<p>Typical features of lightning distribution in the mountain area of Mt. Cimone (2... more <p>Typical features of lightning distribution in the mountain area of Mt. Cimone (2165 m a.s.l. - Northern-Central Italy) have been studied through detections provided by the ground-based LIghtning NETwork data (LINET) and the Lightning Imaging Sensor (LIS) onboard the International Space Station (ISS-LIS).  The study was performed within the context of lightning implications as natural hazard, and its role in a changing climate. Of particular interest are mountain regions because of their orographic impact, which determine most lightning hotspots around the globe. LINET VLF/LF radio measurements allowed the characterization of both cloud-to-ground (CG) and intra-cloud (IC) strokes' geographical distribution and altitude of occurrence over 2012 through 2020. The lightning distribution showed a remarkable clustering of CGs at the mountain top in contrast to a homogeneous distribution of ICs, highlighting the likely impact of orography. IC strokes peaked around 4 to 6 km altitude, consistency with the observed typical cloud range. The joint exploitation of LIS-ISS optical observations of LINET detections extended the study to further features of flashes not seen in radio wavelengths and stands as cross-validation of the two detection methods over such a complex orography. These results give an example of mountain-driven changes in lightning occurrence. The clustering at the Cimone mountain top induced by the orography replicates a general feature of the dependence of global lightning hot-spots from elevation and is of great interest in the understanding of the lighting-climate relationship, considering known effects of elevation-depedent climate change.</p>
<p class="p1">The Mediterranean Basin is often hit by severe meteorologic... more <p class="p1">The Mediterranean Basin is often hit by severe meteorological events, that can cause floods and flash floods. The intensity of these storms is both due to the presence of a warm sea, that contributes to feed the storm with high water vapor amounts, and to the complex orography of the region, which intensifies the precipitation over specific areas. The prediction of these events is very challenging, since different spatial and temporal scales are involved.<span class="Apple-converted-space"> </span></p> <p class="p1">Numerical Weather Prediction (NWP) models with a high spatial horizontal resolution are able to represent these kinds of events, but without a high precision in space, time and amount.<span class="Apple-converted-space">  </span>For a better representation of extreme rainfall events, an important role can be played by the information given at the local scale to the NWP models by initial conditions.<span class="Apple-converted-space"> </span></p> <p class="p1">Data Assimilation (DA) can be a fundamental instrument to help NWP models to improve their prediction, through the production of better initial conditions. However, DA needs observational data, and there is a lack of meteorological data in open sea, where radar data are not available. In this context, satellite observational data are very interesting because they can provide data both over sea and over land.<span class="Apple-converted-space"> </span></p> <p class="p1">The AEROMET (AEROspatial data assimilation for METeorological weather prediction) project aims to study the satellite rain-rate assimilation in the Weather Research and Forecasting (WRF) model to improve the prediction of convective meteorological systems, with a particular focus to systems which originate over the sea. The assimilation method considers a certain rain-rate threshold, which is representative of convective precipitation, avoiding in this way to add an excessive water vapor amount to the model. In this work, we show the preliminary results of the AEROMET project. Examples are presented to show the feasibility of the method and statistics will be shown to quantify its impact on rainfall prediction.</p> <p class="p2"> </p> <p class="p1">ACKNOWLEDGMENTS<span class="Apple-converted-space"> </span></p> <p class="p1">This work was done in the framework of the AEROMET project (A0375-2020-36588 - “Progetti di Gruppi di Ricerca 2020” LazioInnova - FESR Fondo Europeo di Sviluppo Regionale Programma Operativo regionale del Lazio).<span class="Apple-converted-space"> </span></p>
<p>Lightning is an important threat to life and properties and its forecast is impo... more <p>Lightning is an important threat to life and properties and its forecast is important for practical applications. We show the performance of a dynamic lightning scheme for the next-day strokes forecast. The prediction is compared against the LINET network, and the forecast period spans one year. Specifically, a total of 162 case studies were selected between 1 March 2020 and 28 February 2021. The events span a wide range of lightning intensity; 69 cases occurred in summer, 46 in fall, 18 in winter, 29 in spring.</p> <p>Three different settings of the lightning scheme are considered to test the sensitivity of the method to the key parameter of charge transferred in 1 second: 0.5*10<sup>-4</sup> C (L50), 0.75*10<sup>-4</sup> C (L75),  and 1.0*10<sup>-4 </sup>C<sup> </sup>(L100).</p> <p>The meteorological driver is WRF. Each simulation lasts 36h and the first twelve hours are the spin-up time and are discarded from the analysis. The focus is on the next-day forecast (12-36 h). The horizontal resolution of the simulations is 3 km and 50 unevenly spaced vertical levels extend from the surface to 50 hPa.</p> <p>Lightning is closely related to convection in the atmosphere and model errors in the lightning forecast have two main sources: errors in forecasting the convection and errors in the representation of the electric processes inside the clouds. This makes the lightning forecast a difficult task.</p> <p>Results are discussed for the whole year and for different seasons. Moreover, statistics are presented for the land and sea. LINET strokes are remapped into the WRF 3km grid and then further elaborated for comparison with the strokes forecast.</p> <p>Among the three configurations of the lightning scheme, L75 forecasts accurately the total number of strokes recorded for all the cases, L50 underestimates the strokes and L100 overestimates the strokes. The time-series correlation of daily observed and forecasted strokes is around 0.75 and depends on the season.</p> <p>Qualitative scores (FBIAS, ETS, POD, FAR) computed for the 3km grid and different strokes thresholds have low values and upscaling the model output, by summing the forecast and observed strokes over grids with larger grid spaces (from 6 to 48 km), improves the results. Among the different configurations of the dynamic lightning scheme, L75 performs slightly better. However, L50, L75, and L100 show very similar spatial patterns of predicted strokes.</p> <p>The analysis of the fraction skill score shows that the best lightning forecast is for summer, followed by fall, winter, and spring. This happens for all configurations L50, L75, L100.</p> <p>The lightning forecast performance varies between sea and land; the analysis of the Taylor diagram shows better performance over the land than over the sea. This result shows that the convection is better simulated over the land than over the sea, where the effect of topography, partially represented by the model, may focus the convection on specific areas.</p> <p>The result of this study shows that lightning forecast with the dynamic lightning scheme can be performed with success in Italy; nevertheless, a careful inspection of the forecast performance is necessary for tuning the scheme to the specific purpose.</p>
A comprehensive analysis of the July 2021 event that occurred on Lake Como (Italy), during which ... more A comprehensive analysis of the July 2021 event that occurred on Lake Como (Italy), during which heavy hailstorms and floods affected the surroundings of Lake, is presented. The study provides a detailed analysis of the event using different observation sources currently available. The employed techniques include both conventional (rain gauges, radar, atmospheric sounding) and non-conventional (satellite-based Earth observation products, GNSS, and lightning detection network) observations for hydro-meteorological analysis. The study is split in three main topics: event description by satellite-based observations; long-term analysis by the ERA5 model and ASCAT soil water index; and short-term analysis by lightning data, GNSS delays and radar-VIL. The added value of the work is the near-real-time analysis of some of the datasets used, which opens up the potential for use in alerting systems, showing considerable application possibilities in NWP modeling, where it can also be useful fo...
<p>Typical features of lightning distribution in the mountain area of Mt. Cimone (2... more <p>Typical features of lightning distribution in the mountain area of Mt. Cimone (2165 m a.s.l. - Northern-Central Italy) have been studied through detections provided by the ground-based LIghtning NETwork data (LINET) and the Lightning Imaging Sensor (LIS) onboard the International Space Station (ISS-LIS).  The study was performed within the context of lightning implications as natural hazard, and its role in a changing climate. Of particular interest are mountain regions because of their orographic impact, which determine most lightning hotspots around the globe. LINET VLF/LF radio measurements allowed the characterization of both cloud-to-ground (CG) and intra-cloud (IC) strokes' geographical distribution and altitude of occurrence over 2012 through 2020. The lightning distribution showed a remarkable clustering of CGs at the mountain top in contrast to a homogeneous distribution of ICs, highlighting the likely impact of orography. IC strokes peaked around 4 to 6 km altitude, consistency with the observed typical cloud range. The joint exploitation of LIS-ISS optical observations of LINET detections extended the study to further features of flashes not seen in radio wavelengths and stands as cross-validation of the two detection methods over such a complex orography. These results give an example of mountain-driven changes in lightning occurrence. The clustering at the Cimone mountain top induced by the orography replicates a general feature of the dependence of global lightning hot-spots from elevation and is of great interest in the understanding of the lighting-climate relationship, considering known effects of elevation-depedent climate change.</p>
<p class="p1">The Mediterranean Basin is often hit by severe meteorologic... more <p class="p1">The Mediterranean Basin is often hit by severe meteorological events, that can cause floods and flash floods. The intensity of these storms is both due to the presence of a warm sea, that contributes to feed the storm with high water vapor amounts, and to the complex orography of the region, which intensifies the precipitation over specific areas. The prediction of these events is very challenging, since different spatial and temporal scales are involved.<span class="Apple-converted-space"> </span></p> <p class="p1">Numerical Weather Prediction (NWP) models with a high spatial horizontal resolution are able to represent these kinds of events, but without a high precision in space, time and amount.<span class="Apple-converted-space">  </span>For a better representation of extreme rainfall events, an important role can be played by the information given at the local scale to the NWP models by initial conditions.<span class="Apple-converted-space"> </span></p> <p class="p1">Data Assimilation (DA) can be a fundamental instrument to help NWP models to improve their prediction, through the production of better initial conditions. However, DA needs observational data, and there is a lack of meteorological data in open sea, where radar data are not available. In this context, satellite observational data are very interesting because they can provide data both over sea and over land.<span class="Apple-converted-space"> </span></p> <p class="p1">The AEROMET (AEROspatial data assimilation for METeorological weather prediction) project aims to study the satellite rain-rate assimilation in the Weather Research and Forecasting (WRF) model to improve the prediction of convective meteorological systems, with a particular focus to systems which originate over the sea. The assimilation method considers a certain rain-rate threshold, which is representative of convective precipitation, avoiding in this way to add an excessive water vapor amount to the model. In this work, we show the preliminary results of the AEROMET project. Examples are presented to show the feasibility of the method and statistics will be shown to quantify its impact on rainfall prediction.</p> <p class="p2"> </p> <p class="p1">ACKNOWLEDGMENTS<span class="Apple-converted-space"> </span></p> <p class="p1">This work was done in the framework of the AEROMET project (A0375-2020-36588 - “Progetti di Gruppi di Ricerca 2020” LazioInnova - FESR Fondo Europeo di Sviluppo Regionale Programma Operativo regionale del Lazio).<span class="Apple-converted-space"> </span></p>
<p>Lightning is an important threat to life and properties and its forecast is impo... more <p>Lightning is an important threat to life and properties and its forecast is important for practical applications. We show the performance of a dynamic lightning scheme for the next-day strokes forecast. The prediction is compared against the LINET network, and the forecast period spans one year. Specifically, a total of 162 case studies were selected between 1 March 2020 and 28 February 2021. The events span a wide range of lightning intensity; 69 cases occurred in summer, 46 in fall, 18 in winter, 29 in spring.</p> <p>Three different settings of the lightning scheme are considered to test the sensitivity of the method to the key parameter of charge transferred in 1 second: 0.5*10<sup>-4</sup> C (L50), 0.75*10<sup>-4</sup> C (L75),  and 1.0*10<sup>-4 </sup>C<sup> </sup>(L100).</p> <p>The meteorological driver is WRF. Each simulation lasts 36h and the first twelve hours are the spin-up time and are discarded from the analysis. The focus is on the next-day forecast (12-36 h). The horizontal resolution of the simulations is 3 km and 50 unevenly spaced vertical levels extend from the surface to 50 hPa.</p> <p>Lightning is closely related to convection in the atmosphere and model errors in the lightning forecast have two main sources: errors in forecasting the convection and errors in the representation of the electric processes inside the clouds. This makes the lightning forecast a difficult task.</p> <p>Results are discussed for the whole year and for different seasons. Moreover, statistics are presented for the land and sea. LINET strokes are remapped into the WRF 3km grid and then further elaborated for comparison with the strokes forecast.</p> <p>Among the three configurations of the lightning scheme, L75 forecasts accurately the total number of strokes recorded for all the cases, L50 underestimates the strokes and L100 overestimates the strokes. The time-series correlation of daily observed and forecasted strokes is around 0.75 and depends on the season.</p> <p>Qualitative scores (FBIAS, ETS, POD, FAR) computed for the 3km grid and different strokes thresholds have low values and upscaling the model output, by summing the forecast and observed strokes over grids with larger grid spaces (from 6 to 48 km), improves the results. Among the different configurations of the dynamic lightning scheme, L75 performs slightly better. However, L50, L75, and L100 show very similar spatial patterns of predicted strokes.</p> <p>The analysis of the fraction skill score shows that the best lightning forecast is for summer, followed by fall, winter, and spring. This happens for all configurations L50, L75, L100.</p> <p>The lightning forecast performance varies between sea and land; the analysis of the Taylor diagram shows better performance over the land than over the sea. This result shows that the convection is better simulated over the land than over the sea, where the effect of topography, partially represented by the model, may focus the convection on specific areas.</p> <p>The result of this study shows that lightning forecast with the dynamic lightning scheme can be performed with success in Italy; nevertheless, a careful inspection of the forecast performance is necessary for tuning the scheme to the specific purpose.</p>
A comprehensive analysis of the July 2021 event that occurred on Lake Como (Italy), during which ... more A comprehensive analysis of the July 2021 event that occurred on Lake Como (Italy), during which heavy hailstorms and floods affected the surroundings of Lake, is presented. The study provides a detailed analysis of the event using different observation sources currently available. The employed techniques include both conventional (rain gauges, radar, atmospheric sounding) and non-conventional (satellite-based Earth observation products, GNSS, and lightning detection network) observations for hydro-meteorological analysis. The study is split in three main topics: event description by satellite-based observations; long-term analysis by the ERA5 model and ASCAT soil water index; and short-term analysis by lightning data, GNSS delays and radar-VIL. The added value of the work is the near-real-time analysis of some of the datasets used, which opens up the potential for use in alerting systems, showing considerable application possibilities in NWP modeling, where it can also be useful fo...
17th Plinius Conference on Mediterranean Risks - Call for Abstract, 2020
The objective of the 2020 edition is to provide an interdisciplinary forum for discussions on our... more The objective of the 2020 edition is to provide an interdisciplinary forum for discussions on our current state of knowledge of Mediterranean risks in a climate change context. Different aspects related to monitoring, assessment, diagnosis, prediction, and definition of weather extremes and hydro-geological effects, impacts on natural resources, agriculture, health and society, as well as adaptation capacity and preservation strategies for natural and cultural heritage at risk, will be addressed with a multi-sectorial approach. This will be achieved by bringing together scientific experts in the fields of meteorology, hydrology, geomorphology, sociology, engineering, cultural heritage conservation, and also governmental or private risk management actors. On behalf of the Steering Committe and Scientific Committee, we cordially invite you to submit a short abstract for oral or poster presentation in one of the following 7 Sessions: 1. Diagnosis, trends, causalities, and predictions of extreme weather events in a climate change environment 2. Earth Observation data and techniques for the definition, characterization and monitoring of natural hazards 3. Hydro-geological effects of extreme events (e.g., floods, landslides, erosions, coastal dynamics, storm surges etc.) 4. Socioeconomic impacts: exposure, vulnerability, prospectives, and adaptation 5. Safeguarding and management of cultural and natural heritage at risk from climate extreme events 6. Natural hazards for ecosystems and agriculture 7. Air quality and Health in the Mediterranean Important dates: Abstract submission closed: 30 April 2020 Notification of Abstract acceptance: 15 May 2020 Letter of schedule (programme publication):
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1. Diagnosis, trends, causalities, and predictions of extreme weather events in a climate change environment
2. Earth Observation data and techniques for the definition, characterization and monitoring of natural hazards
3. Hydro-geological effects of extreme events (e.g., floods, landslides, erosions, coastal dynamics, storm surges etc.)
4. Socioeconomic impacts: exposure, vulnerability, prospectives, and adaptation
5. Safeguarding and management of cultural and natural heritage at risk from climate extreme events
6. Natural hazards for ecosystems and agriculture
7. Air quality and Health in the Mediterranean
Important dates: Abstract submission closed: 30 April 2020 Notification of Abstract acceptance: 15 May 2020 Letter of schedule (programme publication):