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.

A modeling framework is formulated and applied to assess the sensitivity of the hydrological regime of two catchments in a convective rainfall environment with respect to projected climate change. The study uses likely rainfall scenarios with high spatiotemporal resolution that are dependent on projected changes in the driving regional meteorological synoptic systems. The framework was applied to a case study in two medium-sized Mediterranean catchments in Israel, affected by convective rainfall, by combining the HiReS-WG rainfall generator and the SAC-SMA hydrological model. The projected climate change impact on the hydrological regime was examined for the RCP4.5 and RCP8.5 emission scenarios, comparing the historical (beginning of the 21st century) and future (mid-21st-century) periods from three general circulation model simulations available from CMIP5. Focusing on changes in the occurrence frequency of regional synoptic systems and their impact on rainfall and streamflow patterns, we find that the mean annual rainfall over the catchments is projected to be reduced by 15% (outer range 2–23%) and 18% (7–25%) for the RCP4.5 sand RCP8.5 emission scenarios, respectively. The mean annual streamflow volumes are projected to be reduced by 45% (10–60%) and 47% (16–66%). The average events' streamflow volumes for a given event rainfall depth are projected to be lower by a factor of 1.4–2.1. Moreover, the streamflow season in these ephemeral streams is projected to be shorter by 22% and 26–28% for the RCP4.5 and RCP8.5, respectively. The amplification in reduction of streamflow volumes relative to rainfall amounts is related to the projected reduction in soil moisture, as a result of fewer rainfall events and longer dry spells between rainfall events during the wet season. The dominant factors for the projected reduction in rainfall amount were the reduction in occurrence of wet synoptic systems and the shortening of the wet synoptic systems durations. Changes in the occurrence frequency of the two dominant types of the regional wet synoptic systems (active Red Sea trough and Mediterranean low) were found to have a minor impact on the total rainfall.

Runoff and flash flood generation are very sensitive to rainfall's$\backslash$nspatial and temporal variability. The increasing use of radar and$\backslash$nsatellite data in hydrological applications, due to the sparse$\backslash$ndistribution of rain gauges over most catchments worldwide, requires$\backslash$nfurthering our knowledge of the uncertainties of these data. In 2011, a$\backslash$nnew super-dense network of rain gauges containing 14 stations, each with$\backslash$ntwo side-by-side gauges, was installed within a 4 km(2) study area near$\backslash$nKibbutz Galed in northern Israel. This network was established for a$\backslash$ndetailed exploration of the uncertainties and errors regarding rainfall$\backslash$nvariability within a common pixel size of data obtained from remote$\backslash$nsensing systems for timescales of 1 min to daily. In this paper, we$\backslash$npresent the analysis of the first year's record collected from this$\backslash$nnetwork and from the Shacham weather radar, located 63 km from the study$\backslash$narea. The gauge-rainfall spatial correlation and uncertainty were$\backslash$nexamined along with the estimated radar error. The nugget parameter of$\backslash$nthe inter-gauge rainfall correlations was high (0.92 on the 1 min scale)$\backslash$nand increased as the timescale increased. The variance reduction factor$\backslash$n(VRF), representing the uncertainty from averaging a number of rain$\backslash$nstations per pixel, ranged from 1.6% for the 1 min timescale to 0.07%$\backslash$nfor the daily scale. It was also found that at least three rain stations$\backslash$nare needed to adequately represent the rainfall (VRF\textless 5 %) on a typical$\backslash$nradar pixel scale. The difference between radar and rain gauge rainfall$\backslash$nwas mainly attributed to radar estimation errors, while the gauge$\backslash$nsampling error contributed up to 20% to the total difference. The ratio$\backslash$nof radar rainfall to gauge-areal-averaged rainfall, expressed by the$\backslash$nerror distribution scatter parameter, decreased from 5.27 dB for 3 min$\backslash$ntimescale to 3.21 dB for the daily scale. The analysis of the radar$\backslash$nerrors and uncertainties suggest that a temporal scale of at least 10$\backslash$nmin should be used for hydrological applications of the radar data.$\backslash$nRainfall measurements collected with this dense rain gauge network will$\backslash$nbe used for further examination of small-scale rainfall's spatial and$\backslash$ntemporal variability in the coming years.