Numerical Weather Prediction Applied to Aeronautical Meteorology : Study of Local Hazardous Phenomena

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Físicas, leída el 27-11-2020Aviation and meteorology are intrinsically related. Even if the safety level of the industry is indisputable, the sustained growth represents a constant challenge to maintain the standards assumed today. In this task weather hazards are one of the priorities, as some of these still pose alarge risk for aircraft operation. The main objective of this doctoral thesis is to improve the knowledge of numerical weather prediction models when applied to aeronautical meteorology events. This is done by means of the evaluation of four different hazards: mountain wave icing, low visibility, deep convective precipitation and microbursts. These phenomena are linked not only by the disruption they may create to aircraft operation, but also by the fact that they can occur in very local and reduced spatiotemporal domains, which renders them very difficult to predict. The events are analysed using simulations run by a mesoscale atmospheric numerica lmodel, mostly the Weather Research and Forecasting (WRF) model. Different parametrizations and configurations are tested. Several skill scores and validation methods are applied, adapted to each phenomenon. Other nowcasting techniques, not based in numerical weather prediction, are used to support the assessment...La aviación y la meteorología están intrínsecamente relacionadas. A pesar de que los niveles de seguridad operacional de la industria son indiscutibles, el crecimiento sostenido supone un desafío constante para mantener los estándares asumidos a día de hoy. En esta tarea, los peligros relacionados con la meteorología son una de las prioridades, ya que algunos de ellos todavía suponen un gran riesgo para la operación de aeronaves. El objetivo principal de esta tesis doctorales mejorar el conocimiento de la predicción numérica aplicada a eventos de meteorología aeronáutica. El mismo se lleva a cabo a través de la evaluación de cuatro eventos peligrosos diferentes: engelamiento en onda de montaña, baja visibilidad, precipitación por convección profunda y micro bursts. Estos fenómenos están relacionados no solo por la alteración que pueden ocasionar en la operación de aeronaves, sino también por el hecho de que pueden darse endominios espacio-temporales muy reducidos y locales, lo cual los hace muy difíciles de predecir. Los eventos se analizan usando simulaciones realizadas con un modelo atmosférico mesoescalar, mayormente el modelo Weather Research and Forecasting (WRF). Se prueban diferentes parametrizaciones y configuraciones. También se aplican diferentes métodos de validación y criterios de cualificación. La evaluación se complementa con el uso de otras técnicas de nowcasting, no basadas en predicción numérica...Fac. de Ciencias FísicasTRUEunpu

Pronóstico de engelamiento y ondas de montaña mediante modelos mesoescalares orientado a mejorar la seguridad aérea

Ponencia presentada en: VI Simposio Nacional de Predicción, celebrado en los servicios centrales de AEMET, en Madrid, del 17 al 19 de septiembre de 2018.La turbulencia y la formación de hielo en las aeronaves son dos de los fenómenos meteorológicos más peligrosos en la seguridad de la aviación. Por lo tanto, se recomienda encarecidamente evitar las áreas con alta probabilidad de episodios de formación de hielo a lo largo de las rutas de llegada a, y salida de, los aeropuertos. Este problema es relativamente común en el aeropuerto internacional Madrid-Barajas Adolfo Suárez (LEMD), por lo que es necesario caracterizar estos episodios y mejorar su pronóstico. En este trabajo se ha utilizado el modelo Weather Research and Forecasting (WRF) para la simulación de episodios de ondas de montaña previamente observados. También se han usado herramientas de teledetección tanto para la verificación de las salidas del modelo como para su aplicación al nowcasting o predicción en tiempo real. Esta información puede resultar de gran utilidad en la gestión de las operaciones aeroportuarias, con el objetivo de evitar áreas con riesgo de turbulencia y engelamiento

Pronóstico de engelamiento y ondas de montaña mediante modelos mesoescalares orientado a mejorar la seguridad aérea [Presentación]

Presentación realizada en el VI Simposio Nacional de Predicción "Memorial Antonio Mestre", celebrado en la sede central de AEMET en Madrid del 17 al 19 de septiembre de 2018

Horizontal kinetic energy analysis of tropical transition simulations with the WRF and HARMONIE-AROME models

Four tropical transition (TT) events in the North Atlantic basin are simulated with the Weather Research and Forecasting (WRF) and the HARMONIE-AROME (HAR) models to study the main features of the horizontal kinetic energy (HKE) spectra of these kinds of high-energetic atmospheric system. Though most of the times similar results are obtained with both models, HAR shows a more intense filtering and numerical dissipation, whereas WRF tends to represent overenergized spectra in the synoptic scale and especially at smaller wavelengths. Predictability is dissimilar for the four TTs studied due to the different spectral curve slope obtained for each case, ranging from unlimited to very poor predictability at synoptic scale.This work is funded by the Spanish Ministry of Economy under the research project PID2019-105306RB-I00/AEI/10.13039/501100011033 (IBERCANES)

Microburst detection with the WRF model: effective resolution and forecasting indices

Microbursts are meteorological phenomena in the lower troposphere which can produce damaging surface winds and pose a severe risk to aircraft flying close to the ground. As these events usually span less than 4 km and 15 min, the spatiotemporal resolution is a challenge for numerical simulations. Although research of microburst using operative mesoscale models is scarce, the Weather Research and Forecasting (WRF) model has been used in the diagnosis of this phenomenon. In this paper, such model is used to simulate several microburst conducive days using two different boundary conditions. The energy spectra of the simulations are computed to evaluate the effective resolution of the model. The results are in line with previous studies and produce no notable differences among the boundary conditions. Nonetheless, the energy spectra show an overenergetic troposphere at microscale resolutions, rendering the effective resolution inadequate for microburst forecasting using the simulated physics variables. Thus, mesoscale indices are analyzed as a prognostic tool. The wind index, the wet microburst severity index and the microburst windspeed potential index do not show high forecasting performances, even though improving the results of climatology. Also, notable differences among the boundary conditions can be seen. The most consistent results are achieved by the wet microburst severity index

On the impact of initial conditions in the forecast of Hurricane Leslie extratropical transition

Hurricane Leslie (2018) was a non-tropical system that lasted for a long time undergoing several transitions between tropical and extratropical states. Its trajectory was highly uncertain and difficult to predict. Here the extratropical transition of Leslie is simulated using the Model for Prediction Across Scales (MPAS) with two different sets of initial conditions (IC): the operational analysis of the Integrate Forecast System (IFS) and the Global Forecast System (GFS).This work was partially supported by the research project PID2019-105306RB-I00/AEI/10.13039/501100011033, and the two ECMWF Special Projects (SPESMART and SPESVALE)

Assessing the performance of the HARMONIE-AROME and WRF-ARW numerical models in North Atlantic Tropical Transitions

Producción CientíficaTropical cyclones (TCs) can develop as a result of the tropical transition (TT) process, which occurs when an extratropical cyclone (EC) begins to exhibit tropical characteristics, forming a TC. In this study, four TT processes that lead to a hurricane structure [Delta (2005), Ophelia (2017), Leslie (2018), and Theta (2020)] are evaluated using two high-resolution numerical models (WRF and HARMONIE-AROME). Both tracks and intensities of the cyclones are assessed by comparing the simulated minimum sea level pressure and maximum wind speed to an observational dataset. Moreover, a spatial verification is performed by comparing the MSG-SEVIRI brightness temperature (BT) and accumulated precipitation (IMERG) to the corresponding simulations accomplished by both models. Analyzing the track results, the WRF model, on average, outstands HARMONIE-AROME. However, it is the HARMONIE-AROME model that performs better than WRF when reproducing the intensity of these cyclones. Concerning the BT spatial validation, HARMONIE-AROME slightly outperformed WRF when reproducing the cyclone's structure but failed when simulating the BT amplitude. Besides, both models achieved a nearly perfect cyclone location. In terms of accumulated precipitation results, the HARMONIE-AROME model overestimates the larger structures while underestimating the smaller ones, whereas the WRF model underestimates the bigger structures, being poorly located by both models. Although it is difficult to establish which numerical model performs better, the overall results show an outstanding of the HARMONIE-AROME model over the WRF model when simulating TT processes.IBERCANES (Project PID2019-105306RB-I00/AEI/10.13039/501100011033)Ministerio de Ciencia e Innovación de España - FPI program (PRE2020-092343

Assessment of HARMONIE-AROME in the simulation of the convective activity associated to a subtropical transition using satellite data

Producción CientíficaSubtropical transition events (STT) are a challenge for forecasting and research due to the hybrid characteristics they give to the cyclones. The ability and skillfulness of the HARMONIE-AROME model to reproduce the cloud structure and convection associated to the October 2014 STT is here evaluated. Brightness temperature, cloud top height and accumulated precipitation are assessed against satellite data using traditional skill scores and object-based techniques specific to forecasting spatial evaluation. The results present differences in the simulation of the cyclone between the periods before and after the transition. They also show a very good performance of the model in the location of the events and a good simulation of the intensity of the variables. The performance is sub-optimal for the estimation of the sizes of the convective objects. Brightness temperature and cloud top heights yield very good results in general, with a slight overestimation in both cases. However, the model struggles to capture the accumulated precipitation. There is scarce work evaluating the HARMONIE-AROME model in this type of events; nevertheless, the results are in line with those produced by the simulations with other numerical models. The overall performance of the model is very adequate, although it might be hindered by the internal stability of the model produced by the deep-convection computation.Agencia Estatal de Investigación (PID2019-105306RB-I00/AEI/10.13039/501100011033)Ministerio de Ciencia e Innovación de España - FPI program (PRE2020-092343

Forecasting of poor visibility episodes in the vicinity of Tenerife Norte Airport

Aviation safety is a priority that may be compromised by adverse weather conditions. This is the case for poor visibility in the vicinity of airports, which can pose a risk during takeoff and landing. For airports that are prone to fog because of their location, an accurate forecast of poor-visibility episodes is vital. However, the forecasting of low clouds is still a challenge in numerical weather prediction, especially when an airport is near complex terrain for which the use of non-hydrostatic mesoscale models is mandatory. All these factors are present at Tenerife Norte Airport, which is commonly affected by poor visibility from low clouds related to persistent trade winds and moist flows from the Atlantic Ocean. In this paper, several methods for estimating visibility based on mesoscale model outputs are tested. Use of the HARMONIE-AROME model is encouraged because of its excellent performance in the detection of poor-visibility episodes (False Alarm Ratio = 0.34–0.38; Frequency Of Misses = 0.22–0.38, depending on the model version and method used). In addition, the use of satellite application facilities is proposed for the nowcasting of low clouds affecting the airport area. Specifically, we used products that estimate cloud type, cloud top altitude, and integrated water vapor content in the boundary layer. Finally, an application is presented for the monitoring of weather conditions in real time to estimate poor-visibility risk.This work was supported by the Aeronautics Annual Plan 2018 of AEMET