Hydrometeorological analysis and forecasting of a 3-day flash-flood-triggering desert rainstorm

Abstract

<jats:p>Abstract. Flash floods are among the most devastating and lethal natural hazards. In 2018, three flash-flood episodes resulted in 46 casualties in the deserts of Israel and Jordan alone. This paper presents the hydrometeorological analysis and forecasting of a substantial storm (25–27 Apr 2018) that hit an arid desert basin (Zin, ~ 1400 km2, southern Israel), claiming 12 human lives. Our aim was to: (a) spatially assess the severity of the storm, (b) quantify the time scale of the hydrological response, and (c) evaluate the available operational precipitation forecasting. Return periods of the storm's maximal rain intensities were derived locally, at 1-km2 resolution, using weather radar data and a novel statistical methodology. A high-resolution grid-based hydrological model was used to study the intra-basin flash-flood magnitudes, which were consistent with direct information from witnesses. The model was further used to examine the hydrological response to different forecast scenarios. A small portion of the basin (1–20 %) experienced extreme precipitation intensities (75- to 100-year return period), resulting in a local hydrological response of a high magnitude (10- to 50-year return period). Hillslope runoff, initiated minutes after the intense rainfall occurred, reached the streams and resulted in peak discharge within tens of minutes. Available deterministic operational precipitation forecasts poorly predicted the hydrological response in the studied basins (tens to hundreds of km2) mostly due to location inaccuracy. There was no gain from assimilating radar estimates in the numerical weather-prediction model. Therefore, we suggest using deterministic forecasts with caution as it might lead to fatal decision making. To cope with such errors a novel cost-effective methodology is applied by spatially shifting the forecasted precipitation fields. In this way, flash-flood occurrences were captured in most of the sub-basins, resulting in few false alarms. </jats:p>

Toward Narrowing Uncertainty in Future Projections of Local Extreme Precipitation

“…Along the coast and in the southern desert, the negative sensitivity to changes in the median intensity (Figures and ) dominates, and the rarest extremes are projected to increase, consistently with Figure 2f. These results imply two adverse effects: (i) amplified water scarcity and reduced flood and landslide risks in most of the region (Alpert et al., 2002; Peleg et al., 2015; Samuels et al., 2009) and (ii) increased intensity of the most severe events along the coast and southern deserts, associated with augmented risk of extreme pluvial flooding in coastal cities, and of flash floods, debris flows and geomorphic responses in the southern deserts (Rinat et al., 2020; Shmilovitz et al., 2020).…”

Coastal and orographic effects on extreme precipitation revealed by weather radar observations

“…Local precipitation climatology emerges from the interaction between weather systems and local terrain features. For instance, mountains constrain the flow of air masses in-F. Marra et al: Coastal and orographic effects on extreme precipitation ducing vertical motions which affect precipitation (Haiden et al, 1992;Houze et al, 2001;Roe, 2005). Similarly, sealand interfaces and lakes may alter the precipitation characteristics due to the interaction of synoptic-scale winds with mesoscale features such as the sea/land breeze, the frictionalinduced convergence associated with deceleration of wind speeds when air is blowing from sea inland, and the contribution of the coastal shape to convergence, with effects which can propagate far inland (Bergeron, 1949;Neumann, 1951;Bummer et al, 1995;Niziol et al, 1995;Colle and Yuter, 2007;Heiblum et al, 2011;Warner et al, 2012;Li and Carbone, 2015;Minder et al, 2015).…”

“…Recent advances in the statistical description of extreme precipitation showed promising advantages over traditional approaches in estimating design precipitation intensities in the presence of problems typical of radar monitoring, such as short data records and measurement errors (Marani and Ignaccolo, 2015;Zorzetto et al, 2016;. These novel methods were tested on satellite data with encouraging results Marani, 2019, 2020;Hu et al, 2020;Mekonnen et al, 2021), but, to the best of our knowledge, no weather radar application is available so far, with the exception of a single storm study case (Rinat et al, 2021).…”

Response to reviewer 2

“…* Thank you for your suggestion, we will add that and make sure to clarify the ending of the sentence. P4,L20: Please note that some studies typify extremes from spatial measurements based on a large enough amount of pixel passing a threshold (Armon et al, 2020), or based on spatialIDF curves (Rinat et al, 2020).…”