Nowcasting of convective cells over Italian Peninsula

International audienceThe aim of the study is the individuation of convective cells over the Italian peninsula with the conjunction use of geostationary satellite data (METEOSAT, MSG satellite) in the IR and WV channels and lightning data. We will use GCD (Global Convective Diagnostic) algorithm developed at Aviation Weather Centre (AWC) of NOAA (National Oceanic and Atmospheric Administration). This algorithm is based on the idea that a deep convective cloud will not have any significant moisture above it. This technique works quite well at identifying active deep convection and can be applied to all the world's geostationary satellites. However it does not always agree with lightning sensors. Low topped convection with lightning will be missed. We will extend the capabilities of GCD using lightning data. The new product will be validate over different cases in the central Italy using the C-band polarimetric radar of ISAC-CNR (Institute of Atmospheric Sciences and Climate-of the Italian National Research Council) Rome

PM-GCD – a combined IR–MW satellite technique for frequent retrieval of heavy precipitation

Abstract. Precipitation retrievals based on measurements from microwave (MW) radiometers onboard low-Earth-orbit (LEO) satellites can reach high level of accuracy – especially regarding convective precipitation. At the present stage though, these observations cannot provide satisfactory coverage of the evolution of intense and rapid precipitating systems. As a result, the obtained precipitation retrievals are often of limited use for many important applications – especially in supporting authorities for flood alerts and weather warnings. To tackle this problem, over the past two decades several techniques have been developed combining accurate MW estimates with frequent infrared (IR) observations from geosynchronous (GEO) satellites, such as the European Meteosat Second Generation (MSG). In this framework, we have developed a new fast and simple precipitation retrieval technique which we call Passive Microwave – Global Convective Diagnostic, (PM-GCD). This method uses MW retrievals in conjunction with the Global Convective Diagnostic (GCD) technique which discriminates deep convective clouds based on the difference between the MSG water vapor (6.2 μm) and thermal-IR (10.8 μm) channels. Specifically, MSG observations and the GCD technique are used to identify deep convective areas. These areas are then calibrated using MW precipitation estimates based on observations from the Advanced Microwave Sounding Unit (AMSU) radiometers onboard operational NOAA and Eumetsat satellites, and then finally propagated in time with a simple tracking algorithm. In this paper, we describe the PM-GCD technique, analyzing its results for a case study that refers to a flood event that struck the island of Sicily in southern Italy on 1–2 October 2009

Lightning-based propagation of convective rain fields

Abstract. This paper describes a new multi-sensor approach for continuously monitoring convective rain cells. It exploits lightning data from surface networks to propagate rain fields estimated from multi-frequency brightness temperature measurements taken by the AMSU/MHS microwave radiometers onboard NOAA/EUMETSAT low Earth orbiting operational satellites. Specifically, the method allows inferring the development (movement, morphology and intensity) of convective rain cells from the spatial and temporal distribution of lightning strokes following any observation by a satellite-borne microwave radiometer. Obviously, this is particularly attractive for real-time operational purposes, due to the sporadic nature of the low Earth orbiting satellite measurements and the continuous availability of ground-based lightning measurements – as is the case in most of the Mediterranean region. A preliminary assessment of the lightning-based rainfall propagation algorithm has been successfully made by using two pairs of consecutive AMSU observations, in conjunction with lightning measurements from the ZEUS network, for two convective events. Specifically, we show that the evolving rain fields, which are estimated by applying the algorithm to the satellite-based rainfall estimates for the first AMSU overpass, show an overall agreement with the satellite-based rainfall estimates for the second AMSU overpass

Estimation of local and external contributions of biomass burning to PM2.5 in an industrial zone included in a large urban settlement

A total of 85 PM2.5 samples were collected at a site located in a large industrial zone (Porto Marghera, Venice, Italy) during a 1-year-long sampling campaign. Samples were analyzed to determine water-soluble inorganic ions, elemental and organic carbon, and levoglucosan, and results were processed to investigate the seasonal patterns, the relationship between the analyzed species, and the most probable sources by using a set of tools, including (i) conditional probability function (CPF), (ii) conditional bivariate probability function (CBPF), (iii) concentration weighted trajectory (CWT), and (iv) potential source contribution function (PSCF) analyses. Furthermore, the importance of biomass combustions to PM2.5 was also estimated. Average PM2.5 concentrations ranged between 54 and 16 μg m−3 in the cold and warm period, respectively. The mean value of total ions was 11 μg m−3 (range 1–46 μg m−3): The most abundant ion was nitrate with a share of 44 % followed by sulfate (29 %), ammonium (14 %), potassium (4 %), and chloride (4 %). Levoglucosan accounted for 1.2 % of the PM2.5 mass, and its concentration ranged from few ng m−3 in warm periods to 2.66 μg m−3 during winter. Average concentrations of levoglucosan during the cold period were higher than those found in other European urban sites. This result may indicate a great influence of biomass combustions on particulate matter pollution. Elemental and organic carbon (EC, OC) showed similar behavior, with the highest contributions during cold periods and lower during summer. The ratios between biomass burning indicators (K+, Cl−, NO3−, SO42−, levoglucosan, EC, and OC) were used as proxy for the biomass burning estimation, and the contribution to the OC and PM2.5 was also calculated by using the levoglucosan (LG)/OC and LG/PM2.5 ratios and was estimated to be 29 and 18 %, respectively

A procedure to evaluate the factors determining the elemental composition of PM2.5. Case study: the Veneto region (northeastern Italy)

The Po Valley is one of the most important hot spots in Europe for air pollution. Morphological features and anthropogenic pressures lead to frequent breaching of air quality standards and to high-pollution episodes in an ~46 Ã\u97 103-km2-wide alluvial lowland. Therefore, it is increasingly important to study the air quality in a wide geographical scale to better implement possible and successful mitigation measures. The Veneto region lies in the eastern part of the Po Valley and the elemental composition of PM has been mainly studied in the Venice area, whereas scarce data are available for the remaining territory of the region. In this study, the elemental composition of PM2.5was investigated over 1 year (2012â\u80\u932013) at six major cities of the Veneto region. Samples were analyzed for 16 elements (Ca, Al, Fe, S, K, Mg, Ti, Mn, Zn, Ba, As, Ni, Pb, Sb, V, and Cu), and results were processed to investigate spatial and seasonal variations, the influence of meteorological factors, and the most probable sources by using a procedure based on (i) elemental ratios (Cu/Sb, Cu/Zn, Cu/Pb, Mn/V, V/Ni, and Zn/Pb), (ii) cluster analysis on wind data, and (iii) conditional probability function (CPF). The percentage of elements in PM2.5ranged between 11 and 20%, and Ca and S were the most abundant elements in the region. Typical seasonal variations and similar trends were exhibited by each element, especially in the lowland. Some elements such as Zn, K, Mn, Pb, and Sb were found at high concentrations during the cold period. However, no similar dispersion processes were observed throughout the region, and their concentrations were mostly depending on individual local sources. In the alpine and foothill parts of the region, lower concentrations were recorded with respect to the Po Valley cities, which resulted enriched of most of the elements considered in this study. The cluster analysis on wind data and the CPF of the ratio-related sources demonstrated that a widespread pollution condition exists in the region, apart from the coastal area. However, specific directions (e.g., a link with high-traffic roads, industrial areas, and airports) resulted the most probable explanation for each ratio-related source. In addition, the Veneto region hosts one of the most important Mediterranean ports for the cruise sector (Venice harbor), and its impact was previously demonstrated in the historical city center. In this study, the impact of Venice shipping emissions was estimated to be 3.5% of PM2.5in some particular days