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An important objective of the Global Precipitation Measurement (GPM) mission is the detection of falling snow, since it accounts for a significant fraction of precipitation in the mid-high latitudes. The GPM Core Observatory carries the first spaceborne Dual-frequency Precipitation Radar (DPR), designed with enhanced sensitivity to detect lighter liquid and solid precipitation. The primary goal of this study is to assess the DPR's ability to identify snowfall using near-coincident CloudSat Cloud Profiling Radar (CPR) observations and products as an independent reference dataset. CloudSat near global coverage and high sensitivity of the W-band CPR make it very suitable for snowfall-related research. While DPR/CPR radar sensitivity disparities contribute substantially to snowfall detection differences, this study also analyzes other factors such as precipitation phase discriminators that produce snowfall identification discrepancies. Results show that even if the occurrence of snowfall events correctly detected by DPR products is quite small compared to CPR (around 5–7%), the fraction of snowfall mass is not negligible (29–34%). A direct comparison of CPR and DPR reflectivities illustrates that DPR misdetection is worsened by a noise-reducing DPR algorithm component that corrects the measured reflectivity. This procedure eliminates the receiver noise and side lobe clutter effects, but also removes radar signals related to snowfall events that are associated with relatively low reflectivity values. In an effort to increase DPR signal fidelity associated with snowfall, this paper proposes a simple algorithm using matched DPR Ku/Ka radar reflectivities producing an increase of the fraction of snowfall mass detected by DPR up to 59%.

The first Special Observation Period (SOP1) field campaign of the HyMeX (HYdrological cycle in the Mediterranean EXperiment) program was held in fall 2012 and was devoted to the investigation of heavy precipitation and floods in the Western Mediterranean. Both the Italian research and operational meteorological communities actively participated by providing a valuable contribution through the organization of an ad hoc national Operational Centre. The paper presents an overview of this participation, resulting in a fruitful multidisciplinary experience able to build a bridge between academia, researchers, forecasters, end-users and decision makers. The benefits provided by the wide national involvement and the consequent possible national impacts and progress are discussed within the context of the complex organization of meteorology in Italy.

The Mediterranean area is a particular meteorological environment and a weather forecasting challenge, because severe weather events of different nature often originates over the relatively warm sea and develops to hit coastal regions, often rich in assets and densely populated, causing major damages and casualties. In the last years tropical-like precipitation systems, i.e. with large horizontal extent, tropical cyclone features (i.e. Medicanes), or characterized by very deep and intense convection, have become more and more frequent. A number of studies have recently been devoted to the analysis of these severe weather events, both from the observational and numerical modeling points of view. The complex orography that characterizes most of the Mediterranean coast, as well as the need to monitor these severe events during their offshore development, make the use of conventional ground-based rain measuring systems (i.e., raingauges and weather radars) inadequate to fully provide the observational details which are necessary to improve the monitoring and forecasting of precipitation in terms of time, location, and amounts. The increasing global multi-mission Earth Observation (EO) observational capacity provides today an unprecedented potential to observe, describe and predict hydrological parameters, such as precipitation, and key processes governing the water cycle from local to global scales. Satellite precipitation products are developed and made available by space agencies (NASA, NOAA, JAXA) and through international programs/projects, and can be used for floods and droughts monitoring, hydrological applications, and for climate studies. The goal of this presentation is to show the potentials of the constellation of passive microwave (PMW) radiometers orbiting around the Earth to monitor precipitation associated to extreme events, also in particularly challenging regions, with complex orography and extremely variable surface conditions, such as the Mediterranean area. Such constellation has recently reached an optimal configuration thanks to the advent of the NASA/JAXA Global Precipitation Measurement (GPM) mission. By combining the overpasses from different radiometers it is possible to obtain precipitation estimates at different temporal scales (i.e., daily, monthly) in agreement with reference ground-based radar and raingauge measurements. Moreover, the GPM Core Observatory is equipped with the most advanced microwave radiometer (GPM Microwave Imager, GMI) in terms of spatial resolution and channel assortment, and with the first spaceborne dual-frequency precipitation radar (DPR), allowing the analysis of the 3-D structure of precipitation. Extreme precipitation events that hit the coast of Italy in the last years will be presented and analyzed.

One of the main goals of the Global Precipitation Measurement (GPM) mission is to improve snowfall retrieval accuracy, as snowfall is, the predominant component of the global precipitation amount at mid and high latitudes. The GPM Core Observatory (GPM-CO) is equipped with two instruments: the GMI, the most advanced conical precipitation radiometer with respect to both channel assortment and spatial resolution; and the Dual-frequency Precipitation Radar (DPR) [composed of two radars, a Ku-band Precipitation Radar (KuPR) (13.6-GHz) and a Ka-band (35.5-GHz) Precipitation Radar (KaPR)]. Advancements in snowfall detection and accuracy in quantitative estimates of snowfall rates at mid-high latitudes is expected from both the GMI and DPR. Moreover, thanks to the exploitation of the high-frequency channels (> 100 GHz) available on most of radiometers in the GPM constellation, providing very good coverage at mid-high latitudes (hourly or less), snowfall monitoring is now possible. Among these radiometers, the Advanced Technology Microwave Sounder (ATMS) onboard Suomi-NPP is the most advanced cross track radiometer with 22 channels, 5 of which in the 183 GHz oxygen absorption band. On the other hand, CloudSat carries the W-band (94GHz) Cloud Profiling Radar (CPR) that has collected data since its 2006 launch. While CPR was designed as primarily a cloud remote sensing mission, its high-latitude coverage (up to ;82° latitude) and hi gh radar sensitivity (~-28dBZ) make it very suitable for snowfall-related research. We will show the results of a study where CPR is used to: 1) assess snowfall detection and estimate capabilities of DPR; 2) analyze snowfall signatures in the high frequency channels of the passive microwave radiometers in relation to fundamental environmental conditions. A number of global datasets made of coincident observations of snowfall producing clouds from the spaceborne radars DPR and CPR and from the most advanced radiometers available (GMI and ATMS) are analyzed. We have assessed the snowfall detection and estimation capabilities of DPR, comparing its observations and precipitation products with those available from CPR. We have estimated that DPR radars miss a very large fraction of snowfall precipitation (more than 90% of the events and around 70% of the precipitating snowfall mass). This is due mostly to the sensitivity limits of the DPR radar and secondly to the effect of the DPR radar side lobe clutter. An algorithm that combines the measured reflectivities from the two Ku-band and Ka-band radars exploiting the weak signals related to snowfall has been developed. Results from this study will be presented, showing improved DPR detection capabilities up to more than 50% of the snowfall mass obtained with the newly developed algorithm. Moreover the coincident observations of ATMS - CPR and of the GMI - DPR have been analyzed in order to study the multichannel brightness temperature signal related to snowfall. The main results of this study show that the high frequency channels (and the 183 GHz band channels in particular) can be successfully used in order to identify and quantify snowfall. The degree of success strongly depends on the type of surface background which requires proper detection and identification. Moreover, some ancillary data must be used (i.e. the columnar water vapor content is of paramount importance) for the correct use of the measurements towards snowfall detection. In this context an algorithm for surface classification of snow over land and ice over ocean using primarily the PMW low frequency channels is proposed and will be presented.

Precipitation retrievals exploiting the available passive microwave (PMW) observations by cross-track and conically scanning satellite-borne radiometers in the Global Precipitation Measurement (GPM) mission era are used to monitor and characterize heavy precipitation events that occurred during the Fall 2014 in Italy. The analysis focuses on specific features of three selected case studies over the Italian area, in order to evidence suitability and limitations of PMW precipitation retrievals from the different radiometers to estimate quantitatively the precipitation rate and to characterize extreme events. Different physically based PMW precipitation retrieval algorithms are used: the Cloud Dynamics and Radiation Database (CDRD) and Passive microwave Neural network Precipitation Retrieval (PNPR), used operationally in the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on support to Operational Hydrology and Water Management (H-SAF), and the National Aeronautics and Space Administration (NASA) Goddard PROFiling algorithm (GPROF). The assessment of the accuracy of the satellite precipitation estimates has been carried out using the available polarimetric ground-based radar and/or raingauge measurements. The different characteristics of the radiometers (i.e., viewing geometry, spatial resolution, channel assortment) and of retrieval techniques, as well as the limitations of the ground-based reference datasets, are taken into consideration in the evaluation of the accuracy and consistency of the retrievals. Results show that PMW precipitation retrievals from the GPM constellation of radiometers provide a reliable and quantitative description of the precipitation (instantaneous and on the daily scale) throughout the evolution of the precipitation systems in the Mediterranean region. The comparable relative errors among gauges, radar, and combination of radiometer overpasses legitimize the use of PMW estimates as a valuable and independent tool for monitoring precipitation. The pixel-based comparison with radars and raingauges indicates the ability of the different sensors to identify different precipitation areas and regimes (0.60 < POD < 0.76; 0.28 < FAR < 0.45; 0.42 < ETS < 0.59; -1.6 mm/h < ME < 1.1 mm/h, with values depending on the radiometer and on the precipitation product). This is particularly relevant in the presence of complex orography in proximity of coastal areas, as for the analyzed cases. For both CDRD and PNPR, some weaknesses in the PMW detection of light precipitation are found, while the areas affected by the most intense precipitation are generally well identified (the opposite is found for the GPROF products). Good consistency in CDRD and PNPR precipitation retrievals is found for (near) coincident overpasses of the different radiometers, with discrepancies that are comparable to the differences between ground-based instruments (i.e., raingauges and radar). In spite of their low spatial resolution and relatively poor temporal sampling, PMW precipitation retrievals from CDRD and PNPR, specifically designed for the Mediterranean area, provide good estimates of total precipitation amounts for the areas that are affected by the most intense precipitation, especially when the events are localized and persistent.

The ongoing NASA/JAXA Global Precipitation Measuring mission (GPM) requires the full exploitation of the complete constellation of passive microwave (PMW) radiometers orbiting around the globe for global precipitation monitoring. In this context the coherence of the estimates of precipitation using different passive microwave radiometers is a crucial need. We have developed two different passive microwave precipitation retrieval algorithms: one is the Cloud Dynamics Radiation Database algorithm (CDRD), a physically ¬based Bayesian algorithm for conically scanning radiometers (i.e., DMSP SSMIS); the other one is the Passive microwave Neural network Precipitation Retrieval (PNPR) algorithm for cross¬- track scanning radiometers (i.e., NOAA and MetOp¬A/B AMSU-¬A/MHS, and NPP Suomi ATMS). The algorithms, originally created for application over Europe and the Mediterranean basin, and used operationally within the EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF, http://hsaf.meteoam.it), have been recently modified and extended to Africa and Southern Atlantic for application to the MSG full disk area. The two algorithms are based on the same physical foundation, i.e., the same cloud-radiation model simulations as a priori information in the Bayesian solver and as training dataset in the neural network approach, and they also use similar procedures for identification of frozen background surface, detection of snowfall, and determination of a pixel based quality index of the surface precipitation retrievals. In addition, similar procedures for the screening of not ¬precipitating pixels are used. A novel algorithm for the detection of precipitation in tropical/sub-tropical areas has been developed, applicable to all available PMW radiometers in the GPM constellation of satellites (including NPP Suomi ATMS, and GMI). A verification study over the African region on detection capabilities and retrievals from the CDRD and PNPR algorithms has been carried out using large datasets of coincidences with spaceborne precipitation radars (TRMM-PR for 2011-2012-2013, and GPM DPR for 2014). The results of this study aims at assessing the consistency and accuracy of precipitation retrievals from different sensors in different climatic regions and precipitation regimes. Results show a very good level of coherence of the precipitation estimates and patterns between the two algorithms exploiting different radiometers both for instantaneous precipitation and for daily/monthly means. Results also show an overall high correlation with respect to the spaceborne radars, with an overestimation over all surfaces. The novel precipitation detection algorithm shows a small rate of false alarms (also over arid/desert regions), and a superior detection capability in comparison with other widely used screening algorithms. Recent developments aimed at the full exploitation of the GPM constellation of satellites for optimal precipitation/drought monitoring will be also presented.

The key objective of the project "Use of the MSG SEVIRI channels in a combined SSM/I, TRMM and geostationary IR method for rapid updates of rainfall" is the development of algorithms for rapid-update of satellite rainfall estimations at the geostationary (GEO) scale. The new channels available with the Spinning Enhanced Visible and Infrared Imager (SEVIRI) radiometer in the visible (VIS), near infrared (NIR) and infrared (IR) portions of the spectrum provide new insights into the microphysical and dynamic structure of precipitating clouds thus allowing for a more precise identification of precipitation intensities. Passive microwave (PMW) radiometers on board low Earth orbiting (LEO) satellites are used to determine information on the vertical cloud structure. Key features of the new method(s) are: 1. Microphysical characterization of precipitating clouds with VIS/IR sensors; 2. Creation of cloud microphysical and radiative databases from cloud model outputs and aircraft penetrations; 3. Tuning of PMW algorithms for different cloud systems (maritime, continental, convective, stratiform,...); 4. Combination of data from different algorithms and application to a rapid updatecycle at the GEO scale. The project provided the background for EURAINSAT "European Satellite Rainfall Estimation and Monitoring at the Geostationary Scale", a research project co-funded by the Energy, Environment and Sustainable Development Programme of the European Commission within the topic "Development of generic Earth observation technologies". The project web site is accessible at http://www.isac.cnr.it/~eurainsat/. Moreover, it has represented the European framework for the launch of the International Precipitation Working Group (IPWG). A brief account of the major research and organizational results will be given in the following.

In November'02 an episode of intense precipitation impacted portions of Northern Italy, Switzerland, and the southern part of France causing the rise of lake and river levels and in some areas hazardous flooding. Rains began on 24 November in the western part of the Alps, over the Liguria (Genoa) and Lombardia (Milan) regions. Warm and humid air originating from the Mediterranean was driven northward towards the Alps where it met cold and dry air originating in the Atlantic eastern. An intense Sirocco wind was present throughout the Italian peninsula, raising surface temperatures up to 25^oC in northwest Sardinia (Alghero). On 25 November, the storm system moved towards the eastern area of the Alps, spawning intense thunderstorms, and in some cases hail, over Lombardia and Friuli. Heavy rains continued into 26 November when the precipitation terminated in response to subsidence from a high pressure system centered over eastern Europe. Observations suggest that the event featured extensive cold air damming against the Alps that enhanced the lifting over Milan. Since the 0C isotherm was only 2000 m above sea level, strong snowfall occurred over the Alps with accumulations between 250 and 400 cm. At Genoa, ~17 cm of rain was recorded on 24 November, and 29 cm on 26 November contributing to a 3-day total of some 46 cm. At Milan, ~24 cm of rain was observed for the 3-day period. A cloud resolving simulation of the event using the University of Wisconsin Nonhydrostatic Modeling System (UW-NMS) will be presented. The simulation is being performed as an entry to a Cloud Radiation Data Base (CRDB) used for satellite microwave precipitation retrieval. The CRDB is a collection of precipitating storm simulations from which the associated microphysics, thermodynamics, and dynamics are used as the physical underpinnings for rain retrieval algorithms. The robustness of this data base for Mediterranean regions applications will be discussed. Comparisons and contrasts of this simulation with simulations of other late-year flood-producing storms in the Mediterranean region will also be discussed.

Strong winds and heavy rains pummeled the North African coast over the period from 9 November 10 to November 2001 in association with the movement of a deep upper level trough over the region from the northwest. Heavy rain fell in the city of Algiers beginning late Friday November 9 and ending near noon on Saturday November 10. Over 100mm of rain fell in a 6-hour period early that Saturday. The rains were accom- panied with strong winds. The heavy rains led to massive flooding killing 737 people in Algeria and leaving 23,000 homeless. This amounted to the worst flooding and second worst natural disaster to hit Algeria since independence in 1962. The unusual weather continued for nearly 48 hours and was associated with strong winds along the Mediterranean coast, and yellow clouds producing heavy dust laden rains in Rome. CNR lidar measurements confirmed the heavy dust presence on 12 and 14 November. In this paper, a high-resolution numerical simulation of the storm is presented. Results show that the storm was preceded by a southward penetration of the jet stream into northern Africa associated with an unusually deep tropopause fold. With the fold was a strong potential vorticity maximum aloft that spawned an intense low-level response producing a strong surge of low-level flow from the north in the western Mediterranean and a strong low-level surge from the south into the south-central Mediterranean north of Libya. It was the northerly flow surge that picked up moisture from the Mediter- ranean and produced the orographic rains and wind affecting Algiers. The southerly surge built northward, producing the strong winds over Rome. The two wind streams together created strong low-level vorticity and together with the moisture drawn from the Mediterranean and convection resulting created conditions favorable of the trop- ical (warm-core) storm genesis. The result was the growth of an intense low-level cyclone with unusually strong winds and tropical characteristics north of Algiers and west of Sardinia that moved northward slowly and persisted into November 11. The event was interesting not only because of the damage suffered, but because of the se- ries of mesoscale and synoptic scale interactions that led to its development including the effects of several mountain ranges, the fluxes of moisture from the water surface and associated deep moist convection, and thermal fluxes from the floor of the Sa- hara desert. Together these events came together to produce 2001Ss most significant weather event. Modeling results depicting how these mesoscale structures evolved will be discussed at the oral presentation.