component analysis. The analyses showed that rainfall in the area underwent a significant break in 1970 with an 11%–16% deficit between the period before the break and the period after the break that resulted in a deficit three times greater for both surface and base flows. This significant deficit in flow results from the combined effect of a decrease in rainfall and an increase in evapotranspiration. The response of the catchment to the slight increase in rainfall after 1990 was highly dependent on hydrological processes. At Samendéni, on the Mouhoun River, the flow increased with a slight delay as compared to rainfall, because of the slow response of the base flow. Whereas at Nasso on the Kou river, the flow steadily decreased. The analysis showed that the groundwater level responds to rainfall with a delay. Its response time to seasonal fluctuations ranges from 1 to 4 months and its response time to interannual variations exceeds the timescale of one year. This response is highly dependent on the local aquifer’s physical characteristics, which could explain the spatial heterogeneity of the groundwater response