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Gridded precipitation datasets have been developed for data assimilation and evaluation tasks of weather and climate models and for climate analyses. Gridded data uncertainty evaluation is crucial to understand the limitations and feasibility. The development of high‐resolution daily gridded precipitation datasets is desirable, but several factors need to be considered, namely rain gauge station availability, their spatial distribution, and orographic and climate characteristics of a study area. Quality assessment of gridded datasets can present difficulties when the influence of these factors is not thoroughly analysed. The main objective of this study was a detailed validation of precipitation grids based on four factors, that is, station density used for grid construction, grid spatial resolution, station altitude, and climate type. To this end, 18 grids were built using six spatial resolutions (0.01°, 0.025°, 0.05°, 0.1°, 0.2° and 0.4°) and three station densities (25, 50 and 75% of all available stations). Results indicate larger differences among the grids as a function of analysed factors. Station density was found to be the main factor, whereas grid spatial resolution had minor importance. However, the latter factor becomes more relevant in areas with strong altitude gradients and when a high station density is available. In addition, weak and moderate precipitation is overestimated on daily grids, whereas heavy precipitation cells are less frequent, reducing data variability. On the contrary, monthly and annual aggregates present less deviation from the observed distribution than daily comparisons. These findings question the applicability of the daily grid datasets for validation studies and climate analysis on a grid cell level. Funding came from projects LE240P18 (Consejería de Educación, Junta de Castilla y León) and CGL2016‐78702‐C2‐1‐R, PID2019‐108470RB‐C22, CGL2016‐80609‐R and PID2019‐108470RB‐C21 (Ministerio de Economía y Competitividad).

After 5 years in orbit, the Global Precipitation Measurement (GPM) mission has produced enough qualitycontrolled data to allow the first validation of their precipitation estimates over Spain. High-quality gauge data from the meteorological network of the Spanish Meteorological Agency (AEMET) are used here to validate Integrated Multisatellite Retrievals for GPM (IMERG) level 3 estimates of surface precipitation. While aggregated values compare notably well, some differences are found in specific locations. The research investigates the sources of these discrepancies, which are found to be primarily related to the underestimation of orographic precipitation in the IMERG satellite products, as well as to the number of available gauges in the GPCC gauges used for calibrating IMERG. It is shown that IMERG provides suboptimal performance in poorly instrumented areas but that the estimate improves greatly when at least one rain gauge is available for the calibration process. A main, generally applicable conclusion from this research is that the IMERG satellite-derived estimates of precipitation are more useful (r2 > 0.80) for hydrology than interpolated fields of rain gauge measurements when at least one gauge is available for calibrating the satellite product. If no rain gauges were used, the results are still useful but with decreased mean performance (r2 ~ 0.65). Such figures, however, are greatly improved if no coastal areas are included in the comparison. Removing them is a minor issue in terms of hydrologic impacts, as most rivers in Spain have their sources far from the coast. Funding from projects CGL2013- 48367-P, CGL2016-78702-C2-1-R, CGL2016-80609-R (Ministerio de Economía y Competitividad), UNCM08-1E-086 (Ministerio de Ciencia e Innovación), and Development of Numerical Weather Prediction and Data Application Technique 1365002970/KMA2018-00721 (Korea Meteorological Administration) is gratefully acknowledged.

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.

Daily time series from the Climate Prediction Center (CPC) Africa Rainfall Climatology version 2.0 (ARC2), Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) and Tropical Applications of Meteorology using SATellite (TAMSAT) African Rainfall Climatology And Time series version 2 (TARCAT) high-resolution long-term satellite rainfall products are exploited to study the spatial and temporal variability of East Africa (EA, 5S–20N, 28–52E) rainfall between 1983 and 2015. Time series of selected rainfall indices from the joint CCl/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices are computed at yearly and seasonal scales. Rainfall climatology and spatial patterns of variability are extracted via the analysis of the total rainfall amount (PRCPTOT), the simple daily intensity (SDII), the number of precipitating days (R1), the number of consecutive dry and wet days (CDD and CWD), and the number of very heavy precipitating days (R20). Our results show that the spatial patterns of such trends depend on the selected rainfall product, as much as on the geographic areas characterized by statistically significant trends for a specific rainfall index. Nevertheless, indications of rainfall trends were extracted especially at the seasonal scale. Increasing trends were identified for the October–November–December PRCPTOT, R1, and SDII indices over eastern EA, with the exception of Kenya. In March–April–May, rainfall is decreasing over a large part of EA, as demonstrated by negative trends of PRCPTOT, R1, CWD, and R20, even if a complete convergence of all satellite products is not achieved. This study was supported by the European Union’s Seventh Programme for research, technological development, and demonstration under Grant Agreement 603608 (eartH2Observe).

Ponencia presentada en: XXXV Jornadas Científicas de la AME y el XIX Encuentro Hispano Luso de Meteorología celebrado en León, del 5 al 7 de marzo de 2018. Un pronóstico meteorológico preciso es indispensable para la aviación, ya que del mismo depende tanto la gestión del vuelo como de los riesgos a los que está expuesta. Las condiciones meteorológicas adversas son la causa de múltiples incidentes y accidentes de aviación, constituyendo la presencia del engelamiento una de las situaciones más peligrosas para la seguridad en vuelo (Caliskan & Hajiyev, 2013). Sin embargo, los modelos numéricos suelen sobreestimar la presencia de agua en fase sólida y subestimar la presencia de agua subfundida, de tal manera que no se pronostica con precisión la concentración de SLD (Fernández-González, et al. 2014). Esto genera que el pronóstico de las condiciones de engelamiento en meteorología aeronáutica sea manifiestamente mejorable. A través de un caso de estudio, este trabajo evalúa, la idoneidad de la información meteorológica aeronáutica previa a un vuelo y analiza si es adecuada para anticipar casos de engelamiento. Se analizan las condiciones atmosféricas a escala sinóptica y posteriormente, se modelizan las condiciones a mesoescala para estudiar la predictibilidad del episodio. Finalmente se investigan posibles herramientas de nowcasting usando teledetección.

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.

Estimating space-time variability of precipitation is an important task in East Africa, considering the observed increased frequency of extreme events, drought episodes in particular. These events deeply affect the population with implications on agriculture and consequently food security. Daily accumulated precipitation time series from satellite retrieval algorithms, ARC, CHIRPS, TAMSAT, TMPA-3B42, and CMORPH are exploited to study the spatial and temporal variability of East Africa (EA - 5°S-20°N, 28°E-52°E) precipitation during last decades (1983-2013 for ARC, CHIRPS, and TAMSAT; 1998-2014 for TMPA-3B42 and CMORPH). The analysis is carried out by directly investigating the precipitation time series and computing the time series of the joint CCI/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI, http://etccdi.pacificclimate.org/index.shtml), i.e. RX1day, RX5day, CDD, CWD, SDII, PRCPTOT, R10, and R20, at the yearly and seasonal scales. The purpose is to identify the occurrence of extreme events (droughts and floods), and extract precipitation spatial patterns of variation by trend analysis (Mann-Kendall technique). Prior to the analysis satellite time series are checked for the possible presence of inhomogeneities due to variations in rain gauge density and/or in the satellite retrieval algorithms. Preliminary results relative to the trend analysis of the yearly precipitation indices reveal a consensus of the different satellite products on a positive trend of the annual total precipitation (PRCPTOT) over Somalia and East Ethiopia. More problematic is the situation over West Ethiopia, Sudan, and Uganda, where is not possible to converge to a common type of trend (e.g., negative trend for CMORPH, ARC, and TMPA-3B42 and positive trend for TAMSAT and CHIRPS over west Ethiopia). Similar behaviors are found for other indices (e.g., SDII - average precipitation on wet days over a year, and R1 - annual number of precipitating days). As for CDD (maximum number of consecutive dry days) ARC, CMORPH, and TAMSAT agree on a negative trend over Somalia, East Ethiopia, and most of Kenya. CHIRPS exhibits a predominance of weak positive trends almost over all EA, whereas the contrary is true for TAMSAT. For this parameter only very limited areas are characterized by high significance levels of the trends.

Accurate estimation of snowfall episodes several hours or even days in advance is essential to minimize risks to transport and other human activities. Every year, these episodes cause severe traffic problems on the northwestern Iberian Peninsula. In order to analyze the influence of different parameterization schemes, 15 snowfall days were analyzed with the Weather Research and Forecasting (WRF) model, defining three nested domains with resolutions of 27, 9, and 3 km. We implemented four microphysical parameterizations (WRF Single‐Moment 6‐class scheme, Goddard, Thompson, and Morrison) and two planetary boundary layer schemes (Yonsei University and Mellor‐Yamada‐Janjic), yielding eight distinct combinations. To validate model estimates, a network of 97 precipitation gauges was used, together with dichotomous data of snowfall presence/absence from snowplow requests to the emergency service of Spain and observatories of the Spanish Meteorological Agency. The results indicate that the most accurate setting of WRF for the study area was that using the Thompson microphysical parameterization and Mellor‐Yamada‐Janjic scheme, although the Thompson and Yonsei University combination had greater accuracy in determining the temporal distribution of precipitation over 1 day. Combining the eight deterministic members in an ensemble average improved results considerably. Further, the root mean square difference decreased markedly using a multiple linear regression as postprocessing. In addition, our method was able to provide mean ensemble precipitation and maximum expected precipitation, which can be very useful in the management of water resources. Finally, we developed an application that allows determination of the risk of snowfall above a certain threshold. This paper was supported by the following grants: TEcoAgua, METEORISK PROJECT(RTC‐2014‐1872‐5), Granimetro(CGL2010‐15930) and MINECO(CGL2011‐25327, RTC‐2014‐1872‐5 and ESP2013‐47816‐C4‐4P), and LE220A11‐2 and LE003B009 awarded by the Junta de Castilla and León.

Surface icing can cause dramatic consequences on human activities. What is more, numerical weather prediction models are not very accurate in determining freezing drizzle, which creates uncertainty when forecasting this type of weather phenomenon. Therefore, it is essential to improve the forecast accuracy of these models for such phenomena to mitigate risks caused by unforeseen freezing drizzle events. On 5 February 2012, an episode of freezing drizzle took place in the Guadarrama Mountains, at the center of the Iberian Peninsula. This episode was preceded by weak snowfall. After the freezing drizzle, moderate snowfall was recorded in the study area. This event was simulated using the Weather Research and Forecasting model. Through this analysis, we identified the meteorological factors at both synoptic scale and mesoscale that caused this episode. Wind perpendicular to an orographic barrier-generated updrafts and retention of moisture upwind, which caused orographic clouds to appear on the north side of the Guadarrama Mountains. Atmospheric stability prevented cloud formation at midlevels at the time of the freezing drizzle, which maintained cloud top temperatures warmer than −15ºC during the episode. The entrance of moisture and instability at midlevels caused cloud top temperatures substantially colder than −15º C, which coincided with snow in the mountain range. Cloud top temperature and thickness control the efficiency of the glaciation process, thereby determining the type of precipitation at the surface. Freezing drizzle risk and in-cloud icing algorithms were developed with the aim of predicting similar events in the study area, which could mitigate impacts on human activities. This paper was supported by the following grants: TEcoAgua, METEORISK PROJECT (RTC-2014-1872-5), Granimetro (CGL2010-15930) and CGL2011-25327 of MINECO, and LE220A11-2 and LE003B009 awarded by the Junta de Castilla y León.

Hailstorms have become a serious meteorological risk in mid-latitude countries because of their small-scale development and short time span, and their forecasting remains problematic. Moreover, the lack of reliable hailstorm databases is an important handicap for Numerical Weather Prediction (NWP) model validation, time trend studies and establishment of hailstorm relationships with global warming and climate change. However, this can be overcome by ascertaining physical relationships between favourable synoptic patterns and mesoscale trigger factors for hailstorm development in a local study area. North-eastern Spain is one of the European regions with largest number of hailstorm days (HD) observed in the summer. Since 2001, from May through September, reliable databases of hailstorm occurrence in the middle Ebro Valley have been constructed, which include intensity, temporal frequency and spatial coordinate data. June and July 2006 had the largest number of HD in 2001–2010. With the objective of analysing meteorological factors responsible for this anomaly, atmospheric patterns at low and mid-tropospheric levels were studied. We determined a set of special synoptic configurations, with an evident deviation from climatic values generating anomalies of 850 hPa temperature relative to the characteristic values of 2001–2010 and 1950–2010. An analysis of these anomalies detected a positive trend of 850 hPa temperature and geopotential height in the western Mediterranean area. As a consequence, the characteristic synoptic circulation has changed since 1950, towards low-level patterns favouring adequate thermodynamic environments for hailstorm development in north-eastern Spain. Finally, after a cluster analysis, we studied periodicities in the monthly 850 hPa temperature field to improve knowledge for seasonal forecasting of hailstorms. The study was supported by the Plan Nacional de I+D of Spain through grant CGL2010-15930 and the Junta de Castilla y León through grant LE176A11-2.

168 p. [ES] La observación y predicción de los fenómenos convectivos severos presenta importantes retos. La mejora en el conocimiento de estos fenómenos es de sumo interés para reducir los riesgos que ocasionan sobre la población y el medio ambiente. En el presente trabajo, se han desarrollado algoritmos para la identificación de cumulonimbos y caídas de granizo. La creación de los algoritmos se ha llevado a cabo mediante un modelo de regresión logística binaria, combinando datos de diferentes canales del satélite Meteosat Segunda Generación (MSG). . En este estudio se ha desarrollado una metodología para la caracterización de las precipitaciones convectivas de granizo en diferentes escalas, en el valle medio del Ebro, con el objetivo de mejorar la predicción de estos fenómenos. La caracterización sinóptica y mesoescalar se ha realizado mediante los modelos numéricos mesoescalares MM5 y WRF. Estos resultados ponen de relieve la interrelación existente entre los entornos sinóptico, las configuraciones mesoescalares y los parámetros predictores de granizo. Por este motivo, para caracterizar las tormentas con granizo es necesario el estudio conjunto de estos tres pilares básicos. La información obtenida de esta caracterización puede ser de gran ayuda para la predicción operativa de tormentas de granizo. En conclusión, los resultados que se muestran en esta memoria permiten avanzar en el estudio y conocimiento de la convección severa y de las tormentas de granizo. Para ello se ha profundizado en la observación, análisis y predicción de estos fenómenos. En el futuro, el desarrollo de nuevas tecnologías de detección, y la mejora de las predicciones numéricas ayudarán a resolver el reto que hoy en día supone el estudio de las precipitaciones de granizo.

Ponencia presentada en: VIII Congreso de la Asociación Española de Climatología celebrado en Salamanca entre el 25 y el 28 de septiembre de 2012. [ES]Las tormentas de granizo son uno de los riesgos meteorológicos más importantes del SW de Europa. Concretamente el Valle Medio del Ebro (VME) es el área que registra la mayor frecuencia de eventos de granizo de España, con unas pérdidas económicas de alrededor de 100 M€ anuales. El Grupo de Física de la Atmósfera (GFA) de la Universidad de León realiza campañas de investigación en el VME desde 2001 de forma continuada, registrando un promedio de 60 días de tormenta cada verano, mediante un radar meteorológico. [EN]Hailstorms are one of the principal risks in the SW of Europe. Specifically, the Mid-Ebro Valley (VME), is the area that has the greatest frequency of registered hail events in Spain, with economic losses of approximately 100 M€ annually. The Group for Atmospheric Physics (GFA) at the University of León has done research campaigns in the VME continuously since 2001, registering 60 storm days per year via meteorological radar. Este estudio ha sido financiado por los proyectos REN 2000-1210 CLI, REN 2003-09617-C02-01, CGL 2006-13372-C02-01, CGL 2010-15930 del Plan Nacional del I+D+i.

35 páginas, ilustraciones [ES] El cambio climático es uno de los mayores problemas ambientales al que nos enfrentamos actualmente como sociedad. La frecuencia y severidad de los fenómenos climáticos extremos como sequías e inundaciones no deja de crecer debido a aumentos en la temperatura media global y a cambios en los patrones de movimiento atmosférico. El objetivo de este trabajo es verificar la existencia de tendencias en el territorio español peninsular para la temperatura, precipitación e índice NAO, definido como la diferencia anómala entre el anticiclón de las Azores y la borrasca islandesa. Se busca analizar también cómo afecta la oscilación del Atlántico norte en las precipitaciones y la temperatura española en diferentes estaciones. Utilizando el programa de análisis estadístico Rstudio junto a datos de 67 estaciones meteorológicas con seguimiento durante al menos ochenta años, se realizaron cuatro tipos de pruebas capaces de analizar tendencias y establecer patrones relacionales entre distribuciones de datos. Una prueba K-S, una regresión lineal, la prueba de Mann-Kendall y una correlación de kendall. Se encontraron evidencias claras de la existencia de tendencias positivas en la temperatura durante todo el siglo pasado, afectando especialmente al interior de la peninsula y al litoral mediterráneo. En cuanto a la precipitación, se determinó que el cambio climático no afecta significativamente a los regímenes de precipitación a escala local, pero si lo hace de forma indirecta, modificando la oscilación del Atlántico norte de tal forma que los movimientos atmosféricos tiendan a dirigirse hacia Centroeuropa llevándose las nubes con ellos, disminuyendo la precipitación y aumentando la temperatura en la península [EN] Climate change is one of the biggest environmental problems we are currently facing as a society. The frequency and severity of extreme climatic phenomena such as droughts and floods is constantly increasing due to increases in global mean temperature and changes in atmospheric movements. The aim of this work is to verify the existence of trends in the Spanish peninsular territory in temperature, precipitation and NAO index, defined as the anomalous difference between the Azores anticyclone and the Icelandic cyclone , as well as to determine how the orth Atlantic oscillation affects Spanish precipitation and temperature in different seasons. Using the statistical analysis program Rstudio together with data from 67 meteorological stations tracked for at least eighty years, four types of tests capable of analyzing trends and establishing relational patterns between data distributions were performed. A K-S test, a linear regression, the Mann-Kendall test and a kendall correlation. Clear evidence was found for the existence of positive trends in temperature throughout the last century, especially affecting the interior of the peninsula and the Mediterranean coast. As for precipitation, it was determined that climate change does not significantly affect precipitation regimes on a local scale, but does so indirectly, modifying the North Atlantic oscillation in such a way that atmospheric movements tend to move towards Central Europe, taking clouds with them, decreasing precipitation and increasing temperature in the peninsula

30 páginas, ilustraciones [ES] En este trabajo se muestreó la dolina denominada Prado Veneiro, dentro del valle del río Luna (León), con el objetivo de conocer las condiciones atmosféricas a nivel sinóptico que favorecen la formación de Piscinas de Aire Frío (CAPs), una clase de inversión térmica muy localizada en el espacio y a veces persistente en el tiempo. Para ello, se realizó una comparación de las temperaturas mínimas y máximas entre la dolina y una ubicación ajena a estos fenómenos. Con los datos recogidos en campo, se realizó un Análisis de Componentes Principales (PCA) acompañado por un análisis clúster no jerárquico, así como un test de correlación de Pearson con diversas variables atmosféricas extraídas del Reanálisis ERA-5. Los resultados, además de arrojar registros nunca observados en los fondos de valle leoneses (-29,7ºC) indicaron la gran magnitud de las CAPs registradas en esta zona durante todo el año, llegando a superar los 20ºC de diferencia. Además, destacó la aparición de episodios de Piscinas de Aire Frío Permanentes (PCAPs) en los meses invernales, que se desarrollaron durante las horas centrales del día. Por último, se observó que las CAPs y PCAPs se encuentran correlacionadas con distintas variables atmosféricas, indicando la importancia de la presencia de nieve reciente para la formación de las segundas [EN] The Prado Veneiro sinkhole, within the Luna River valley (León), was researched aiming to understand the atmospheric conditions at synoptic scale that trigger the formation of Cold Air Pools (CAPs), a kind of thermal inversion which is strongly localized in space, but sometimes quite persistent in time. Thus, a comparison of the minimum and maximum temperatures between the sinkhole and a location external to these phenomena was carried out. Subsequently, after the field work was made, a Principal Component Analysis (PCA) was carried out accompanied by a non-hierarchical cluster analysis, as well as a Pearson correlation test with various atmospheric variables extracted from the Reanalysis data from ERA-5. Results showed record-breaking temperatures never observed before in the low valleys of León (-29.7ºC), demonstrating the strength of the CAPs recorded in this area throughout the year, which reached differences of over 20ºC. In addition, the presence of Permanent Cold Air Pools (PCAPs) in the winter months, which developed during the midday, was highlighted. Ultimatelly, CAPs and PCAPs showed they were correlated with different atmospheric variables, suggesting the need of a recent snow base for a strong PCAP development

149 p. Las precipitaciones de granizo son un fenómeno convectivo severo frecuente en la Europa mediterránea, causando graves daños en las actividades económicas y pudiendo suponer riesgo para la población. Su identificación y predicción tienen por tanto una gran importancia, pero siguen suponiendo un importante reto en la actualidad, debido a la pequeña escala espacial y temporal del fenómeno. La detección y correcta identificación del granizo es vital para poder estudiar las características de este tipo de precipitaciones, así como las condiciones atmosféricas que las originan. El primero de los objetivos de esta memoria de tesis es la mejora en la detección remota y el seguimiento de las tormentas de granizo para el sur de Francia, mediante el empleo de datos de satélite. Otro de los objetivos abordados en esta memoria es la mejora en la predicción de las granizadas en el sur de Francia. Debido a su pequeña escala, las precipitaciones de granizo no han sido incluidas entre los campos de predicción de la mayoría de modelos numéricos. Tradicionalmente, la predicción de las tormentas de granizo se ha basado en el empleo de índices de estabilidad que caracterizan los ambientes preconvectivos. Estos índices son calculados a partir de los perfiles verticales extraídos de radiosondeos. Sin embargo, se ha comprobado en numerosos estudios que ningún índice funciona mejor que otro en todas las regiones y situaciones preconvectivas. Numerosos autores han empleado métodos que hacen uso de técnicas de regresión logística para combinar varios de estos índices en algoritmos con una mayor capacidad predictiva. Además, la representatividad espacial y temporal de los radiosondeos tradicionales es muy limitada. Por ello, actualmente se está tendiendo al uso de perfiles verticales extraídos de modelos numéricos para el cálculo de índices y parámetros usados en la predicción. En esta memoria de tesis se ha desarrollado una nueva herramienta para su uso en la predicción operativa a corto plazo de tormentas de granizo en el suroeste de Francia mediante la caracterización de los patrones termodinámicos preconvectivos. Este estudio se ha basado en la metodología desarrollada por Gascón et al (2015). El último objetivo planteado en esta memoria es el estudio de las tendencias en la aparición de granizo en el sur de Francia e inferir cuál será su evolución futura en el marco del calentamiento global. El ascenso de las temperaturas implicaría, en principio, un aumento en la energía disponible para la convección. La presente memoria de tesis presentada por la modalidad de compendio de artículos recoge por tanto tres publicaciones en una revista científica de impacto donde se exponen los trabajos encaminados a completar el estudio del granizo en el sur de Francia. Estos trabajos se centran en la mejora de la detección y seguimiento de las tormentas de granizo de manera remota mediante satélite; la predicción a corto plazo de la distribución e intensidad de las granizadas a partir de los patrones termodinámicos preconvectivos; y el estudio de las tendencias en los entornos atmosféricos a nivel sinóptico favorables al desarrollo de convección severa en la región

187 p. La presente tesis doctoral tiene como objetivo principal la mejora de la predicción de episodios convectivos o precipitaciones de gran intensidad, ya sean de nieve o granizo, a partir de dos herramientas diferentes: uso del modelo Weather Research and Forecasting (WRF) y de los datos obtenidos en medidas en continuo por un radiómetro de microondas multicanal (MMWR). Por un lado, en este trabajo se ha querido profundizar en el conocimiento de los mecanismos que producen las tormentas de nieve en la Península Ibérica y para ello se analizó un episodio convectivo invernal desarrollado en la Sierra de Guadarrama en 2011 y que dio como resultado la mejor comprensión de los mecanismos tanto a nivel sinóptico, como mesoescalar y termodinámico. Y, por otro lado, se ha trabajado en la creación de una nueva herramienta, complementaria a las ya existentes, para la toma de decisiones en la predicción de las precipitaciones de granizo en el Valle Medio del Ebro (MEV).