Influence of small scale rainfall variability on standard comparison tools between radar and rain gauge data

Abstract

radar - rain gauge comparison, Universal Multifractals, downscalingInternational audienceRain gauges and weather radars do not measure rainfall at the same scale; roughly 20 cm for the former and 1 km for the latter. This significant scale gap is not taken into account by standard comparison tools (e.g. cumulative depth curves, normalized bias, RMSE) despite the fact that rainfall is recognized to exhibit extreme variability at all scales. In this paper we suggest to revisit the debate of the representativeness of point measurement by explicitly modelling small scale rainfall variability with the help of Universal Multifractals. First the downscaling process is validated with the help of a dense networks of 16 disdrometers (in Lausanne, Switzerland), and one of 16 rain gauges (Bradford, United Kingdom) both located within a 1 km2 area. Second this downscaling process is used to evaluate the impact of small scale (i.e.: sub - radar pixel) rainfall variability on the standard indicators. This is done with rainfall data from the Seine-Saint-Denis County (France). Although not explaining all the observed differences, it appears that this impact is significant which suggests changing some usual practice

Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas – a review

“…Rainfall measurements have to be adjusted based on rain gauges and disdrometers. Various techniques have been studied to calibrate radars (Wood et al, 2000), to combine radar-rainfall measurements with rain gauge data for ground truthing (Cole and Moore, 2008;Smith et al, 2012;Wang et al, 2013;Gires et al, 2014;Nielsen et al, 2014;Wang et al, 2015b) and to define the uncertainty related to radarrainfall estimation (Ciach and Krajewski, 1999;Quirmbach and Schultz, 2016;Villarini et al, 2008;Mandapaka et al, 2009;Peleg et al, 2013;Villarini et al, 2014). These studies show that in most of the cases, radar measurements underestimate the rainfall compared to rain gauge measurements (Smith et al, 2012;Overeem et al, 2009a;Overeem et al, 2009b;van de Beek et al, 2010).…”

“…The variance reduction factor method was introduced for the first time by Rodriguez-Iturbe and Mejıa (1974) and lately applied in various studies (Krajewski et al, 2000;Villarini et al, 2008;Peleg et al, 2013). Gires et al (2014) focused on the gap between rain gauges and radar spatial scale, considering that a rain gauge usually collects rainfall over 20 cm of surface and the spatial resolution of most used radars is of 1 km ×1 km. They evaluate the impact of small-scale rainfall variability using a universal multifractal downscaling method.…”

Intensity–duration–frequency curves from remote sensing rainfall estimates: comparing satellite and weather radar over the eastern Mediterranean

“…The small-scale representativeness of rain gauge measurements makes them not suitable for a large-scale quantitative assessment of remote sensing products (Gires et al, 2014;Peleg et al, 2017b). Here, we take advantage of their long records to empirically quantify the uncertainty in rainfall frequency analysis related to the use of short records in different climatic conditions.…”

“…Radar reproduces better the skewness of the IDF curves and radar IDFs are, with the exception of the arid case, within the rain gauge confidence interval. Note that these results represent the local scale; while interpreting them, one should take into account the different scales of rain gauges (point scale) and remote sensing datasets (∼ 8 × 8 km 2 , in this case) and the natural variability that extreme rainfall presents when relatively short records are used (Gires et al, 2014;Peleg et al, 2017b).…”

Mapping Annual Precipitation across Mainland China in the Period 2001–2010 from TRMM3B43 Product Using Spatial Downscaling Approach

“…In the future, monthly or seasonal precipitation can be estimated using, for instance, the fraction method proposed by Duan and Bastiaanssen [24]. It should be also noted that there is still a scale gap between rain-gauge data and final rainfall product in this study because a rain gauge typically collects rainfall at ground level with a sample area of roughly 50 cm 2 [71]. It is, therefore, suggested that gap be taken into account in future studies, especially at finer time scales.…”