Space‐time variability of the rainfall over the western Mediterranean region: A statistical analysis

Abstract

[1] This study aims at better understanding the space-time statistical properties of rain over a Mediterranean region. To this end we analyzed temporal, spatial, and spatio-temporal spectra of rain field maps provided by an X-band radar situated in the southeast part of France. The database extends from 2009 to 2012 and has a spatial and temporal resolution of 1 km 2 and 5 min. The analysis highlights several scaling regimes, which are interpreted in terms of meteorological structures (convective cells, mesoscale structures, and midlatitude cyclones). The analysis of spectra per month confirms the dependency of the spectral signature to the underlying meteorological process. Nevertheless, our results also reveal that for a given range of scales (20-45 min in time and 7-20 km in space), spectral slope is monthly invariant. It means that rain behaves identically, in terms of scaling, whatever the mechanism that generated it (convection, front). Moreover, spectral analysis shows that the temporal decorrelation scale is 10 days, which can possibly be related to the longest lifetime of a meteorological phenomenon in the region (i.e., about 10 days). An approach to compute the scaling anisotropy between space and time is proposed. It reveals that, over two distinct ranges of scales (7-20 km/20-45 min and 20-70 km/45 min-3 h), the scaling anisotropic coefficient is equal to 2. It also reveals that the ratio of spectral slope of 2-D angle averaged spatial spectrum versus 1-D temporal spectrum is equal to 1 over these ranges of scales. It suggests a similarity in the second-order properties (e.g., correlation) of temporal and spatial rain field. All these results are important to better understand rainfall statistical behavior and could also be used for the development of downscaling schemes and the validation of numerical weather models.

10th European Conference on Radar in Meteorology and Hydrology (ERAD 2018) : 1-6 July 2018, Ede-Wageningen, The Netherlands

“…This could be explained by the fact that the average wind speeds during the events was around 11 km/h which may explain why the air mass scanned by the RHI scans up to a distance of 10 km from the radar was identical to the air mass scanned above the radar within the hour. This result is also comparable to the findings from a study by Rysman et al (2013) for summer precipitation in the Mediterranean region. They reported similar spectral slopes for the 20-45 minutes temporal range and the 7-20 km spatial range.…”

“…A comparison of the spatial and temporal components of the two campaigns is given in Figure 5. Overall, the temporal data has slightly lower values, which may be attributed to small discontinuities in rainfall in the temporal data which have the effect of diminishing the spectral slope and as such also the fractions of variance explained by the larger scale components (De Montera et al, 2009;Rysman et al, 2013;Verrier et al, 2011). Nevertheless, for the Payerne case the variability observed at the hourly time scale is very similar to the variability at the 20 to 15 kilometres scale.…”

Estimating chemical composition of atmospheric deposition fluxes from mineral insoluble particles deposition collected in the western Mediterranean region

“…After 30 min of contact time and automatic shaking, we reproduced the CARAGA sampling of wet deposition through filters and collected the filtrated solution. The time of 30 min corresponds to the most prevalent average time of rainfall in the western Mediterranean Basin (Rysman et al, 2013). A day (24 h) later, we rinsed the filter holder using 100 ± 5 mL of ultrapure water to simulate the rinsing step of the CARAGA protocol.…”

Characterization of vertical cloud variability over Europe using spatial lidar observations and regional simulation

“…In summer, the variability is strongly 532 modulated by local events (storms and mesoscale convective systems). These events, occurring typically at 533 spatial scales ranging between 10 km to 100 km during less than 3 hours (Rysman et al 2013), are more easily 534 missed by CALIPSO considering its undersampling. It generates significant differences of variability between 535 the two samplings (Fig.…”