A new stochastic high-resolution synoptically conditioned weather generator (HiReS-WG) appropriate for climate regimes with a substantial proportion of convective rainfall is presented. The simu- lated rain fields are of high spatial (0.53 0.5 km2) and temporal (5 min) resolution and can be used for most hydrological applications. The WG is composed of four modules: the synoptic generator, the motion vector generator, the convective rain cell generator, and the low-intensity rainfall generator. The HiReS-WG was applied to a study region on the northwestern Israeli coastline in the Eastern Mediterranean, for which 12 year weather radar and synoptic data were extensively analyzed to derive probability distributions of con- vective rain cells and other rainfall properties for different synoptic classifications; these distributions were used as input to the HiReS-WG. Simulated rainfall data for 300 years were evaluated for annual rain depth, season timing, wet-/dry-period durations, rain-intensity distributions, and spatial correlations. In general, the WG well represented the above properties compared to radar and rain-gauge observations from the studied region, with one limitation—an inability to reproduce the most extreme cases. The HiReS-WG is a good tool to study catchments' hydrological responses to variations in rainfall, especially small-size to medium-size catchments, and it can also be linked to climate models to force the prevailing synoptic conditions.
Considering the popularity of using data-driven non-linear methods for forecasting streamflow, there has been no exploration of how well such models perform in climate regimes with differing hydrological characteristics, nor has the performance of these models, coupled with wavelet transforms, been compared for lead times of less than one month. This study compares the use of four different models, namely artificial neural networks (ANNs), support vector regression (SVR), wavelet-ANN, and wavelet-SVR in a Mediterranean, Oceanic, and Hemiboreal watershed. Model performance was tested for one, two and three day forecasting lead times, measured by fractional standard error, the coefficient of determination, Nash–Sutcliffe model efficiency, multiplicative bias, probability of detection and false alarm rate. SVR based models performed best overall, but no one model outperformed the others in more than one watershed, suggesting that some models may be more suitable for certain types of data. Overall model performance varied greatly between climate regimes, suggesting that higher persistence and slower hydrological processes (i.e. snowmelt, glacial runoff, and subsurface flow) support reliable forecasting using daily and multi-day lead times.
Identification of a geomorphic index to represent lower thresholds for minor flows in ephemeral, alluvial streams in arid environments is an essential step in reliable flash flood hazard estimations and establishing flood warning systems. An index, termed Alluvial wadi Flood Incipient Geomorphologic Index (AFIG), is presented. Analysis of data from an extensive field survey in the arid ephemeral streams in southern and eastern Israel was conducted to investigate the AFIG and the control over its value across the region. During the survey we identified distinguishable flow marks in the lower parts of streams' banks, such as niches, vegetation line, and change in bank material, which are indicative of low flows. The cross-sectional characteristics of the AFIG were studied in relationship with contributing drainage basin characteristics such as lithology, topography, and precipitation. Drainage area and hardness of the exposed lithology (presented as a basin-wide index) are the preferred descriptors to be used in estimating a specific AFIG in un-surveyed sites. Analyses of discharge records from seven hydrometric stations indicate that the recurrence interval of the determined AFIG is equal to or more frequent than 0.5 year.
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.
The spaceborne weather radar onboard the Tropical Rainfall Measuring Mission (TRMM) satellite can be used to adjust Ground-based Radar (GR) echoes, as a function of the range from the GR site. The adjustment is based on the average linear radar reflectivity in circular rings around the GR site, for both the GR and attenuation-corrected NearSurfZ TRMM Precipitation Radar (TPR) images. In previous studies, it was found that in winter, for the lowest elevation of the Cyprus C-band radar, the GR/TPR equivalent rain rate ratio was decreasing, on average, of approximately 8 dB per decade. In this paper, the same analysis has been applied to another C-band radar in the southeastern Mediterranean area. For the lowest elevation of the “Shacham” radar in Israel, the GR/TPR equivalent rain rate ratio is found to decrease of approximately 6 dB per decade. The average departure at the “reference”, intermediate range is related to the calibration of the GR. The negative slope of the range dependence is considered to be mainly caused by an overshooting problem (increasing sampling volume of the GR with range combined with non-homogeneous beam filling and, on average, a decreasing vertical profile of radar reflectivity). To check this hypothesis, we have compared the same NearSurfZ TPR images versus GR data acquired using the second elevation. We expected these data to be affected more by overshooting, especially at distant ranges: the negative slope of the range dependence was in fact found to be more evident than in the case of the lowest GR elevation for both the Cypriot and Israeli radar.
ak data, catchment area and occurrence date for 99 events (69 from the North-Western region and 30 from the South-Eastern region). Analysis is carried out in terms of relationship of flood peaks with catchment area and sea- sonality. Results show that the envelope curve for the South- Eastern region exhibits a more pronounced decreasing with catchment size with respect to the curve of the North-Western region. The differences between the two relationships reflect changes in the effects of storm coverage and hydrological characteristics between the two regions. Seasonality analy- sis shows that the events in the North-Western region tend to occur between August and November, whereas those in the South-Eastern area tend to occur in the period between October and May, reflecting the relevant patterns in the syn- optic conditions leading to the intense precipitation events. In the second part, the focus is on the rainfall-runoff rela- tionships for 13 selected major flash flood events (8 from the North-Western area and 5 from the South-Eastern area) for which rainfall and runoff properties are available. These flash floods are characterised in terms of climatic features of the impacted catchments, duration and amount of the gener- ating rainfall, and runoff ratio. Results show that the rainfall duration is shorter and the rainfall depth lower in the South- Eastern region. The runoff ratios are rather low in both re- gions, whereas they are more variable in the South-Eastern area. No clear relationship between runoff ratio and rainfall depth is observed in the sample of floods, showing the major influence of rainfall intensity and the initial wetness condi- tion in the runoff generation for these events.
This letter assesses the quality of temperature and rainfall daily retrievals of the European Climate Assessment and Dataset (ECA&D) with respect to measurements collected locally in various parts of the Euro-Mediterranean region in the framework of the Hydrological Cycle in the Mediterranean Experiment (HyMeX), endorsed by the Global Energy and Water Cycle Experiment (GEWEX) of the World Climate Research Program (WCRP). The ECA&D, among other gridded datasets, is very often used as a reference for model calibration and evaluation. This is for instance the case in the context of the WCRP Coordinated Regional Downscaling Experiment (CORDEX) and its Mediterranean declination MED-CORDEX. This letter quantifies ECA&D dataset uncertainties associated with temperature and precipitation intra-seasonal variability, seasonal distribution and extremes. Our motivation is to help the interpretation of the results when validating or calibrating downscaling models by the ECA&D dataset in the context of regional climate research in the Euro-Mediterranean region.
This paper examines the spatiotemporal characteristics of convective rain cells over the eastern Mediterranean (northern Israel) and their relationship to synoptic patterns. Information on rain cell features was extracted from high-resolution weather radar data. The radar-gauge adjustment, validation, cell segmentation and tracking techniques are discussed at length at the beginning of the paper. Convective rain cells were clustered into three synoptic types (two winter lows—deep Cyprus lows and shallow lows—and one tropical intrusion, Active Red Sea Trough) using several NCEP/NCAR parameters, and empirical distributions were computed for their spatial and temporal features. In the study region, it was found that the Active Red Sea Trough rain cells are larger, live for less time and possess lower rain intensities than the rain cells generated by the winter lows. The Cyprus low rain cells were found to be less intense and slightly larger on average than the shallow low rain cells. It was further discovered that the preferential orientation of the rain cells is associated with the direction and velocity of the wind. The effect of distance from the coastline was also examined. An increase in the number and area of the rain cells near the coastline was observed, presumably due to the sea breeze convection. The mean rainfall intensity was found to peak near the shore and decrease with distance inland. This information is of great importance for understanding rain patterns and can be further applied in exploring the hydrological responses of the basins in this region
A comprehensive investigation of rainstorms and their consequent impacts on landscape evolution is geomorphologically important, but only scant information may be available on exceptional events, because parameters on synoptic conditions, rainstorm, landforms and hydrology for such events may be incomparable with previous knowledge. We studied an exceptional storm on April 2, 2006, in the Ramot Menashe region, Israel. Our investigation of rainfall, landslides, debris flows and channel suggests the effectiveness of such an event on the development of basin-scale morphology. The storm caused damage and casualties although it covered relatively narrow strips. Neither direct rainfall nor runoff measurements exist for the most severely affected area of Ramot Menashe, but the geomorphologic evidence combined with high-resolution meteorological radar data provides the basic understanding of the processes and hazardous conditions which prevailed at the time. In the storm core, based on estimation from meteorological radar data, 263mm of rain fell within 3h with a maximum intensity of 220mmh -1 for 10min, triggering both sporadic landslides at the soil/bedrock contact on the upper slopes and widespread landslides at the fractured/massive bedrock contact on the lower slopes. The 1st order channels on the alternation of chalk and marl also underwent erosion, and the produced sediment deposited on alluvial fans at the confluence with the main channel. The specific peak discharges for catchment size of 0.3-10km 2 were 11 to 73m 3s -1km -2, higher than any recorded floods in the Mediterranean climatic region of Israel. The effectiveness of the flood for geomorphic work, represented by shear stress and stream power per unit boundary area reached 87-398Nm -2 and 212-2134Wm -2, respectively. This kind of analysis can be applied to hazard prediction in other areas under similar geomorphological conditions. ?? 2012 Elsevier B.V.
Flash floods caused by convective rain storms are highly sensitive to the space–time character- istics of rain cells. In this study we exploit the high space–time resolution of the radar data to study the characteristics of the rain cells and their impact on flash flood magnitudes. A rain cell model is applied to the radar data of an actual storm and the rain fields represented by the model further serve as input into a hydrological model. Global sensitivity analysis is applied to identify the most important factors affecting the flash flood peak discharge. As a case study we tested an extreme storm event over a semi-arid catchment in southern Israel. The rain cell model was found to simulate the rain storm adequately. We found that relatively small changes in the rain cell's location, speed and direction could cause a three-fold increase in flash flood peak discharge at the catchment outlet.
In ancient times human activities were tightly related and sensitive to rainfall amounts and seasonal distribution. East Mediterranean settlements were concentrated around numerous small to large springs, such as the Judean Mountains area. The goals of this study were to determine (a) the sensitivity of total discharge, recession curve, and response time of such springs to annual precipitation patterns, and (b) how spring hydrology responds to series of drought or wet years and to transitions from drought to normal and/or wet episodes (and vice versa). These goals were achieved by setting a finite-element hydro-geological flow model for selected perched springs that characterize the numerous springs throughout the carbonate karst terrain in the Judean Mountains. In addition, we estimated the effect of proposed regional past climate changes on the springs; in so doing, we transfer climate change to community size, livelihood and economic strength that were highly dependent on agricultural productivity. The results of the hydro-geological model revealed that these mountainous communities had the potential to prosper during historically wetter episodes and were probably adapted to short-term variability in annual rainfall. However, moderate to extreme droughts lasting only a few years could have led to a partial or even total abandonment of the springs as focal sites of intensive agricultural production. Spring drying eliminated the primary cause for the location of settlement. This occurred simultaneously in numerous settlements around the mountains of the southern Levant and therefore, must have caused dramatic economic and societal changes in the entire region, perhaps even resonating afar.
The FLASH project was implemented from 2006 to 2010 under the EU FP6 framework. The project focused on using lightning observations to better understand and predict convective storms that result in flash floods. As part of the project 23 case studies of flash floods in the Mediterranean region were examined. For the analysis of these storms lightning data from the ZEUS network were used together with satellite derived rainfall estimates in order to understand the storm development and electrification. In addition, these case studies were simulated using mesoscale meteorological models to better understand the meteorological and synoptic conditions leading up to these intense storms. As part of this project tools for short term predictions (nowcasts) of intense convection across the Mediterranean and Europe, and long term forecasts (a few days) of the likelihood of intense convection were developed. The project also focused on educational outreach through our website http:// flashproject.org supplying real time lightning observations, real time experimental now- casts, forecasts and educational materials. While flash floods and intense thunderstorms cannot be prevented as the climate changes, long-range regional lightning networks can supply valuable data, in real time, for warning end-users and stakeholders of imminent intense rainfall and possible flash floods.
Antibodies directed to citrullinated proteins (anti-cyclic citrullinated peptide) are highly specific for rheumatoid arthritis (RA). Recent data suggest that the antibodies may be involved in the disease process of RA and that several RA-associated genetic factors might be functionally linked to RA via modulation of the production of anti-cyclic citrullinated peptide antibodies or citrullinated antigens.
Fresh water resources, human societies, and ecosystems are expected to be strongly impacted by climate change, with precipitation trends being one of the most important elements that will be closely monitored. However, the natural variability of precipitation data can often mask existing trends such that the results appear as statistically insignificant. Information on the limitations of trend detection is important for risk assessment and for decision making related to adaption strategies under inherent uncertainties. This paper reports on an effort to quantify and map minimal detectable absolute trends in annual precipitation data series on a global scale. Monte Carlo simulations were conducted to generate realizations of trended precipitation data for different precipitation means and coefficients of variance, and the MannKendall method was applied for detecting the trend significance. Global Precipitation Climatology Centre (GPCC) VASClimO data was used to compute the mean and coefficient of variance of annual precipitation over land and to map minimal detectable absolute trends. It was found that relatively high magnitude trends (positive or negative) have a low chance of being detected as a result of high natural variance of the precipitation data. The largest undetectable trends were found for the tropics. Arid and semiarid regions also present high relative values in terms of percent change from the mean annual precipitation. Although the present analysis is based on several simplified assumptions, the goal was to point out an inherent problem of potentially undetectable high absolute trends that must be considered in analyzing precipitation data series and assessing risks in adaption strategies to climate change.
The FLASH project was implemented from 2006 to 2010 under the EU FP6 framework. The project focused on using lightning observations to better understand and predict convective storms that result in flash floods. As part of the project 23 case studies of flash floods in the Mediterranean region were examined. For the analysis of these storms lightning data from the ZEUS network were used together with satellite derived rainfall estimates in order to understand the storm development and electrification. In addition, these case studies were simulated using mesoscale meteorological models to better understand the meteorological and synoptic conditions leading up to these intense storms. As part of this project tools for short term predictions (nowcasts) of intense convection across the Mediterranean and Europe, and long term forecasts (a few days) of the likelihood of intense convection were developed. The project also focused on educational outreach through our website http://flashproject.org supplying real time lightning observations, real time experimental nowcasts, forecasts and educational materials. While flash floods and intense thunderstorms cannot be prevented as the climate changes, long-range regional lightning networks can supply valuable data, in real time, for warning end-users and stakeholders of imminent intense rainfall and possible flash floods. ?? 2011 Elsevier Ltd.
While intense scientific efforts have focused on radar precipitation estimation in temperate climatic regimes, relatively few studies have examined dry climatic regions. This paper examines rain depth estimation for a 19 day rainfall period in Israel, where the gauge spatial distribution is particularly nonhomogeneous. This fact exacerbates the main drawback of rain gauge observations, which is undersampling. Meteorological ground‐ based radar (GR) can supplement the desired information on precipitation distribution. However, especially in a complex orographic region, radar scientists are faced with beam broadening with distance, nonhomogeneous beam filling, and partial‐beam occultation, together with changes in the vertical reflectivity profile. This paper presents an improvement of GR precipitation estimates thanks to a range adjustment based on spaceborne meteorological radar. In the past, the Tropical Rainfall Measuring Mission (TRMM) satellite radar was used for checking the GR mean field bias around the world. To our knowledge, however, it is the first time that GR‐derived cumulative rainfall amounts show a better agreement with gauges, thanks to the mean field bias and range‐ dependent compensation derived using the well‐calibrated Ku band TRMM radar as a reference. The average bias improves from +1.0 dB to −0.3 dB; more interesting and difficult to obtain is a reduction of the dispersion of the error. Using TRMM‐based range compensation, the scatter decreases from 2.21 dB to 1.93 dB. We conclude that it is well worth trying to compensate for the GR range degradation.
The climate of the eastern Mediterranean (EM), at the transition zone between the Mediterranean climate and the semi‐arid/arid climate, has been studied for a 39‐year period to determine whether climate changes have taken place. A thorough trend analysis using the nonparametric Mann‐Kendall test with Sen's slope estimator has been applied to ground station measurements, atmospheric reanalysis data, synoptic classification data and global data sets for the years 1964–2003. In addition, changes in atmospheric regional patterns between the first and last twenty years were determined by visual comparisons of their composite mean. The main findings of the analysis are: 1) changes of atmospheric conditions during summer and the transitional seasons (mainly autumn) support a warmer climate over the EM and this change is already statistically evident in surface temperatures having exhibited positive trends of 0.2–1°C/decade; 2) changes of atmospheric conditions during winter and the transitional seasons support drier conditions due to reduction in cyclogenesis and specific humidity over the EM, but this change is not yet statistically evident in surface station rain data, presumably because of the high natural precipitation variance masking such a change. The overall conclusion of this study is that the EM region is under climate change leading to warmer and drier conditions.
A new parameter is introduced: the lightning potential index (LPI), which is a measure of the potential for charge generation and separation that leads to lightning flashes in convective thunderstorms. The LPI is calculated within the charge separation region of clouds between 0°C and −20°C, where the noninductive mechanism involving collisions of ice and graupel particles in the presence of supercooled water is most effective. As shown in several case studies using the Weather Research and Forecasting (WRF) model with explicit microphysics, the LPI is highly correlated with observed lightning. It is suggested that the LPI may be a useful parameter for predicting lightning as well as a tool for improving weather forecasting of convective storms and heavy rainfall.
Flash floods cause some of the most severe natural disasters in Europe but Mediterranean areas are especially vulnerable. They can cause devastating damage to property, infrastructures and loss of human life. The complexity of flash flood generation processes and their dependency on different factors related to watershed properties and rainfall characteristics make flash flood prediction a difficult task. In this study, as part of the EU-FLASH project, we used an uncalibrated hydrological model to simulate flow events in a 27km2 Mediterranean watershed in Israel to analyze and better understand the various factors influencing flows. The model is based on the well-known SCS curve number method for rainfall-runoff calculations and on the kinematic wave method for flow routing. Existing data available from maps, GIS and field studies were used to define model parameters, and no further calibration was conducted to obtain a better fit between computed and observed flow data. The model rainfall input was obtained from the high temporal and spatial resolution radar data adjusted to rain gauges. Twenty flow events that occurred within the study area over a 15year period were analyzed. The model shows a generally good capability in predicting flash flood peak discharge in terms of their general level, classified as low, medium or high (all high level events were correctly predicted). It was found that the model mainly well predicts flash floods generated by intense, short-lived convective storm events while model performances for low and moderate flows generated by more widespread winter storms were quite poor. The degree of urban development was found to have a large impact on runoff amount and peak discharge, with higher sensitivity of moderate and low flow events relative to high flows. Flash flood generation was also found to be very sensitive to the temporal distribution of rain intensity within a specific storm event. ?? 2010 Elsevier B.V.