Problematika orokorra: migrapena, langabezia, komunikabideak, mendiak, urtegiak, euskara, nekazaritza = Problemática general: emigración, paro, comunicaciones, montes, pantanos, euskera, agricultura

Descripción de los principales problemas político-sociales de la Merindad de Sangüesa.Zangozako merindadeko arazo politiko eta sozial nagusien deskribapena

Modelling the occurrence of heat waves in maximum and minimum temperatures over Spain and projections for the period 2031-60.

The occurrence of extreme heat events in maximum and minimum daily temperatures is modelled using a non-homogeneous common Poisson shock process. It is applied to five Spanish locations, representative of the most common climates over the Iberian Peninsula. The model is based on an excess over threshold approach and distinguishes three types of extreme events: only in maximum temperature, only in minimum temperature and in both of them (simultaneous events). It takes into account the dependence between the occurrence of extreme events in both temperatures and its parameters are expressed as functions of time and temperature related covariates. The fitted models allow us to characterize the occurrence of extreme heat events and to compare their evolution in the different climates during the observed period. This model is also a useful tool for obtaining local projections of the occurrence rate of extreme heat events under climate change conditions, using the future downscaled temperature trajectories generated by Earth System Models. The projections for 2031-60 under scenarios RCP4.5, RCP6.0 and RCP8.5 are obtained and analysed using the trajectories from four earth system models which have successfully passed a preliminary control analysis. Different graphical tools and summary measures of the projected daily intensities are used to quantify the climate change on a local scale. A high increase in the occurrence of extreme heat events, mainly in July and August, is projected in all the locations, all types of event and in the three scenarios, although in 2051-60 the increase is higher under RCP8.5. However, relevant differences are found between the evolution in the different climates and the types of event, with a specially high increase in the simultaneous ones

Testing independence between two nonhomogeneous point processes in time

Point processes are often used to model the occurrence times of different phenomena, such as heatwaves or spike trains. Many of those problems require to study the independence between nonhommogeneous point processes in time, and this work develops three families of tests to assess that hypothesis. They can be applied to different types of processes, and all together they cover a wide range of situations appearing in real problems. The first family includes two tests for Poisson processes. The second family is based on the close point distance, and the third one on cross dependence functions. An extensive simulation study of the size and power of the tests is carried out and some practical rules to select the most appropriate test in different cases, are provided. The proposed tests are demonstrated on a real data application about the occurrence of extreme heat events in three Spanish locations

Modelos para la precipitación diaria en el marco de los modelos lineales generalizados

En la memoria se desarrollan modelos estadísticos que permiten caracterizar, en un grado adecuado, el comportamiento de la precipitación diaria en un observatorio. La modelización elegida representa el proceso de lluvia mediante dos componentes, la ocurrencia de precipitación, representada por una variable binaria, y la cantidad medida en los días lluviosos, cada una de las cuales requiere construir un submodelo. En ambos casos, la distribución de la variable de interés no es Gaussiana y su valor esperado depende de covariables atmosféricas; por esto, el marco de los modelos lineales generalizados (GLM) y sus extensiones que permiten considerar la dependencia entre respuesta sucesivas, resulta un esquema de modelización adecuado. En el capítulo 1 se hace una revisión bibliográfica de los modelos de precipitación y una presentación de la familia de modelos a utilizar. El capítulo 2 de la memoria se dedica al análisis de las herramientas de crítica de los modelos y a hacer una propuesta de valoración de los mismos. Se propone una metodología que tiene en cuenta, además de las medidas habituales, la capacidad de los modelos para clasificar correctamente las observaciones, reproducir el ciclo estacional, la evolución interanual de la lluvia o la distribución de la longitud de las rachas seca y húmeda. El capítulo 3 se dedica a la construcción de modelos y al análisis de su capacidad para ajustar las series de precipitación de cuatro observatorios de la cuenca del Ebro con diferentes características climáticas e información atmosférica dispar. Los modelos de ocurrencia considerados son cadenas de Markov cuyas probabilidades de transición se estiman mediante regresión logística. La estrategia de construcción estudia, en pasos sucesivos, la significación de diferentes convariables: indicadores de ocurrencia en los días previos, armónicos para representar el ciclo anual y covariables climática. El objetivo del capítulo 4 es construir un modelo que predsiga la precipitación de un observatorio. En el capítulo 5 se desarrolla un "downscaling" de las precipitaciones en un escenario de cambio climático

Bayesian variable selection in generalized extreme value regression: modeling annual maximum temperature

In many applications, interest focuses on assessing relationships between covariates and the extremes of the distribution of a continuous response. For example, in climate studies, a usual approach to assess climate change has been based on the analysis of annual maximum data. Using the generalized extreme value (GEV) distribution, we can model trends in the annual maximum temperature using the high number of available atmospheric covariates. However, there is typically uncertainty in which of the many candidate covariates should be included. Bayesian methods for variable selection are very useful to identify important covariates. However, such methods are currently very limited for moderately high dimensional variable selection in GEV regression. We propose a Bayesian method for variable selection based on a stochastic search variable selection (SSVS) algorithm proposed for posterior computation. The method is applied to the selection of atmospheric covariates in annual maximum temperature series in three Spanish stations

RecordTest: An R Package to Analyze Non-Stationarity in the Extremes Based on Record-Breaking Events

The study of non-stationary behavior in the extremes is important to analyze data in environmental sciences, climate, finance, or sports. As an alternative to the classical extreme value theory, this analysis can be based on the study of record-breaking events. The R package RecordTest provides a useful framework for non-parametric analysis of non-stationary behavior in the extremes, based on the analysis of records. The underlying idea of all the non-parametric tools implemented in the package is to use the distribution of the record occurrence under series of independent and identically distributed continuous random variables, to analyze if the observed records are compatible with that behavior. Two families of tests are implemented. The first only requires the record times of the series, while the second includes more powerful tests that join the information from different types of records: upper and lower records in the forward and backward series. The package also offers functions that cover all the steps in this type of analysis such as data preparation, identification of the records, exploratory analysis, and complementary graphical tools. The applicability of the package is illustrated with the analysis of the effect of global warming on the extremes of the daily maximum temperature series in Zaragoza, Spain

Statistical analysis of extreme and record-breaking daily maximum temperatures in peninsular Spain during 1960–2021

This work analyses the effects of global warming in the upper extremes of daily temperature series over Spain. This objective implies specific analysis, since time evolution of mean temperature is not always parallel to evolution of the extremes. We propose the use of several record tests to study the behavior of the extreme and record-breaking events in different temperature signals, at different time and spatial scales. The underlying idea of the tests is to compare the occurrence of the extreme events in the observed series and the occurrence in a stationary climate. Given that under global warming, an increasing trend, or an increasing variability, can be expected, the alternative is that the probability of the extremes is higher than in a stationary climate. Some of the tests, based on a permutation approach, can be applied to sets of correlated series and this allows the analysis of short periods of time and regional analysis, where series are measured in close days and/or locations. Using these tests, we evaluate and compare the effects of climate change in temperature extreme and record-breaking events using 36 series of daily maximum temperature from 1960 to 2021, all over peninsular Spain. We also compare the behavior in different Spanish regions, in different periods of the year, and in different signals such as the annual maximum temperature. Significant evidences of the effect of an increasing trend in the occurrence of upper extremes are found in most of Spain. The effects are heterogeneous within the year, being autumn the season where the effects are weaker and summer where they are stronger. Concerning the spatial variability, the Mediterranean and the North Atlantic region are the areas where the effects are more and less clear, respectively

Caracterización espacio-temporal de la evolución de la precipitación anual en la cuenca del Ebro

Ponencia presentada en: III Congreso de la Asociación Española de Climatología “El agua y el clima”, celebrado en Palma de Mallorca del 16 al 19 de junio de 2002.[ES]El objetivo de este trabajo es realizar una caracterización espacio-temporal de la evolución de la precipitación en la cuenca del Ebro. Para ello se construye una base de datos con 29 series con información mensual del periodo 1916-2000. Por estaciones, y posteriormente con las series anuales, se realiza un proceso de homogeneización. Mediante un análisis de conglomerados, complementado con un análisis de las tendencias en la lluvia anual, se efectúa una regionalización de la cuenca. Para cada una de las regiones definidas se construye una serie temporal que describe la evolución de la lluvia en ese territorio. Sobre esas series regionales se realiza un análisis de tendencias.[EN]The aim of this work is the spatial-time characterisation of the rainfall evolution in the Ebro river basin. A database for a network of 29 meteorological stations throughout the basin with monthly rainfall information for the period 1916-2000 has been built. The corresponding seasonal and annual series were subjected to a homogenization process. A cluster analysis complemented with a trend analysis of annual rainfall allows us to classify the basin in eight homogeneous areas. Finally, regional time series describing the rainfall evolution in each defined region have been built and analysed to study their trend behaviour.Este trabajo ha sido financiado por la Oficina de Planificación Hidrológica de la Confederación Hidrográfica del Ebro (asistencia técnica 2001-PH-14-I)

Record tests to detect non-stationarity in the tails with an application to climate change

The analysis of trends and other non-stationary behaviours at the extremes of a series is an important problem in global warming. This work proposes and compares several statistical tools to analyse that behaviour, using the properties of the occurrence of records in i.i.d. series. The main difficulty of this problem is the scarcity of information in the tails, so it is important to obtain all the possible evidence from the available data. First, different statistics based on upper records are proposed, and the most powerful is selected. Then, using that statistic, several approaches to join the information of four types of records, upper and lower records of forward and backward series, are suggested. It is found that these joint tests are clearly more powerful. The suggested tests are specifically useful in analysing the effect of global warming in the extremes, for example, of daily temperature. They have a high power to detect weak trends and can be widely applied since they are non-parametric. The proposed statistics join the information of M independent series, which is useful given the necessary split of the series to arrange the data. This arrangement solves the usual problems of climate series (seasonality and serial correlation) and provides more series to find evidence. These tools are used to analyse the effect of global warming on the extremes of daily temperature in Madrid

Model-based tools for assessing space and time change in daily maximum temperature: an application to the Ebro basin in Spain

There is continuing interest in the investigation of change in temperature over space and time. We offer a set of tools to illuminate such change temporally, at desired temporal resolution, and spatially, according to region of interest, using data generated from suitable space-time models. These tools include predictive spatial probability surfaces and spatial extents for an event. Working with exceedance events around the center of the temperature distribution, the probability surfaces capture the spatial variation in the risk of an exceedance event, while the spatial extents capture the expected proportion of incidence of a given exceedance event for a region of interest. Importantly, the proposed tools can be used with the output from any suitable model fitted to any set of spatially referenced time series data. As an illustration, we employ a dataset from 1956 to 2015 collected at 18 stations over Arag\'{o}n in Spain, and a collection of daily maximum temperature series obtained from posterior predictive simulation of a Bayesian hierarchical daily temperature model. The results for the summer period show that although there is an increasing risk in all the events used to quantify the effects of climate change, it is not spatially homogeneous, with the largest increase arising in the center of Ebro valley and Eastern Pyrenees area. The risk of an increase of the average temperature between 1966-1975 and 2006-2015 higher than $1^\circ$C is higher than 0.5 all over the region, and close to 1 in the previous areas. The extent of daily temperature higher than the reference mean has increased 3.5% per decade. The mean of the extent indicates that 95% of the area under study has suffered a positive increment of the average temperature, and almost 70% higher than $1^{\circ}$C.Comment: 23 pages main manuscript and 7 pages supplemen