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In spite of the high relevance of the satellite data for collecting information regarding precipitation at global scale, validating satellite retrievals with measurements collected by sensors at ground is still a challenging task. To date, the Dual-frequency Precipitation Radar (DPR) aboard the Core Satellite of the Global Precipitation Measurement (GPM) mission is the only one able to provide, at global scale, vertical profiles of rainfall rate, radar reflectivity, and Drop Size Distribution (DSD) parameters. In this study, we compare near surface GPM retrievals with almost 6 years of DSD parameters estimated by a laser disdrometer in Rome (Italy) since the launch of GPM mission. The comparison shows limited difference in performances of the different GPM algorithms, also with reference to the dual frequency algorithm with respect to the single frequency one. Furthermore, the agreement between satellite and ground based data depends on the considered precipitation variable as well as on the spatial and temporal scale matching constrains.

An analysis of backscattering radar echoes from single and distributed scatterers is illustrated. Ground-based weather radars are briefly described to understand how they measure precipitation. Meteorological targets (such as rain, snow and ice) are described as volume-distributed scatterers by separating them from other scatterers (mountains and man-made targets). A theoretical study follows to explain the relation between the radar equation in meteorology and the single target radar equation. Experimental measurements are then shown in this work: clear air data to validate radar equation for single scatterers and precipitation data to validate radar equation in meteorology. Results are shown using a C-band weather radar located in Rome (Italy) and managed by ISAC CNR. The analysis can be useful for future studies aiming at characterize ground-clutter returns both for classification and calibration purposes. A useful expression of the equivalent radar cross section from the equivalent reflectivity factor is also proposed.

During an eruptive event, the near-real-time monitoring of volcanic explosion onset and its mass flow rate (MFR) is a key factor to predict ash plume dispersion and to mitigate risk to air traffic. Microwave (MW) weather radars have proved to be a fundamental instrument to derive eruptive source parameters. We extend this capability to include an early-warning detection scheme within the overall volcanic ash radar retrieval methodology. This scheme, called the volcanic ash detection (VAD) algorithm, is based on a hybrid technique using both fuzzy logic and conditional probability. Examples of VAD applications are shown for some case studies, including the Icelandic Grímsvötn eruption in 2011, the Eyjafjallajökull eruption in 2010, and the Italian Mt. Etna volcano eruption in 2013. Estimates of the eruption onset from the radar-based VAD module are compared with infrasonic array data. One-dimensional numerical simulations and analytical model estimates of MFR are also discussed and intercompared with sensor-based retrievals. Results confirm in all cases the potential of MW weather radar for ash plume monitoring in near real time and its complementarity with infrasonic array for early-warning system design.

Satellite microwave and infrared radiometric imagery, acquired during the recent Calbuco eruption in April 2015, are discussed to demonstrate the complementarity of microwave (MW) and thermal infrared (TIR) spaceborne observations for volcanic plume and ash cloud monitoring. TIR brightness temperatures clearly saturate in the proximity of the volcanic vent of the sub-Plinian column due to high optical extinction of the plume at those wavelengths. The use of microwave sounding can retrieve information below the volcanic plume top height, even though satellite MW radiometers still suffer of a relatively poor spatial resolution (tens of kilometers) with respect to TIR imagers (few kilometers). Preliminary estimates of tephra mass loading and plume height from MW data are also discussed.

The goal of this work is to show potentials and drawbacks of Dual Polarization measurements of volcanic plume from microwave ground-based X-band radar (DPX). Measurements of brightness temperature (BT) from the space-orbiting microwave radiometer are used as well and compared with DPX retrievals of total columnar content (TCC). The latter is estimated from the radar variables using the volcanic ash radar retrieval for dual-polarization X band systems (VARR-PX) algorithm whereas BT's have been acquired from the Special Sensor Microwave Imager/Sounder (SSMIS). Model simulations of volcanic plume evolution are generated to carry out comparisons with radar estimates of TCC. The Active Tracer High-Resolution Atmospheric Model (ATHAM) of eruption plume is used for this purpose. Results show that high- spatial-resolution DPX radar data identify an evident volcanic plume signature, even though the interpretation of the polarimetric variables and the related retrievals is not always easy, likely due to the possible formation of ash and ice particle aggregates, the radar signal depolarization induced by turbulence effects, and the partial filling of the radar beam. A forth degree polynomial relationship is in good agreement with BT - TCC measured samples with correlation of -0.71. The variability of TCC, described by the ATHAM simulations, seems to include the spatial and temporal variation of the radar retrievals.

The metropolitan areas of Rome and Naples are the most populous in Italy, having a population of 4,233,000 and 3,020,000 peoples, respectively, and being within the first 10th-most populous urban areas in the European Union. Within such areas population, industry, commerce, transport and government activities are highly affected by severe weather associated with convective storms, flash floods and mood slides as well as other damages caused by hail, lightning, wind gusts all year round (mainly in autumn). In this respect weather radars' capability to monitor precipitation at high spatial and temporal scales is of outmost importance and stimulates a significant interest within both meteorological and hydrological community. This is due to the fact that improving intense storm and flash flood forecast requires accurate quantitative rain measurements at small scales. In this context two low-cost single-polarization X-band weather radar systems have been installed and tested in Rome and Naples metropolitan areas. Herein some preliminary results are described, showing the usefulness and potentiality of such X-band low-cost systems at urban scale.

Active remote sensing retrieval from ground, in terms of detection, estimation and sensitivity, of volcanic ash plumes is not only dependent on the sensors' specifications, but also on the range and ash cloud distribution. The minimum detectable signal can be increased, for a given system and ash plume scenario, by decreasing the observation range and increasing the operational frequency using a multi-sensor approach, but also exploiting possible polarimetric capabilities. This work, starting from the results of a previous study and from above mentioned issues, is aimed at quantitatively assessing the optimal choices for microwave and millimeter-wave radar systems with a dual-polarization capability for real-time ash cloud remote sensing to be used in combination with an optical lidar. The physical-electromagnetic model of ash particle distributions is systematically reviewed and extended to include non-spherical particle shapes, vesicular composition, silicate content and orientation phenomena. The radar and lidar scattering and absorption response is simulated and analyzed in terms of self-consistent polarimetric signatures for ash classification purposes and correlation with ash concentration and mean diameter for quantitative retrieval aims. A sensitivity analysis to ash concentration, as a function of sensor specifications, range and ash category, is carried out trying to assess the expected multi-sensor multi-spectral system performances and limitations.

The sub-glacial Plinian explosive eruption of the Grimsvotn volcano on May 2011 was continuously monitored by the Keflavik C-band weather radar, located at a distance of about 260 km from the volcano vent. This work provides an analysis and quantitative interpretation by using these ground-based weather radar data and the Volcanic Ash Radar Retrieval (VARR) physically-based technique. The VARR methodology, herein briefly summarized, was applied to available radar time series to estimate the volume, mass and the plume maximum height, every 5 minutes. Deposited ash at ground was also retrieved from radar data by empirically reconstructing the vertical profile of radar reflectivity and estimating the near-surface ash fallout. The obtained results establish a further step towards the assessment of the VARR algorithm as an effective approach in the field volcanic ash cloud radar remote sensing.

The sub-glacial Plinian explosive eruption of the Grimsvotn volcano on May 2011 is analyzed and quantitatively interpreted by using satellite passive microwave observations. The prevailing southerly winds stretched the erupted plume toward the Artic pole, thus preventing the ash cloud to move towards continental Europe and threatening the airline traffic (differently from the less explosive Eyjafjoll eruption on April and May 2010). Satellite microwave radiometric imagery is investigated to show the potential contribution and limitations to the understanding and modeling of explosive volcanic ash eruptions. We show the correlation of spaceborne microwave brightness temperatures with the ash columnar content derived from ground-based C-band radar retrievals. Microphysical sensitivity of satellite microwave brightness temperatures to the eruption plume fine and coarse ash suggests their exploitation in synergy with satellite thermal infrared radiometer and ground-based microwave radar observations.

This paper presents an investigation on the rainfall signature for two COSMO-SkyMed (CSK) satellite case studies. Both of them are relative to a severe precipitation weather event, occurred in northwestern Italy (close to Liguria region) on November 3–8, 2011. This event was monitored by using a number of CSK images provided by the Italian Space Agency (ASI). In this case CSK X-SAR data have been compared with the weather radar (WR) Italian Radar National Mosaic. A third case study is relative to Hurricane “Irene” event, occurred in Eastern United States (close to Delaware) on late August 2011. CSK X-SAR images are compared with respect to concurrent ground-based S-band NEXRAD weather radar reflectivities. The correlation of the precipitating cloud fields between CSK X-SAR and WR images is significant in all case studies. An application of a refined XSAR-based precipitation retrieval method is presented. The X-SAR surface response is estimated using ancillary data, such as land cover maps and a digital elevation model (DEM).

Spaceborne Interferometric Synthetic Aperture Radar (InSAR) is a well established technique useful in many land applications, such as tectonic movements, landslide monitoring and digital elevation model extraction. One of its major limitation is the atmospheric effect, and in particular the high water vapour spatial and temporal variability which introduces an unknown delay in the signal propagation. This paper describes the general approach and some results achieved in the framework of an ESA funded project devoted to the mapping of the water vapour with the aim to mitigate its effect in InSAR applications. Ground based (microwave radiometers, radiosoundings, GPS) and spaceborne observations (AMSR-E, MERIS, MODIS) of columnar water vapour were compared with Numerical Weather Prediction model runs in Central Italy during a 15-day experiment. A dense network of GPS receivers was deployed close to Como, in Northern Italy, to complement the operational network in order to derive Zenith Total Delay as well as Slant Delay which can support InSAR processing. A comparison with Atmospheric Phase Screens (APS) derived from a sequence of Envisat multi pass interferometric acquisitions processed using the Permanent Scatters technique on the two test sites has been also performed. The acquired experimental data and their comparison give a valuable idea of what can be done to gather information on water vapour, which, besides InSAR applications, plays a fundamental role in weather prediction and radio propagation studies. The work has been carried out in the framework of an ESA funded project, named “Mitigation of Electromagnetic Transmission errors induced by Atmospheric Water Vapour Effects” (METAWAVE). This paper presents the general approach an the various methodologies exploited in the project, together with the overall intercomparison of the results. In deep details on the comparison with the InSAR APS maps derived by the PS technique, as well as on GPS receiver processing and water vapour tomography are reported in two companion papers.

Spaceborne Interferometric Synthetic Aperture Radar (InSAR) is a well established technique useful in many land applications, such as monitoring tectonic movements and landslides or extracting digital elevation models. One of its major limitations is the atmospheric variability, and in particular the high water vapor spatial and temporal variability, which introduces an unknown delay in the signal propagation. On the other hand, these effects might be exploited, so as InSAR could become a tool for highresolution water vapor mapping. This paper describes the approach and some preliminary results achieved in the framework of an ESA funded project devoted to the mitigation of the water vapor effects in InSAR applications. Although very preliminary, the acquired experimental data and their comparison give a first idea of what can be done to gather valuable information on water vapor, which play a fundamental role in weather prediction and radio propagation studies.

Dual-polarized weather radars are capable to detect and identify different classes of hydrometeors, within stratiform and convective storms exploiting polarimetric diversity. A model-supervised Bayesian method for hydrometeor classification (BRAHC), tuned for S- and X- band, is described in this study. The critical issue of X-band radar data processing is the path attenuation correction, usually negligible at S-band. During the IHOP experiment (Oklahoma, 2002) two dualpolarized radars, at S- and X- bands, were deployed and jointly operated with closely matched scanning strategies, giving the opportunity to perform experimental comparisons between coincident measurements at different frequencies. Results of hydrometeor classification and water content estimates at S- and X- bands are discussed and the impact of path attenuation correction is quantitatively analyzed.

Requirements and preliminary specifications to design a micro-satellite flower constellation, named FLORAD, of millimeter-wave (MMW) radiometers for atmospheric observations are here introduced. The FLORAD small-mission scientific objectives are aimed at the retrieval of thermo-dynamical and hydrological properties of the atmosphere. Radiometer specifications and inversion algorithms are briefly discussed, pointing out the trade-off between performances and complexity for low-cost low-weight micro-satellite platforms. In order to fulfill the goal of a short revisit time for meteorological monitoring and now casting purposes, a flower constellation (FC) of micro-satellites is proposed due to its design flexibility.

Given the rising and renewed interest towards the study of Moon the European space Agency (ESA) approved, in March 2006, the phase-A for the feasibility study of the European Student Moon Orbiter (ESMO) mission proposed by the Student Space Exploration & Technology Initiative (SSETI). The objective of the ESMO mission is to acquire images of the moon in stable orbit, transmit them to the Earth and then to actively involve European students in a real space program experience. In order to accomplish the ESMO mission objectives, a Micro Wave Radiometric Sounder (MiWaRS) has been selected as a possible choice for flying on board of the ESMO satellite. This work summarizes the preliminary results obtained during the phase-A for the MiWaRS with special attention to the description of the radiometric system design and its scientific objectives.

Recent research has demonstrated the value of polarimetric measurements for the correction of rain-path attenuation at X-band radar frequency and the estimation of rain parameters including drop-size distributions (DSD). The issue this paper is concerned with is to what degree uncertainties in attenuation correction can affect the estimation of DSD. Since attenuation-correction uncertainty enhances with rain path, our hypothesis is that DSD retrieval uncertainty at X-band may deteriorate with range. In this paper, we evaluate the relative accuracy of X-band DSD retrieval against DSD estimates from S-band radar observations and in situ disdrometer spectra. We present comparisons of various techniques for estimating DSD model parameters from attenuation-corrected X-band dual-polarization radar data. Coincident X-band polarimetric-radar (XPOL) and S-band polarimetric-radar dual-polarized radar measurements from the International H2O Project experiment as well as coincident XPOL (MP-X) measurements over disdrometer during a typhoon storm case in Japan are used to assess the accuracy of the different DSD retrieval algorithms applied to X-band radar measurements.

Dual-polarized weather radars are capable to detect and identify different classes of hydrometeors, within stratiform and convective storms exploiting polarimetric diversity. A model- supervised Bayesian method for hydrometeor classification (BRAHC), tuned for S- and X- band, is described in this study. The critical issue of X-band radar data processing is the path attenuation correction, usually negligible at S-band. During the IHOP experiment (Oklahoma, 2002) two dual-polarized radars, at S- and X- bands, were deployed and jointly operated with closely matched scanning strategies, giving the opportunity to perform experimental comparisons between coincident measurements at different frequencies. Results of hydrometeor classification and water content estimates at S- and X- bands are discussed and the impact of path attenuation correction is quantitatively analyzed.

A large data set of rain drop size distribution (RSD) measurements collected with Joss-Waldvogel (JWD) and 2D video disdrometers (2DVD) in UK, Athens, Japan and USA are analyzed. The objective of this work are manifold: i) show the differences of a wide climatological DSD-derived moments; ii) retrieve from this disdrometer data set the driving parameters of the normalized gamma RSD and perform a sensitivity analysis of these results by using different best-fitting techniques; iii) exploit the correlation structure of the estimated RSD parameters as input of a vector autoregressive stationary model in order to simulate time series (or horizontal profiles) of RSDs and, consequently, of either rain rate or path attenuation; iv) characterize the distribution of the inter-rain duration (or dry periods: DP) and rain duration (or wet periods: WP) to design a simple semi-Markov chain to represent the intermittency feature of rainfall process. The overall stochastic procedure to randomly synthetize (or generate) RSD time series is named Vector Autoregressive Raindrop Markov Synthesizer (VARMS) model. This stochastic RSD generation tool may find useful applications both in hydro-meteorology and radio-propagation.