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The Mediterranean area is prone to intense rainfall events triggering flash floods, characterized by very short response times that sometimes lead to dramatic consequences in terms of casualties and damages. These events can affect large territories, but their impact may be very local in catchments that are generally ungauged. These events remain difficult to predict and the processes leading to their generation still need to be clarified. The HyMeX initiative (Hydrological Cycle in the Mediterranean Experiment, 2010-2020) aims at increasing our understanding of the water cycle in the Mediterranean basin, in particular in terms of extreme events. In order to better understand processes leading to flash floods, a four-year experiment (2012-2015) was conducted in the Cévennes region (South-East) France as part of the FloodScale project. Both continuous and opportunistic measurements during floods were conducted in two large catchments (Ardèche and Gard rivers) with nested instrumentation from the hillslopes to catchments of about 1, 10, 100 to 1000 km2 covering contrasted geology and land use. Continuous measurements include distributed rainfall, stream water level, discharge, water temperature and conductivity and soil moisture measurements. Opportunistic measurements include surface soil moisture and geochemistry sampling during events and gauging of floods using non-contact methods: portable radars to measure surface water velocity or image sequence analysis using LS-PIV (Large Scale Particle Image Velocimetry). During the period 2012-2014, and in particular during autumn 2014, several intense events affected the catchments and provided very rich data sets. Data collection was complemented with modelling activity aiming at simulating observed processes. The modelling strategy was setup through a wide range of scales, in order to test hypotheses about physical processes at the smallest scales, and aggregated functioning hypothesis at the largest scales. During the project, a focus was also put on the improvement of rainfall fields characterization both in terms of spatial and temporal variability and in terms of uncertainty quantification. Rainfall reanalyses combining radar and rain gauges were developed. Rainfall simulation using a stochastic generator was also performed. Another effort was dedicated to the improvement of discharge estimation during floods and the quantification of streamflow uncertainties using Bayesian techniques. The paper summarizes the main results gained from the observations and the subsequent modelling activity in terms of flash flood process understanding at the various scales. It concludes on how the new acquired knowledge can be used for prevention and management of flash floods.

Nonuniform beam filling associated with the vertical variation of atmospheric reflectivity is an important source of error in the estimation of rainfall rates by radar. It is, however, possible to correct for this error if the vertical profile of reflectivity (VPR) is known. This paper presents a method for identifying VPRs from volumetric radar data. The method aims at improving an existing algorithm based on the analysis of ratios of radar measurements at multiple elevation angles. By adding a rainfall classification procedure defining more homogeneous precipitation patterns, the issue of VPR homogeneity is specifically addressed. The method is assessed using the dataset from a volume-scanning strategy for radar quantitative precipitation estimation designed in 2002 for the Bollene radar (France). The identified VPR is more representative of the rain field than are other estimated VPRs. It has also a positive impact on radar data processing for precipitation estimation: while scatter remains unchanged, an overall bias reduction at all time steps is noticed (up to 6% for all events) whereas performance varies with type of events considered (mesoscale convective systems, cold fronts, or shallow convection) according to the radar-observation conditions. This is attributed to the better processing of spatial variations of the vertical profile of reflectivity for the stratiform regions. However, adaptation of the VPR identification in the difficult radar measurement context in mountainous areas and to the rainfall classification procedure proved challenging because of data fluctuations. DOI: 10.1175/2010JAMC2369.1

The RadAlp experiment aims at improving quantitative precipitation estimation (QPE) in the Alps thanks to X-band polarimetric radars and in situ measurements deployed in the region of Grenoble, France. In this article, we revisit the physics of propagation and attenuation of microwaves in rain. We first derive four attenuation–reflectivity (AZ) algorithms constrained, or not, by path-integrated attenuations (PIAs) estimated from the decrease in the return of selected mountain targets when it rains compared to their dry weather levels (the so-called mountain reference technique – MRT). We also consider one simple polarimetric algorithm based on the profile of the total differential phase shift between the radar and the mountain targets. The central idea of the work is to implement these five algorithms all together in the framework of a generalized sensitivity analysis in order to establish useful parameterizations for attenuation correction. The parameter structure and the inherent mathematical ambiguity of the system of equations makes it necessary to organize the optimization procedure in a nested way. The core of the procedure consists of (i) exploring with classical sampling techniques the space of the parameters allowed to be variable from one target to the other and from one time step to the next, (ii) computing a cost function (CF) quantifying the proximity of the simulated profiles and (iii) selecting parameters sets for which a given CF threshold is exceeded. This core is activated for a series of values of parameters supposed to be fixed, e.g., the radar calibration error for a given event. The sensitivity analysis is performed for a set of three convective events using the 0 ∘ elevation plan position indicator (PPI) measurements of the Météo-France weather radar located on top of the Moucherotte mountain (altitude of 1901 m a.s.l. – above sea level). It allows the estimation of critical parameters for radar QPE using radar data alone. In addition to the radar calibration error, this includes the time series of radome attenuation and estimations of the coefficients of the power law models relating the specific attenuation and the reflectivity (A – Z relationship) on the one hand and the specific attenuation and the specific differential phase shift (A – Kdp relationship) on the other hand. It is noteworthy that the A – Z and A – Kdp relationships obtained are consistent with those derived from concomitant drop size distribution measurements at ground level, in particular with a slightly non-linear A – Kdp relationship (A=0.28 Kdp1.1). X-Band radome attenuations as high as 15 dB were estimated, leading to the recommendation of avoiding the use of radomes for remote sensing of precipitation at such a frequency. [ABSTRACT FROM AUTHOR]

Sensitivity analysis using two simulated but realistic profiles helps test the efficiency of an inverse method to identify vertical profile of reflectivity. Application of this method produces acceptable results, indicating the operational efficiency of the method. The method is successfully applied for two rainfall events observed in the Cevennes region of France. A comparative study of the theoretical results with data from rain gauges and radar reveals that introduction of a correction term for the influence of vertical profiles of reflectivity improves the accuracy of the estimation of rainfall from radar data.

The RadAlp experiment aims at developing advanced methods for rainfall and snowfall estimation using weather radar remote sensing techniques in high mountain regions for improved water resource assessment and hydrological risk mitigation. A unique observation system has been deployed since 2016 in the Grenoble region of France. It is composed of an X-band radar operated by Météo-France on top of the Moucherotte mountain (1901 m above sea level; hereinafter MOUC radar). In the Grenoble valley (220 m above sea level; hereinafter a.s.l.), we operate a research X-band radar called XPORT and in situ sensors (weather station, rain gauge and disdrometer). In this paper we present a methodology for studying the relationship between the differential phase shift due to propagation in precipitation (Φdp) and path-integrated attenuation (PIA) at X band. This relationship is critical for quantitative precipitation estimation (QPE) based on polarimetry due to severe attenuation effects in rain at the considered frequency. Furthermore, this relationship is still poorly documented in the melting layer (ML) due to the complexity of the hydrometeors' distributions in terms of size, shape and density. The available observation system offers promising features to improve this understanding and to subsequently better process the radar observations in the ML. We use the mountain reference technique (MRT) for direct PIA estimations associated with the decrease in returns from mountain targets during precipitation events. The polarimetric PIA estimations are based on the regularization of the profiles of the total differential phase shift (Ψdp) from which the profiles of the specific differential phase shift on propagation (Kdp) are derived. This is followed by the application of relationships between the specific attenuation (k) and the specific differential phase shift. Such k – Kdp relationships are estimated for rain by using drop size distribution (DSD) measurements available at ground level. Two sets of precipitation events are considered in this preliminary study, namely (i) nine convective cases with high rain rates which allow us to study the ϕdp –PIA relationship in rain, and (ii) a stratiform case with moderate rain rates, for which the melting layer (ML) rose up from about 1000 up to 2500 m a.s.l., where we were able to perform a horizontal scanning of the ML with the MOUC radar and a detailed analysis of the ϕdp –PIA relationship in the various layers of the ML. A common methodology was developed for the two configurations with some specific parameterizations. The various sources of error affecting the two PIA estimators are discussed, namely the stability of the dry weather mountain reference targets, radome attenuation, noise of the total differential phase shift profiles, contamination due to the differential phase shift on backscatter and relevance of the k – Kdp relationship derived from DSD measurements, etc. In the end, the rain case study indicates that the relationship between MRT-derived PIAs and polarimetry-derived PIAs presents an overall coherence but quite a considerable dispersion (explained variance of 0.77). Interestingly, the nonlinear k – Kdp relationship derived from independent DSD measurements yields almost unbiased PIA estimates. For the stratiform case, clear signatures of the MRT-derived PIAs, the corresponding ϕdp value and their ratio are evidenced within the ML. In particular, the averaged PIA/ϕdp ratio, a proxy for the slope of a linear k – Kdppage3732 relationship in the ML, peaks at the level of the copolar correlation coefficient (ρhv) peak, just below the reflectivity peak, with a value of about 0.42 dB per degree. Its value in rain below the ML is 0.33 dB per degree, which is in rather good agreement with the slope of the linear k – Kdp relationship derived from DSD measurements at ground level. The PIA/ϕdp ratio remains quite high in the upper part of the ML, between 0.32 and 0.38 dB per degree, before tending towards 0 above the ML. [ABSTRACT FROM AUTHOR]

The RadAlp experiment aims at developing advanced methods for rain and snow estimation using weather radar remote sensing techniques in high mountain regions for improved water resource assessment and hydrological risk mitigation. A unique observation system has been deployed since 2016 in the Grenoble region, France. It is composed of a X-band radar operated by Météo-France on top of the Mt Moucherotte (1970 m asl; MOUC radar hereinafter). In the Grenoble valley (220 m asl), we operate a research X-band radar called XPORT and in situ sensors (weather station, rain gauge, disdrometer). We present in this article a methodology for studying the relationship between the total differential phase (ψdp) and path-integrated attenuation (PIA) at X-Band, a relationship critical for the implementation of attenuation corrections based on polarimetry. We use the Mountain Reference Technique for direct PIA estimations associated with the decrease of returns from mountain targets during precipitation events. The polarimetric PIA estimations are based on the regularization of the ψdp radial profiles and their derivation in terms of specific differential phase (Kdp) profiles, followed by the application of relationships between the specific attenuation and the specific differential phase. Such k - Kdp relationships are estimated for rain by using available DSD measurements, empirical oblateness models for raindrops and a scattering model. Two contrasted precipitation events are considered in this preliminary study: (i) a convective case with strong rainrates allows us to study the Φdp-PIA relationship in rain; (ii) during a stratiform case with moderate rainrates, for which the melting layer (ML) rose up from about 1000 m asl up to 2500 m asl, we were able to perform a horizontal scanning of the ML with the MOUC radar and a detailed analysis of the Φdp-PIA relationship in the various parts of the ML. The rain case study indicates that the relationship between MRT-derived PIAs and polarimetry-derived PIAs presents a considerable dispersion (explained variance of 0.72) in rain. Interestingly, the non-linear k - Kdp relationship derived from independent DSD measurements allows obtaining almost unbiased PIA estimates. For the stratiform case, the averaged PIA/ψdp ratio peaks within the melting layer at the level of the co-polar correlation coefficient (ρhv) peak, just below the reflectivity peak, with a value of about 0.4 dB°-1. Its value in rain below the ML is 0.27 dB°-1, in very good agreement with the slope of the linear k - Kdp relationship derived from DSD measurements at ground level. The PIA/ψdp ratio remains quite strong in the upper part of the ML, between 0.32 and 0.38 dB°-1, before tending towards 0 above the ML. [ABSTRACT FROM AUTHOR]

This paper describes an integrated, high-resolution dataset of hydro-meteorological variables (rainfall and discharge) concerning a number of high-intensity flash floods that occurred in Europe and in the Mediterranean region from 1991 to 2015. This type of dataset is rare in the scientific literature because flash floods are typically poorly observed hydrological extremes. Valuable features of the dataset (hereinafter referred to as the EuroMedeFF database) include (i) its coverage of varied hydro-climatic regions, ranging from Continental Europe through the Mediterranean to Arid climates, (ii) the high space–time resolution radar rainfall estimates, and (iii) the dense spatial sampling of the flood response, by observed hydrographs and/or flood peak estimates from post-flood surveys. Flash floods included in the database are selected based on the limited upstream catchment areas (up to 3000 km 2), the limited storm durations (up to 2 days), and the unit peak flood magnitude. The EuroMedeFF database comprises 49 events that occurred in France, Israel, Italy, Romania, Germany and Slovenia, and constitutes a sample of rainfall and flood discharge extremes in different climates. The dataset may be of help to hydrologists as well as other scientific communities because it offers benchmark data for the identification and analysis of the hydro-meteorological causative processes, evaluation of flash flood hydrological models and for hydro-meteorological forecast systems. The dataset also provides a template for the analysis of the space–time variability of flash flood triggering rainfall fields and of the effects of their estimation on the flood response modelling. The dataset is made available to the public with the following DOI: 10.6096/MISTRALS-HyMeX.1493. [ABSTRACT FROM AUTHOR]

This paper describes an integrated, high-resolution dataset of hydro-meteorological variables (rainfall and discharge) concerning a number of high-intensity flash floods that occurred in Europe and in the Mediterranean region from 1991 to 2015. This type of dataset is rare in the scientific literature because flash floods are typically poorly observed hydrological extremes. Valuable features of the dataset (hereinafter referred to as EuroMedeFF database) include i) its coverage of varied hydro-climatic regions, ranging from Continental Europe through the Mediterranean to Arid climates, ii) the high space-time resolution radar-rainfall estimates, and iii) the dense spatial sampling of the flood response, by observed hydrographs and/or flood peak estimates from post-flood surveys. Flash floods included in the database are selected based on the limited upstream catchment areas (up to 3000 km2), the limited storm durations (up to 2 days), and the unit peak flood magnitude. The EuroMedeFF database comprises 49 events that occurred in France, Israel, Italy, Romania, Germany, and Slovenia, and constitutes a sample of rainfall and flood discharge extremes in different climates. The dataset may be of help to hydrologists as well as other scientific communities because it offers benchmark data for the identification and analysis of the hydro-meteorological causative processes, evaluation of flash flood hydrological models and for hydro-meteorological forecast systems. The dataset also provides a template for the analysis of the space-time variability of flash flood-triggered rainfall fields and of the effects of their estimation on the flood response modelling. [ABSTRACT FROM AUTHOR]

Mediterranean regions are prone to heavy rainfall, flash floods, and erosion issues. Drop size distribution (DSD) is a key element for studying these phenomena through the hydrological variables which can be derived from it (rainfall rates and totals, kinetic energy fluxes). This paper proposes a five-year (2012-2016) DSD climatology, summarized by scaling parameters for concentration, size, and shape. The DSD network is composed of two longitudinal transects of three OTT Parsivel optical disdrometers each, across the Mediterranean Cevennes-Vivarais region. The influence of several factors are analysed: location (distance from the sea, orographic environment), season, daily synoptic weather situation (derived from geopotential heights, at 700 and 1000 hPa), rainfall type (analysed from 5 min radar data), as well as some combinations of these factors. It was found and/or confirmed that the orographic environment, season, weather patterns associated with the exposure to low level atmospheric flows, and rainfall types influenced the microphysical processes, leading to rainfall, measured at the ground. Consequently, the DSD characteristics, as well as the relationships between the rainfall rate and reflectivity factor, are influenced by these factors. [ABSTRACT FROM AUTHOR]

A comprehensive hydrometeorological dataset is presented spanning the period 1 January 2011-31 December 2014 to improve the understanding of the hydrological processes leading to flash floods and therelation between rainfall, runoff, erosion and sediment transport in a mesoscale catchment (Auzon, 116 km²)of the Mediterranean region. Badlands are present in the Auzon catchment and well connected to high-gradientchannels of bedrock rivers which promotes the transfer of suspended solids downstream. The number of observedvariables, the various sensors involved (both in situ and remote) and the space-time resolution (~km²,~min) of this comprehensive dataset make it a unique contribution to research communities focused on hydrometeorology, surface hydrology and erosion. Given that rainfall is highly variable in space and time in this region, the observation system enables assessment of the hydrological response to rainfall fields. Indeed, (i) rainfall dataare provided by rain gauges (both a research network of 21 rain gauges with a 5 min time step and an operationalnetwork of 10 rain gauges with a 5 min or 1 h time step), S-band Doppler dual-polarization radars (1 km², 5 minresolution), disdrometers (16 sensors working at 30 s or 1 min time step) and Micro Rain Radars (5 sensors, 100m height resolution). Additionally, during the special observation period (SOP-1) of the HyMeX (HydrologicalCycle in the Mediterranean Experiment) project, two X-band radars provided precipitation measurements at very fine spatial and temporal scales (1 ha, 5 min). (ii) Other meteorological data are taken from the operationalsurface weather observation stations of Météo-France (including 2m air temperature, atmospheric pressure, 2mrelative humidity, 10m wind speed and direction, global radiation) at the hourly time resolution (six stationsin the region of interest). (iii) The monitoring of surface hydrology and suspended sediment is multi-scale andbased on nested catchments. Three hydrometric stations estimate water discharge at a 2-10 min time resolution. Two of these stations also measure additional physico-chemical variables (turbidity, temperature, conductivity)and water samples are collected automatically during floods, allowing further geochemical characterization ofwater and suspended solids. Two experimental plots monitor overland flow and erosion at 1 min time resolutionon a hillslope with vineyard. A network of 11 sensors installed in the intermittent hydrographic network continuouslymeasures water level and water temperature in headwater subcatchments (from 0.17 to 116 km²) at atime resolution of 2-5 min. A network of soil moisture sensors enables the continuous measurement of soil volumetricwater content at 20 min time resolution at 9 sites. Additionally, concomitant observations (soil moisturemeasurements and stream gauging) were performed during floods between 2012 and 2014. Finally, this datasetis considered appropriate for understanding the rainfall variability in time and space at fine scales, improvingareal rainfall estimations and progressing in distributed hydrological and erosion modelling. [ABSTRACT FROM AUTHOR]

A comprehensive hydrometeorological dataset is presented spanning the period 1 January 2011-31 December 2014 to improve the understanding of the hydrological processes leading to flash floods and the relation between rainfall, runoff, erosion and sediment transport in a mesoscale catchment (Auzon, 116 km2) of the Mediterranean region. Badlands are present in the Auzon catchment and well connected to high gradient channels of bedrock rivers which promotes the transfer of suspended solids downstream. The specificity of the dataset is its high space-time resolution, especially concerning rainfall and the hydrological response which is particularly adapted to the highly spatially variable rainfall events that may occur in this region. This type of dataset is rare in scientific literature because of the quantity and type of sensors for meteorology and surface hydrology. Rainfall data include continuous precipitation measured by rain gauges (5 min time step for the research network of 21 rain gauges and 5 min or 1 h time step for the operational network of 10 rain gauges), S-band Doppler dual-polarization radars (1 km2, 5 min resolution), disdrometers (16 sensors working at 30 s or 1 min time step) and Micro Rain Radars (5 sensors, 100 m height resolution). Additionally, during the special observation period (SOP-1) and enhanced observation period (Sep-Dec 2012, Sep-Dec 2013) of the HyMeX (Hydrological Cycle in the Mediterranean Experiment) project, two X-band radars provided precipitation measurements at very fine spatial and temporal scales (1 ha, 5 min). Meteorological data are taken from the operational surface weather observation stations of Météo-France (including 2-m air temperature, atmospheric pressure, 2-m relative humidity, 10-m wind speed and direction, global radiation) at the hourly time resolution (6 stations in the region of interest). The monitoring of surface hydrology and suspended sediment is multi-scale and based on nested catchments. Three hydrometric stations measure water discharge at a 2 to 10 min time resolution. Two of these stations also measure additional physico-chemical variables (turbidity, temperature, conductivity) and water samples are collected automatically during floods allowing further geochemical characterization of water and suspended solids. Two experimental plots monitor overland flow and erosion at 1 min time resolution on a hillslope with vineyard. A network of 11 sensors installed in the intermittent hydrographic network continuously measures water level and water temperature in headwater subcatchments (from 0.17 km2 to 116 km2) at a time resolution of 2-5 min. A network of soil moisture sensors enable the continuous measurement of soil volumetric water content at 20 min time resolution at 9 sites. Additionally, opportunistic observations (soil moisture measurements and stream gauging) were performed during floods between 2012 and 2014. The data are appropriate for understanding the rainfall variability in time and space at fine scales, improving areal rainfall estimations and progressing in distributed hydrological and erosion modelling. [ABSTRACT FROM AUTHOR]

Compared to other estimation techniques, one advantage of geostatistical techniques is that they provide an index of the estimation accuracy of the variable of interest with the kriging estimation standard deviation (ESD). In the context of radar-raingauge quantitative precipitation estimation (QPE), we address in this article the question of how the kriging ESD can be transformed into a local spread of error by using the dependency of radar errors to the rain amount analyzed in previous work. The proposed approach is implemented for the most significant rain events observed in 2008 in the Cévennes-Vivarais region, France, by considering both the kriging with external drift (KED) and the ordinary kriging (OK) methods. A two-step procedure is implemented for estimating the rain estimation accuracy: (i) first kriging normalized ESDs are computed by using normalized variograms (sill equal to 1) to account for the observation system configuration and the spatial structure of the variable of interest (rainfall amount, residuals to the drift); (ii) based on the assumption of a linear relationship between the standard deviation and the mean of the variable of interest, a denormalization of the kriging ESDs is performed globally for a given rain event by using a cross-validation procedure. Despite the fact that the KED normalized ESDs are usually greater than the OK ones (due to an additional constraint in the kriging system and a weaker spatial structure of the residuals to the drift), the KED denormalized ESDs are generally smaller the OK ones, a result consistent with the better performance observed for the KED technique. The evolution of the mean and the standard deviation of the rainfall-scaled ESDs over a range of spatial (5-300km2) and temporal (1-6h) scales demonstrates that there is clear added value of the radar with respect to the raingauge network for the shortest scales, which are those of interest for flash-flood prediction in the considered region. [ABSTRACT FROM AUTHOR]

Radar quantitative precipitation estimates (QPEs) were assessed using reference values established by means of a geostatistical approach. The reference values were estimated from raingauge data using the block kriging technique, and the reference meshes were selected on the basis of the kriging estimation variance. Agreement between radar QPEs and reference rain amounts was shown to increase slightly with the space–time scales. The statistical distributions of the errors were modelled conditionally with respect to several factors using the GAMLSS approach. The conditional bias of the errors presents a complex structure that depends on the space–time scales and the considered geographical sub-domains, while the standard deviation of the errors has a more homogeneous behaviour. The estimation standard deviation of the reference rainfall and the standard deviation of the errors between radar and reference rainfall were found to have the same magnitude, indicating the limitations of the available network in terms of providing accurate reference values for the spatial scales considered (5–100 km2).Editor D. Koutsoyiannis; Guest editor R.J. MooreCitation Delrieu, G., Bonnifait, L., Kirstetter, P.-E., and Boudevillain, B., 2013. Dependence of radar quantitative precipitation estimation error on the rain intensity in the Cévennes region, France. Hydrological Sciences Journal, 59 (7), 1300–1311. http://dx.doi.org/10.1080/02626667.2013.827337 [ABSTRACT FROM AUTHOR]

This study offers an approach to estimate the rainfall kinetic energy (KE) by rain intensity (R) and radar reflectivity factor (Z) separately or jointly on the basis of a one- or two-moment scaled raindrop size distribution (DSD) formulation, which contains (1) R and/or Z observations and (2) the dimensionless probability density function (pdf) of a scaled raindrop diameter. The key point is to explain all variability of the DSD by the evolution of the explaining moments (R and Z); hence the pdf is considered as constant. A robust method is proposed to estimate the climatological values of the parameters with a 28 month DSD data set collected in the Cévennes-Vivarais region of France. Three relationships (KE-R, KE-Z, and KE-RZ), which link the observations (R and/or Z) to rainfall kinetic energy (KE), are established. As expected, the assessment using the disdrometer data indicates that (1) because of the proximity of the moment orders, the KE-Z relationship exhibits less variability than the KE-R relationship and (2) the combination of R and Z yields a significant improvement of the estimation of KE compared to the single-moment formulations. Subsequently, a first attempt to spatialize the kinetic energy using radar and rain gauge measurements is presented for a convective event, showing a promising potential for erosion process studies. Different from the application with the disdrometer data, the performance of the KE-Z relationship degrades compared to the KE-R relationship as a result of a bias and/or the sampling characteristics of the radar data. [ABSTRACT FROM AUTHOR]

Intense rain events frequently result in devastating flash floods in Mediterranean regions. To improve the understanding and prediction of these phenomena, the Cévennes-Vivarais Mediterranean Hydrometeorological Observatory (CVMHO) was set up in 2000. The observation strategies deployed include the detailed and long-lasting (>10 years) observation in the Cévennes-Vivarais region (France) using both operational observation systems and research instrumentation. The present note describes the procedures implemented by CVMHO to critically analyze and generate hydrometeorological products for research. The related data can be viewed or downloaded via the Système d'Extraction et de Visualisation des Données de l'Observatoire en Ligne (SEVnOL) interface on the CVMHO Web site. [ABSTRACT FROM AUTHOR]

The article discusses a study which explores the flash flood in Selška Sora watershed in Western Slovenia on September 18, 2007. It notes that high speak flood discharges at an estimated 22 cross sections and a complex flood response are revealed in the documentation of the flash flood. It further states that the lessons learned from the disaster include importance of having quality controlled weather radar data.

Abstract: On 8–9 September 2002, an extreme rainfall event caused by a stationary mesoscale convective system (MCS) occurred in the Gard region, France. Distributed hydrologic and hydraulic modelling has been carried out to assess and compare the various sources of data collected operationally and during the post-event field surveys. Distributed hydrological modelling was performed with n-TOPMODELs and assessed for ungauged basins with the discharge estimates of the post-event surveys. A careful examination of the occurrence in time and space of the flash floods over the head watersheds indicates that flooding was controlled by the trajectory of the convective part of the MCS. Stationarity of the MCS over the Gardon watershed (1858km2 at Remoulins) for 28h was responsible for the exceptional magnitude of the flood at this scale. The flood dynamics were characterized by an extensive inundation of the Gardonnenque plain upstream of the Gardon Gorges resulting in a significant peak flow reduction downstream. One-dimensional unsteady-flow hydraulic modelling was found to be required to reproduce these dynamics. Hydraulic modelling also proved to be potentially useful for the critical analysis and extrapolation of operational discharge rating curves. [Copyright &y& Elsevier]

A full radar simulator for high-resolution (1-5 km) nonhydrostatic models has been developed within the research nonhydrostatic mesoscale atmospheric (Meso-NH) model. This simulator is made up of building blocks, each of which describes a particular physical process (scattering, beam bending, etc.). For each of these blocks, several formulations have been implemented. For instance, the radar simulator offers the possibility to choose among Rayleigh, Rayleigh-Gans, Mie, or T-matrix scattering methods, and beam bending can be derived from an effective earth radius or can depend on the vertical gradient of the refractive index of air. Moreover, the radar simulator is fully consistent with the microphysical parameterizations used by the atmospheric numerical model. Sensitivity experiments were carried out using different configurations for the simulator. They permitted the specification of an observation operator for assimilation of radar reflectivities by high-resolution nonhydrostatic numerical weather prediction systems, as well as for their validation. A study of the flash flood of 8-9 September 2002 in southeastern France, which was well documented with volumetric data from an S-band radar, serves to illustrate the capabilities of the radar simulator as a validation tool for a mesoscale model. [ABSTRACT FROM AUTHOR]

The present study aims to demonstrate the major influence of the vertical heterogeneity of rainfall on radar–rain gauge assessment. For this purpose, an experimental setup was deployed during the HYDROMET Integrated Radar Experiment (HIRE-98) based on a conventional S-band weather radar operating at long range (90 km), an X-band vertically pointing radar, and a network of 25 tipping-bucket rain gauges. After calibration and attenuation corrections, the X-band radar data enables the estimation of the vertical profile of reflectivity (VPR) time series. Screening and VPR correction factors are derived for the distant S-band radar measurements. The raw and corrected S-band radar estimates are compared to rain gauge measurements for various integration time steps (6–30 min). Considering about 12 h of intense Mediterranean precipitation, the VPR influence at the X-band radar site is clear for all the time steps considered. For instance, a continuous increase in the Nash efficiency for the corrected radar data compared to the rain gauge data (0.85 for the 6-min time step, up to 0.93 for the 30-min time step) is observed while this criterion remains less than 0.15 for the raw radar data, regardless of the time step. The effect of the low-level reflectivity enhancement on the radar–rain gauge assessment was also found to be very important in the considered configuration. The establishment of reliable VPR climatologies is therefore a challenge in order to better account for such effects that are not observable at long range from the radars. The spatial validity of the VPR correction derived from a point sensor like the vertically pointing radar is also investigated. As a result of the high space–time variability of rainfall, such a punctual VPR correction has an efficiency limited to areas of about 20 km2 (200 km2) for the 6-min (30 min) integration time step. [ABSTRACT FROM AUTHOR]

The authors recently showed that when attenuating wavelengths are used mountain returns may allow estimation of path-integrated attenuations (PIAs) between a ground-based weather radar and a given mountain, an application of the well-known Surface Reference Technique originally proposed for spaceborne radar configurations. This information proved to be valuable for the quantitative interpretation of X-band weather radar data in terms of rainfall rate for an urban hydrological application in Marseilles, France. In this paper, a further verification of this concept is presented with the comparison of mountain-derived PIAs and direct measurements obtained by means of a receiving antenna installed in the Balcons de Belledonne mountain ridge near Grenoble, France. Maximum PIAs in the range of 8-16 dB are obtained over the considered 9-km propagation path for various rain events observed between May and July 1997. A physical model of the mountain return power is developed leading to the formulation of two mountain PIA estimators under various hypotheses concerning 1) the stability of both the radar equipment and the electromagnetic properties of the mountain surfaces and 2) the effects of the rain falling over the mountain. A geometric calculation based on the use of a digital terrain model then allows the authors to estimate both the radar-positioning errors and the rain beamfilling factors of the mountain-cluttered radar bins. The dry-weather mountain return time series are also studied, showing a good stability of the average value from one rain event to the next with, however, a marked effect of the wetting of the mountain surfaces. The time variability of these values is also characterized in order to assess the minimum detectable mountain PIA, estimated in the present case to be about 2.25 dB. Finally, a good agreement is observed between the estimated mountain PIAs and the measured ones (with correlation coefficients and regression slopes reaching... [ABSTRACT FROM AUTHOR]

Studies the equation describing attenuation effects in rain for ground-based weather radar systems operating at X- or C-band wavelengths. Relations between average values of the equivalent reflectivity factor, attenuation coefficient and rain rate; Path-integrated attenuation; Influence of the drop size distribution; Instability of the attenuation equation.

The great success of the Tropical Rainfall Measuring Mission (TRMM) and its successor Global Precipitation Measurement (GPM) has accelerated the development of global high-resolution satellite-based precipitation products (SPP). However, the quantitative accuracy of SPPs has to be evaluated before using these datasets in water resource applications. This study evaluates the following GPM-era and TRMM-era SPPs based on two years (2014–2015) of reference daily precipitation data from rain gauge networks in ten mountainous regions: Integrated Multi-SatellitE Retrievals for GPM (IMERG, version 05B and version 06B), National Oceanic and Atmospheric Administration (NOAA)/Climate Prediction Center Morphing Method (CMORPH), Global Satellite Mapping of Precipitation (GSMaP), and Multi-Source Weighted-Ensemble Precipitation (MSWEP), which represents a global precipitation data-blending product. The evaluation is performed at daily and annual temporal scales, and at 0.1 deg grid resolution. It is shown that GSMaPV07 surpass the performance of IMERGV06B Final for almost all regions in terms of systematic and random error metrics. The new orographic rainfall classification in the GSMaPV07 algorithm is able to improve the detection of orographic rainfall, the rainfall amounts, and error metrics. Moreover, IMERGV05B showed significantly better performance, capturing the lighter and heavier precipitation values compared to IMERGV06B for almost all regions due to changes conducted to the morphing, where motion vectors are derived using total column water vapor for IMERGV06B. [ABSTRACT FROM AUTHOR]

The RadAlp experiment aims at developing advanced methods for rain and snow estimation using weather radar remote sensing techniques in high mountain regions for improved water resource assessment and hydrological risk mitigation. A unique observation system has been deployed in the French Alps, Grenoble region. It is composed of a Météo-France operated X-band MOUC radar (volumetric, Doppler and polarimetric) on top of the Mt Moucherotte (1920 m ASL), the X-band XPORT research radar (volumetric, Doppler, polarimetric), a K-band micro rain radar (MRR, Doppler, vertically pointing) and in situ sensors (rain gauges, disdrometers), latter three operated on the Grenoble campus (220 m ASL). Based on the observation that the precipitation phase changes at/below the elevation of mountain-top MOUC radar for more than 60% of the significant events, an algorithm for ML identification has been developed using valley-based radar systems: it uses the quasi vertical profiles of XPORT polarimetric measurements (horizontal and vertical reflectivity, differential reflectivity, cross-polar correlation coefficient) and the MRR vertical profiles of apparent falling velocity spectra. The algorithm produces time series of the altitudes and values of peaks and inflection points of the different radar observables. A literature review allows us to link the micro-physical processes at play during the melting process with the available polarimetric and Doppler signatures, e.g., (i) regarding the altitude differences between the peaks of reflectivity, cross-polar correlation coefficient and differential reflectivity, as well as (ii) regarding the co-variation of the profiles of Doppler velocity spectra and cross-polar correlation coefficient. A statistical analysis of the ML based on 42 rain events (98 h of XPORT data) is then proposed. Among other results, this study indicates that (i) the mean value of the ML width in Grenoble is 610 m with a standard deviation of 160 m; (ii) the mean altitude difference between the horizontal reflectivity and the ρ H V peaks is 90 m and the mean altitude difference between the ρ H V and Zdr peaks is 30 m; (iii) even for the limited rainrate range in the dataset (0–8.5 mm h − 1 ), the "intensity effect" is clear on the reflectivity profile and the ML width, as well as on polarimetric variables such as ρ H V peak value and the Zdr enhancement in the upper part of the profile. On the contrary, the study of both the "density effect" and the influence of the 0   ° C isotherm altitude did not yield significant results with the considered dataset; (iv) a principal component analysis on one hand shows the richness of the dataset since the first 2 PCs explain only 50% of the total variance and on the other hand the added-value of the polarimetric variables since they rank high in a ranking of the total variance explained by individual variables. [ABSTRACT FROM AUTHOR]

In the French Alps the quality of the radar Quantitative Precipitation Estimation (QPE) is limited by the topography and the vertical structure of precipitation. A previous study realized in all the French Alps, has shown a general bias between values of the national radar QPE composite and the rain gauge measurements: a radar QPE over-estimation at low altitude (+20% at 200 m a.s.l.), and an increasing underestimation at high altitudes (until −40% at 2100 m a.s.l.). This trend has been linked to altitudinal gradients of precipitation observed at ground level. This paper analyzes relative altitudinal gradients of precipitation estimated with rain gauges measurements in 2016 for three massifs around Grenoble, and for different temporal accumulations (yearly, seasonal, monthly, daily). Comparisons of radar and rain gauge accumulations confirm the bias previously observed. The parts of the current radar data processing affecting the bias value are pointed out. The analysis shows a coherency between the relative gradient values estimated at the different temporal accumulations. Vertical profiles of precipitation detected by a research radar installed at the bottom of the valley also show how the wide horizontal variability of precipitation inside the valley can affect the gradient estimation. [ABSTRACT FROM AUTHOR]