Raindrop Size Distribution variability from high resolution\ud 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

A Field Study of Pixel-Scale Variability of Raindrop Size Distribution in the MidAtlantic Region

The spatial variability of parameters of the raindrop size distribution and its derivatives is investigated through a field study where collocated Particle Size and Velocity (Parsivel2) and two-dimensional video disdrometers were operated at six sites at Wallops Flight Facility, Virginia, from December 2013 to March 2014. The three-parameter exponential function was employed to determine the spatial variability across the study domain where the maximum separation distance was 2.3 km. The nugget parameter of the exponential function was set to 0.99 and the correlation distance d0 and shape parameter s0 were retrieved by minimizing the root-mean-square error, after fitting it to the correlations of physical parameters. Fits were very good for almost all 15 physical parameters. The retrieved d0 and s0 were about 4.5 km and 1.1, respectively, for rain rate (RR) when all 12 disdrometers were reporting rainfall with a rain-rate threshold of 0.1 mm h1 for 1-min averages. The d0 decreased noticeably when one or more disdrometers were required to report rain. The d0 was considerably different for a number of parameters (e.g., mass-weighted diameter) but was about the same for the other parameters (e.g., RR) when rainfall threshold was reset to 12 and 18 dBZ for Ka- and Ku-band reflectivity, respectively, following the expected Global Precipitation Measurement missions spaceborne radar minimum detectable signals. The reduction of the database through elimination of a site did not alter d0 as long as the fit was adequate. The correlations of 5-min rain accumulations were lower when disdrometer observations were simulated for a rain gauge at different bucket sizes

Characterization of surface radar cross sections at W-band at moderate incidence angles

This paper presents the results of a recent flight campaign conducted over the Great Lakes region and reports the first observations of the W-band normalized backscattered cross section ( σ0 ) for V and H polarization and the linear depolarization ratios (LDRs) from different types of surfaces at moderate incidence angles (<70°). For sea surfaces, while the observed σ0 behaves as previously reported at small incidence angles, it features a marked decrease with increasing incidence angles between 20° and 50°. There is a strong dependence of normalized backscattered cross sections both on the wind speed and on the wind direction, with larger values found in the presence of higher wind speeds and when the radar antenna is looking upwind. This is in line with theoretical models (though models tend to overpredict the range of variability at a given incidence angle) and with observations at lower frequencies. The LDRs are steadily increasing from values certainly lower than −30 dB, at vertical incidence, to the values of about −10 dB, at the incidence angles of about 60°–70°, with a good matching between observations and theoretical predictions. On the other hand, land surface backscattering properties are not characterized by a strong angular dependence: σ0 and LDR values typically range between −20 and 0 dB and between −15 and −5 dB, respectively. This paper is relevant for spaceborne concepts of W-band radars, which envisage moderate incidence angles to achieve a broad swath needed for global coverage

Observing the Full Spectrum of the Rain Drop Size Distribution

GPM DSD retrievals exhibit inconsistencies between GV, DPR and Combined algorithm retrievals. Development of positive bias in convective Dm rain DSD noted, and strongest in KuPR retrieval. Associated epsilons are too low and result in markedly reduced convective rain rates (a current issue in the retrievals). Source may be NUBF. Issues with the large end of the DSD not withstanding, on the small end of the DSD, combined MPS and 2DVD measurements fit with generalized gamma functions exhibit strong potential for representing the entire spectrum of the DSD and subsequently the whole rain rate spectrum

Comparison of GPM Core Observatory and Ground-Based Radar Retrieval of Mass-Weighted Mean Raindrop Diameter at Midlatitude

Abstract One of the main goals of the National Aeronautics and Space Administration (NASA) Global Precipitation Measurement (GPM) mission is to retrieve parameters of the raindrop size distribution (DSD) globally. As a standard product of the Dual-Frequency Precipitation Radar (DPR) on board the GPM Core Observatory satellite, the mass-weighted mean diameter Dm and the normalized intercept parameter Nw are estimated in three dimensions at the resolution of the radar. These are two parameters of the three-parameter gamma model DSD adopted by the GPM algorithms. This study investigates the accuracy of the Dm retrieval through a comparative study of C-band ground radars (GRs) and GPM products over Italy. The reliability of the ground reference is tested by using two different approaches to estimate Dm. The results show good agreement between the ground-based and spaceborne-derived Dm, with an absolute bias being generally lower than 0.5 mm over land in stratiform precipitation for the DPR algorithm and the combined DPR–GMI algorithm. For the DPR–GMI algorithm, the good agreement extends to convective precipitation as well. Estimates of Dm from the DPR high-sensitivity (HS) Ka-band data show slightly worse results. A sensitivity study indicates that the accuracy of the Dm estimation is independent of the height above surface (not shown) and the distance from the ground radar. On the other hand, a nonuniform precipitation pattern (interpreted both as high variability and as a patchy spatial distribution) within the DPR footprint is usually associated with a significant error in the DPR-derived estimate of Dm

Comparative investigation of Pludix disdrometer capability as Present Weather Sensor (PWS) during the Wasserkuppe campaign

Pludix is an X-band disdrometer based on the Doppler effect, that provides rainfall intensity and drop size distribution output, and exhibits potential capabilities as a Present Weather Sensor (PWS). A Present Weather Sensor is an instrument capable of automatically detecting weather phenomena present at the time of observation. In order to verify the latter, two different methods have been developed to identify the precipitation types according to the WMOcodes in its table 4680. With the first method (P-method), twelve precipitation codes are identified by analysing the characteristics of the Pludix power spectrum. With the second method (S-method), a statistical one based on a pattern recognition type algorithm, twenty- three precipitation codes are identified. With both methods main precipitation types are identified: drizzle, rain, snow, hail, ice crystals, mixed precipitation. Pludix is compared with the reference observations of a human observer during a campaign performed at the weather station of Wasserkuppe (central Germany, 950 m a.s.l.). Two years of data are analysed (December 2000–January 2003); in this time interval there was a fair amount of both liquid and solid precipitation events, allowing us to evaluate the instrument capabilities. Pludix is also compared with the Vaisala FD12P PWS and with the optical disdrometer Parsivel which were tested in the same campaign. Since the S-method has only recently been developed and it is under investigation, the present analysis is mainly focusing on the P-method. The results show that Pludix performs quite well in distinguishing the precipitation type and it is generally in agreement with the human observations, especially for the rain case. Pludix also detects some situations (especially rain-showers with hail) that the human observer sometimes does not detect. The instrument is less sensitive to the slight precipitation, especially because it samples on a small measurement volume. We also test the performance of Pludix in measuring the rainfall-intensity, finding that it works better than the other instruments in the case of rain

Triple-Frequency Doppler Retrieval of Characteristic Raindrop Size

A retrieval for characteristic raindrop size and width of the drop size distribution (DSD) based on triple-frequency vertical Doppler radar measurements is developed. The algorithm exploits a statistical relation that maps measurements of the differential Doppler velocities at X and Ka and at Ka and W bands into the two aforementioned DSD moments. The statistical mapping has been founded on 7,900 hr of disdrometer-observed DSDs and their simulated Doppler velocities. Additionally, a retrieval of D-m based only on DDVX-W measurements is also presented, and its performance is compared to the analogous algorithm exploiting DDVKa-W data. The retrievals are tested using triple-frequency radar data collected during a recent field campaign held at the Juelich Observatory for Cloud Evolution (JOYCE, Germany) where in situ measurements of the DSD were carried out only few meters away from the vertically pointing radars. The triple-frequency retrieval is able to obtain D-m with an uncertainty below 25% for D-m ranging from 0.7 to 2.4 mm. Compared to previously published dual-frequency retrievals, the third frequency does not improve the retrieval for small D-m (< 1.4 mm). However, it significantly surpasses the DDVKa-W algorithm for larger D-m (20% versus 50% bias at 2.25 mm). Also compared to DDVX-W method, the triple-frequency retrieval is found to provide an improvement of 15% in terms of bias for D-m = 2.25 mm. The triple-frequency retrieval of sigma(m) performs with an uncertainty of 20-50% for 0.2 < sigma(m) < 1.3 mm, with the best performance for 0.25 < sigma(m) < 0.8 mm

Triple‐Frequency Doppler Retrieval of Characteristic Raindrop Size

A retrieval for characteristic raindrop size and width of the drop size distribution (DSD) based on triple-frequency vertical Doppler radar measurements is developed. The algorithm exploits a statistical relation that maps measurements of the differential Doppler velocities at X and Ka and at Ka and W bands into the two aforementioned DSD moments. The statistical mapping has been founded on 7,900 hr of disdrometer-observed DSDs and their simulated Doppler velocities. Additionally, a retrieval of Dm based only on DDVX−W measurements is also presented, and its performance is compared to the analogous algorithm exploiting DDVKa−W data. The retrievals are tested using triple-frequency radar data collected during a recent field campaign held at the Juelich Observatory for Cloud Evolution (JOYCE, Germany) where in situ measurements of the DSD were carried out only few meters away from the vertically pointing radars. The triple-frequency retrieval is able to obtain Dm with an uncertainty below 25% for Dm ranging from 0.7 to 2.4 mm. Compared to previously published dual-frequency retrievals, the third frequency does not improve the retrieval for small Dm (< 1.4 mm). However, it significantly surpasses the DDVKa−W algorithm for larger Dm (20% versus 50% bias at 2.25 mm). Also compared to DDVX−W method, the triple-frequency retrieval is found to provide an improvement of 15% in terms of bias for Dm = 2.25 mm. The triple-frequency retrieval of m performs with an uncertainty of 20–50% for 0.2 < m < 1.3 mm, with the best performance for 0.25 < m < 0.8 mm

Triple-Frequency Doppler Retrieval of Characteristic Raindrop Size

A retrieval for characteristic raindrop size and width of the drop size distribution (DSD) based on triple-frequency vertical Doppler radar measurements is developed. The algorithm exploits a statistical relation that maps measurements of the differential Doppler velocities at X and Ka and at Ka and W bands into the two aforementioned DSD moments. The statistical mapping has been founded on 7,900 hr of disdrometer-observed DSDs and their simulated Doppler velocities. Additionally, a retrieval of (Formula presented.) based only on (Formula presented.) measurements is also presented, and its performance is compared to the analogous algorithm exploiting (Formula presented.) data. The retrievals are tested using triple-frequency radar data collected during a recent field campaign held at the Juelich Observatory for Cloud Evolution (JOYCE, Germany) where in situ measurements of the DSD were carried out only few meters away from the vertically pointing radars. The triple-frequency retrieval is able to obtain (Formula presented.) with an uncertainty below 25% for (Formula presented.) ranging from 0.7 to 2.4 mm. Compared to previously published dual-frequency retrievals, the third frequency does not improve the retrieval for small (Formula presented.) ((Formula presented.) mm). However, it significantly surpasses the (Formula presented.) algorithm for larger (Formula presented.) (20% versus 50% bias at 2.25 mm). Also compared to (Formula presented.) method, the triple-frequency retrieval is found to provide an improvement of 15% in terms of bias for (Formula presented.) mm. The triple-frequency retrieval of (Formula presented.) performs with an uncertainty of 20–50% for (Formula presented.) mm, with the best performance for (Formula presented.) mm

Impact of Lightning Data Assimilation on the Short-Term Precipitation Forecast over the Central Mediterranean Sea

Lightning data assimilation (LDA) is a powerful tool to improve the weather forecast of convective events and has been widely applied with this purpose in the past two decades. Most of these applications refer to events hitting coastal and land areas, where people live. However, a weather forecast over the sea has many important practical applications, and this paper focuses on the impact of LDA on the precipitation forecast over the central Mediterranean Sea around Italy. The 3 h rapid update cycle (RUC) configuration of the weather research and forecasting (WRF) model) has been used to simulate the whole month of November 2019. Two sets of forecasts have been considered: CTRL, without lightning data assimilation, and LIGHT, which assimilates data from the LIghtning detection NETwork (LINET). The 3 h precipitation forecast has been compared with observations of the Integrated Multi-satellitE Retrievals for Global Precipitation Mission (GPM) (IMERG) dataset and with rain gauge observations recorded in six small Italian islands. The comparison of CTRL and LIGHT precipitation forecasts with the IMERG dataset shows a positive impact of LDA. The correlation between predicted and observed precipitation improves over wide areas of the Ionian and Adriatic Seas when LDA is applied. Specifically, the correlation coefficient for the whole domain increases from 0.59 to 0.67, and the anomaly correlation (AC) improves by 5% over land and by 8% over the sea when lightning is assimilated. The impact of LDA on the 3 h precipitation forecast over six small islands is also positive. LDA improves the forecast by both decreasing the false alarms and increasing the hits of the precipitation forecast, although with variability among the islands. The case study of 12 November 2019 (time interval 00–03 UTC) has been used to show how important the impact of LDA can be in practice. In particular, the shifting of the main precipitation pattern from land to the sea caused by LDA gives a much better representation of the precipitation field observed by the IMERG precipitation product