Publications

2021
Neta A, Gafni R, Elias H, Bar-Shmuel N, Shaltiel-Harpaz L, Morin E, Morin S. Decision support for pest management: Using field data for optimizing temperature-dependent population dynamics models. Ecological Modelling [Internet]. 2021;440 (July 2020) :109402. Publisher's VersionAbstract
Insect physiology is highly dependent on the environmental temperature, and the relationship can be mathematically defined. Thus, many models that aim to predict insect-pest population dynamics, use meteorological data as input to descriptive functions that predict the development rate, survival and reproduction of pest populations. In most cases, however, these functions/models are laboratory-driven and are based on data from constant-temperature experiments. Therefore, they lack an important optimization and validation steps that test their accuracy under field conditions. Here, we developed a realistic and robust regional framework for modeling the field population dynamics of the global insect pest Bemisia tabaci. First, two non-linear functions, development rate (DR) and female reproduction (EN) were fitted to data collected in constant temperature experiments. Next, nine one-generation field experiments were conducted in order to establish a field-derived database of insect performance, representing a variety of growing conditions (different seasons, regions and host plants). Then, sensitivity analyses were performed for identifying the optimal time-scale for which the running-averaged temperatures should be fed to the model. Setting the time to 6 h (i.e., each of the 24-time steps per day represents the last 6 h average) produced the best fit (RMSD score of 1.59 days, 5.7% of the mean) between the field observations and the model simulations. We hypothesize that the 6 h ‘relevant biological time-scale' captures the insect's physiological memory of daily cycling temperature events. Lastly, we evaluated the potential of the developed modeling framework to serve as a decision support tool in pest-management programs by correlating the model predictions with field-observations of three pest control inspectors during 2019. The model successfully predicted the first notable appearance of the insect in the field (completion of the third generation in May). Also, the model correctly identified the sharp rise in abundance (outbreak point) in mid-July (completion of the fifth generation), and the persistent rise in abundance through August and September. Comparing the simulations of the 2018 and 2019 seasons indicated that the model can also serve as a tool for retrospective systematic assessment of major decisions. Taken together, these data demonstrate the model robustness and its potential to provide an excellent decision-making support platform in regional control of pest species.
Shmilovitz Y, Marra F, Wei H, Argaman E, Nearing M, Goodrich D, Assouline S, Morin E. Frequency analysis of storm-scale soil erosion and characterization of extreme erosive events by linking the DWEPP model and a stochastic rainfall generator. Science of the Total Environment [Internet]. 2021;787 :147609. Publisher's VersionAbstract
Soil erosion affects agricultural landscapes worldwide, threatening food security and ecosystem viability. In arable environments, soil loss is primarily caused by short, intense rainstorms, typically characterized by high spatiotemporal variability. The complexity of erosive events challenges modeling efforts and explicit inclusion of extreme events in long-term risk assessment is missing. This study is intended to bridge this gap by quantifying the discrete and cumulative impacts of rainstorms on plot-scale soil erosion and providing storm-scale erosion risk analyses for a cropland region in northern Israel. Central to our analyses is the coupling of (1) a stochastic rainfall generator able to reproduce extremes down to 5-minute temporal resolutions; (2) a processes-based event-scale cropland erosion model (Dynamic WEPP, DWEPP); and, (3) a state-of-the-art frequency analysis method that explicitly accounts for rainstorms occurrence and properties. To our knowledge, this is the first study in which DWEPP runoff and soil loss are calibrated at the plot-scale on cropland (NSE is 0.82 and 0.79 for event runoff and sediment, respectively). We generated 300-year stochastic simulations of event runoff and sediment yield based on synthetic precipitation time series. Based on this data, the mean annual soil erosion in the study site is 0.1 kg m−2 [1.1 t ha−1]. Results of the risk analysis indicate that individual extreme rainstorms (>50 return period), characterized by high rainfall intensities (30-minute maximal intensity > $\sim$60 mm h−1) and high rainfall depth (>$\sim$200 mm), can trigger soil losses even one order of magnitude higher than the annual mean. The erosion efficiency of these rainstorms is mainly controlled by the short-duration (≤30 min) maximal intensities. The results demonstrate the importance of incorporating the impact of extreme events into soil conservation and management tools. We expect our methodology to be valuable for investigating future changes in soil erosion with changing climate.
Dente E, Lensky NG, Morin E, Enzel Y. From straight to deeply incised meandering channels: Slope impact on sinuosity of confined streams. Earth Surface Processes and Landforms. 2021;46 (5) :1041–1054.Abstract
Meandering channels and valleys are dominant landscape features on Earth. Their morphology and remnants potentially indicate past base-level fluctuations and changing regional slopes. The prevailing presence of meandering segments in low-slope areas somewhat confuses the physically based relationships between slope and channel meandering. This relationship underlies a fundamental debate: do incised sinuous channels actively develop during steepening of a regional slope, or do they inherit the planform of a preexisting sinuous channel through vertical incision? This question was previously explored through reconstructed evolution of meandering rivers, numerical simulations, and controlled, scaled-down laboratory experiments. Here, we study a rare, field-scale set of a dozen adjacent perennial channels, evolving in recent decades in a homogeneous erodible substrate in response to the Dead Sea level fall (> 30 m over 40 years). These channels are fed by perennial springs and have no drainage basin or previous fluvial history; they initiated straight and transformed into incising meandering channels following the emergence of the preexisting lake bathymetry, which resulted in increased channel lengths and regional slopes at different rates for each channel. This field setting allows testing the impact of changing regional slope on the sinuosity of a stream in the following cases: (a) relatively long and low-gradient shelf-like margins, (b) a sharp increase in the basinward gradient at the shelf-slope transition, and (c) gradually steepening slopes. Under a stable and low valley slope, the channels mainly incise vertically, inheriting a preexisting sinuous pattern. When the regional slope steepens, the channels start to meander, accompanying the vertical incision. The highest sinuosity evolved in the steepest channel, which also developed the deepest and widest valley. These results emphasize the amplifying impact of steepening regional slope on sinuosity. This holds when the flow is confined and chute cutoffs are scarce.
Rinat Y, Marra F, Armon M, Metzger A, Levi Y, Khain P, Vadislavsky E, Rosensaft M, Morin E. Hydrometeorological analysis and forecasting of a 3-d flash-flood-triggering desert rainstorm. Natural Hazards and Earth System Sciences [Internet]. 2021;21 (3) :917–939. Publisher's Version
Marra F, Armon M, Borga M, Morin E. Orographic Effect on Extreme Precipitation Statistics Peaks at Hourly Time Scales. Geophysical Research Letters [Internet]. 2021;48 (5) :e2020GL091498. Publisher's VersionAbstract
Abstract Orographic impact on extreme subdaily precipitation is critical for risk management but remains insufficiently understood due to complicated atmosphere-orography interactions and large uncertainties. We investigate the problem adopting a framework able to reduce uncertainties and isolate the systematic interaction of Mediterranean cyclones with a regular orographic barrier. The average decrease with elevation reported for hourly extremes is found enhanced at subhourly durations. Tail heaviness of 10-min intensities is negligibly affected by orography, suggesting self-similarity of the distributions at the convective scale. Orography decreases the tail heaviness at longer durations, with a maximum impact around hourly scales. These observations are explained by an orographically induced redistribution of precipitation toward stratiform-like processes, and by the succession of convective cores in multihour extremes. Our results imply a breaking of scale-invariance at subhourly durations, with important implications for natural hazards management in mountainous areas.
Marra F, Armon M, Adam O, Zoccatelli D, Gazal O, Garfinkel CI, Rostkier-Edelstein D, Dayan U, Enzel Y, Morin E. Toward Narrowing Uncertainty in Future Projections of Local Extreme Precipitation. Geophysical Research Letters [Internet]. 2021;48 (5) :e2020GL091823. Publisher's VersionAbstract
Abstract Projections of extreme precipitation based on modern climate models suffer from large uncertainties. Specifically, unresolved physics and natural variability limit the ability of climate models to provide actionable information on impacts and risks at the regional, watershed and city scales relevant for practical applications. Here, we show that the interaction of precipitating systems with local features can constrain the statistical description of extreme precipitation. These observational constraints can be used to project local extremes of low yearly exceedance probability (e.g., 100-year events) using synoptic-scale information from climate models, which is generally represented more accurately than the local scales, and without requiring climate models to explicitly resolve extremes. The novel approach, demonstrated here over the south-eastern Mediterranean, offers a path for improving the predictability of local statistics of extremes in a changing climate, independent of pending improvements in climate models at regional and local scales.
2020
Hu L, Nikolopoulos EI, Marra F, Morin E, Marani M, Anagnostou EN. Evaluation of MEVD-based precipitation frequency analyses from quasi-global precipitation datasets against dense rain gauge networks. Journal of Hydrology [Internet]. 2020;590 (September) :125564. Publisher's VersionAbstract
Precipitation extremes and associated hydrological hazards pose a significant global risk to society and economy. To be effective, mitigation strategies require the best possible estimation of the intensity and frequency of precipitation extremes. Traditional approaches to precipitation frequency analysis rely on long-term records from in-situ observations, which are limited in terms of global coverage. Satellite-based precipitation products provide global coverage, but errors in these estimates may lead to large biases in the quantification of extremes. Previous studies have demonstrated the ability of the novel Metastatistical Extreme Value Distribution (MEVD) framework to provide robust estimates of high quantiles in the presence of short-term data records and the uncertainties typical of remote sensing precipitation products. Here, we evaluate MEVD-based precipitation frequency analyses for four widely used quasi-global precipitation products (IMERG-v6, GSMaP-v6, CMORPH-v1.0, and MSWEP-v2) over high-density gauge networks in five hydroclimatic regions (Austria, Italy, Florida, Texas, and Arizona). We show dependence of MEVD-based estimation error on the characteristics of each dataset and the hydroclimatic region. Additionally, we evaluate the sub-grid variability of extreme precipitation and demonstrate the impact of spatial scale mismatch (that is, single in-situ gauge versus satellite pixel) on the frequency analysis of extremes. This work provides an assessment of the use of MEVD for estimating precipitation extremes from globally available datasets and an understanding of the variability of sub-daily precipitation extremes in different hydroclimatic regions of the world.
Metzger A, Marra F, Smith JA, Morin E. Flood frequency estimation and uncertainty in arid/semi-arid regions. Journal of Hydrology [Internet]. 2020;590 (May) :125254. Publisher's VersionAbstract
At site flood frequency analysis (FFA) in arid/semi-arid watersheds poses unique challenges to researchers and practitioners due to the generally limited data records. This study presents a comprehensive evaluation of FFA in arid/semi-arid watersheds in relation to the unique characteristics of these regions, such as the limited number of floods occurring each year and the large variability of the flood peak discharges. Study cases in Israel and the US are examined and compared with non-arid watersheds, characterized by Mediterranean climate, and with synthetic flood records. Results show that the tail of extreme value distributions describing arid/semi-arid watersheds is found to be heavier than the one describing Mediterranean watersheds. The number of yearly floods and the variability of flood peak discharge are shown to have a crucial impact on the accuracy of the quantile estimates with smaller number of events per year and larger coefficient of variation of flood peak discharge being related to larger errors in the estimated quantiles. Partial duration series approach provides a slightly reduced bias in the estimates, but should not be blindly preferred over annual maxima series as it presents comparable estimation uncertainty. In general, the generalized extreme value and the generalized Pareto distribution are found to be non-optimal choices for the examined arid/semi-arid watersheds.
Marra F, Borga M, Morin E. A Unified Framework for Extreme Subdaily Precipitation Frequency Analyses Based on Ordinary Events. Geophysical Research Letters. 2020;47 (18) :1–8.Abstract
The metastatistical extreme value approach proved promising in the frequency analysis of daily precipitation from ordinary events, outperforming traditional methods based on sampled extremes. However, subdaily applications are currently restrained by two knowledge gaps: It is not known if ordinary events can be consistently examined over durations, and it is not clear to what extent their entire distributions represent extremes. We propose here a unified definition of ordinary events across durations and suggest the simplified metastatistical extreme value formulation for dealing with extremes emerging from the tail, rather than the entire distributions, of ordinary events. This unified framework provides robust estimates of extreme quantiles (\textless10% error on the 100 yr from a 26 yr long record) and allows representations in which ordinary and extreme events share the scaling exponent. Future applications could improve our knowledge of subdaily extreme precipitation and help investigate the impact of local factors and climatic forcing on their frequency.
Armon M, Dente E, Shmilovitz Y, Mushkin A, Cohen TJ, Morin E, Enzel Y. Determining bathymetry of shallow and ephemeral desert lakes using satellite imagery and altimetry. Geophysical Research Letters [Internet]. 2020;n/a (n/a) :e2020GL087367. Publisher's VersionAbstract
Abstract Water volume estimates of shallow desert lakes are the basis for water balance calculations, important both for water resource management and paleohydrology/climatology. Water volumes are typically inferred from bathymetry mapping; however, being shallow, ephemeral and remote, bathymetric surveys are scarce in such lakes. We propose a new, remote-sensing based, method to derive the bathymetry of such lakes using the relation between water occurrence, during \textgreater30-yr of optical satellite data, and accurate elevation measurements from the new Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2). We demonstrate our method at three locations where we map bathymetries with \~0.3 m error. This method complements other remotely sensed, bathymetry-mapping methods as it can be applied to: (a) complex lake systems with sub-basins, (b) remote lakes with no in-situ records, and (c) flooded lakes. The proposed method can be easily implemented in other shallow lakes as it builds on publically accessible global data sets.
Grodek T, Morin E, Helman D, Lensky I, Dahan O, Seely M, Benito G, Enzel Y. Eco-hydrology and geomorphology of the largest floods along the hyperarid Kuiseb River, Namibia. Journal of Hydrology [Internet]. 2020;582 :124450. Publisher's VersionAbstract
Flood-fed aquifers along the sandy lower reach of the Kuiseb River sustain a 130-km-long green belt of lush oases across the hyperarid Namib desert. This oasis is a year-round source for water creating dense-tall woodland along the narrow corridor of the ephemeral river valley, which, in turn, supports human activity and fauna including during the long dry austral winters and multi-year droughts. Occasional floods, originating at the river's wetter headwaters, travel ∼280 km downstream, before recharging these aquifers. We analyzed the flood-aquifer-vegetation dynamics at-a-site and along the river, determining the relative impact of floods with diverse magnitude and frequency on downstream reaches. We find that flood discharge that feeds the alluvial aquifers also affects vegetation dynamics along the river. The downstream aquifers are fed only by the largest floods that allow the infrequent germination of plants; mean annual recharge volume is too low to support the aquifers level. These short-term vegetation cycles of green-up and then fast senescence in-between floods are easily detected by satellite-derived vegetation index. This index identifies historical floods and their magnitudes in arid and hyperarid regions; specifically, it determines occurrences of large floods in headwater-fed, ephemeral Namib streams as well as in other hyperarid regions. Our study reveals the importance of flood properties on the oasis life cycle, emphasizing the impact of drought and wet years on the Namib's riparian vegetation.
Zoccatelli D, Marra F, Smith J, Goodrich D, Unkrich C, Rosensaft M, Morin E. Hydrological modelling in desert areas of the eastern Mediterranean. Journal of Hydrology [Internet]. 2020 :124879. Publisher's VersionAbstract
The performances of hydrological models in arid areas are significantly lower than other climates. The reasons are numerous, from the scales involved, to specific processes and the lack of adequate measurements. Effective parameters have been often observed to change between runoff events, limiting the predictive capacity of the models. We look at the problems that can be found in an operational setting and present an analysis to improve the understanding of the errors. Our method characterizes the conditions where the model fails systematically, and the conditions where the parameterization holds between floods. We applied KINEROS2 to 24 years of radar rainfall and streamflow data in 6 arid catchments. A GLUE probabilistic framework is used to characterize model performance, and a method is developed to identify floods with similar calibration. The analysis shows that uninformative conditions are difficult to generalize. A basin-specific analysis can help to identify conditions where the model fails and exclude them from calibration. Despite the large uncertainties, similar catchments display groups of floods with similar parameterization. In some basin we find that it is important to quantify antecedent moisture conditions. Hydrological models show some consistency within limited conditions. These conditions, however, depend on the errors involved, and are site-specific. There is some potential for parameter transfer, but proximity alone might not be enough, and other factors such as mean annual rainfall or storm type, should be taken into account.
Shmilovitz Y, Morin E, Rinat Y, Haviv I, Carmi G, Mushkin A, Enzel Y. Linking frequency of rainstorms, runoff generation and sediment transport across hyperarid talus-pediment slopes. Earth Surface Processes and Landforms [Internet]. 2020;n/a (n/a). Publisher's VersionAbstract
Abstract Documenting hillslope response to hydroclimatic forcing is crucial to our understanding of landscape evolution. The evolution of talus-pediment sequences (talus flatirons) in arid areas was often linked to climatic cycles, although the physical processes that may account for such a link remain obscure. Our approach is to integrate field measurements, remote sensing of rainfall and modeling to link between storm frequency, runoff, erosion and sediment transport. We present a quantitative hydrometeorological analysis of rainstorms, their geomorphic impact and their potential role in the evolution of hyperarid talus-pediment slopes in the Negev desert, Israel. Rainstorm properties were defined based on intensity–duration–frequency curves and using a rainfall simulator, artificial rainstorms were executed in the field. Then, the obtained measured experimental results were up-scaled to the entire slope length using a fully distributed hydrological model. In addition, natural storms and their hydro-geomorphic impacts were monitored using X-band radar and time-lapse cameras. These integrated analyses constrain the rainfall threshold for local runoff generation at rain intensity of 14 to 22 mm h-1 for a duration of five minutes and provide a high-resolution characterization of small-scale runoff-generating rain cells. The current frequency of such runoff-producing rainstorms is \~1–3 per year. However, extending this local value into the full extent of hillslope runoff indicates that it occurs only under rainstorms with ≥ 100-years return interval, or 1% annual exceedance probability. Sheetwash efficiency rises with downslope distance; beyond a threshold distance of \~100 m, runoff during rainstorms with such annual exceedance probability are capable of transporting surface clasts. The erosion efficiency of these discrete rare events highlights their potential importance in shaping the landscape of arid regions. Our results support the hypothesis that a shift in the properties and frequency of extreme events can trigger significant geomorphic transitions in areas that remained hyperarid during the entire Quaternary. © 2020 John Wiley & Sons, Ltd.
Armon M, Marra F, Enzel Y, Rostkier-Edelstein D, Morin E. Radar-based characterisation of heavy precipitation in the eastern Mediterranean and its representation in a convection-permitting model. Hydrology and Earth System Sciences. 2020;24 (3) :1227–1249.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.
Garfinkel CI, Adam O, Morin E, Enzel Y, Elbaum E, Bartov M, Rostkier-Edelstein D, Dayan U. The Role of Zonally Averaged Climate Change in Contributing to Intermodel Spread in CMIP5 Predicted Local Precipitation Changes. Journal of Climate [Internet]. 2020;33 (3) :1141–1154. Publisher's VersionAbstract
AbstractWhile CMIP5 models robustly project drying of the subtropics and more precipitation in the tropics and subpolar latitudes by the end of the century, the magnitude of these changes in precipitation varies widely across models: for example, some models simulate no drying in the eastern Mediterranean while others simulate more than a 50% reduction in precipitation relative to the model-simulated present-day value. Furthermore, the factors leading to changes in local subtropical precipitation remain unclear. The importance of zonal-mean changes in atmospheric structure for local precipitation changes is explored in 42 CMIP5 models. It is found that up to half of the local intermodel spread over the Mediterranean, northern Mexico, East Asia, southern Africa, southern Australia, and southern South America is related to the intermodel spread in large-scale processes such as the magnitude of globally averaged surface temperature increases, Hadley cell widening, polar amplification, stabilization of the tropical upper troposphere, or changes in the polar stratosphere. Globally averaged surface temperature increases account for intermodel spread in land subtropical drying in the Southern Hemisphere but are not important for land drying adjacent to the Mediterranean. The factors associated with drying over the eastern Mediterranean and western Mediterranean differ, with stabilization of the tropical upper troposphere being a crucial factor for the former only. Differences in precipitation between the western and eastern Mediterranean are also evident on interannual time scales. In contrast, the global factors examined here are unimportant over most of the United States, and more generally over the interior of continents. Much of the rest of the spread can be explained by variations in local relative humidity, a proxy also for zonally asymmetric circulation and thermodynamic changes.
2019
Zoccatelli D, Marra F, Armon M, Rinat Y, Smith JA, Morin E. Contrasting rainfall-runoff characteristics of floods in Desert and Mediterranean basins. Hydrology and Earth System Sciences Discussions. 2019;12 :2665–2678.Abstract
Abstract. Catchment scale hydrological studies on drylands are lacking because of the scarcity of consistent data: observations are often available at the plot scale, but their relevance for the catchment scale remains unclear. A database of 24 years of stream gauge discharge and homogeneous high-resolution radar data over the eastern Mediterranean allows to describe the properties of moderate floods over catchments spanning from Desert to Mediterranean climates. Comparing two climatic regions, Desert and Mediterranean, we are able to better identify specific rainfall-runoff properties. Despite the large differences in rainfall forcing between the two regions, the resulting unit peak discharges and runoff coefficients are comparable. In Mediterranean areas rain depth and antecedent conditions are the most important properties to shape flood response. In Deserts, instead, storm core properties display a strong correlation with unit peak discharge and, to a less extent, with runoff coefficient. In this region, an inverse correlation with mean catchment annual precipitation suggests also a strong influence of local surface properties. Preliminary analyses suggest that floods in catchments with wet headwater and dry lower section are more similar to desert catchments, with a strong influence of storm core properties on runoff generation.
Silver M, Karnieli A, Marra F, Fredj E. An evaluation of weather radar adjustment algorithms using synthetic data. Journal of Hydrology [Internet]. 2019;576 (February) :408–421. Publisher's VersionAbstract
Adjustment of weather radar estimates using observed precipitation has been an accepted procedure for decades. Ground observations of precipitation typically come from rain gauges, but can also include data from diverse networks of sensors, with different levels of reliability. This study presents a standardized framework for evaluating adjustment algorithms using synthetically constructed, but realistic, rain grids and weather radar rainfall. Ground observation points are randomly placed throughout the synthetic storm domain and the precipitation for each sensor is extracted from the true rain. Then a subset of the sensors are defined as unreliable, and a log-normal error factor is applied at those locations. This double network of rain sensors could be applicable, for example, when rainfall is derived from signal attenuation between commercial microwave link (CML) antennas. Past research has tested CML observations as a source of precipitation data and validated various radar adjustment algorithms. However, a comprehensive evaluation of adjustment algorithms using accurate gauge data mixed with CML observations at different densities is lacking. Five adjustment algorithms are applied to the synthetic radar grid: Mean Field Bias (MFB), a Multiplicative algorithm, Mixed (additive and multiplicative), Conditional Merge (CondMerge) and Kriging with External Drift (KED). Generation of the synthetic framework, and application of the adjustment algorithms is repeated for 150 realizations. Comparison of coefficient of determination (R2), root mean square error and linear regression for all adjustment procedures over all realizations indicates the following results. Only MFB and KED adjustments performed well when using accurate gauges. The kriging based KED was able to achieve good adjustment also with the addition of error-prone sensors. CondMerge and the Mixed and Multiplicative, however, resulted in poorer adjustments.
Armon M, Morin E, Enzel Y. Overview of modern atmospheric patterns controlling rainfall and floods into the Dead Sea: Implications for the lake's sedimentology and paleohydrology. Quaternary Science Reviews [Internet]. 2019;216 :58–73. Publisher's VersionAbstract
The Dead Sea sedimentary fill is the basis for interpreting limnological conditions and regional paleo- hydrology. Such interpretations require an understanding of present-day hydroclimatology to reveal the relative impact of different atmospheric circulation patterns on water and sediment delivery to the Dead Sea. Here we address the most important meteorological conditions governing regional and local rain- storm occurrences, with different discharge characteristics. These meteorological controls over the Dead Sea watershed offer insights into past hydrometeorological processes that could have governed the Dead Sea water budget, seasonal and annual flows, floods, and the resultant sedimentology. Rainfall is typically associated with synoptic-scale circulation patterns forced by an upper-level trough that include Medi- terranean cyclones (MCs), active Red Sea troughs (ARSTs), and active subtropical jets (STJs), although other rainstorms and sub-synoptic processes also affect the region. We point to their relative importance in inflow volume, peak discharges, and delivery of sediments from the various environments of the basin. MCs control the annual water amount discharging into the Dead Sea. A change in their frequency, in- tensity, or latitude can substantially alter the lake water balance. A change in frequency or intensity of ARSTs and STJs affects extreme flood and sediment discharge. Floods reach the lake through (a) the Mediterranean-climate-controlled Lower Jordan River, (b) desert-climate-controlled Nahal HaArava, and (c) the arid wadies draining directly into the Dead Sea, some with wetter headwaters. Floods in the wetter parts of the watershed are mainly controlled by MCs, and characterized by larger frequency, volume, and duration, but lower peak discharges and possibly sediment delivery, than floods in the desert parts, which can be produced by the three synoptic types. ARSTs contribute to heavy rainfall, typically of a spotty nature, in the desert parts of the watershed. STJs are currently rare, but their rainfall accumulation may be greater than the annual mean over a broad area in the southern dry Dead Sea watershed. This article presents a review of recent studies, which is extended with new analyses of meteorological, rainfall and flood data, underlining the importance of the Lower Jordan River in sup- plying water volume to the Dead Sea, as compared to the high-discharge, low-volume floods of the arid part of the watershed. Our analyses will help interpret paleoenvironmental conditions in the Dead Sea sedimentary record, and cope with the region's changing climate.
Marra F, Nikolopoulos EI, Anagnostou EN, Bárdossy A, Morin E. Precipitation frequency analysis from remotely sensed datasets: A focused review. Journal of Hydrology [Internet]. 2019;574 (October 2018) :699–705. Publisher's VersionAbstract
Information on extreme precipitation is essential to managing weather-related risks and designing hydraulic structures. Research attention to frequency analyses based on remotely sensed precipitation datasets, such as those obtained from weather radars and satellites, has been rapidly increasing owing to their potential to provide information for ungauged regions worldwide. Together with the ability to measure the areal scale directly, these analyses promise to overcome the sampling limitations of traditional methods based on rain gauges. This focused review of the literature depicts the state of the art after a decade of efforts, and identifies the crucial gaps in knowledge and methodology that currently hinder the quantitative use of remotely sensed datasets in water resources system design and operation. It concludes by highlighting a set of research directions promising immediate impact with regard to the separation of the sources of uncertainty currently affecting applications based on remotely sensed datasets, the development of statistical methods that can cope with the peculiar characteristics of these datasets, and the improvement of validation methods. Important gains in knowledge are expected from the explicit inclusion of the areal dimension in the analyses and from the fine-scale investigation of extreme precipitation climatology.
Marra F, Zoccatelli D, Armon M, Morin E. A simplified MEV formulation to model extremes emerging from multiple nonstationary underlying processes. Advances in Water Resources [Internet]. 2019;127 (March) :280–290. Publisher's VersionAbstract

This paper presents a Simplified Metastatistical Extreme Value formulation (SMEV) able to model hydro- meteorological extremes emerging from multiple underlying processes. The formulation explicitly includes the average intensity and probability of occurrence of the processes allowing to parsimoniously model changes in these quantities to quantify changes in the probability of occurrence of extremes. SMEV allows (a) frequency analyses of extremes emerging from multiple underlying processes and (b) computationally efficient analyses of the sensitivity of extreme quantiles to changes in the characteristics of the underlying processes; moreover, (c) it provides a robust framework for explanatory models, nonstationary frequency analyses, and climate projections. The methodology is applied to daily precipitation data from long recording stations in the eastern Mediter-
ranean, using Weibull distributions to model daily precipitation amounts generated by two classes of synoptic systems. At-site application of SMEV provides spatially consistent estimates of extreme quantiles, in line with regional GEV estimates and generally characterized by reduced uncertainties. The sensitivity of extreme quan- tiles to changes and uncertainty in the intensity and yearly occurrences of events generated by different synoptic classes is examined, and an application of SMEV for the projection of future extremes is provided.

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