Bayesian statistical analysis of ground-clutter for the relative calibration of dual polarization weather radars

A new data processing methodology, based on the statistical analysis of ground-clutter echoes and aimed at investigating the stability of the weather radar relative calibration, is presented. A Bayesian classification scheme has been used to identify meteorological and/or ground-clutter echoes. The outcome is evaluated on a training dataset using statistical score indexes through the comparison with a deterministic clutter map. After discriminating the ground clutter areas, we have focused on the spatial analysis of robust and stable returns by using an automated region-merging algorithm. The temporal series of the ground-clutter statistical parameters, extracted from the spatial analysis and expressed in terms of percentile and mean values, have been used to estimate the relative clutter calibration and its uncertainty for both co-polar and differential reflectivity. The proposed methodology has been applied to a dataset collected by a C-band weather radar in southern Italy

Performance Evaluation of a New Dual-Polarization Microphysical Algorithm Based on Long-Term X-Band Radar and Disdrometer Observations

Abstract Accurate estimation of precipitation at high spatial and temporal resolution of weather radars is an open problem in hydrometeorological applications. The use of dual polarization gives the advantage of multiparameter measurements using orthogonal polarization states. These measurements carry significant information, useful for estimating rain-path signal attenuation, drop size distribution (DSD), and rainfall rate. This study evaluates a new self-consistent with optimal parameterization attenuation correction and rain microphysics estimation algorithm (named SCOP-ME). Long-term X-band dual-polarization measurements and disdrometer DSD parameter data, acquired in Athens, Greece, have been used to quantitatively and qualitatively compare SCOP-ME retrievals of median volume diameter D0 and intercept parameter NW with two existing rain microphysical estimation algorithms and the SCOP-ME retrievals of rain rate with three available radar rainfall estimation algorithms. Error statistics for rain rate estimation, in terms of relative mean and root-mean-square error and efficiency, show that the SCOP-ME has low relative error if compared to the other three methods, which systematically underestimate rainfall. The SCOP-ME rain microphysics algorithm also shows a lower relative error statistic when compared to the other two microphysical algorithms. However, measurement noise or other signal degradation effects can significantly affect the estimation of the DSD intercept parameter from the three different algorithms used in this study. Rainfall rate estimates with SCOP-ME mostly depend on the median volume diameter, which is estimated much more efficiently than the intercept parameter. Comparisons based on the long-term dataset are relatively insensitive to path-integrated attenuation variability and rainfall rates, providing relatively accurate retrievals of the DSD parameters when compared to the other two algorithms

Coupling radio propagation and weather forecast models to maximize Ka-band channel transmission rate for interplanetary missions

Deep space (DS) missions for interplanetary explorations are aimed at acquiring information about the solar system and its composition. To achieve this result a radio link is established between the space satellite and receiving stations on the Earth. Significant channel capacity must be guaranteed to such spacecraft-to-Earth link considering their large separation distance as well. Terrestrial atmospheric impairments on the space-to-Earth propagating signals are the major responsible for the signal degradation thus reducing the link’s channel temporal availability. Considering the saturation and the limited bandwidth of the conventional systems used working at X-band (around 8.4 GHz), frequencies above Ku-band (12-18 GHz) are being used and currently explored for next future DS missions. For example, the ESA mission EUCLID, planned to be launched in 2020 to reach Sun-Earth Lagrange point L2, will use the K-band (at 25.5-27 GHz). The BepiColombo (BC) ESA mission to Mercury, planned to be launched in 2016, will use Ka-band (at 32-34 GHz) with some modules operating at X-band too. The W-band is also being investigated for space communications (Lucente et al., IEEE Systems J., 2008) as well as near-infrared band for DS links (Luini at al., 3rd IWOW, 2014; Cesarone et al., ICSOS, 2011). If compared with X-band channels, K-band and Ka-band can provide an appealing data rate and signal-to-noise ratio in free space due to the squared-frequency law increase of antenna directivity within the downlink budget (for the same physical antenna size). However, atmospheric path attenuation can be significant for higher frequencies since the major source of transmission outage is not only caused by convective rainfall, as it happens for lower frequencies too, but even non-precipitating clouds and moderate precipitation produced by stratiform rain events are detrimental. This means that accurate channel models are necessary for DS mission data link design at K and Ka band. A physical approach can offer advanced radiopropagation models to take into account the effects due to atmospheric gases, clouds and precipitation. The objective of this work is to couple a weather forecast numerical model with a microphysically- oriented radiopropagation model, providing a description of the atmospheric state and of its effects on a DS downlink. This work is developed in the framework of the RadioMeteorological Operations Planner (RMOP) program, aimed at performing a feasibility study for the BC mission (Biscarini et al., EuCAP 2014). The RMOP chain for the link budget computation is composed by three modules: weather forecast (WFM), radio propagation (RPM) and downlink budget (DBM). WFM is aimed at providing an atmospheric state vector. Among the available weather forecast models, for RMOP purposes we have used the Mesoscale Model 5. The output of the WFM is the input of the RPM for the computation of the atmospheric attenuation and sky-noise temperature at the receiving ground station antenna. RPM makes use of radiative transfer solver based on the Eddington approximations well as accurate scattering models. Time series of attenuation and sky-noise temperature coming from the RPM are converted into probability density functions and then ingested by the DBM to compute the received data volume (DV). Using the BC mission as a reference test case for the Ka-band ground station at Cebreros (Spain), this work will show the advantages of using a coupled WFM-RPM approach with respect to climatological statistics in a link budget optimization procedure. The signal degradation due to atmospheric effects in DS links in terms of received DV will be also investigated not only at Ka band, but also at X, K and W for intercomparison. The quality of the DS downlink will be given in terms of received DV and the results at different frequencies compared showing the respective advantages and drawbacks

Cross-validation of active and passive microwave snowfall products over the continental United States

Surface snowfall rate estimates from the Global Precipitation Measurement (GPM) mission’sCoreObservatorysensors and theCloudSatradar are compared to those from the Multi-Radar Multi-Sensor (MRMS) radarcomposite product over the continental United States during the period from November 2014 to September 2020. Theanalysis includes the Dual-Frequency Precipitation Radar (DPR) retrieval and its single-frequency counterparts, the GPMCombined Radar Radiometer Algorithm (CORRA), theCloudSatSnow Profile product (2C-SNOW-PROFILE), and twopassive microwave retrievals, i.e., the Goddard Profiling algorithm (GPROF) and the Snow Retrieval Algorithm for GMI(SLALOM). The 2C-SNOW retrieval has the highest Heidke skill score (HSS) for detecting snowfall among the productsanalyzed. SLALOM ranks second; it outperforms GPROF and the other GPM algorithms, all detecting only 30% of thesnow events. Since SLALOM is trained with 2C-SNOW, it suggests that the optimal use of the information content in theGMI observations critically depends on the precipitation training dataset. All the retrievals underestimate snowfall ratesby a factor of 2 compared to MRMS. Large discrepancies (RMSE of 0.7–1.5 mm h21) between spaceborne and ground-based snowfall rate estimates are attributed to the complexity of the ice scattering properties and to the limitations of theremote sensing systems: the DPR instrument has low sensitivity, while the radiometric measurements are affected by theconfounding effects of the background surface emissivity and of the emission of supercooled liquid droplet layers

Microwave Radiometric Remote Sensing of Volcanic Ash Clouds From Space: Model and Data Analysis

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Correction of Polarimetric Radar Reflectivity Measurements and Rainfall Estimates for Apparent Vertical Profile in Stratiform Rain

AbstractA method for correcting the vertical profile of reflectivity measurements and rainfall estimates (VPR) in plan position indicator (PPI) scans of polarimetric weather radars in the melting layer and the snow layer during stratiform rain is presented. The method for the detection of the boundaries of the melting layer is based on the well-established characteristic of local minimum of copolar correlation coefficient in the melting layer. This method is applied to PPI scans instead of a beam-by-beam basis with the addition of new acceptance criteria adapted to the radar used in this study. An apparent vertical profile of reflectivity measurements, or rainfall estimate, is calculated by averaging the range profiles from all of the available azimuth directions in each PPI scan. The height of each profile is properly scaled with melting-layer boundaries, and the reflectivity, or rainfall estimate, is normalized with respect to its value at the lower boundary of the melting layer. This approach allows variations of the melting-layer boundaries in space and time and variations of the shape of the apparent VPR in time. The application of the VPR correction to reflectivity and rainfall estimates from a reflectivity–rainfall algorithm and a polarimetric algorithm showed that this VPR correction method effectively removes the bias that is due to the brightband effect in PPI scans. It performs also satisfactorily in the snow region, removing the decrease of the observed VPR with range but with an overestimation by 2 dB or more. This method does not require a tuning using climatological data, and it can be applied on any algorithm for rainfall estimation

A multi-sensor approach for volcanic ash cloud retrieval and eruption characterization: the 23 November 2013 Etna lava fountain

Volcanic activity is observed worldwide with a variety of ground and space-based remote sensing instruments, each with advantages and drawbacks. No single system can give a comprehensive description of eruptive activity, and so, a multi-sensor approach is required. This work integrates infrared and microwave volcanic ash retrievals obtained from the geostationary Meteosat Second Generation (MSG)-Spinning Enhanced Visible and Infrared Imager (SEVIRI), the polar-orbiting Aqua-MODIS and ground-based weather radar. The expected outcomes are improvements in satellite volcanic ash cloud retrieval (altitude, mass, aerosol optical depth and effective radius), the generation of new satellite products (ash concentration and particle number density in the thermal infrared) and better characterization of volcanic eruptions (plume altitude, total ash mass erupted and particle number density from thermal infrared to microwave). This approach is the core of the multi-platform volcanic ash cloud estimation procedure being developed within the European FP7-APhoRISM project. The Mt. Etna (Sicily, Italy) volcano lava fountaining event of 23 November 2013 was considered as a test case. The results of the integration show the presence of two volcanic cloud layers at different altitudes. The improvement of the volcanic ash cloud altitude leads to a mean difference between the SEVIRI ash mass estimations, before and after the integration, of about the 30%. Moreover, the percentage of the airborne “fine” ash retrieved from the satellite is estimated to be about 1%–2% of the total ash emitted during the eruption. Finally, all of the estimated parameters (volcanic ash cloud altitude, thickness and total mass) were also validated with ground-based visible camera measurements, HYSPLIT forward trajectories, Infrared Atmospheric Sounding Interferometer (IASI) satellite data and tephra deposits

Mesoscale high-resolution meteorological and radiative transfer models for satellite downlink budget design at millimeter-wave frequencies

Deep space (DS) missions for interplanetary explorations are aimed at acquiring information about the solar system and its composition. To achieve this result a radio link is established between the space satellite and receiving stations on the Earth. Significant channel capacity must be guaranteed to such spacecraft-to-Earth link considering their large separation distance as well. Terrestrial atmospheric impairments on the space-to-Earth propagating signals are the major responsible for the signal degradation thus reducing the link’s channel temporal availability. Considering the saturation and the limited bandwidth of the conventional systems used working at X-band (around 8.4 GHz), frequencies above Ku-band (12-18 GHz) are being used and currently explored for next future DS missions. For example, the ESA mission EUCLID, planned to be launched in 2020 to reach Sun-Earth Lagrange point L2, will use the K-band (at 25.5-27 GHz). The BepiColombo (BC) ESA mission to Mercury, planned to be launched in 2016, will use Ka-band (at 32-34 GHz) with some modules operating at X-band too. The W-band is also being investigated for space communications (Lucente et al., IEEE Systems J., 2008) as well as near-infrared band for DS links (Luini at al., 3rd IWOW, 2014; Cesarone et al., ICSOS, 2011). If compared with X-band channels, higher frequency bands can provide an appealing data rate and signal-to-noise ratio in free space due to the squared-frequency law increase of antenna directivity within the downlink budget (for the same physical antenna size). In particular, W-band (75–110 GHz) can be one valid alternative to K- and Ka-bands; theoretically, W-band should provide high channel capacities due to the large bandwidth availability and a more robust immunity to signal interference. However, atmospheric path attenuation can be significant for higher frequencies since the major source of transmission outage is not only caused by convective rainfall, as it happens for lower frequencies too, but even non-precipitating clouds and moderate precipitation produced by stratiform rain events are detrimental. This means that accurate channel models are necessary for DS mission data link design. A physical approach can offer advanced radiopropagation models to take into account the effects due to atmospheric gases, clouds and precipitation. The objective of this work is to couple a weather forecast numerical model with a microphysically-oriented radiopropagation model, providing a description of the atmospheric state and of its effects on a DS downlink. This work is the continuation of a study developed in the framework of the RadioMeteorological Operations Planner (RMOP) program, aimed at performing a feasibility study for the BC mission (Biscarini et al., EuCAP 2014). The RMOP chain for the link budget computation is composed by three modules: weather forecast (WFM), radio propagation (RPM) and downlink budget (DBM). WFM is aimed at providing an atmospheric state vector. Among the available weather forecast models, for RMOP purposes we have used the Mesoscale Model 5. The output of the WFM is the input of the RPM for the computation of the atmospheric attenuation and sky-noise temperature at the receiving ground station antenna. RPM makes use of radiative transfer solver, based on the Eddington approximations well as accurate scattering models. Time series of attenuation and sky-noise temperature coming from the RPM are converted into probability density functions and then ingested by the DBM to compute the received data volume (DV). RMOP project was originally aimed at investigating the Ka-band for DS mission focusing the attention on the advantages of using a coupled WFM- RPM approach with respect to climatological statistics in a link budget optimization procedure. In this work we extended the study to the W- and K- band. The signal degradation, due to atmospheric effects in DS links in terms of received DV, is investigated and a comparison among K-, Ka-, W- and the more commonly used X-band is carried out. The quality of the DS downlink will be given in terms of received DV and the results at different frequencies compared showing the respective advantages and drawbacks

Investigating Ka-band science data transfer for BepiColombo mission by using radiometeorological numerical models

Deep space (DS) exploration is aimed at acquiring information about the solar system and its composition, a purpose that can be achieved only if a significant communication capacity can be provided to spacecrafts at very large distances [1]. The Ka-band (at 32-34 GHz) and higher frequency band channels can provide this capacity if compared to the current X-band (around 8.4 GHz) [2]-[4]. Ka-band can offer a striking performance advantage over X-band because of the square-frequency law increase of directivity of the downlink beam for the same physical antenna size. This opens up a possible and useful trade space for Ka-band missions with the same antenna size (and spacecraft constraints) and radio frequency power, since a Ka-band mission can return four times more data than a comparable X–band mission. For the European Space Agency (ESA), the next step in this direction will be the utilisation of Ka-band downlinks both to generate radiometric observables (in combination with X-band uplink) as well as to increase science data transfer [5]. The first satellite mission adopting such frequency operationally will be BepiColombo (BC), the ESA cornerstone mission to Mercury (expected launch in 2015) including the Mercury Orbiter Radio Experiment (MORE) at X-Ka band [6]. The optimal allocation of channel resources above Ku band is limited by the significant impact of radio- meteorological factors which can irremediably degrade the quality of service for fairly high percentage of time [7]. At Ka band, for instance, attenuation due to cloudy and rainy troposphere can be even one order of magnitude larger than at X-band. The major cause of outages at Ka band and above is due to rainfall, as well as non-precipitating clouds. For small carrier-to-noise ratio (CNR), the impact of atmospheric noise temperature can become non-negligible [4]. In order to achieve the optimum data return at Ka-band, a different approach with respect to the link budget computation at lower frequencies (e.g., S or X band) is necessary [2]. Such link analysis is based on the maximization of the expected data return in a probabilistic framework rather than on a specified link statistical availability. Recent methods uses monthly statistics collected at the receiving site with the aim of defining average values of expected received data volume [5] and the exploitation of numerical weather forecasting is also foreseen [3]. This paper introduces the preliminary concept of the RadioMetOP (RadioMeteorological Operations Planner) technique and describes its main modelling components and objectives, limiting the analysis to rainfall effects. Numerical results in terms of received frame data for unconstrained and constrained system scenarios are also described together with a discussion about the possible impact of RadioMetOP methods on BC operations

The HyMeX Special Observation Period in Central Italy: Precipitation Measurements, Retrieval Techniques and Preliminary Results

The Mediterranean area concentrates the major natural risks related to the water cycle, including heavy precipitation and flash-flooding during the fall season. The capability to predict such high-impact events remains weak because of the contribution of very fine-scale processes and their non-linear interactions with the larger scale processes. These societal and science issues motivate the HyMeX (Hydrological cycle in the Mediterranean Experiment, http://www.hymex.orgl) experimental programme. HyMeX aims at a better quantification and understanding of the water cycle in the Mediterranean with emphasis on intense events. The observation strategy of HyMEX is organized in a long-term (4 years) Enhanced Observation Periods (EOP) and short-term (2 months) Special Observation Periods (SOP). HyMEX has identified 3 main Mediterranean target areas: North-West (NW), Adriatic (A) and South-East (SE). Within each target area several hydrometeorological sites for heavy rainfall and flash flooding have been set up. The hydrometeorological sire in Central Italy (CI) is interested by both western and eastern fronts coming from the Atlantic Ocean and Siberia, respectively. Orographic precipitations play an important role due to the central Apennine range, which reaches nearly 3000 m (Gran Sasso peak). Moreover, convective systems commonly develop in CI during late summer and beginning of autumn, often causing localized hailstorms with cluster organized cells. Western fronts may heavily hit the Tiber basin crossing large urban areas (Rome), whereas eastern fronts can cause flash floods along the Adriatic coastline. Two major basins are involved within Cl region: Tiber basin (1000 km long) and its tributary Aniene and the Aterno-Pescara basin (300 km long). The first HyMeX SOP1.1 was carried out from Sept. till Nov. 2012 in the NW target area The Italian SOP1.1 was coordinated by the Centre of Excellence CETEMPS, University of L'Aquila, a city located in the CI heart. The CI area was covered by a uniquely dense meteorological instrumentation thanks to a synergy between Italian institutions and NASA-GSFC. The following RADARs were operated: a Doppler single-polarization C-band radar located at Mt Midia; the Polar 55C Doppler dual-polarization C-band radar located in Rome; a Doppler C-hand polarimetric radar located at Il Monte (Abnazo); a polarimetric X-band mini-radar in L' Aquila; a polarimetric X-hand portable mini-radar in Rome; a single-polarization X-band mini-radar in Rome. DISDROMETERs were also deployed: 4 Parsivel optical disdrometers in Rome (at Sapienza, CNR-ISAC and CNR-INSEAN); 1 2D-video disdrometer in Rome; 3 Parsivels optical disdrometer respectively in L'Aquila (Abnazo), Avezzano (Abruzzo) and Pescara (Abnazo). Other INSTRUMENTS were available: 1 K-band vertically-pointing micro rain-radar (MRR), 2 Pludix X-band disdrometers, 1 VLF lightning sensor, 1 microwave radiometer at 23-31 GHz in Rome (at Sapienza); the raingauge network with more than 200 stations in Central Italy. Three overpasses in CI were also performed by the Falcon 20 aircraft equipped with the 950Hz cloud radar RASTA Analysis of the SOP1.1 main events in CI will be described by focusing on the raindrop size distribution statistics and its geographical variability. Intercomparison of rainfall estimates from disdrometers, raingauges and radars will be illustrated with the aim to provide a quality-controlled and physically consistent rainfall dataset for meteorological modeling validation and assimilation purposes