Abstract
Abstract. Heavy precipitation events (HPEs) can lead to natural hazards (e.g. floods and debris flows) and contribute to water resources. Spatiotemporal rainfall patterns govern the hydrological, geomorphological, and societal effects of HPEs. Thus, a correct characterisation and prediction of rainfall patterns is crucial for coping with these events. Information from rain gauges is generally limited due to the sparseness of the networks, especially in the presence of sharp climatic gradients. Forecasting HPEs depends on the ability of weather models to generate credible rainfall patterns. This paper characterises rainfall patterns during HPEs based on high-resolution weather radar data and evaluates the performance of a high-resolution, convection-permitting Weather Research and Forecasting (WRF) model in simulating these patterns. We identified 41 HPEs in the eastern Mediterranean from a 24-year radar record using local thresholds based on quantiles for different durations, classified these events into two synoptic systems, and ran model simulations for them. For most durations, HPEs near the coastline were characterised by the highest rain intensities; however, for short durations, the highest rain intensities were found for the inland desert. During the rainy season, the rain field's centre of mass progresses from the sea inland. Rainfall during HPEs is highly localised in both space (less than a 10 km decorrelation distance) and time (less than 5 min). WRF model simulations were accurate in generating the structure and location of the rain fields in 39 out of 41 HPEs. However, they showed a positive bias relative to the radar estimates and exhibited errors in the spatial location of the heaviest precipitation. Our results indicate that convection-permitting model outputs can provide reliable climatological analyses of heavy precipitation patterns; conversely, flood forecasting requires the use of ensemble simulations to overcome the spatial location errors.
Highlights
Heavy precipitation events (HPEs) cause natural hazards such as flash, riverine, and urban floods as well as landslides and debris flows; they serve as a resource for recharging groundwater and surface water reservoirs (e.g. Bogaard and Greco, 2016; Borga et al, 2014; Borga and Morin, 2014; Doswell et al, 1996; Nasta et al, 2018; RavehRubin and Wernli, 2015; Samuels et al, 2009; Taylor et al, 2013; UN-Habitat, 2011)
This resembles the observed pattern of high rain intensities near the coast, rather than inland (Karklinsky and Morin, 2006; Peleg and Morin, 2012; Sharon and Kutiel, 1986), which has been reported for extreme precipitation quantiles observed from both weather radar and satellite sensors (Marra et al, 2017)
The reported higher extreme rain amounts for shorter durations are in agreement with previous studies, which showed that highly localised convective rainfall is more common during HPEs in the desert than in other climatic environments in the EM (Marra et al, 2017; Marra and Morin, 2015; Sharon, 1972)
Summary
Heavy precipitation events (HPEs) cause natural hazards such as flash, riverine, and urban floods as well as landslides and debris flows; they serve as a resource for recharging groundwater and surface water reservoirs (e.g. Bogaard and Greco, 2016; Borga et al, 2014; Borga and Morin, 2014; Doswell et al, 1996; Nasta et al, 2018; RavehRubin and Wernli, 2015; Samuels et al, 2009; Taylor et al, 2013; UN-Habitat, 2011). Heavy precipitation events (HPEs) cause natural hazards such as flash, riverine, and urban floods as well as landslides and debris flows; they serve as a resource for recharging groundwater and surface water reservoirs Diverse rainfall patterns during HPEs cause different hydrological responses; an accurate representation of rainfall patterns during these events is crucial for detecting and predicting climate-change-induced precipitation changes (Maraun et al, 2010; Trenberth et al, 2003). Bloschl and Sivapalan, 1995; Cristiano et al, 2017). Highresolution observation and HPE forecasts remain a challenge (Borga et al, 2011; Collier, 2007; Doswell et al, 1996)
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