Assessment and tuning of the behaviour of a microphysical characterisation scheme

International audienceThe correct classification of prevailing bulk hydrometeor type within a radar resolution volume is a challenge task even if a full set of polarimetric radar observables is available. Indeed scattering and propagation effects from the variety of hydrometeors present interact each others and sometimes, if not often, tend to obscure the characteristic signature of each weather radar target type. This consideration is enforced when the atmospheric volume is sampled with a wavelength where both Mie scattering effects and attenuation start to become relevant. In this paper, we utilize the hydrometeor classification scheme developed at the National Severe Storms Laboratory (USA). Briefly, the scheme uses a fuzzy logic approach to combine different polarimetric variables and environmental temperature in order to determine the most likely type of prevalent hydrometeor in the radar volume. This means that the resulting classification is based on two characteristics: the volume polarimetric responses and the thermal value. The relative balance between these two is managed through the coefficients in the fuzzy scheme. We have observed that these parameters are crucial in order to get "physical reasonable result", independently from the meteorological character of the event investigated. Our work is based on a reduced set of polarimetric variables (Z and ZDR) as input. Data used in this study were collected by a C-band radar over weather events ranging from convective to stratiform

IR-based satellite and radar rainfall estimates of convective storms over northern Italy

Convective precipitation events in northern Italy during 1996 and 1997 are analysed using two infrared-based geosynchronous satellite rainfall estimation methods to verify the level of applicability of the techniques for operational applications in the area, their quantitative results, and relative performances. The Negri–Adler–Wetzel (NAW) and the convective stratiform technique (CST) are applied to METEOSAT's thermal infrared (IR) data. C-band radar reflectivity fields detail the vertical and horizontal structure of the cloud systems, and radar rainfall data are retrieved. Satellite rain areas are checked against simultaneous radar rainfall retrievals through a contingency analysis procedure. A semi-quantitative analysis is presented. Positive brightness temperature differences between water vapour and thermal IR channels are also examined and related to the storms' development stage and rainrate. Results show that NAW and CST perform reasonably in delimiting rain areas during active convection and care should be used in the initial and final development stage when statistical parameters lose most of their significance. NAW tends to overestimate rainfall while CST approaches more closely radar measurements. Most common errors arise from considering only portions of the storm, contamination from cold non-precipitating cloud, and merging of two or more cloud masses of independent origin. Operational applications, though not completely quantitative, are also possible, including positive values of the difference between water vapour and IR brightness temperature

Statistical analysis and modelling of weather radar beam propagation conditions in the Po Valley (Italy)

Ground clutter caused by anomalous propagation (anaprop) can affect seriously radar rain rate estimates, particularly in fully automatic radar processing systems, and, if not filtered, can produce frequent false alarms. A statistical study of anomalous propagation detected from two operational C-band radars in the northern Italian region of Emilia Romagna is discussed, paying particular attention to its diurnal and seasonal variability. The analysis shows a high incidence of anaprop in summer, mainly in the morning and evening, due to the humid and hot summer climate of the Po Valley, particularly in the coastal zone. Thereafter, a comparison between different techniques and datasets to retrieve the vertical profile of the refractive index gradient in the boundary layer is also presented. In particular, their capability to detect anomalous propagation conditions is compared. Furthermore, beam path trajectories are simulated using a multilayer ray-tracing model and the influence of the propagation conditions on the beam trajectory and shape is examined. High resolution radiosounding data are identified as the best available dataset to reproduce accurately the local propagation conditions, while lower resolution standard TEMP data suffers from interpolation degradation and Numerical Weather Prediction model data (Lokal Model) are able to retrieve a tendency to superrefraction but not to detect ducting conditions. Observing the ray tracing of the centre, lower and upper limits of the radar antenna 3-dB half-power main beam lobe it is concluded that ducting layers produce a change in the measured volume and in the power distribution that can lead to an additional error in the reflectivity estimate and, subsequently, in the estimated rainfall rate

Doppler radar wind field retrieval over the Po Valley

Although methods of using multiple Doppler radars to study wind fields have long been proposed, and many research studies have been made, very few operational radar operators adopt methods which require the use of specific scanning strategies to allow the extraction of wind information. Here we report a collaborative study on dual-Doppler radars based on two Doppler radars in the Po valley, Italy. Unusually, the radars are only about 90 km apart, though operated by the same authority. The wind field syntheses are carried out on a 30 km by 30 km region where the two radars have overlapping scan coverage. An iterative method based on the linear wind model and the equation of mass continuity is used to construct the wind fields. The methodology has been validated by two different methods. The first method is to reconstruct the radial wind observed by each radar, and the second method is calculating and comparing the along-track component with that derived from the observations. Both two comparisons show good agreement with the original data

Reconstruction of reflectivity vertical profiles and data quality control for C-band radar rainfall estimation

International audienceMicrowave Doppler radars are considered a fairly established technique to retrieve rain rate fields from measured reflectivity volumes. However, in a complex orographic environment radar observations are affected by several impairments which should be carefully evaluated. Together with the enhancement of ground-clutter effects, the major limitation is represented by partial or total beam blocking caused by natural obstructions which very often impose to scan at high-elevation angles. These range-related limitations tend to reduce the potential role of operational weather radars in monitoring precipitation amount at ground within mountainous areas since, if either the nature or intensity of rainfall varies with height (e.g., melting effects during stratiform rain), radar returns at higher altitudes may be not representative of surface rain rate. Therefore, before to use the radar data, it is necessary to reduce, as much as possible, this evaluation errors and to estimate the reliability of the processed data. Near to the quality control, are needed quality indexes, taking into account each correction and elaboration step, that could be useful to retrieve a final quality value. In this work, we analyse the main factors that could be affect the efficiency of a reconstruction methodology of near-surface reflectivity fields from high-elevation reflectivity bins, in presence of complex orography. A climatologic schema is applied to infer near-surface reflectivity at a given range interval. The technique is developed in polar coordinates partially taking into account the antenna beam width degradation at longer ranges and overall computational efficiency for operational purposes. Thereafter, it is applied on a rainfall event observed by a C-band Doppler radar operating in S. Pietro Capofiume (Bologna, Italy) and the relation between the reconstruction error and possible quality indicators is analysed and discussed

Effects of propagation conditions on radar beam-ground interaction: impact on data quality

International audienceA large part of the research in the radar meteorology is devoted to the evaluation of the radar data quality and to the radar data processing. Even when, a set of absolute quality indexes can be produced (like as ground clutter presence, beam blockage rate, distance from radar, etc.), the final product quality has to be determined as a function of the task and of all the processing steps. In this paper the emphasis lies on the estimate of the rainfall at the ground level taking extra care for the correction for ground clutter and beam blockage, that are two main problems affecting radar reflectivity data in complex orography. In this work a combined algorithm is presented that avoids and/or corrects for these two effects. To achieve this existing methods are modified and integrated with the analysis of radar signal propagation in different atmospheric conditions. The atmospheric refractivity profile is retrieved from the nearest in space and time radiosounding. This measured profile is then used to define the `dynamic map' used as a declutter base-field. Then beam blockage correction is applied to the data at the scan elevations computed from this map. Two case studies are used to illustrate the proposed algorithm. One is a summer event with anomalous propagation conditions and the other one is a winter event. The new algorithm is compared to a previous method of clutter removal based only on static maps of clear air and vertical reflectivity continuity test. The improvement in rain estimate is evaluated applying statistical analysis and using rain gauges data. The better scores are related mostly to the ``optimum" choice of the elevation maps, introduced by the more accurate description of the signal propagation. Finally, a data quality indicator is introduced as an output of this scheme. This indicator has been obtained from the general scheme, which takes into account all radar data processing steps

DEBRIS FLOWS IN VAL PARMA AND VAL BAGANZA (NORTHERN APENNINES) DURING THE 12-13TH OCTOBER 2014 ALLUVIAL EVENT IN PARMA PROVINCE (ITALY)

During the 13 October 2014 rainstorm event that affected the Val Parma and Val Baganza area, several debris flows affected the Mt. Cervellino relief (northern Apennines, Italy), causing severe and widespread damages to check-dams, roads and other infrastructures. Such event, together with the Piacenza province event of 2015, has generated the perception of debris flows as a breaking new potential cause of widespread damages in the Emilia-Romagna. The meteorological event of October 2014, reconstructed by means of rain gauges and radar data, reached intensities as high as 80 mm/hour, which is well above any debris flow triggering thresholds presented in literature. However, data show that debris flows have occurred in any location where 30 mm/hour were exceeded. The result was the occurrence of tens of debris flows, which were triggered in zones of failure of slope debris coverage along the streams, and that remobilized and scoured debris along the track and destroyed several check dams and damaged roads that were overflown by debris. This paper is aimed to document the distribution and characteristics of the debris flow events that occurred during such event. By doing so, it also warns against this potentially destructive events that, in a changing meteorological framework, might result much more frequent and widespread than expected also in the northern Apennines

Hydrometeor classification from dual-polarized weather radar: extending fuzzy logic from S-band to C-band data

International audienceA model-based fuzzy classification method for C-band polarimetric radar data, named Fuzzy Radar Algorithm for Hydrometeor Classification at C-band (FRAHCC), is presented. Membership functions are designed for best fitting simulation data at C-band, and they are derived for ten different hydrometeor classes by means of a scattering model, based on T-Matrix numerical method. The fuzzy logic classification technique uses a reduced set of polarimetric observables, i.e. copolar reflectivity and differential reflectivity, and it is finally applied to data coming from radar sites located in Gattatico and S. Pietro Capofiume in North Italy. The final purpose is to show qualitative accuracy improvements with respect to the use of a set of ten bidimensional MBFs, previously adopted and well suited to S-band data but not to C-band data

Fast-Processing DEM-Based Urban and Rural Inundation Scenarios from Point-Source Flood Volumes

Flooding has always been a huge threat to human society. Global climate change coupled with unsustainable regional planning and urban development may cause more frequent inundations and, consequently, higher societal and economic losses. In order to characterize floods and reduce flood risk, flood simulation tools have been developed and widely applied. Hydrodynamic models for inundation simulation are generally sophisticated, yet they normally require massive setup and computational costs. In contrast, simplified conceptual models may be more easily applied and efficient. Based on the Hierarchical Filling-and-Spilling or Puddle-to-Puddle Dynamic Filling-and-Spilling Algorithms (i.e., HFSAs), Safer_RAIN has been developed as a fast-processing DEM-based model for modelling pluvial flooding over large areas. This study assesses Safer_RAIN applicability outside the context for which it was originally developed by looking at two different inundation problems with point-source flooding volumes: (1) rural inundation modelling associated with levee breaching/overtopping; (2) urban flooding caused by drainage systems outflow volumes

Screening of dietary ingredients against the honey bee parasite Nosema ceranae

Nosema ceranae is a major pathogen in the beekeeping sector, responsible for nosemosis. This disease is hard to manage since its symptomatology is masked until a strong collapse of the colony population occurs. Conversely, no medicaments are available in the market to counteract nosemosis, and only a few feed additives, with claimed antifungal action, are available. New solutions are strongly required, especially based on natural methods alternative to veterinary drugs that might develop resistance or strongly pollute honey bees and the environment. This study aims at investigating the nosemosis antiparasitic potential of some plant extracts, microbial fermentation products, organic acids, food chain waste products, bacteriocins, and fungi. Honey bees were singularly infected with 5 × 104 freshly prepared N. ceranae spores, reared in cages and fed ad libitum with sugar syrup solution containing the active ingredient. N. ceranae in the gut of honey bees was estimated using qPCR. The results showed that some of the ingredients administered, such as acetic acid at high concentration, p-coumaric acid, and Saccharomyces sp. strain KIA1, were effective in the control of nosemosis. On the other hand, wine acetic acid strongly increased the N. ceranae amount. This study investigates the possibility of using compounds such as organic acids or biological agents including those at the base of the circular economy, i.e., wine waste production, in order to improve honeybee health