The Effect of Rain–No Rain Intermittency on the Estimation of the Universal Multifractals Model Parameters

Abstract

The multifractal properties of rain are investigated within the framework of universal multifractals. The database used in this study includes measurements performed over several months in different locations by means of a disdrometer, the dual-beam spectropluviometer (DBS). An assessment of the effect of the rain–no rain intermittency shows that the analysis of rain-rate time series may lead to a spurious break in the scaling and to erroneous parameters. The estimation of rain multifractal parameters is, therefore, performed on an event-by-event basis, and they are found to be significantly different from those proposed in scientific literature. In particular, the parameter H, which has often been estimated to be 0, is more likely to be 0.53, thus meaning that rain is a fractionally integrated flux (FIF). Finally, a new model is proposed that simulates high-resolution rain-rate time series based on these new parameters and on a simple threshold.

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

“…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.…”

2DVD Data Revisited: Multifractal Insights into Cuts of the Spatiotemporal Rainfall Process

“…Some authors reported not a single scaling regime but various ones separated by breaks; typically at few minutes and few days in time and few kilometres in space. Various types of data have been used; rain gauges (de Lima and de Lima 2009, de Lima and Grasman 1999, Fraedrich and Larnder 1993, Ladoy et al 1993, Olsson 1995, Tessier et al 1996, disdrometers (de Montera et al 2009, Gires et al 2014, weather radars (Gires et al 2011, Nykanen and Harris 2008, Tessier et al 1993, Verrier et al 2010, satellite with TRMM data ) and even numerical outputs of climate simulations (Royer et al 2008) or meso-scale models (Gires et al 2011). The highest resolutions mentioned before are rather coarse with regards to the mm scale down to which atmospheric turbulence -the embedding field of rainfall -is known to exhibit scaling behaviour (see Anselmet et al 2001 for a review).…”

Nonstationarity in Intermittent Rainfall: The “Dry Drift”

“…Albeit useful, the b model turned out to be too simplistic to fully describe the distribution and the space-time structure of rainfall intermittency (Schmitt et al 1998). Since then, and despite several decades of research and numerous alternatives (e.g., Olsson 1998;Schmitt et al 1998;de Montera et al 2009; Gires et al 2013), the correct representation of intermittency within the multifractal framework still remains an open question.…”