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- Mediterranean dust outbreaks, dynamic meteorological patterns and weather
types-
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Abstract: Abstract Dust outbreak events characterized by high PM10 concentration values are frequently caused by long range transport of particulate matter originating from desert areas. Over the Mediterranean basin several of such events are recorded each year, that decisively contribute to the exceedance of legal limit values for PM10. Hence the quantitative characterization of the desert dust episodes is very important. Such events are the result of a sequence of dynamical events, beginning with the dust uplift in desert areas, followed by the high altitude long-range transport and terminating with the deposition in remote regions much far away from the origin. An approach for the identification of such events has been devised by merging numerical modelling results with observed data from an air quality monitoring stations network. Moreover, this analysis has been completed by integrating its results with a recently implemented local weather types classification approach.
PubDate: 2024-08-24
- Cloud characteristics in the Aravalli ranges of Western India: Insights
from ground-based Lidar measurements-
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Abstract: Abstract Clouds are integral components of the hydrological cycle and exert significant influence on regional and global weather patterns. Understanding cloud height, layers, and fraction in the atmosphere is crucial for precipitation and regulating Earth’s energy balance. This study investigates the cloud characteristics such as the cloud base height (CBH), cloud top height (CTH), and the vertical visibility over Udaipur, an urban city situated in the Aravalli ranges of Western India, employing ground-based Lidar (Ceilometer), satellite (MODIS), and reanalysis datasets (ERA5). The analysis focuses on CBH observations from Ceilometer Lidar during 2021-22, evaluating reanalysis and satellite-derived CBH. Results reveal peak detection (cloud presence or fully obscured sky) during the southwest monsoon, with frequencies reaching approximately 44%, 79%, 71%, and 37% in June, July, August, and September, respectively. While single-layer clouds are prevalent throughout the observation period, multiple layers are primarily observed during the monsoon, peaking in July and August. CBH exhibits a seasonal pattern, remaining low during the monsoon and high during pre-monsoon periods. Cloud type quantification based on CTH properties from MODIS satellites shows cirrostratus clouds as the most prevalent (approximately 36%) during the study period. Although CBH derived from MODIS CTH aligns with Ceilometer observations, the overall correlation is weak. Additionally, a seasonal variation is observed in ERA5 reanalysis performance regarding cloud base height detection over Udaipur. Therefore, the findings could contribute to broader scientific knowledge on cloud formation over complex hilly regions and these insights are crucial for improving weather prediction models by offering detailed data on cloud behavior, essential for accurate local weather forecasts.
PubDate: 2024-08-22
- Assessment of the urban pollution island intensity in Rome (Italy) from
in-situ PM measurements-
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Abstract: Abstract The Urban Pollution Island (UPI), describing the temporal and spatial distribution of pollutants’ concentration attributed to the presence of urban features and activities, is one of the major problems affecting urban areas and has become more severe with rapid urbanization. To correctly evaluate the UPI Intensity (UPII), i.e., the difference in pollution concentration between the urban agglomeration and its rural surroundings, it is crucial to carefully select rural and, above all, urban reference stations, as local factors such as orography, location of the air quality monitoring stations, and street orientation can significantly impact UPII values. In this work, the UPII in Rome (Italy) is determined using daily-averaged concentrations of PM10 and PM2.5 collected by in-situ stations over the period 2018–2023. Three different methods for the assessment of UPII are tested and compared by varying the sub-set of selected urban stations, according to their environmental classification. The approach proposed will have significant implications on the management of urban environment and on the tailored design of urban air quality improvement strategies. Results show slight differences in the monthly-averaged concentrations of both PM10 and PM2.5 between the “urban traffic” and “urban background” stations, suggesting that the proximity of the emission sources to the monitoring stations moderately influences the concentrations, potentially due to limited ventilation within street canyons, which can inhibit mixing processes. The annual variation of UPII reveals that PM10 is more sensitive to the selection of the stations particularly during winter, when the differences between the three assessment methods reach 100%. Our findings also indicate that, in the case of Rome, using the largest number of stations available in the urban area could enhance the UPII evaluation, taking into consideration the urban structure and the specific characteristics of local emission sources. The results presented here, although related to a single city, demonstrate that the selection of urban stations for the evaluation of UPII is not straightforward and requires further investigation.
PubDate: 2024-08-12
- Anatomy of the uncertainty of satellite vicarious calibration using
radiosondes: concepts and preliminary results for microwave radiometric
observations-
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Abstract: Abstract Calibration of satellite observations is crucial for ensuring the quality of retrieved products essential for meteorological and climate applications. Calibration is obtained and monitored through a cascade of stages, including postlaunch vicarious calibration/validation activities through comparison with independent reference measurements. Here, the vicarious calibration method using radiative transfer simulations based on reference radiosondes is considered in the framework of the calibration/validation activities for the Microwave Imager (MWI) and the Ice Cloud Imager (ICI) to be launched with the Second Generation of the EUMETSAT Polar System. This paper presents an overview of the uncertainty characterizing the vicarious calibration of MWI and ICI using radiosondes as performed within the EUMETSAT-funded VICIRS study. The uncertainty characterization is pursued following a metrological approach, providing a preliminary estimation of all the identified sources. The same approach is used to develop a rigorous method for estimating the number of comparison pairs (i.e., observations vs. simulations) needed to reach a certain level of accuracy in bias determination.
PubDate: 2024-08-06
- Dynamics of urban heat island intensity in Lecce, Italy: seasonal, diurnal
and heat wave influence-
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Abstract: Abstract This study investigates the impact of Heat Waves (HWs) on Urban Heat Island Intensity (UHII) in Lecce, a Mediterranean city in southern Italy. UHII was assessed using air temperature data from six weather stations over a four-year period (2020–2023). The results indicate that UHII is generally higher in winter and spring, with the ARPA (Environmental Protection Regional Agency) station consistently showing the highest values, particularly in summer, attributed to urban characteristics. The diurnal cycle of UHII reveals a peak in the early morning at most stations, followed by a decrease to near zero or slightly negative values during midday. Evening values then increase and persist throughout the night. Stations surrounded by green areas or located in suburban settings recorded the lowest UHII values. A total of eleven HWs occurred during the study period, with an average duration of 10 days. UHII was significantly more intense during HWs at all stations, with the greatest average observed at the ARPA station (2.60 °C) and the smallest at the LST (Liceo Scientifico Tabacchi) station (0.74 °C). These findings highlight the significant impact of HWs on UHI intensification in Lecce, especially in densely developed areas compared to suburban regions. This study emphasizes the importance of investigating UHII dynamics in Mediterranean cities to develop strategies for mitigating the Urban Heat Island (UHI) effect during extreme heat events.
PubDate: 2024-07-29
- Inertial oscillation modelling of low-level jets: an application to the
complex terrain and double-nosed wind profiles-
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Abstract: Abstract This study investigates the role of inertial oscillations in the evolution of a nocturnal Low-Level Jet (LLJ) in complex terrain and explores the impacts of local perturbations on wind dynamics. Specifically, a conceptual model based on inertial oscillations (Van de Wiel et al. J Atmos Sci 67(8):2679–2689 (2010)) is used to replicate the evolution of an LLJ in a gentle-sloping valley ensuring to capture its long-period dynamics under weak synoptic forcing. The analysis is performed on an already-analysed case study from the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) data set, taking advantage of the known local flow characteristics and the existence of a temporary anomaly in the LLJ shape called double-nosed LLJ. In an attempt to capture this last flow feature, a model modification is introduced, revealing appropriate to capture the double-nosed shape of the LLJ. Further observational studies will be needed to corroborate the operational use of this model and explore its application potential in different wind and energy sectors.
PubDate: 2024-07-22
- Evaluation and application of satellite rainfall datasets using Google
Earth Engine platform in Arunachal Pradesh, Eastern Himalayan Region of
India-
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Abstract: Abstract The blended satellite and ground-based datasets are publicly accessible and valuable for detecting rainfall geographical and temporal variation at a finer resolution. These products have been utilised extensively in weather and climate modelling, hydrology, and agricultural research. However, it’s important to note that the accuracy of these satellite products can vary spatially and across different datasets. Three satellite and one reanalysis gridded rainfall products CHIRPS (Climate Hazards Group InfraRed Precipitation with Station Data Version 2), TRMM (TRMM 3B43: Monthly Precipitation Estimates), TerraClimate (High-resolution global dataset of monthly climate University of Idaho), and ERA-5 (Land monthly Averaged-ECMWF Climate Reanalysis Version 5) were analysed using Google Earth Engine (GEE) and evaluated with station-based observed rainfall data to determine the representative dataset for trend analysis in different agroclimatic zones in Arunachal Pradesh, Northeast India. The trend analysis was conducted based on 20-year long-term precipitation data at an annual and seasonal scale in different agroclimatic regions of Arunachal Pradesh, India. The global performance index (GPI) ranking identified CHIRPS as the most suitable alternative data for station-observed data records. It was then used for the spatial trend analysis of different agroclimatic zones on an annual and seasonal scale at the pixel level in GEE. Several approaches were used to identify trends, including the nonparametric Mann-Kendall test, Sen’s slope estimator, and Z statistics. The patterns derived from grid-based data were compared to observed precipitation data. Seasonally, a significant declining trend was noted for the alpine zone (AZ) and the Temperate sub-alpine zone (TSAZ). Mid-tropical hill zone (MTHZ) and Sub-tropical hill region (STHR) reported a minor decline trend. Overall, in all Arunachal Pradesh agroclimatic zones, the findings indicated a general decreasing trend on an annual and seasonal scale. Observed and satellite rainfall gridded data trend analysis revealed the same pattern with different magnitudes.
PubDate: 2024-07-19
- A case study on more recent heat wave occurred in South Africa, based on
background weather synoptic and dynamic characteristics analysis-
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Abstract: Abstract This study investigates the characteristics of the more recent heat wave episode in South Africa during January 2023. The evaluation of several meteorological parameters using different reanalysis models and observational datasets have demonstrated that the domination of the anticyclonic pattern over the study area associated with a omega-blocking high. The dominant subtropical Botswana subtropical high along with the low-level omega blocking high pressure over South Africa is one of the main factors for the abnormally hot weather event. The upper-level anomaly wind analysis illustrates the weakening of the zonal wind accompanied by the Rossby waves meridionally stretching. Also, this is correlated to abnormal both tropical easterly and southern westerly jets meandering around an omega-blocking pattern weather system over South Africa which causes warm air mass trapping over the study region. The outcome model results prove the anomalies of the surface higher temperature happened close to the center of the blocking high, where an intensified southward shift of the easterly tropical jet along with the northward shift (jet entrance) of an intensified westerly jet formed two strong cores creating confluent. This research also shows that the January heat wave is demonstrated by an anomalous upper tropospheric anticyclonic inflow (southern hemisphere) causing the strong subsidence, resulting in the surface temperature increase. In comparison with the heat wave event in January 2016, the current study displays the high impact of the internal and local dynamical processes. Also, the current case study addressed in drier condition with less health risk than the previous case study noticed in 2016.
PubDate: 2024-06-15
DOI: 10.1007/s42865-024-00068-9
- Climate extreme scenarios affecting the Italian energy system with a
multi-hazard approach-
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Abstract: Abstract The operation of the energy system can be compromised by extreme weather events that can impact generation, transmission and distribution infrastructure, as well as energy demand, and will face even more critical situations in the coming decades due to ongoing climate change. The challenge concerns particularly the infrastructures with long technical life. To support decision makers in planning adaptation actions for increasing the resilience of the Italian Energy System, some analyses about the expected meteorological threats over Italy have been carried out. The study aims to identify the Italian regions more prone to climate extremes at short- (2021–2050), medium- (2041–2070) and long-term (2071–2100) by using 12 high-resolution Euro-CORDEX models under the emission pathways RCP8.5, RCP4.5 and RCP2.6. For this purpose, a subset of the WMO ETCCDI indices was used. In addition, a multi-hazard analysis was carried out by defining the three indices DRO, STO, and MUHZ to characterize respectively drought conditions, strong winds and heavy rainfalls, and the areas affected to multiple threats, considering the hazards at which power infrastructure are particularly vulnerable. At short term, under RCP4.5 and RCP8.5 hypotheses, the Southern Italy and Islands will already have to deal with a significant increase of drought conditions, that are projected to progressively extend from summer to autumn and then to spring, whereas the Central-Northern Italy will be mainly affected by storms. A decrease of wet days and, consequently, a lengthening of dry spells are generally expected, but extreme precipitations will be more frequent and more destructive, in particular over Po Valley and the eastern Italian coasts. Po Valley, Adriatic and Tyrrhenian coasts are projected to be the areas most exposed to a plurality of threats, but no Italian region will be safe from an enhancement of climate change hazards both in frequency and intensity during the 21st century in all three RCPs, with more and more severe conditions from RCP2.6 to RCP8.5 and from short- to long-term.
PubDate: 2024-06-05
DOI: 10.1007/s42865-024-00067-w
- Added value of amateur observational network for high-resolution
climatological analysis: a case study in the aterno valley, abruzzo, Italy
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Abstract: Abstract The ecological transition calls for an increasing need for local climate services. A fine spatial characterization of atmospheric relevant quantities (temperature, precipitation, humidity, wind, solar radiation, etc.) at long-term climatological scales is typically based on observational networks run by public entities such as the European Union (e.g. Copernicus services) and national and regional Agencies (e.g. National Met Office, Hydrographic Offices). The aim of this work is to verify if the density of these networks is adequate to represent the variability over the territory, with particular regard to a complex terrain area such as the Aterno river Valley in Abruzzo, Central Italy. We use a combination of public networks and the available dense amateur network of weather stations. We subject the database to careful data quality check both in terms of temporal and spatial anomalies. We found that the public network is generally adequate to represent the spatial and temporal variability over the area in terms of temperature and precipitation, but this is not the case for wind and relative humidity for the lack of sensors. We suggest that an integration of public and non-institutional observational networks is desirable for a finer climatological characterization of a complex territory and for allowing the description of more phenomena, in order to better inform adaptation measures with respect to climate change.
PubDate: 2024-04-23
DOI: 10.1007/s42865-024-00066-x
- Employing optical lightning data to identify lightning flashes associated
to terrestrial gamma-ray flashes-
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Abstract: Abstract Terrestrial gamma-ray flashes (TGFs) are bursts of energetic X- and gamma-rays emitted from thunderstorms. The Atmosphere-Space Interactions Monitor (ASIM) mounted onto the International Space Station (ISS) is dedicated to measure TGFs and optical signatures of lightning; ISS LIS (Lightning Imaging Sensor) detects lightning flashes allowing for simultaneous measurements with ASIM. Whilst ASIM measures \(\sim \) 300-400 TGFs per year, ISS LIS detects \(\sim 10^6\) annual lightning flashes giving a disproportion of four orders of magnitude. Based on the temporal evolution of lightning flashes and the spatial pattern of the constituing events, we present an algorithm to reduce the number of space-detected flashes potentially associated with TGFs by \(\sim \) 60% and of associated LIS groups by \(\sim \) 95%. We use ASIM measurements to confirm that the resulting flashes are indeed those associated with TGFs detected at approx. 400 km altitude and thus benchmark our algorithm preserving 70–80% of TGFs from concurrent ASIM-LIS measurements. We compare how the radiance, footprint size and the global distribution of lightning flashes of the reduced set relates to the average of all measured lightning flashes and do not observe any significant difference. Finally, we present a parameter study of our algorithm and discuss which parameters can be tweaked to maximize the reduction efficiency whilst keeping flashes associated to TGFs. In the future, this algorithm will hence be capable of facilitating the search for TGFs in a reduced set of lightning flashes measured from space.
PubDate: 2024-04-01
DOI: 10.1007/s42865-024-00065-y
- The ARPAL atmospheric operational modeling chain and its applications:
description and validation-
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Abstract: Abstract The paper describes the model chain operational at the Meteo-Hydrological Center of the Liguria Region (ARPAL) based on the CNR-ISAC models BOLAM (BOlogna Limited Area Model) and MOLOCH (MOdello LOCale in Hybrid coordinates). Some of the chain applications and a statistical verification of its most recent implementation are also shown. The first operational run of the BOLAM numerical weather prediction (NWP) model at ARPAL was launched in September 1999, in correspondence with the beginning of the Mesoscale Alpine Programme Special Observing Period field campaign. Since then, the collaboration between CNR-ISAC and ARPAL has allowed to maintain and update the operational chain, also thanks to a continuous upgrade of the computational resources available at ARPAL. Since 2005, the non-hydrostatic model MOLOCH has been added to the forecasting chain. In the present operational setup, BOLAM is run over a European domain at the horizontal resolution of about 8 km, using ECMWF-IFS analysis and forecasts as initial and boundary conditions. MOLOCH model is nested in BOLAM, and it runs over a domain including the entire Italian territory, on a 1.5-km horizontal resolution grid. The forecast products, consisting in 72-h BOLAM and 48-h MOLOCH predictions, are available in 1.5 h after the reception of the ECMWF-IFS data. Four runs every day are performed. Other modeling systems in cascade are driven by NWP models. For several years, wind fields obtained from the atmospheric modeling chain have been used to force the wave model WAVEWATCH III, implemented at different resolutions over the Mediterranean basin. Other applications in cascade consist in hydrological prediction for the basins of the Liguria Region, wildfire, and ocean circulation modeling. Moreover, the different initializations of the BOLAM and MOLOCH models provide an important contribution to the ARPAL operational Poor Man’s Ensemble prediction system. A verification based on 3 years of data available from the ARPAL ground observing network shows a general capability of the high-resolution models in better forecasting heavy precipitation events, due to a better description of convective phenomena, while a less marked improvement with respect to large-scale models is shown for low precipitation thresholds. Results also show an improvement of model performance for all monitored variables, precipitation, 2-m temperature, and 10-m winds, when resolution increases and when model domains are enlarged.
PubDate: 2024-01-16
DOI: 10.1007/s42865-024-00064-z
- Introducing the Marzano Award “Gutta Aurea”: aims, rules, and outcome
of the first edition-
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PubDate: 2023-12-26
DOI: 10.1007/s42865-023-00063-6
- Assessing the status of air pollution related to traffic using dispersion
modeling: the case of Megenagna, Addis Ababa, Ethiopia-
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Abstract: Abstract In emerging countries’ expanding megacities, traffic is currently the main source of air pollution. Vehicles are the primary source of air pollution in Addis Ababa, the capital city of Ethiopia, because of the unimproved age of cars and bad road conditions. One of the city’s major hub squares, Megenagna (between the Bole and Yeka sub-cities of Addis Ababa), has six significant road crossings that clog up traffic. The purpose of this study was to evaluate and forecast air pollution levels in the Megenagna region using the dispersion model (AERMOD). A sample campaign was run for 2 months (January and February) at 43 sampling stations. Hand-held Air-test Model-CW-HAT2005 and Aeroqual series 5000 devices were used to measure gaseous pollutants (SO2 and NO2) and particulate matter (PM2.5 and PM10). There is a lot of spatial variation throughout the study site, as shown by the statistically significant difference between sampling locations (p < 0.05). The sensitivity variation of 1 m/s and the 45° wind direction with respect to the horizontal of the receptor of the self-monitored sample location were ideal for the prediction, calibration, and validation of pollutants in AERMOD. It was anticipated that gaseous and particulate pollution would vary from site to site, with SO2 exceeding the threshold. This study demonstrates the need for additional research into the spatiotemporal variance of emissions due to traffic in Addis Ababa.
PubDate: 2023-12-14
DOI: 10.1007/s42865-023-00062-7
- WRF data assimilation of weather stations and lightning data for a
convective event in northern Italy-
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Abstract: Abstract The present work shows the relevance of assimilating mesoscale observations and lightning data in the Weather Research and Forecasting (WRF) model, to simulate a strong convective event in northern Italy, poorly forecasted by available weather models even a few hours before the event itself. The data assimilation was conducted by testing the 3D-VAR and 4D-VAR assimilation algorithms implemented in the WRF data assimilation (WRFDA) suite, with different configurations and different assimilation windows. An extensive sensibility test has been operated to properly analyze the effect that the assimilation of a single station has on the model outcomes. Input data were taken from two networks of more than 1000 citizen-science meteorological stations, available in northern Italy, and from lightning flashes derived from Earth Networks Total Lightning Network, assimilated using the atmospheric water vapor as a proxy variable. Rain forecasts over an area in the north of Milan were compared to the station’s measurements in the same area; POD, FAR, and CSI categorical statistics have been calculated. Results showed a positive improvement in the forecasted rain amounts with the ingestion of mesoscale weather data into 3D-VAR and 4D-VAR algorithms, more pronounced using 4D-VAR with a more frequent input data integration. A few improvements were reported by the 3D-VAR, with the lightning data assimilation, probably caused by the absence of the model’s spin-up time with this configuration. An ideal simulation, which increased the water vapor of the air mass 2 h before the convective event, reported a positive enhancement of the rain amounts. The tests conducted on a single convective event are nevertheless encouraging, because they show a positive improvement of forecast with the assimilation of near-ground weather data and tropospheric water vapor 1 or 2 h before the beginning of the convection activity.
PubDate: 2023-09-14
DOI: 10.1007/s42865-023-00061-8
- Evaluation of the performance of the World Wide Lightning Location Network
(WWLLN) using the lightning detection network (LINET) as a truth-
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Abstract: Abstract Observations from lightning detection networks are useful for forecasting or monitoring several phenomena or parameters such as bushfires or nitrogen oxide production. As networks are constantly expanding and their detection capabilities are improving, it is essential to understand their performance. A systematic evaluation of the performance of the World Wide Lightning Location Network (WWLLN) in northern Benin is carried out using data from the lightning detection network (LINET) data as ground truth. The study runs from 18 June to 18 November 2006. The detection efficiency of the WWLLN is found to be strongly dependent on the peak current. It is low and reveals the distance of the sensors from the area. This same sensitivity to peak current explains the bias between the spatial and temporal localisation of the two networks. The peak of the period, in terms of the number of events observed, is obtained in July for the LINET and in September for the WWLLN. The diurnal variation indicates an overall peak of activity in the evening for both networks but with a slight time lag for WWLLN. However, taking into account the flashes with peak current greater than or equal to 30 kA, it is noted that the two networks are almost identically located. The results also show that the WWLLN is capable of locating both cloud-to-ground (CG) and inter-cloud (IC) lightning. Additional receiving stations are continuously added to the network, which improves detection efficiency.
PubDate: 2023-07-31
DOI: 10.1007/s42865-023-00060-9
- Development of an airfoil-based passive volumetric air sampling and flow
control system for fixed-wing UAS-
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Abstract: Abstract This study aims to develop a concept of a passive volumetric flow control system for gas sampling applications onboard fixed-wing UAS based on the pressure field around airfoils. The passive flow control system utilizes the aerodynamics of a UAS to create a vacuum pump effect that ensures constant gas sampling, which can be used to facilitate airborne aerosol and gas measurements. The pump effect is achieved by short-circuiting the pressure field’s minima and maxima points around an airfoil through pipes and 3D printed structures that could function both as a pump system and a gas measurement chamber. The design of this structurally integrated functionality brings many advantages for scientific applications, especially onboard small research UAS, which would dispense entirely with complex active pump systems, thus reducing weight and ensuring gas sampling at a constant volumetric flow rate independent of altitude and atmospheric variance. In favor of developing further applications, this paper outlines the development steps of the passive pump concept starting from the theory and numerical modeling of the effect to the implementation on board a fixed-wing UAS. Finally, possible improvements based on numerical models and flight measurements are discussed.
PubDate: 2023-07-18
DOI: 10.1007/s42865-023-00057-4
- Professional LoRaWAN IoT Decentlab sensors: 1 year of data and analysis
within the experimental project of meteorological monitoring in the
Regional Forest of Pian Cansiglio (north-east region of Italy)-
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Abstract: Abstract Within the experimental project of meteorological monitoring in the Regional Forest of Pian Cansiglio (mountain Regions of Veneto and Friuli Venezia Giulia, Italy—https://www.piancansigliometeowebcam.it), three professional sensors with LoRaWAN technology have been installed in 2020 and 2021, in three specific experimental locations, chosen for their peculiar climatic conditions (I Bech, 983 m a.s.l.; Valmenera, 903 m a.s.l.; and Rif. Carlo e Massimo Semenza, 2.020 m a.s.l.). After 1 year of data and detailed analysis, Decentlab professional sensors (Decentlab GmbH n.d.), operating in the severe environmental context of the Pian Cansiglio Regional Forest, were found suitable for such monitoring purposes, ensuring accurate measurements in sites where minimum values can drop below − 30 °C and moisture is constant, with big ice accumulations on all surfaces which can completely cover the transmitters. As a further level of development in the IoT segment, a self-built electronic board (called “LoRa Weather board”) was implemented by Dr. Mauro Girotto, based on LoRaWAN technology (Environmental monitoring using LoRaWAN technology: experimental measurements and data analytics platform– Dr. Luigi Laricchia – MSc Informatics (University of Bologna – Italy) n.d.) and The Things Network (The Things Network n.d.). The board has been designed for battery-powered applications and, at the hardware level, is ready for mounting various sensors, depending on the application, including thermo-hygrometers, rain gauges, and barometers. Data are collected since January 2022, and the hardware will be tested in coming winters to achieve the necessary robustness for harsh environmental conditions.
PubDate: 2023-06-01
DOI: 10.1007/s42865-023-00059-2
- Extreme convective precipitation in Liguria (Italy): a brief description
and analysis of the event occurred on October 4, 2021-
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Abstract: Abstract An extreme precipitation episode, occurred in Liguria region on October 4, 2021, is presented and discussed in the present paper. In particular, a series of V-shaped quasi-stationary convective systems repeatedly affected central and western Liguria producing impressive and, in some cases, unprecedented rainfall amounts (up to 378 mm in 3 h, 496 mm in 6 h, and 741 mm in 12 h). A peculiar feature of this case study is its occurrence and propagation downwind the Apennines Mountain range. The main characteristics of the event, in terms of synoptic and mesoscale triggering processes as well as its dynamics, are discussed. It is found that the larger moisture contribution seems to have a Mediterranean origin and a possible role of a cold pool generated in the first phase of the event in the evolution of the convective system is hypothesized. This paper follows a workshop on high-impact weather jointly organized by the newly formed Italia Meteo Agency and the Italian Association of Atmospheric Sciences and Meteorology (AISAM) in September 2022, to promote the sharing of the experiences among operational and research meteorological centers in Italy. The preliminary results presented here are intended to stimulate further work on the topic to gain a better understanding of the dynamics of such extreme precipitation events and to improve the predicting capability.
PubDate: 2023-05-17
DOI: 10.1007/s42865-023-00058-3
- On the parametrizations for the dissipation rate of the turbulence kinetic
energy in stable conditions-
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Abstract: Abstract Observations acquired in the stable surface layer during two field experiments (The Mountain Terrain Atmospheric Modeling and Observations Program and the Climate Change Tower Integrated Project) are considered to test different parametrizations of the dissipation rate of turbulence kinetic energy (TKE). Particular attention is dedicated to the effect of the submeso motions on these parametrizations. The analysis shows that TKE-based formulations are particularly prone to the submeso effect, while better results are obtained if the vertical velocity variance is considered. In the latter case, stability must be taken into account explicitly in Mellor-Yamada type parametrizations but not in shear-based formulations.
PubDate: 2023-05-09
DOI: 10.1007/s42865-023-00055-6
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