Raindrop Size Distribution variability from high resolution disdrometer networks

The characteristics of the raindrop size distribution (DSD) have been widely studied since Marshall and Palmer (1948) introduced specific version of exponential distribution for the observed size spectra, based on measurements of raindrops records on dyed filter papers. Across the decades, interest in measuring and studying rain DSD has grown due to applications in cloud physics studies, in calibration of space-borne and ground-based microwave active precipitation sensors and in soil science and agriculture. The study of DSD and of the processes that determine it, are always been challenging from both theoretical and experimental point of view. Moreover, the study of DSD in natural rain is hindered by the difficulties (logistic and economic) in the management of dense disdrometer networks. Based on the unprecedented datasets available, this Thesis aims to contribute in characterizing, from a microphysical point of view, the precipitation structure and the processes that generate it. In particular, the vertical and horizontal DSD variability is analyzed, starting from the study of collisional break-up mechanism in natural rain. The signature of collisional break-up, first evidenced in a particular shape of Doppler power spectrum of a microwave disdrometer, is then searched and characterized in DSD spectrum, assessing its variability with altitude. The horizontal variability of DSD is studied both analyzing the occurrence of equilibrium DSD among the different datasets available and evaluating the correlation of integral and non-integral DSD parameters at small scale. In the first part of the Thesis, an overview on past and recent studies on different aspects of DSD is given. The main mechanisms that govern the rain development are firstly summarized, then the DSD parameterization and the DSD variability in natural rain are discussed. Finally, the description of the characteristics of instruments and of the field campaigns considered in this work are presented. The vertical variability of DSD has been studied thanks to the development of specific algorithms able to detect and characterize both the collisional break-up and the equilibrium DSD. I analyzed the signature of collisional break-up both on the Pludix Doppler power spectrum and on DSD spectrum. The analysis is carried out developing two algorithms that detect the collisional break-up as well as estimate the break-up diameter as function of altitude. The results show a decrease of break-up diameter with altitude, due to the reduction of air density, that plays a critical role in the energetic balance of the collision between two raindrops. The analysis also indicates that, regardless the altitude, the collisional break-up occurs if the kinetic energy of the collision exceeds 12.2 μJ. The results, together with the detailed analysis of some case study at high altitude (over the Tibetan Plateau), show also that the dominance of the break-up process is required to reach the equilibr ium DSD. The study of the DSD variability was deepened focusing the analysis on the 2DVD DSD properties to evaluate the occurrence of equilibrium DSD in natural rain. Another algorithm, based on 2DVD characteristics, is set up to automatically detect the equilibrium DSD by using the great amount of high quality disdrometric data available from the datasets of Ground Validation program of NASAGlobal Precipitation Measurement mission. The results shows a good agreement between the experimental equilibrium DSD and the equilibrium DSD obtained by theoretical models. The analysis shows also that the equilibrium DSD is mainly reached during convective rain and its dependence on season and latitude (no equilibrium DSD is observed at high latitude - 60°N). The occurrence of equilibrium DSD is a rare event in natural rain (maximum 8% of selected minutes), while an increase is observed if transition situations are considered. The results are also analyzed to estimate the goodness of fitting the equilibrium DSD by a three parameter gamma distribution, that is widely used to parameterize the DSD. The low correlation between the experimental DSDs and the gamma distribution evidences that the gamma is not the best parametric form to fit the experimental equilibrium DSD. The behavior of the rain and DSD parameters is studied as function of break-up occurrence and shows that they can be considered an additional indicators to screen out the situations that are not expected to reach the equilibrium DSD. The data collected from two high-resolution disdrometric dataset are used to study the horizonta l DSD spatial variability at small scale. The size of the measuring fields are different but comparable with a ground radar pixel or satellite footprint and this makes the analysis of the particular interest . The rainfall rate and other DSD parameters are analyzed using a three parameter exponential function to estimate their correlation at small scale. The estimated correlation distance shows that the most of the rain and DSD parameters are correlated within a radar pixel or satellite footprint (generally, the integral DSD parameters – rainfall rate, radar reflectivity, liquid water content, etc. – are less correlated than the non integral DSD parameters – maximum diameter, mean mass diameter, etc.). The root mean square error evidences a very good fit of the function used with respect the experimental data, indicating a good reliability of data. The results presented in this Thesis, first, increase the knowledge of break-up phenomenon and its effect on the DSD up to reach the equilibrium DSD, and can be used to improve the parameterizat ion form for break-up and equilibrium DSD occurrence and the modeling of cloud and precipitat ion mechanisms. Secondly, they give reliable indications about the spatial variability of the structure of precipitation within a radar pixel and/or a satellite footprint, with an immediate application to the interpretation of remote sensing measurements to improve precipitation retrieval from radar/satellite measurements, especially after the launch of Dual-frequency Polarization Radar in the frame of Global Precipitation Measurement mission. The results obtained in this Thesis lead to the study of many other aspects that can be investigated to better characterize the precipitation. The time evolution of the precipitation with particular emphasis to the time necessary to the break-up to modify the DSD to reach equilibrium DSD can be investigated by using the algorithms proposed here. A new parameterization of DSD affected by break-up and of equilibrium DSD is necessary to improve the remote sensing of precipitation. Finally, a deeper study of DSD spatial variability is needed to have more information about rain structures at small/medium spatial scales, by different techniques and datasets in different season/location

Time evolution of storms producing terrestrial gamma-ray flashes using era5 reanalysis data, gps, lightning and geo-stationary satellite observations

In this article, we report the first investigation over time of the atmospheric conditions around terrestrial gamma-ray flash (TGF) occurrences, using GPS sensors in combination with geostationary satellite observations and ERA5 reanalysis data. The goal is to understand which characteristics are favorable to the development of these events and to investigate if any precursor signals can be expected. A total of 9 TGFs, occurring at a distance lower than 45 km from a GPS sensor, were analyzed and two of them are shown here as an example analysis. Moreover, the lightning activity, collected by the World Wide Lightning Location Network (WWLLN), was used in order to identify any links and correlations with TGF occurrence and precipitable water vapor (PWV) trends. The combined use of GPS and the stroke rate trends identified, for all cases, a recurring pattern in which an increase in PWV is observed on a timescale of about two hours before the TGF occurrence that can be placed within the lightning peak. The temporal relation between the PWV trend and TGF occurrence is strictly related to the position of GPS sensors in relation to TGF coordinates. The life cycle of these storms observed by geostationary sensors described TGF-producing clouds as intense with a wide range of extensions and, in all cases, the TGF is located at the edge of the convective cell. Furthermore, the satellite data provide an added value in associating the GPS water vapor trend to the convective cell generating the TGF. The investigation with ERA5 reanalysis data showed that TGFs mainly occur in convective environments with unexceptional values with respect to the monthly average value of parameters measured at the same location. Moreover, the analysis showed the strong potential of the use of GPS data for the troposphere characterization in areas with complex territorial morphologies. This study provides indications on the dynamics of con-vective systems linked to TGFs and will certainly help refine our understanding of their production, as well as highlighting a potential approach through the use of GPS data to explore the lightning activity trend and TGF occurrences.publishedVersio

A Combined IR-GPS Satellite Analysis for Potential Applications in Detecting and Predicting Lightning Activity

Continuous estimates of the vertical integrated precipitable water vapor content from the tropospheric delay of the signal received by the antennas of the global positioning system (GPS) are used in this paper, in conjunction with the measurements of the Meteosat Second Generation (MSG) spinning enhanced visible and infrared imager (SEVIRI) radiometer and with the lightning activity, collected here by the ground-based lightning detection network (LINET), in order to identify links and recurrent patterns useful for improving nowcasting applications. The analysis of a couple of events is shown here as an example of more general behavior. Clear signs appear before the peak of lightning activity on a timescale from 2 to 3 h. In particular, the lightning activity is generally preceded by a period in which the difference between SEVIRI brightness temperature (TB) at channel 5 and channel 6 (i.e., ∆TB) presents quite constant values around 0 K. This trend is accompanied by an increase in precipitable water vapor (PWV) values, reaching a maximum in conjunction with the major flash activity. The results shown in this paper evidence good potentials of using radiometer and GPS measurements together for predicting the abrupt intensification of lightning activity in nowcasting systems

A Machine Learning Snowfall Retrieval Algorithm for ATMS

This article describes the development of a machine learning (ML)-based algorithm for snowfall retrieval (Snow retrievaL ALgorithm fOr gpM–Cross Track, SLALOM-CT), exploiting ATMS radiometer measurements and using the CloudSat CPR snowfall products as references. During a preliminary analysis, different ML techniques (tree-based algorithms, shallow and convolutional neural networks—NNs) were intercompared. A large dataset (three years) of coincident observations from CPR and ATMS was used for training and testing the different techniques. The SLALOM-CT algorithm is based on four independent modules for the detection of snowfall and supercooled droplets, and for the estimation of snow water path and snowfall rate. Each module was designed by choosing the best-performing ML approach through model selection and optimization. While a convolutional NN was the most accurate for the snowfall detection module, a shallow NN was selected for all other modules. SLALOM-CT showed a high degree of consistency with CPR. Moreover, the results were almost independent of the background surface categorization and the observation angle. The reliability of the SLALOM-CT estimates was also highlighted by the good results obtained from a direct comparison with a reference algorithm (GPROF)

A 4-Year Climatological Analysis Based on GPM Observations of Deep Convective Events in the Mediterranean Region

Since early March 2014, the NASA/JAXA Global Precipitation Measurement Core- Observatory (GPM-CO) satellite has allowed analysis of precipitation systems around the globe, thanks to the capabilities of the GPM Microwave Imager (GMI) and Dual-Frequency Precipitation Radar (DPR). In this work, we demonstrate how GPM-CO measurements obtained from 4 years of observations over the Mediterranean area can be used as an extremely effective tool to study the main climatological characteristics of the most intense Mediterranean storm structures. DPR and GMI-based Precipitation Features (PFs) parameters are used as proxies of the vertical structure and microphysical properties of these events, and their statistical distribution is analyzed to identify extremes. The analysis of annual, seasonal and geographical distribution of the identified deep convective systems highlights substantial differences in their diurnal cycle and in the distribution between land-sea and summer-winter. There is a general shift of the convective systems from the south (mostly over the sea) in the cold season, to the north (mostly over land) in the warm season. The analysis shows also that the inferred convective intensity is not always related to heavy precipitation. Known DPR and GMI-based criteria were adopted to identify overshooting top events and potential hailstorms, identify extreme deep convection signatures, like those observed for tropical and subtropical systems, and the most intense occur mostly over the sea. Although the analysis is limited to four years, the results show that the GPM-CO offers unprecedented measurements to identify and characterize extreme weather events in the Mediterranean region, with unique potentials for future long-term climatology and interannual variability analysis

Rainfall microphysical characterization over the Mediterranean area during the GPM era

The NASA/JAXA Global Precipitation Measurement (GPM) Core Observatory (CO) was launched on 27th February, 2014. It carries, for the first time, a Dual-frequency Precipitation Radar (DPR) designed to provide insights into the 3-D structure of precipitating clouds and rain intensity by using its Ka- and Ku-band frequencies. In addition to characterize the 3-D structure of precipitation, the DPR is used as calibrator for the GPM Microwave Imager (GMI). Single-frequency (SF) (both Ku- and Ka-only) and double-frequency (DF) based products provide, among the others, particle-size distribution (PSD) parameters (namely the mass-weighted mean diameter Dm and the normalized intercept parameter Nw), as well as precipitation rates. This book chapter focuses on reliability of the PSD parameters (limited to rainfall events, in this case we'll talk about of DSD - drop size distribution) over the Mediterranean area by taking as reference the DSD parameters estimated by ground-based radar measurement. Before of this, an inter-comparison between the SF and DF DPR outputs considering five years of data from GPM-CO mission is carried out. The goal is to investigate the reliability of SF-based products by assessing their quality compared to the DF-based ones, treated as a reference

RAINBOW: An Operational Oriented Combined IR-Algorithm

In this paper, precipitation estimates derived from the Italian ground radar network (IT GR) are used in conjunction with Spinning Enhanced Visible and InfraRed Imager (SEVIRI) measurements to develop an operational oriented algorithm (RAdar INfrared Blending algorithm for Operational Weather monitoring (RAINBOW)) able to provide precipitation pattern and intensity. The algorithm evaluates surface precipitation over five geographical boxes (in which the study area is divided). It is composed of two main modules that exploit a second-degree polynomial relationship between the SEVIRI brightness temperature at 10.8 µm TB10.8 and the precipitation rate estimates from IT GR. These relationships are applied to each acquisition of SEVIRI in order to provide a surface precipitation map. The results, based on a number of case studies, show good performance of RAINBOW when it is compared with ground reference (precipitation rate map from interpolated rain gauge measurements), with high Probability of Detection (POD) and low False Alarm Ratio (FAR) values, especially for light to moderate precipitation range. At the same time, the mean error (ME) values are about 0 mmh−1, while root mean square error (RMSE) is about 2 mmh−1, highlighting a limited variability of the RAINBOW estimations. The precipitation retrievals from RAINBOW have been also compared with the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Support to Operational Hydrology and Water Management (H SAF) official microwave (MW)/infrared (IR) combined product (P-IN-SEVIRI). RAINBOW shows better performances than P-IN-SEVIRI, in terms of both detection and estimates of precipitation fields when they are compared to the ground reference. RAINBOW has been designed as an operational product, to provide complementary information to that of the national radar network where the IT GR coverage is absent, or the quality (expressed in terms of Quality Index (QI)) of the RAINBOW estimates is low. The aim of RAINBOW is to complement the radar and rain gauge network supporting the operational precipitation monitoring

Fulmini ed agricoltura in tempi di cambiamento climatico

Lightning meteorology investigates the dynamic and microphysical evolution of convective meteorological systems through the monitoring of lightning. The timely information provided by the distribution of electrical discharges in the atmosphere is closely related to atmospheric convection, which is often followed by the arrival of hailstorms. However, the distribution of electrical discharges in the atmosphere also provides information on the production of nitrogen compounds, natural soil fertilizers. Lightning are already included in warning systems of a different nature and will be increasingly assimilated into Numerical Weather Prediction models, along with other observations to explain, monitor, and possibly mitigate the effects of extreme events and climatic variations. A general overview and some specific ideas will be presented to discuss the evolution of some possible applications to agriculture

Evaluation of the Sensitivity of Medicane Ianos to Model Microphysics and Initial Conditions Using Satellite Measurements

Tropical-like cyclone (TLC or medicane) Ianos formed during mid-September 2020 over the Southern Mediterranean Sea, and, during its mature stage on days 17–18, it affected southern Italy and especially Greece and its Ionian islands, where it brought widespread disruption due to torrential rainfall, severe wind gusts, and landslides, causing casualties. This study performs a sensitivity analysis of the mature phase of TLC Ianos with the WRF model to different microphysics parameterization schemes and initial and boundary condition (IBC) datasets. Satellite measurements from the Global Precipitation Measurement Mission-Core Observatory (GPM-CO) dual-frequency precipitation radar (DPR) and the Advanced Scatterometer (ASCAT) sea-surface wind field were used to verify the WRF model forecast quality. Results show that the model is most sensitive to the nature of the IBC dataset (spatial resolution and other dynamical and physical differences), which better defines the primary mesoscale features of Ianos (low-level vortex, eyewall, and main rainband structure) when using those at higher resolution (~25 km versus ~50 km) independently of the microphysics scheme, but with the downside of producing too much convection and excessively low minimum surface pressures. On the other hand, no significant differences emerged among their respective trajectories. All experiments overestimated the vertical extension of the main rainbands and display a tendency to shift the system to the west/northwest of the actual position. Especially among the experiments with the higher-resolution IBCs, the more complex WRF microphysics schemes (Thompson and Morrison) tended to outperform the others in terms of rain rate forecast and most of the other variables examined. Furthermore, WSM6 showed a good performance while WDM6 was generally the least accurate. Lastly, the calculation of the cyclone phase space diagram confirmed that all simulations triggered a warm-core storm, and all but one also exhibited axisymmetry at some point of the studied lifecycle

Evaluation of the Sensitivity of Medicane Ianos to Model Microphysics and Initial Conditions Using Satellite Measurements

Tropical-like cyclone (TLC or medicane) Ianos formed during mid-September 2020 over the Southern Mediterranean Sea, and, during its mature stage on days 17–18, it affected southern Italy and especially Greece and its Ionian islands, where it brought widespread disruption due to torrential rainfall, severe wind gusts, and landslides, causing casualties. This study performs a sensitivity analysis of the mature phase of TLC Ianos with the WRF model to different microphysics parameterization schemes and initial and boundary condition (IBC) datasets. Satellite measurements from the Global Precipitation Measurement Mission-Core Observatory (GPM-CO) dual-frequency precipitation radar (DPR) and the Advanced Scatterometer (ASCAT) sea-surface wind field were used to verify the WRF model forecast quality. Results show that the model is most sensitive to the nature of the IBC dataset (spatial resolution and other dynamical and physical differences), which better defines the primary mesoscale features of Ianos (low-level vortex, eyewall, and main rainband structure) when using those at higher resolution (~25 km versus ~50 km) independently of the microphysics scheme, but with the downside of producing too much convection and excessively low minimum surface pressures. On the other hand, no significant differences emerged among their respective trajectories. All experiments overestimated the vertical extension of the main rainbands and display a tendency to shift the system to the west/northwest of the actual position. Especially among the experiments with the higher-resolution IBCs, the more complex WRF microphysics schemes (Thompson and Morrison) tended to outperform the others in terms of rain rate forecast and most of the other variables examined. Furthermore, WSM6 showed a good performance while WDM6 was generally the least accurate. Lastly, the calculation of the cyclone phase space diagram confirmed that all simulations triggered a warm-core storm, and all but one also exhibited axisymmetry at some point of the studied lifecycle