Towards flash-flood prediction in the dry Dead Sea region utilizing radar rainfall information

et al. 2017

Self Cite

Abstract. Intensity-duration-frequency (IDF) curves are widely used to quantify the probability of occurrence of rainfall extremes. The usual rain gauge-based approach provides accurate curves for a specific location, but uncertainties arise when ungauged regions are examined or catchment-scale information is required. Remote sensing rainfall records, e.g. from weather radars and satellites, are recently becoming available, providing high-resolution estimates at regional or even global scales; their uncertainty and implications on water resources applications urge to be investigated. This study compares IDF curves from radar and satellite (CMORPH) estimates over the eastern Mediterranean (covering Mediterranean, semiarid, and arid climates) and quantifies the uncertainty related to their limited record on varying climates. We show that radar identifies thicker-tailed distributions than satellite, in particular for short durations, and that the tail of the distributions depends on the spatial and temporal aggregation scales. The spatial correlation between radar IDF and satellite IDF is as high as 0.7 for 2-5-year return period and decreases with longer return periods, especially for short durations. The uncertainty related to the use of short records is important when the record length is comparable to the return period ( ∼ 50, ∼ 100, and ∼ 150 % for Mediterranean, semiarid, and arid climates, respectively). The agreement between IDF curves derived from different sensors on Mediterranean and, to a good extent, semiarid climates, demonstrates the potential of remote sensing datasets and instils confidence on their quantitative use for ungauged areas of the Earth.

Section: Mediterraneanmentioning

confidence: 99%

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

Marra

Morin

et al. 2017

Self Cite

“…Rainfall occurs from October to May, with no rain during summer (Goldreich, 2003). Intensities and duration of extreme events differ dramatically within the study area, with the relative frequency of high rainfall intensities increasing as the mean annual precipitation decreases (Marra et al, 2017;Marra and Morin, 2015;Morin et al, 2009;Sharon and Kutiel, 1986). Most intense rainfall episodes over the study area, and the EM in general, are associated with the cold fronts of mid-latitude lows: the Cyprus low -a Mediterranean low located around Cyprus, and the Syrian low -a well-developed Mediterranean low located over Syria (Dayan et al, 2015;Dayan and Morin, 2006;Goldreich, 2003;Kahana et al, 2002).…”

Section: Climatementioning

confidence: 99%

Convective rainfall in a dry climate: relations with synoptic systems and flash-flood generation in the Dead Sea region

Belachsen

Marra

et al. 2017

Self Cite

Abstract. Spatiotemporal patterns of rainfall are important characteristics that influence runoff generation and flashflood magnitude and require high-resolution measurements to be adequately represented. This need is further emphasized in arid climates, where rainfall is scarce and highly variable. In this study, 24 years of corrected and gaugeadjusted radar rainfall estimates are used to (i) identify the spatial structure and dynamics of convective rain cells in a dry climate region in the Eastern Mediterranean, (ii) to determine their climatology, and (iii) to understand their relation with the governing synoptic systems and with flashflood generation. Rain cells are extracted using a segmentation method and a tracking algorithm, and are clustered into three synoptic patterns according to atmospheric variables from the ERA-Interim reanalysis. On average, the cells are about 90 km 2 in size, move 13 m s −1 from west to east, and live for 18 min. The Cyprus low accounts for 30 % of the events, the low to the east of the study region for 44 %, and the Active Red Sea Trough for 26 %. The Active Red Sea Trough produces shorter rain events composed of rain cells with higher rain intensities, longer lifetime, smaller area, and lower velocities. The area of rain cells is positively correlated with topographic height. The number of cells is negatively correlated with the distance from the shoreline. Rain-cell intensity is negatively correlated with mean annual precipitation. Flash-flood-related events are dominated by rain cells of large size, low velocity, and long lifetime that move downstream with the main axis of the catchments. These results can be further used for stochastic simulations of convective rain storms and serve as input for hydrological models and for flash-flood nowcasting systems.

“…Data from this radar have been used extensively for climatology and hydrology studies over the last decade (see Karklinsky and Morin, 2006;Morin et al, 2001Morin et al, , 2009Morin and Gabella, 2007;Peleg and Morin, 2012;Rozalis et al, 2010;Yakir and Morin, 2011). The radar is a C-band (5.35 cm wavelength), non-Doppler system with a maximal transmitting power of Table 2.…”

Section: Radar Datamentioning

confidence: 99%

Radar subpixel-scale rainfall variability and uncertainty: lessons learned from observations of a dense rain-gauge network

Ben-Asher

Morin

2013

108

102

Abstract. Runoff and flash flood generation are very sensitive to rainfall's spatial and temporal variability. The increasing use of radar and satellite data in hydrological applications, due to the sparse distribution of rain gauges over most catchments worldwide, requires furthering our knowledge of the uncertainties of these data. In 2011, a new superdense network of rain gauges containing 14 stations, each with two side-by-side gauges, was installed within a 4 km 2 study area near Kibbutz Galed in northern Israel. This network was established for a detailed exploration of the uncertainties and errors regarding rainfall variability within a common pixel size of data obtained from remote sensing systems for timescales of 1 min to daily. In this paper, we present the analysis of the first year's record collected from this network and from the Shacham weather radar, located 63 km from the study area. The gauge-rainfall spatial correlation and uncertainty were examined along with the estimated radar error. The nugget parameter of the inter-gauge rainfall correlations was high (0.92 on the 1 min scale) and increased as the timescale increased. The variance reduction factor (VRF), representing the uncertainty from averaging a number of rain stations per pixel, ranged from 1.6 % for the 1 min timescale to 0.07 % for the daily scale. It was also found that at least three rain stations are needed to adequately represent the rainfall (VRF < 5 %) on a typical radar pixel scale. The difference between radar and rain gauge rainfall was mainly attributed to radar estimation errors, while the gauge sampling error contributed up to 20 % to the total difference. The ratio of radar rainfall to gauge-areal-averaged rainfall, expressed by the error distribution scatter parameter, decreased from 5.27 dB for 3 min timescale to 3.21 dB for the daily scale. The analysis of the radar errors and uncertainties suggest that a temporal scale of at least 10 min should be used for hydrological applications of the radar data. Rainfall measurements collected with this dense rain gauge network will be used for further examination of small-scale rainfall's spatial and temporal variability in the coming years.