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

2017 ◽  
Vol 21 (11) ◽  
pp. 5459-5476 ◽  
Author(s):  
Ida Maiello ◽  
Sabrina Gentile ◽  
Rossella Ferretti ◽  
Luca Baldini ◽  
Nicoletta Roberto ◽  
...  

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.

2016 ◽  
Author(s):  
Ida Maiello ◽  
Sabrina Gentile ◽  
Rossella Ferretti ◽  
Luca Baldini ◽  
Nicoletta Roberto ◽  
...  

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.


2021 ◽  
Author(s):  
Vincenzo Mazzarella ◽  
Rossella Ferretti ◽  
Errico Picciotti ◽  
Frank S. Marzano

Abstract. The precipitation forecast over the Mediterranean basin is still a challenge because of the complex orographic region which amplifies the need for local observation to correctly initialize the forecast. In this context the data assimilation techniques play a key role in improving the initial conditions and consequently the timing and position of precipitation pattern. For the first time, the ability of a cycling 4D-Var to reproduce a severe weather event in central Italy, as well as to provide a comparison with the largely used cycling 3D-Var, is evaluated in this study. The radar reflectivity measured by the Italian ground radar network is assimilated in the WRF model to simulate an event occurred on May 3, 2018 in central Italy. In order to evaluate the impact of data assimilation, several simulations are objectively compared by means of a Fraction Skill Score (FSS), which is calculated for several threshold values, and a Receiver Operating Characteristic (ROC) curve. The results suggest that both assimilation methods in cycling mode improve the 1, 3 and 6-hourly quantitative precipitation estimation. More specifically, the cycling 4D-Var with a warm start initialization shows the highest FSS values in the first hours of simulation both with light and heavy precipitation. Finally, the ROC curve confirms the benefit of 4D-Var: the area under the curve is 0.91 compared to the 0.88 of control experiment without data assimilation.


2008 ◽  
Vol 17 ◽  
pp. 71-77 ◽  
Author(s):  
X. Yan ◽  
V. Ducrocq ◽  
P. Poli ◽  
G. Jaubert ◽  
A. Walpersdorf

Abstract. The impact of assimilating Zenith Total delay (ZTD) observations from a mesoscale ground-based GPS network over Western Europe is evaluated for the heavy precipitation event of 5–9 September 2005 over Southern France. The ZTD assimilation is performed using a three dimensional variational data assimilation system at the 9.5-km horizontal resolution. Then using as initial conditions the 3DVAR analyses with and without assimilation of ZTD, we perform 2.4-km non-hydrostatic MESO-NH simulations. The results of the fine-scale simulations indicate that assimilation of ZTD help to improve the forecast of the tropospheric water vapour content and the quantitative precipitation forecast. We have also assessed through single observation experiments the influence of the formulation of the observation operator which is used to compute the model equivalent ZTD.


2021 ◽  
Vol 21 (9) ◽  
pp. 2849-2865
Author(s):  
Vincenzo Mazzarella ◽  
Rossella Ferretti ◽  
Errico Picciotti ◽  
Frank Silvio Marzano

Abstract. Forecasting precipitation over the Mediterranean basin is still a challenge because of the complex orographic region that amplifies the need for local observation to correctly initialize the forecast. In this context, data assimilation techniques play a key role in improving the initial conditions and consequently the timing and position of the precipitation forecast. For the first time, the ability of a cycling 4D-Var to reproduce a heavy rain event in central Italy, as well as to provide a comparison with the largely used cycling 3D-Var, is evaluated in this study. The radar reflectivity measured by the Italian ground radar network is assimilated in the Weather Research and Forecasting (WRF) model to simulate an event that occurred on 3 May 2018 in central Italy. In order to evaluate the impact of data assimilation, several simulations are objectively compared by means of a fraction skill score (FSS), which is calculated for several threshold values, and a receiver operating characteristic (ROC) curve. The results suggest that both assimilation methods in the cycling mode improve the 1-, 3- and 6-hourly quantitative precipitation estimation. More specifically, the cycling 4D-Var with a warm start initialization shows the highest FSS values in the first hours of the simulation both with light and heavy precipitation. Finally, the ROC curve confirms the benefit of 4D-Var: the area under the curve is 0.91 compared to 0.88 for the control experiment without data assimilation.


2021 ◽  
Author(s):  
Antonio Ricchi ◽  
Vincenzo Mazzarella ◽  
Lorenzo Sangelantoni ◽  
Gianluca Redaelli ◽  
Rossella Ferretti

<div> <p><span>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. </span></p> </div>


Atmosphere ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1177
Author(s):  
Diana Arteaga ◽  
Céline Planche ◽  
Christina Kagkara ◽  
Wolfram Wobrock ◽  
Sandra Banson ◽  
...  

The Mediterranean region is frequently affected in autumn by heavy precipitation that causes flash-floods or landslides leading to important material damage and casualties. Within the framework of the international HyMeX program (HYdrological cycle in Mediterranean EXperiment), this study aims to evaluate the capabilities of two models, WRF (Weather Research and Forecasting) and DESCAM (DEtailed SCAvenging Model), which use two different representations of the microphysics to reproduce the observed atmospheric properties (thermodynamics, wind fields, radar reflectivities and precipitation features) of the HyMeX-IOP7a intense precipitating event (26 September 2012). The DESCAM model, which uses a bin resolved representation of the microphysics, shows results comparable to the observations for the precipitation field at the surface. On the contrary, the simulations made with the WRF model using a bulk representation of the microphysics (either the Thompson scheme or the Morrison scheme), commonly employed in NWP models, reproduce neither the intensity nor the distribution of the observed precipitation—the rain amount is overestimated and the most intense cell is shifted to the East. The different simulation results show that the divergence in the surface precipitation features seems to be due to different mechanisms involved in the onset of the precipitating system: the convective system is triggered by the topography of the Cévennes mountains (i.e., south-eastern part of the Massif Central) in DESCAM and by a low-level flux convergence in WRF. A sensitivity study indicates that the microphysics properties have impacted the thermodynamics and dynamics fields inducing the low-level wind convergence simulated with WRF for this HyMeX event.


2020 ◽  
Author(s):  
Antonio Ricchi ◽  
Vincenzo mazzarella ◽  
Lorenzo Sangelantoni ◽  
Gianluca Redaelli ◽  
Rossella Ferretti

<p>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.</p>


2016 ◽  
Vol 38 (2) ◽  
pp. 1077
Author(s):  
Luana Ribeiro Macedo ◽  
João Luiz Martins Basso ◽  
Yoshihiro Yamasaki

The WRF mesoscale system 4DVAR data assimilation technique have been used with the purpose of evaluating the impact of the meteorological data assimilation on the numeric time prognosis over the Rio Grande do Sul state. It has been done utilizing the surface and altitude data. The consistency analysis has been done evaluating the numerical prognosis exploring the differences between the analysis with and without data assimilation. The produced prognosis results have been compared spatially using the TRMM satellite data as well as the Canguçu radar reflectivity data. The accumulated rainfall has been validated and compared spatially with the TRMM data for the time period of 12 hours comprehended between October 29th and 30th of 2014. It was possible to realize that as well as the WRF, the WRFVAR overestimated the rainfall values. The radar reflectivity field without data assimilation for October 30th at 06:00UTC detected most accurately the reflectivity centers over the state. On the other hand this field with data assimilation did not present good skill. The temperature field analyses reveal that the 4DVAR assimilation system contributes, one way or another, presenting a little improvement for some points compared to the real data.


2021 ◽  
Author(s):  
Alberto Caldas-Alvarez ◽  
Samiro Khodayar ◽  
Peter Knippertz

Abstract. Heavy precipitation is one of the most devastating weather extremes in the western Mediterranean region. Our capacity to prevent negative impacts from such extreme events requires advancements in numerical weather prediction, data assimilation and new observation techniques. In this paper we investigate the impact of two state-of-the-art data sets with very high resolution, Global Positioning System-Zenith Total Delays (GPS-ZTD) with a 10 min temporal resolution and radiosondes with ~700 levels, on the representation of convective precipitation in nudging experiments. Specifically, we investigate whether the high temporal resolution, quality, and coverage of GPS-ZTDs can outweigh their lack of vertical information or if radiosonde profiles are more valuable despite their scarce coverage and low temporal resolution (24 h to 6 h). The study focuses on the Intensive Observation Period 6 (IOP6) of the Hydrological Cycle in the Mediterranean eXperiment (HyMeX; 24 September 2012). This event is selected due to its severity (100 mm/12 h), the availability of observations for nudging and validation, and the large observation impact found in preliminary sensitivity experiments. We systematically compare simulations performed with the COnsortium for Small scale MOdelling (COSMO) model assimilating GPS, high- and low vertical resolution radiosoundings in model resolutions of 7 km, 2.8 km and 500 m. The results show that the additional GPS and radiosonde observations cannot compensate errors in the model dynamics and physics. In this regard the reference COSMO runs have an atmospheric moisture wet bias prior to precipitation onset but a negative bias in rainfall, indicative of deficiencies in the numerics and physics, unable to convert the moisture excess into sufficient precipitation. Nudging GPS and high-resolution soundings corrects atmospheric humidity, but even further reduces total precipitation. This case study also demonstrates the potential impact of individual observations in highly unstable environments. We show that assimilating a low-resolution sounding from Nimes (southern France) while precipitation is taking place induces a 40 % increase in precipitation during the subsequent three hours. This precipitation increase is brought about by the moistening of the 700  hPa level (7.5 g kg−1) upstream of the main precipitating systems, reducing the entrainment of dry air above the boundary layer. The moist layer was missed by GPS observations and high-resolution soundings alike, pointing to the importance of profile information and timing. However, assimilating GPS was beneficial for simulating the temporal evolution of precipitation. Finally, regarding the scale dependency, no resolution is particularly sensitive to a specific observation type, however the 2.8 km run has overall better scores, possibly as this is the optimally tuned operational version of COSMO. In follow-up experiments the Icosahedral Nonhydrostatic Model (ICON) will be investigated for this case study to assert whether its numerical and physics updates, compared to its predecessor COSMO, are able to improve the quality of the simulations.


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