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Cloud electrification and related lightning activity in thunderstorms have their origin in the charge separation and resulting distribution of charged iced particles within the cloud. So far, the ice distribution within convective clouds has been investigated mainly by means of ground-based meteorological radars. In this paper we show how the products from Cloud Profiling Radar (CPR) on board CloudSat, a polar satellite of NASA's Earth System Science Pathfinder (ESSP), can be used to obtain information from space on the vertical distribution of ice particles and ice content and relate them to the lightning activity. The analysis has been carried out, focusing on 12 convective events over Italy that crossed CloudSat overpasses during significant lightning activity. The CPR products considered here are the vertical profiles of cloud ice water content (IWC) and the effective radius (ER) of ice particles, which are compared with the number of strokes as measured by a ground lightning network (LINET). Results show a strong correlation between the number of strokes and the vertical distribution of ice particles as depicted by the 94 GHz CPR products: in particular, cloud upper and middle levels, high IWC content and relatively high ER seem to be favourable contributory causes for CG (cloud to ground) stroke occurrence. [ABSTRACT FROM AUTHOR]

The impact of the aerosol optical properties on the ultraviolet index (UVI) in the urban area of Rome is investigated in this study. In particular, the influence of aerosol optical depth (AOD) and single scattering albedo (SSA), estimated at the wavelength of 340 nm, and of the Ångström exponent, calculated in the range 340–500 nm, over a period of 11 years (2010–2020) in the months from March to September are analyzed. The UVI is monitored by a Brewer spectrophotometer, whereas measurements of the direct Sun and diffuse sky irradiances are performed by a co-located PREDE-POM sun–sky radiometer of the ESR/SKYNET network; the aerosol optical properties are obtained by the Skyrad MRIv2 retrieval. A novel method, based on physical principles and easily adaptable to other contexts, is developed to extrapolate the aerosol properties to the UV range during periods when only visible to near-infrared measurements are available. The retrievals from the sun–sky radiometer are consistent with the chemical characterization of urban PM 10 (particulate matter 10 mm or less in diameter) samples collected during an intensive field campaign held in summer 2011 at the same site (URBan Sustainability Related to Observed and Monitored Aerosol – URBS ROMA). The PM macro components identified during the campaign are grouped in order to evaluate the contribution of the main macro sources (soil, sea, secondary inorganic, organics, and traffic) whose relative role is indeed expected to strongly affect the aerosol absorption capability. The surface forcing efficiency, calculated as the change in the UV index for a unit AOD variation, shows that AOD is the primary parameter affecting the surface irradiance under clear-sky conditions in Rome. SSA and the Ångström exponent are also identified as secondary influencing factors, i.e., the surface forcing efficiency is found to be greater for smaller zenith angles and for larger and more absorbent particles in the UV range (such as, e.g., mineral dust). [ABSTRACT FROM AUTHOR]

We analyzed a sample of 278 TGFs detected by the RHESSI, AGILE, and Fermi satellites between 2003 and 2015, occurring within the 60°W and 60°E longitude range. Each of these events has an associated lightning sferic occurring within ±500 µs, detected by the World Wide Lightning Location Network (WWLLN), that provides the best geographic localization of the source thunderstorm (<20 km). We performed a systematic analysis of the 278 TGF-associated storms, by exploiting data acquired by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument, onboard the Meteosat Second Generation (MSG) geostationary satellites (i.e., Meteosat-8/9/10, or MSG-1/2/3). For each storm, we analyzed several meteorological parameters, such as the cloud top temperature, the cloud extension, the cloud top altitude, the convective level, and the lightning flash rate, provided by the WWLLN. Furthermore, we studied those quantities at the time that TGFs occurred (taken into account the MSG time resolution), and their evolution within a time interval of ±100 min about the TGF time.The TGF-associated thunderstorms turn out to follow the typical behavior of tropical thunderstorms, peaking in the afternoons and over continental regions. The study of the meteorological parameters shows that these systems exhibit a wide range of values, mostly involving storms with lowest cloud top temperatures (<-75°C), highest top heights (>15 km), and large top extensions (> 35,000 km2), confirming what already found in other studies; morevoer, the study of the time evolution shows that TGFs tend to take place during the peak of the cooling phase, when the top temperature reaches its lowest value and the lightning flash rate is at its maximum. In order to investigate whether thunderstorms found producing TGFs show peculiar characteristics, with respect to typical thunderstorms, we carried out a cross-check with random storms occurring in the same geographic region, and performed a statistical analysis to establish whether differences are present between the two populations. [ABSTRACT FROM AUTHOR]

The aerosol optical characteristics in the urban area of Rome were retrieved over a period of 7 years from March to September 2010–2016. The impact of aerosol single scattering albedo (SSA), optical depth (AOD), estimated at 400 nm, and Ångström exponent on the ultraviolet (UV) index has been analyzed. Aerosol optical properties are provided by a PREDE-POM sun-sky radiometer of the ESR/SKYNET network and the UV index values were retrieved by a Brewer spectrophotometer both located in Rome. Chemical characterization of urban PM10 (particulate matter 10 micrometers or less in diameter) samples, collected during the URBan Sustainability Related to Observed and Monitored Aerosol (URBS ROMA) intensive filed campaign held in summer 2011 in the same site, was performed. PM macro-components were grouped in order to evaluate the contribution of the main macro-sources (SOIL, SEA, SECONDARY INORGANIC, ORGANICS and TRAFFIC) and the analysis of the modulation of their concentration was found to strongly affects the absorption capability of the atmosphere over Rome. The surface forcing efficiency, provided by the decreasing trend of UV index with AOD, which is the primary parameter affecting the surface irradiance, was found very significant, probably masking the dependence of UV index on SSA and Ångström exponents. Moreover it was found greater for larger particles and with a more pronounced slope at the smaller solar zenith angle. In Rome large particles are generally less absorbing since related to the presence of SOIL and SEA components in the atmosphere. The former contribution was found much higher in summer months because of the numerous episodes of Saharan dust transport. [ABSTRACT FROM AUTHOR]

The estimation of the precipitable water vapour content (W) with high temporal and spatial resolution is of great interest to both meteorological and climatological studies. Several methodologies based on remote sensing techniques have been recently developed in order to obtain accurate and frequent measurements of this atmospheric parameter. Among them, the relative low cost and easy deployment of sun–sky radiometers, or sun photometers, operating in several international networks, allowed the development of automatic estimations of W from these instruments with high temporal resolution. However, the great problem of this methodology is the estimation of the sun-photometric calibration parameters. The objective of this paper is to validate a new methodology based on the hypothesis that the calibration parameters characterizing the atmospheric transmittance at 940 nm are dependent on vertical profiles of temperature, air pressure and moisture typical of each measurement site. To obtain the calibration parameters some simultaneously seasonal measurements of W, from independent sources, taken over a large range of solar zenith angle and covering a wide range of W, are needed. In this work yearly GNSS/GPS datasets were used for obtaining a table of photometric calibration constants and the methodology was applied and validated in three European ESR-SKYNET network sites, characterized by different atmospheric and climatic conditions: Rome, Valencia and Aosta. Results were validated against the GNSS/GPS and AErosol RObotic NETwork (AERONET) W estimations. In both the validations the agreement was very high, with a percentage RMSD of about 6, 13 and 8 % in the case of GPS intercomparison at Rome, Aosta and Valencia, respectively, and of 8 % in the case of AERONET comparison in Valencia. [ABSTRACT FROM AUTHOR]

The estimation of the precipitable water vapor content (W) with high temporal and spatial resolution is of great interest in both meteorological and climatological studies. Several methodologies based on remote sensing techniques have been recently developed, in order to obtain accurate and frequent measurements of this atmospheric parameter. Among them, the relative low cost and easy deployment of sun-sky radiometers, or sun-photometers, operating in several international networks, allowed the development of automatic estimations of W from these instruments with high temporal resolution. However the great problem of this methodology is the estimation of the sun-photometric calibration parameters. The objective of this paper is to validate a new methodology based on the hypothesis that the calibration parameters characterizing the atmospheric transmittance at 940 nm are dependent on vertical profiles of temperature, air pressure and moisture typical of each measurement site. To obtain the calibration parameters some simultaneously seasonal independent measurements of W taken over a large range of solar zenith angle and covering a wide range of W, are needed. In this work yearly GNSS/GPS dataset were used for obtaining a table of photometric calibration constants and the methodology was applied and validated in three European ESR-SKYNET network sites, characterized by different atmospheric and climatic conditions: Rome, Valencia and Aosta. Results were validated against the GNSS/GPS and AErosol Robotic NETwork (AERONET) W estimations. In both the validations the agreement was very high with a percentage RMSD of about 6 %, 13 % and 8 % in the case of GPS intercomparison at Rome, Aosta and Valencia, respectively, and of 8 % in the case of AERONET comparison in Valencia. Analysing the results by W classes, the present methodology was found to clearly improve W estimation at low W content when compared against AERONET in term of %Bias, bringing the agreement with the GPS (considered the reference one), from a %Bias of 5.76 to 0.52. [ABSTRACT FROM AUTHOR]

In this paper, we evaluate the performance of two Global Horizontal solar Irradiance (GHI) estimates, one derived from Meteosat Second Generation (MSG) and another from one-day forecast of the Regional Atmospheric Modeling System (RAMS) mesoscale model. The horizontal resolution of the MSG-GHI is 3*5 km² over Italy, which is the focus area of this study. For this paper, RAMS has the horizontal resolution of 4 km. The performance of MSG-GHI estimate and RAMS-GHI one-day forecast are evaluated for one year (1 June 2013-31 May 2014) against data of twelve ground based pyranometers over Italy spanning a range of climatic conditions, i.e. from maritime Mediterranean to Alpine climate. Statistics on hourly GHI and daily integrated GHI are presented for the four seasons and the whole year for all the measurement sites. Different sky conditions are considered in the analysis. Results on hourly data show an evident dependence on the sky conditions, with the Root Mean Square Error (RMSE) increasing from clear to contaminated, and to overcast conditions. The RMSE increases substantially for Alpine stations in all the seasons, mainly because of the increase of the cloud coverage for these stations, which is not well represented at the satellite and model resolutions. Considering the yearly statistics for the RAMS model, the RMSE ranges from 152 W/m² (31 %) obtained for Cozzo Spadaro, a maritime station, to 287 W/m² (82 %) for Aosta, an Alpine site. Considering the yearly statistics for MSG-GHI, the minimum RMSE is for Cozzo Spadaro (71 W/m², 14 %), while the maximum is for Aosta (181 W/m², 51 %). The Mean Bias Error (MBE) shows the tendency of RAMS to over forecast the GHI, while no specific tendency if found for MSG-GHI. Results for daily integrated GHI show a reduction of the RMSE of at least 10 %, compared to hourly GHI evaluation, for both RAMS-GHI one-day forecast and MSG-GHI estimate. A partial compensation of underestimation and overestimation of the GHI contributes to the RMSE reduction. Furthermore, a post-processing technique, namely Model Output Statistics (MOS), is applied to hourly and daily integrated GHI. The application of MOS shows an improvement for RAMS-GHI up to 24 %, depending on the site considered, while the impact of MOS on MSG-GHI RMSE is small (2-3 %). [ABSTRACT FROM AUTHOR]

The objective of this paper is to describe the development and evaluate the performance of a completely new version of the Passive microwave Neural network Precipitation Retrieval (PNPR v2), an algorithm based on a neural network approach, designed to retrieve the instantaneous surface precipitation rate using the cross-track Advanced Technology Microwave Sounder (ATMS) radiometer measurements. This algorithm, developed within the EUMETSAT H-SAF program, represents an evolution of the previous version (PNPR v1), developed for AMSU/MHS radiometers (and used and distributed operationally within H-SAF), with improvements aimed at exploiting the new precipitation-sensing capabilities of ATMS with respect to AMSU/MHS. In the design of the neural network the new ATMS channels compared to AMSU/MHS, and their combinations, including the brightness temperature differences in the water vapor absorption band, around 183 GHz, are considered. The algorithm is based on a single neural network, for all types of surface background, trained using a large database based on 94 cloud-resolving model simulations over the European and the African areas. The performance of PNPR v2 has been evaluated through an intercomparison of the instantaneous precipitation estimates with co-located estimates from the TRMM Precipitation Radar (TRMM-PR) and from the GPM Core Observatory Ku-band Precipitation Radar (GPM-KuPR). In the comparison with TRMM-PR, over the African area the statistical analysis was carried out for a 2-year (2013–2014) dataset of coincident observations over a regular grid at 0.5°  ×  0.5° resolution. The results have shown a good agreement between PNPR v2 and TRMM-PR for the different surface types. The correlation coefficient (CC) was equal to 0.69 over ocean and 0.71 over vegetated land (lower values were obtained over arid land and coast), and the root mean squared error (RMSE) was equal to 1.30 mm h−1 over ocean and 1.11 mm h−1 over vegetated land. The results showed a slight tendency to underestimate moderate to high precipitation, mostly over land, and overestimate moderate to light precipitation over ocean. Similar results were obtained for the comparison with GPM-KuPR over the European area (15 months, from March 2014 to May 2015 of coincident overpasses) with slightly lower CC (0.59 over vegetated land and 0.57 over ocean) and RMSE (0.82 mm h−1 over vegetated land and 0.71 mm h−1 over ocean), confirming a good agreement also between PNPR v2 and GPM-KuPR. The performance of PNPR v2 over the African area was also compared to that of PNPR v1. PNPR v2 has higher R over the different surfaces, with generally better estimation of low precipitation, mostly over ocean, thanks to improvements in the design of the neural network and also to the improved capabilities of ATMS compared to AMSU/MHS. Both versions of PNPR algorithm have shown a general consistency with the TRMM-PR. [ABSTRACT FROM AUTHOR]

The objective of this paper is to describe the development and evaluate the performance of a totally new version of the Passive microwave Neural network Precipitation Retrieval (PNPR v2), an algorithm based on a neural network approach, designed to retrieve the instantaneous surface precipitation rate using the cross-track ATMS radiometer measurements. This algorithm, developed within the EUMETSAT H-SAF program, represents an evolution of the previous version (PNPR v1), developed for AMSU/MHS radiometers (and used and distributed operationally within H-SAF), with improvements aimed at exploiting the new precipitation sensing capabilities of ATMS with respect to AMSU/MHS. In the design of the neural network the new ATMS channels compared to AMSU/MHS, and their combinations, including the brightness temperature differences in the water vapor absorption band, around 183 GHz, are considered. The algorithm is based on a single neural network, for all types of surface background, trained using a large database based on 94 cloud-resolving model simulations over the European and the African areas. The performance of PNPR v2 has been evaluated through an intercomparison of the instantaneous precipitation estimates with co-located estimates from the TRMM Precipitation Radar (TRMM-PR) and from the GPM Core Observatory Ku-band Precipitation Radar (GPM-KuPR). In the comparison with TRMM-PR, over the African area, the statistical analysis was carried out for a two-year (2013-2014) dataset of coincident observations, over a regular grid at 0.5° × 0.5° resolution. The results have shown a good agreement between PNPR v2 and TRMM-PR for the different surface types. The correlation coefficient (CC) was equal to 0.69 over ocean and 0.71 over vegetated land (lower values were obtained over arid land and coast), and the root mean squared error (RMSE) was equal to 1.30 mm h-1 over ocean and 1.11 mm h-1 over vegetated land. The results showed a slight tendency to underestimate moderate to high precipitation, mostly over land, and overestimate moderate to light precipitation over ocean. Similar results were obtained for the comparison with GPM-KuPR over the European area (15 months, from March 2014 to May 2015 of coincident overpasses) with slightly lower CC (0.59 over vegetated land and 0.57 over ocean) and RMSE (0.82 mm h-1 over vegetated land and 0.71 mm h-1 over ocean), confirming a good agreement also between PNPR v2 and GPM-KuPR. The performance of PNPR v2 over the African area was also compared to that of PNPR v1. PNPR v2 has higher R over the different surfaces, with general better estimate of low precipitation, mostly over ocean, thanks to improvements in the design of the neural network and also to the improved capabilities of ATMS compared to AMSU/MHS. Both versions of PNPR algorithm have shown a general consistency with the TRMM-PR. [ABSTRACT FROM AUTHOR]

Over the past years, ground-based optical observations of transient luminous events (TLEs) have been taken by the Eurosprite network and partners, covering large areas over Europe and parts of the Mediterranean Sea. In particular, a coordinated effort in 2009 through 2013 led to producing the first climatology of more than 8000 TLEs observed above about 1000 thunderstorm systems, and study for the first time their distribution and seasonal variations in these areas. Consistently, lightning were recorded from the World Wide Lightning Location Network (WWLLN) allowing a direct comparison to TLEs. The climatology shows that TLE activity in Europe is intense during summer over continental areas, and in late autumn over coastal areas and sea. The two seasons peak respectively in August and November, whereas almost no TLEs are recorded in March and April. The observed TLE activity, which is composed mostly by sprites, is shown to be consistent with the seasonal distribution of lightning activity. The consistency among individual years makes the observed seasonal cycle a robust general feature of TLE activity above Europe. Because of the inhomogeneous spatial distribution of the adopted ground-based observing systems, observations were treated in terms of anomalies about the yearly mean. Key areas where the observations have a homogeneous coverage and were continued in the following years are identified and discussed. These areas may be used to normalize the overall distribution and for intercomparing with space-based observations from the Atmosphere-Space Interactions Monitor (ASIM) flying on the International Space Station, and to future lightning observations from the Meteosat Third Generation Lightning Imager. [ABSTRACT FROM AUTHOR]

The Mediterranean Sea is a unique meteorological environment and a weather forecasting challenge, where severe weather events of different nature often originate and develop to hit coastal regions, causing major damages and casualties. Conventional ground-based instruments (e.g., raingauges and weather radars) are often inadequate to monitor events during their offshore development. On the other hand, in spite of their irregular time sampling, Low Earth Orbit satellites, carrying passive and active microwave (MW) sensors, can be fully exploited for the characterization and monitoring of heavy precipitation systems over this area. In this respect, the NASA/JAXA Global Precipitation Measurement (GPM) Core Observatory (CO), equipped with the most advanced MW radiometer (GPM Microwave Imager, GMI) and the first spaceborne Dual-frequency Precipitation Radar (DPR), allows for the 3-D analysis of precipitation structures. Moreover the GPM constellation of MW radiometers ensures 1-3 hourly global coverage of precipitation. In this presentation, we show the GPM mission role in the characterization and monitoring of precipitation associated to extreme events, that hit Italy in the last years. Moreover, we test the capabilities and limitations of advanced satellite precipitation products in the GPM era for quantification and monitoring of precipitation associated with very intense and localized convective cells. To this aim, we analyze the flash flood occurred in Livorno, on the coast of Tuscany, Italy, in the night between 9 and 10 Sept. 2017. In this case, the precipitation products based on the GPM constellation of MW radiometers offer a wide spectrum of results, showing that better performances come from algorithms tailored for the specific region, while algorithms designed for global application are less sensitive to such small-scale thunderstorms. An analogous study is carried out for Numa, a Mediterranean tropical-like cyclone occurred on 16-18 November 2017 over southern Italy. GPM-CO measurements are used, in conjunction with LINET (LIghtning NETwork) data, to show how the rain-band structure evolves as the storm develops into its mature phase. High-resolution simulations were carried out with the Regional Atmospheric Modeling System (RAMS) to analyze the key mechanisms leading to the formation and evolution of Numa. We also show the impact of the assimilation of DPR reflectivity on the precipitation forecast. Long data records of reliable satellite precipitation-related measurements and products are becoming available in the GPM era. Here we make a first attempt to exploit them for a preliminary analysis of occurrence and intensity of extreme events in the Mediterranean, where they can be recognized as climate change signatures. This study evidences the need to fully exploit satellite data and products for studying and monitoring severe weather in the Mediterranean area, and to improve forecasting (and nowcasting) capabilities in this complex region. Thus efforts should be undertaken to develop satellite products tailored for these areas (working on algorithm calibration), and to provide the error structure of the products (working on validation). This would enable users to apply the most suitable product for a specific need, including hydrological applications, and for data assimilation of precipitation-related fields over the sea, where these systems often initiate. [ABSTRACT FROM AUTHOR]

State-of-the-art satellite rainfall products are often the only way for measuring precipitation in remote areas of the world. These products are mainly based on the exploitation of microwave (MW) radiometers on board LEO satellites (top-down approach). However, it is well known that they may fail in properly reproducing the amount of precipitation reaching the ground, which is of paramount importance for hydrological applications (natural hazards forecast and mitigation, water management). Currently, one of the major issues impacting the quality of the information retrieved from space is related to the estimation of light precipitation that causes a general underestimation of the total amount of rainfall. This issue is particularly important over land due to the uncertainty and spatial variability of surface emissivity. With the purpose of improving the accuracy of satellite rainfall products, some approaches using satellite soil moisture (SM) data were recently developed (bottom-up approach). In 2013 a new method for estimating rainfall using satellite SM observations, called SM2RAIN, has been proposed. The method is based on the inversion of the soil water balance equation, i.e. it estimates rainfall by using the variation in time of the amount of water stored into to the soil, thus considering it "as a natural rain gauge". SM2RAIN has been applied both at local and global scale with ground- and satellite-based SM data as input with satisfactory results in terms of rainfall estimation. Moreover, previous studies found that the correction of rainfall estimates through SM2RAIN provides improvement in flood modeling. However SM-only based rainfall estimates suffer a number of issues such as the inability to estimate precipitation when the soil is fully saturated, when it is vegetated or snow-covered, besides not providing any precipitation data over the sea. Thus a fully global satellite rainfall product, able to integrate rainfall estimates derived from top-down and bottom-up approaches, has been demonstrated to be highly beneficial for increasing the accuracy of satellite precipitation estimates.Through the EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (HSAF), the SM2RAIN approach together with the MW-based rainfall product H23 are the scientific background for the development of the "H64 precipitation-soil moisture integrated product". H23 provides daily precipitation estimates by combining MW precipitation rate estimates derived from conical (H01) and cross-track (H02) scanning radiometers. SM estimates obtained through H16 and H101 H SAF products are used to estimate rainfall through SM2RAIN, and then merged with H23 precipitation estimates through a simple nudging scheme. H64 has been designed to combine optimally the two different approaches in order to provide a more reliable rainfall product, that can be used in an operational framework. Preliminary results show that H64 can efficiently reproduce the observed rainfall during a 4-year period, providing a useful and reliable source of information over scarcely instrumented areas. This first assessment provides very useful insights about the development of a near-real time rainfall product based on SM2RAIN and MW-based top-down precipitation products. [ABSTRACT FROM AUTHOR]

The development of precipitation retrieval techniques, as well as the quality assessment of satellite-based global precipitation estimates, can now benefit from the availability of unique cloud and precipitation observations by the two spaceborne radars: the Dual-frequency Precipitation Radar (DPR) on board the NASA/JAXA Global Precipitation Measurement (GPM) Core Observatory, and the NASA CloudSat Cloud Profiling Radar (CPR). The multi-year, quasi-global, and complementary DPR and CPR measurements offer a unique and extensive resource to analyze spaceborne microwave radiometer precipitation observational capabilities. This can be particularly useful in remote areas and/or where ground-based observations are sparse or not available and in conditions and regimes where passive MW precipitation retrieval is more challenging. A recent study (Panegrossi et al., 2017) illustrated the potential of the use of these observational datasets to improve snowfall detection and retrieval techniques for MW radiometers at higher latitudes. Recently, a new algorithm for snowfall detection and retrieval for the Global Precipitation Measurement (GPM) Microwave Imager (GMI) (SLALOM, Snow retrievaL ALgorithm fOr gMi) has been developed (Rysman et al., 2018). The algorithm is tuned and evaluated against coincident observations of the CPR, and enables the detection of supercooled water and the retrieval of snow water path (SWP). From a forward-looking perspective we are currently investigating the use of cross-track scanning radiometers, in particular the Advanced Technology MicroWave Sounder (ATMS), for snowfall detection and retrieval. It is worth noticing that ATMS sensor is currently carried by near-polar operational LEO satellites, and therefore it could be used for investigating the higher latitudes. In particular, the potential for snowfall detection of the several high-frequency channels, i.e. the five channels in the 183.3 GHz water vapor absorption band, is being investigated. These channels are very sensitive to snowfall and are less affected by the background surface. The results of a sensitivity study based on the analysis of snowfall events for which triple coincidences of CPR,ATMS, and GMI observations are available is presented. The events analyzed have been extracted from the 3B-CSATGPM dataset (Turk, 2018). A comparison of the different response of ATMS and GMI to the same snowfall event is carried out. In particular, the TBs measured by both radiometers and different channel combinations have been compared considering snowfall profiles obtained by CPR and environmental conditions (i.e., moisture and temperature profiles, and presence of supercooled droplets). Some intense snowfall events has been taken into account, such as an event that took place in Eastern Siberia in 2014/04/30, an event which took place on the Greenland coast 2014/09/21, and an event that took place in the Andes region in 2016/06/03.These studies pave the way towards the definition of future missions for snowfall global monitoring by combining a core satellite equipped with a multi-frequency radar in synergy with current and future MW radiometers (such as the EPS-SG Microwave Imager and Microwave Sounder). [ABSTRACT FROM AUTHOR]