Radar-based nowcasting of severe thunderstorms: A better understanding of the dynamical influence of complex topography and the sea

[eng] Natural disasters of hydro-meteorological origin are the biggest risk worldwide. In Catalonia (NE of the Iberian Peninsula), severe weather and flash floods occur each year, resulting in major damage to property, losses in agriculture, and also of human lives. To reduce its impact, we need to...

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Detalles Bibliográficos
Autor: del Moral Méndez, Anna
Tipo de recurso: tesis doctoral
Estado:Versión publicada
Fecha de publicación:2020
País:España
Institución:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/174135
Acceso en línea:https://hdl.handle.net/2445/174135
http://hdl.handle.net/10803/670869
Access Level:acceso abierto
Palabra clave:Meteorologia
Previsió del temps
Precipitacions (Meteorologia)
Radar
Meteorology
Weather forecasting
Precipitations (Meteorology)
Descripción
Sumario:[eng] Natural disasters of hydro-meteorological origin are the biggest risk worldwide. In Catalonia (NE of the Iberian Peninsula), severe weather and flash floods occur each year, resulting in major damage to property, losses in agriculture, and also of human lives. To reduce its impact, we need to improve the early warning systems and storm short-term forecasting. There’s a need to gain in-depth knowledge of severe thunderstorm dynamics, since the current accused conditions of global warming can impact in factors triggering these storms. The main objective of the present thesis is to enhance the knowledge of severe storms dynamics and to improve their identification and monitoring in real time, in order to help prevent their surface effects on the citizens. The project addresses the unresolved problem of storm anomalous motion, as it becomes a great challenge to predict their evolution and impact in the next few hours. For this purpose, the area of Catalonia has been chosen as the study region of this project, due to the proximity to the sea and complex topography, which are often key factors in varying the weather at a local scale. There is also the advantage of having good radar coverage, which will be the essential tool for characterizing storms. We first propose a methodology that identifies potentially convective days from daily cumulative rainfall fields, selects them to search for storms, and determines if their motion is anomalous. We have found that the area with the highest convective activity between 2008-2015 in Catalonia was located in the eastern Pre-Pyrenees, due to the possible creation of a convergence line. It has also been identified that there are more convective structures with possible anomalous propagation in summer and spring, with the main patterns being related to splitting, merging, stationarity and elongated storms. Once the study sample is defined, we have developed an algorithm to improve the identification and tracking of these thunderstorms, especially those with anomalous propagations. The keys of improvement have been based on proposing new techniques in the three main modules; 2D, 3D identification and tracking. In addition, it incorporates alerts before possible cell splitting or merging. These changes have shown that the algorithm is able to faithfully reproduce storm life cycle, correctly identify in advanced anomalous motion, and correctly distinguish storms in highly dense convective situations. The algorithm has been verified first over 30 severe cases, proving that it can identify anomalous movements with a mean 30-min lead-time, being the splitting, the easiest one to do. It has also been demonstrated a good ability at not only identifying these movements but also separating cases with and without anomalous motion. On the other hand, the algorithm has demonstrated a good performance in cases of heavy rainfall on a Catalan flood-prone coastal area of touristic interest. It is identified that storms are usually organized in convergence lines, and that topography and the sea play a very important role, whether affecting the movement, the time of exposure, or the amount of precipitable water causing flash floods. Finally, the dual-Doppler technique is applied in Catalonia for the first time. This allows getting complete information of the internal dynamics of a thunderstorm, without the need of running idealized models, and then, getting to know the local topographic influence on the evolution and organization. It is demonstrated that the complex local topography changes and/or amplifies the wind flow inside and near thunderstorms, modifying completely their life cycle and their possible interactions with their neighbor cells. It is also shown that this qualitative improvement into storm-scale dynamic knowledge can improve the nowcasting techniques and the early warning systems in the future.