Investigating triggering mechanisms for the large hailstorm event of July 10th, 2019 on the Adriatic Sea

A severe weather events hit Italy on July 9-10, 2019 causing heavy damages by the falling of large-size hail. A trough from Northern Europe affected Italy and the Balkans advecting cold air on the Adriatic Sea. The intrusion of relatively cold and dry air on the Adriatic Sea, in a first stage through the "Bora jets" generated by the Dinaric Alps gave rise to a frontal structure on the ground, which rapidly moved from North to South Adriatic. The large thermal gradient (also with the sea surface), the interaction with the complex orography and the coastal zone, generated several storm structures along the eastern Italian coast. &#160;In particular, on 10 July 2019 between 8UTC and 12UTC a deep convective cell (probably a supercell) developed along the coast North of the city of Pescara, producing intense rainfall (accumulated rainfall reaching 130 mm/3h) and a violent hailstorm with hailstones larger than 10 cm in diameter. The storm quickly moved southward, evolving into a complex multicellular structure clearly visible by observing radar data. &#160;In this work the frontal dynamics and the genesis of the storm cell are investigated using the numerical model WRF (Weather Research and Forecasting system). Numerical experiments are carried out using a 1 km grid on Central Italy, initialized using the ECMWF dataset and the Sea Surface Temperature (SST) taken by MFS-CMEMS Copernicus dataset. The sensitivity study investigated both the impact of the initial conditions, the quality and the anomaly of the SST on the Adriatic basin in those days. Furthermore, in order to quantify the importance of the use of different microphysics, Planetary boundary Layer (PBL) and radiative schemes, several experiments are performed. The role of orography in the development and location of the convective cell is also investigated. Preliminary results show that initialization and SST played a fundamental role. In particular, the initialization several hours before the event, coupled with a detailed SST allows to correctly reproduce the atmospheric fields. The microphysics scheme turned out to play a key role for this event by showing a significant greater impact than the PBL, in terms of frontal genesis on both the synoptic and local scale.

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Investigating triggering mechanisms for the large hailstorm event of July 10th, 2019 on the Adriatic Sea

10.5194/egusphere-egu21-3662 ◽

2021 ◽

Author(s):

Antonio Ricchi ◽

Vincenzo Mazzarella ◽

Lorenzo Sangelantoni ◽

Gianluca Redaelli ◽

Rossella Ferretti

Keyword(s):

Adriatic Sea ◽

Initial Conditions ◽

Central Italy ◽

Radar Data ◽

Sensitivity Study ◽

Convective Cell ◽

Sea Surface ◽

Microphysics Scheme ◽

The Balkans ◽

The Impact

<div> A severe weather events hit Italy on July 9-10, 2019 causing heavy damages by the falling of large-size hail. A trough from Northern Europe affected Italy and the Balkans advecting cold air on the Adriatic Sea. The intrusion of relatively cold and dry air on the Adriatic Sea, in a first stage through the "Bora jets" generated by the Dinaric Alps gave rise to a frontal structure on the ground, which rapidly moved from North to South Adriatic. The large thermal gradient (also with the sea surface), the interaction with the complex orography and the coastal zone, generated several storm structures along the eastern Italian coast. In particular, on 10 July 2019 between 8UTC and 12UTC a deep convective cell (probably a supercell) developed along the coast North of the city of Pescara, producing intense rainfall (accumulated rainfall reaching 130 mm/3h) and a violent hailstorm with hailstones larger than 10 cm in diameter. The storm quickly moved southward, evolving into a complex multicellular structure clearly visible by observing radar data. In this work the frontal dynamics and the genesis of the storm cell are investigated using the numerical model WRF (Weather Research and Forecasting system). Numerical experiments are carried out using a 1 km grid on Central Italy, initialized using the ECMWF dataset and the Sea Surface Temperature (SST) taken by MFS-CMEMS Copernicus dataset. The sensitivity study investigated both the impact of the initial conditions, the quality and the anomaly of the SST on the Adriatic basin in those days. Furthermore, in order to quantify the importance of the use of different microphysics, Planetary boundary Layer (PBL) and radiative schemes, several experiments are performed. The role of orography in the development and location of the convective cell is also investigated. Preliminary results show that initialization and SST played a fundamental role. In particular, the initialization several hours before the event, coupled with a detailed SST allows to correctly reproduce the atmospheric fields. The microphysics scheme turned out to play a key role for this event by showing a significant greater impact than the PBL, in terms of frontal genesis on both the synoptic and local scale. </div>

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Effects of Multiple Doppler Radar data assimilation on the numerical simulation of a Flash Flood Event during the HyMeX campaign

10.5194/hess-2016-320 ◽

2016 ◽

Cited By ~ 1

Author(s):

Ida Maiello ◽

Sabrina Gentile ◽

Rossella Ferretti ◽

Luca Baldini ◽

Nicoletta Roberto ◽

...

Keyword(s):

Hydrological Cycle ◽

Initial Conditions ◽

Flash Flood ◽

Weather Prediction ◽

Central Italy ◽

Heavy Precipitation ◽

Radar Data ◽

Horizontal Resolution ◽

Precipitation Event ◽

The Impact

Abstract. An analysis to evaluate the impact of assimilating multiple radar data with a three dimensional variational (3D-Var) system on a heavy precipitation event is presented. The main goal is to establish a general methodology to quantitatively assess the performance of flash-flood numerical weather prediction at mesoscale. In this respect, during the first Special Observation Period (SOP1) of HyMeX (Hydrological cycle in the Mediterranean Experiment) campaign several Intensive Observing Periods (IOPs) were launched and nine occurred in Italy. Among them IOP4 is chosen for this study because of its low predictability. This event hit central Italy on 14 September 2012 producing heavy precipitation and causing several damages. Data taken from three C-band radars running operationally during the event are assimilated to improve high resolution initial conditions. In order to evaluate the impact of the assimilation procedure at different horizontal resolution and to assess the impact of assimilating multiple radars data, several experiments using Weather Research and Forecasting (WRF) model are performed. Finally, the statistical indexes as accuracy, equitable threat score, false alarm ratio and frequency bias are used to objectively compare the experiments, using rain gauges data as benchmark.

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Role of initial condition and parametric uncertainty in a severe hailstorm forecast

10.5194/egusphere-egu21-7406 ◽

2021 ◽

Author(s):

Patrick Kuntze ◽

Annette Miltenberger ◽

Corinna Hoose ◽

Michael Kunz

Keyword(s):

Initial Conditions ◽

Weather Prediction ◽

Parametric Uncertainty ◽

Radar Data ◽

Cloud Microphysics ◽

Initial Condition ◽

Relative Contribution ◽

Cloud Properties ◽

Set Up ◽

The Impact

Forecasting high impact weather events is a major challenge for numerical weather prediction. Initial condition uncertainty plays a major role but so potentially do uncertainties arising from the representation of physical processes, e.g. cloud microphysics. In this project, we investigate the impact of these uncertainties for the forecast of cloud properties, precipitation and hail of a selected severe convective storm over South-Eastern Germany. To investigate the joint impact of initial condition and parametric uncertainty a large ensemble including perturbed initial conditions and systematic variations in several cloud microphysical parameters is conducted with the ICON model (at 1 km grid-spacing). The comparison of the baseline, unperturbed simulation to satellite, radiosonde, and radar data shows that the model reproduces the key features of the storm and its evolution. In particular also substantial hail precipitation at the surface is predicted. Here, we will present first results including the simulation set-up, the evaluation of the baseline simulation, and the variability of hail forecasts from the ensemble simulation. In a later stage of the project we aim to assess the relative contribution of the introduced model variations to changes in the microphysical evolution of the storm and to the fore- cast uncertainty in larger-scale meteorological conditions.

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Impact of multiple radar reflectivity data assimilation on the numerical simulation of a flash flood event during the HyMeX campaign

Hydrology and Earth System Sciences ◽

10.5194/hess-21-5459-2017 ◽

2017 ◽

Vol 21 (11) ◽

pp. 5459-5476 ◽

Cited By ~ 4

Author(s):

Ida Maiello ◽

Sabrina Gentile ◽

Rossella Ferretti ◽

Luca Baldini ◽

Nicoletta Roberto ◽

...

Keyword(s):

Hydrological Cycle ◽

Initial Conditions ◽

Flash Flood ◽

Central Italy ◽

Heavy Precipitation ◽

Radar Reflectivity ◽

Precipitation Event ◽

Italian Regions ◽

Reflectivity Data ◽

The Impact

Abstract. An analysis to evaluate the impact of multiple radar reflectivity data with a three-dimensional variational (3-D-Var) assimilation system on a heavy precipitation event is presented. The main goal is to build a regionally tuned numerical prediction model and a decision-support system for environmental civil protection services and demonstrate it in the central Italian regions, distinguishing which type of observations, conventional and not (or a combination of them), is more effective in improving the accuracy of the forecasted rainfall. In that respect, during the first special observation period (SOP1) of HyMeX (Hydrological cycle in the Mediterranean Experiment) campaign several intensive observing periods (IOPs) were launched and nine of which occurred in Italy. Among them, IOP4 is chosen for this study because of its low predictability regarding the exact location and amount of precipitation. This event hit central Italy on 14 September 2012 producing heavy precipitation and causing several cases of damage to buildings, infrastructure, and roads. Reflectivity data taken from three C-band Doppler radars running operationally during the event are assimilated using the 3-D-Var technique to improve high-resolution initial conditions. In order to evaluate the impact of the assimilation procedure at different horizontal resolutions and to assess the impact of assimilating reflectivity data from multiple radars, several experiments using the Weather Research and Forecasting (WRF) model are performed. Finally, traditional verification scores such as accuracy, equitable threat score, false alarm ratio, and frequency bias – interpreted by analysing their uncertainty through bootstrap confidence intervals (CIs) – are used to objectively compare the experiments, using rain gauge data as a benchmark.

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Advancing from Convection-Allowing NWP to Warn-on-Forecast: Evidence of Progress

Weather and Forecasting ◽

10.1175/waf-d-17-0145.1 ◽

2018 ◽

Vol 33 (2) ◽

pp. 599-607 ◽

Cited By ~ 20

Author(s):

John R. Lawson ◽

John S. Kain ◽

Nusrat Yussouf ◽

David C. Dowell ◽

Dustan M. Wheatley ◽

...

Keyword(s):

Data Assimilation ◽

Real Time ◽

Initial Conditions ◽

Spatial Scales ◽

Weather Prediction ◽

Radar Data ◽

Model Systems ◽

Deterministic Systems ◽

Forecast Lead Time ◽

The Impact

Abstract The Warn-on-Forecast (WoF) program, driven by advanced data assimilation and ensemble design of numerical weather prediction (NWP) systems, seeks to advance 0–3-h NWP to aid National Weather Service warnings for thunderstorm-induced hazards. An early prototype of the WoF prediction system is the National Severe Storms Laboratory (NSSL) Experimental WoF System for ensembles (NEWSe), which comprises 36 ensemble members with varied initial conditions and parameterization suites. In the present study, real-time 3-h quantitative precipitation forecasts (QPFs) during spring 2016 from NEWSe members are compared against those from two real-time deterministic systems: the operational High Resolution Rapid Refresh (HRRR, version 1) and an upgraded, experimental configuration of the HRRR. All three model systems were run at 3-km horizontal grid spacing and differ in initialization, particularly in the radar data assimilation methods. It is the impact of this difference that is evaluated herein using both traditional and scale-aware verification schemes. NEWSe, evaluated deterministically for each member, shows marked improvement over the two HRRR versions for 0–3-h QPFs, especially at higher thresholds and smaller spatial scales. This improvement diminishes with forecast lead time. The experimental HRRR model, which became operational as HRRR version 2 in August 2016, also provides added skill over HRRR version 1.

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Analysis and Forecast of a Tornadic Thunderstorm Using Multiple Doppler Radar Data, 3DVAR, and ARPS Model

Advances in Meteorology ◽

10.1155/2013/281695 ◽

2013 ◽

Vol 2013 ◽

pp. 1-18

Author(s):

Edward Natenberg ◽

Jidong Gao ◽

Ming Xue ◽

Frederick H. Carr

Keyword(s):

Doppler Radar ◽

Initial Conditions ◽

Three Dimensional ◽

Radar Data ◽

Advanced Regional Prediction System ◽

Regional Prediction ◽

Upper Level ◽

Using Data ◽

Nwp Model ◽

The Impact

A three-dimensional variational (3DVAR) assimilation technique developed for a convective-scale NWP model—advanced regional prediction system (ARPS)—is used to analyze the 8 May 2003, Moore/Midwest City, Oklahoma tornadic supercell thunderstorm. Previous studies on this case used only one or two radars that are very close to this storm. However, three other radars observed the upper-level part of the storm. Because these three radars are located far away from the targeted storm, they were overlooked by previous studies. High-frequency intermittent 3DVAR analyses are performed using the data from five radars that together provide a more complete picture of this storm. The analyses capture a well-defined mesocyclone in the midlevels and the wind circulation associated with a hook-shaped echo. The analyses produced through this technique are used as initial conditions for a 40-minute storm-scale forecast. The impact of multiple radars on a short-term NWP forecast is most evident when compared to forecasts using data from only one and two radars. The use of all radars provides the best forecast in which a strong low-level mesocyclone develops and tracks in close proximity to the actual tornado damage path.

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Impact of radar data assimilation for the simulation of a heavy rainfall case in central Italy using WRF–3DVAR

Atmospheric Measurement Techniques ◽

10.5194/amt-7-2919-2014 ◽

2014 ◽

Vol 7 (9) ◽

pp. 2919-2935 ◽

Cited By ~ 12

Author(s):

I. Maiello ◽

R. Ferretti ◽

S. Gentile ◽

M. Montopoli ◽

E. Picciotti ◽

...

Keyword(s):

Heavy Rainfall ◽

Mesoscale Model ◽

Initial Conditions ◽

Positive Impact ◽

Central Italy ◽

Wrf Model ◽

Forecast Accuracy ◽

Radar Data ◽

Heavy Rainfall Event ◽

Dwr Data

Abstract. The aim of this study is to investigate the role of the assimilation of Doppler weather radar (DWR) data in a mesoscale model for the forecast of a heavy rainfall event that occurred in Italy in the urban area of Rome from 19 to 22 May 2008. For this purpose, radar reflectivity and radial velocity acquired from Monte Midia Doppler radar are assimilated into the Weather Research Forecasting (WRF) model, version 3.4.1. The general goal is to improve the quantitative precipitation forecasts (QPF): with this aim, several experiments are performed using the three-dimensional variational (3DVAR) technique. Moreover, sensitivity tests to outer loops are performed to include non-linearity in the observation operators. In order to identify the best initial conditions (ICs), statistical indicators such as forecast accuracy, frequency bias, false alarm rate and equitable threat score for the accumulated precipitation are used. The results show that the assimilation of DWR data has a large impact on both the position of convective cells and on the rainfall forecast of the analyzed event. A positive impact is also found if they are ingested together with conventional observations. Sensitivity to the use of two or three outer loops is also found if DWR data are assimilated together with conventional data.

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Impact of radar data assimilation using WRF three-dimensional variational system, for the simulation of a heavy rainfall case in Central Italy

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-6-7315-2013 ◽

2013 ◽

Vol 6 (4) ◽

pp. 7315-7353

Author(s):

I. Maiello ◽

R. Ferretti ◽

S. Gentile ◽

M. Montopoli ◽

E. Picciotti ◽

...

Keyword(s):

Data Assimilation ◽

Radial Velocity ◽

Heavy Rainfall ◽

Initial Conditions ◽

Positive Impact ◽

Central Italy ◽

Three Dimensional ◽

Warm Start ◽

The Impact ◽

Dwr Data

Abstract. This work is a first assessment of the role of Doppler Weather radar (DWR) data in a mesoscale model for the prediction of a heavy rainfall. The study analyzes the event occurred during 19–22 May 2008 in the urban area of Rome. The impact of the radar reflectivity and radial velocity acquired from Monte Midia Doppler radar, on the assimilation into the Weather Research Forecasting (WRF) model version 3.2, is discussed. The goal is to improve the WRF high resolution initial condition by assimilating DWR data and using ECMWF analyses as First Guess thus improving the forecast of surface rainfall. Several experiments are performed using different set of Initial Conditions (ECMWF analyses and warm start or cycling) and a different assimilation strategy (3 h-data assimilation cycle). In addition, 3DVAR (three-dimensional variational) sensitivity tests to outer loops are performed for each of the previous experiment to include the non-linearity in the observation operators. In order to identify the best ICs, statistical indicators such as forecast accuracy, frequency bias, false alarm rate and equitable threat score for the accumulated precipitation are used. The results show that the assimilation of DWR data has a positive impact on the prediction of the heavy rainfall of this event, both assimilating reflectivity and radial velocity, together with conventional observations. Finally, warm start results in more accurate experiments as well as the outer loops strategy.

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Processing of 3D Weather Radar Data with Application for Assimilation in the NWP Model

Miscellanea Geographica ◽

10.2478/mgrsd-2014-0023 ◽

2014 ◽

Vol 18 (3) ◽

pp. 31-39 ◽

Cited By ~ 1

Author(s):

Katarzyna Ośródka ◽

Jan Szturc ◽

Bogumił Jakubiak ◽

Anna Jurczyk

Keyword(s):

Quality Control ◽

Data Assimilation ◽

Prediction Models ◽

Initial Conditions ◽

Weather Prediction ◽

Weather Radar ◽

Radar Data ◽

Field Pattern ◽

The Impact ◽

Radar Data Assimilation

Abstract The paper is focused on the processing of 3D weather radar data to minimize the impact of a number of errors from different sources, both meteorological and non-meteorological. The data is also quantitatively characterized in terms of its quality. A set of dedicated algorithms based on analysis of the reflectivity field pattern is described. All the developed algorithms were tested on data from the Polish radar network POLRAD. Quality control plays a key role in avoiding the introduction of incorrect information into applications using radar data. One of the quality control methods is radar data assimilation in numerical weather prediction models to estimate initial conditions of the atmosphere. The study shows an experiment with quality controlled radar data assimilation in the COAMPS model using the ensemble Kalman filter technique. The analysis proved the potential of radar data for such applications; however, further investigations will be indispensable.

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Biochemical responses of oligotrophic Adriatic Sea surface layers to atmospheric deposition inputs

10.5194/egusphere-egu2020-15108 ◽

2020 ◽

Author(s):

Sanja Frka ◽

Andrea Milinković ◽

Abra Penezić ◽

Saranda Bakija Alempijević ◽

Blaženka Gašparović ◽

...

Keyword(s):

Atmospheric Deposition ◽

Source Apportionment ◽

Adriatic Sea ◽

Sea Surface ◽

Environmental Research ◽

Surface Layers ◽

Model Calculations ◽

Deposition Fluxes ◽

Biochemical Responses ◽

The Impact

Biochemical responses of oligotrophic Adriatic Sea surface layers to atmospheric deposition inputs&#160;Frka1, A. Milikovi&#263;1, A. Penezi&#263;1, S. Bakija Alempijevi&#263;1, B. Ga&#353;parovi&#263;1, S. Skeji&#263;2, D. &#352;anti&#263;2, S. Brzaj3, V. D&#382;aja Grgi&#269;in3, S. Vidi&#269;3, I. &#352;imi&#263;4, I. Be&#353;li&#263;4, S. &#381;u&#382;ul4, R. Godec4, G. Pehnec41Division for marine and environmental research, Ru&#273;er Bo&#353;kovi&#263; Institute, Zagreb, Croatia2Institute of Oceanography and Fisheries, Split, Croatia3Croatian Meteorological and Hydrological Service, Zagreb, Croatia4Institute for Medical Research and Occupational Health, Zagreb, Croatia&#160;The atmosphere is a significant pathway by which both natural and anthropogenic material is transported from continents to both coastal and open seas. Once deposited through atmospheric deposition (AD) processing, atmospheric particulate matter (PM) provides the aqueous ecosystems with an external source of nutrients and pollutants. This, in turn, influences the organic matter (OM) production by the phytoplankton, changes CO2 uptake and indirectly affects the climate. The input of AD is especially important in oligotrophic environments and it is expected to increase in the future scenarios of a warmer atmosphere with increased PM emissions and deposition rates. While the majority of the data related to the AD impacts generated so far in the Mediterranean have been conducted on its western and eastern regions, the effects of the AD inputs to oligotrophic surface waters of the Adriatic Sea sub-basin are unknown. This work is designed to assess the impact of AD on complex biochemical responses of Adriatic oligotrophic systems, considering the sea surface microlayer (SML) at the air-water interface.Field campaign was conducted during the period of retrieval of sea surface oligotrophic conditions (February-July 2019) at the Martinska, Central Adriatic, Croatia. On-line black carbon (BC) concentrations were measured while the PM10, wet and total deposition samples as well as the SML and underlying water (ULW; 0.5 m depth) samples were collected simultaneously. The temporal dynamics of the SML biology as well as concentrations of&#160; inorganic and organic constituents enabled the assessment of their sources and the nature of the enrichments taking place within the SML. The first comprehensive insight into concentration levels of macro nutrients (N, P), trace metals (eg. Cu, Pb, Cd, Ni, Zn, Co) and OM (including aromatic pollutants) in atmospheric samples, their transport history, source apportionment and deposition fluxes to the oligotrophic Adriatic area will be presented. Daily and seasonal variations of PM10 composition were affected by local traffic and open-fire events as well as by local meteorological conditions and long-range transport. The BC contribution of biomass burning versus fossil fuel combustion changed seasonally. Source apportionment module of LOTOS-EUROS chemical transport model enabled identification and quantification of main source areas contributing to deposition of PM. The main PM contributor is a public power sector outside Croatia while other contributing sectors are energy production, traffic, residential combustion as well as shipping. First deposition fluxes estimates show reasonable agreement between model calculations and measured data, and could be used for more general assessments of atmospheric inputs.&#160;Acknowledgment: This work has been supported by Croatian Science Foundation under the IP-2018-01-3105 project: Biochemical responses of oligotrophic Adriatic surface ecosystems to atmospheric deposition inputs.

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