The study of the extreme weather space events is important for a technological‐dependent society. Extreme value theory could be decisive to characterize those extreme events in order to have the knowledge to make decisions in technological, economic, and social matters, in all fields with possible impacts. In this work, the hourly values of the Dst geomagnetic index have been studied for the period 1957–2014 using the peaks‐over‐threshold technique. The shape parameter obtained from the fit of the generalized Pareto distribution to the extreme values of the |Dst| index leads to a negative value implying an upper bound for this time series. This result is relevant because the estimation of this limit for the extreme values leads to 850 nT as the highest expected value for this geomagnetic index. Thus, from the previous characterization of the Carrington geomagnetic storm and our results, it could be considered the worst‐case scenario.
A statistical study was made of the temporal trend in extreme rainfall in the region of Extremadura (Spain) during the period 1961–2009. A hierarchical spatio-temporal Bayesian model with a GEV parameterization of the extreme data was employed. The Bayesian model was implemented in a Markov chain Monte Carlo framework that allows the posterior distribution of the parameters that intervene in the model to be estimated. The results show a decrease of extreme rainfall in winter and spring and a slight increase in autumn. The uncertainty in the trend parameters obtained with the hierarchical approach is much smaller than the uncertainties obtained from the GEV model applied locally. Also found was a negative relationship between the NAO index and the extreme rainfall in Extremadura during winter. An increase was observed in the intensity of the NAO index in winter and spring, and a slight decrease in autumn.
<p>Different ways to estimate future return levels for extreme rainfall are described and applied to the Iberian Peninsula (IP), based on Extreme Value Theory (EVT). This study is made for an ensemble of high quality rainfall time series observed in the Iberian Peninsula over the period 1961-2010. Both, peaks-over-threshold (POT) approach and block maxima with the Generalized Extreme Value (GEV) distribution will be used and their results compared when linear trends are assumed in the parameters: threshold and scale parameter for POT and location and scale parameter for GEV. Both all-days and rainy-days-only data sets were considered, because rainfall over the IP is a special variable in that a large number of the values are 0. Another methodology is then tested, for rainy days only, considering the role of how the mean, variance, and number of rainy days evolve. T<span>he 20-year return levels (RLs) expected in 2020 were estimated using these methodologies for three seasons: fall, spring and winter. </span>GEV is less reliable than POT because fixed blocks lead to the selection of non-extreme values. Future RLs obtained with POT are higher than those estimated with GEV, mainly for some observatories showing significant positive trend for the number of rainy days. Fall becomes the season with heaviest rainfall, rather than winter nowadays, for some regions.</p>
Heat wave (HW) events are becoming more frequent, and they have important consequences because of the negative effects they can have not only on the human population in health terms but also on biodiversity and agriculture. This motivated a study of the trends in HW events over Extremadura, a region in the southwest of Spain, with much of its area in summer devoted to the production of irrigated crops such as maize and tomatoes. Heat waves were defined for the study as two consecutive days with temperatures above the 95th percentile of the summer (June–August) maximum temperature (Tmax) time series. Two datasets were used: One consisted of 13 daily temperature records uniformly distributed over the Region, and the other was the SPAIN02 gridded observational dataset, extracting just the points corresponding to Extremadura. The trends studied were in the duration, intensity and frequency of HW events, and in other parameters such as the mean, low (25th percentile) and high (75th percentile) values. In general terms, the results showed significant positive trends in those parameters over the east, the northwest and a small area in the south of the region. In order to study changes in HW characteristics (duration, frequency and intensity) considering different subperiods, a stochastic model was used to generate 1000 time series equivalent to the observed ones. The results showed that there were no significant changes in HW duration in the last 10-year subperiod in comparison with the first. But, the results were different for warm events (WE), defined with a lower threshold (the 75th percentile), which are also important for agriculture. For several sites, there were significant changes in WE duration, frequency and intensity.
Non-stationary future return levels for extreme rainfall over Extremadura (southwestern Iberian Peninsula)Published: 30 May 2017 by Informa UK Limited in Hydrological Sciences Journal
 Heat wave event trends over the Iberian Peninsula (IP) are studied using extreme value theory, specifically the peaks‐over‐threshold (POT) approach. Summer (June–August) daily temperature records from 20 observatories regularly distributed over Iberia in places far from urban effects were available for the common period 1961–2010. Heat waves are defined as days occurring above the 95th percentile of the temperature distribution, considering both maximum (Tmax) and minimum (Tmin) temperatures. These events were identified using a “run declustering” scheme to select independent extreme events exceeding the threshold. Also, the dates of occurrence of the independent events were fitted to a Poisson process. Trends in the following parameters were studied: the scale parameter of the POT approach, the Poisson intensity, mean, return level period, and low (25th percentile) and high (75th percentile) values. The optimal trends in the Poisson intensity considering both Tmax and Tmin show a major increase in the occurrence of heat waves. Also, the rise in the return level trend was less than that in the mean of Tmin and Tmax, and the analysis of the values of Tminand Tmax showed a greater increasing trend in the low values (25th percentile) than in the high values (75th percentile), especially for Tmax, leading to a decrease in the variance. Over the IP, temperature extremes are increasing but not as much as the mean because the variance is tending to decrease. This highlights the important role of variance in the evolution of extremes.
In order to analyze the effects of the duration of precipitation events, trends in extreme rainfall over the Iberian Peninsula (IP) for multi-day extreme precipitation events (1 to 7 days) were evaluated from records of 52 observatories regularly distributed over Iberia with no missing data for the common period 1958–2004. Two approaches were used: first, the nonparametric Mann–Kendall test together with the Sen method, and second, a parametric test based on the statistical theory of extreme values, involving time-dependent parameters to account for possible temporal changes in the frequency distribution. It was found that, in winter, there were significant negative trends for a great part of the Iberian Peninsula, but significant positive trends for the southeast over areas that shrank as the number of days considered for the precipitation event increased. Spring also showed negative trends for a great part of the IP but with a major area of positive trend over the northeast that remained unchanged when considering the maxima of from 1 to 7 days of rainfall. Autumn showed a bipolar spatial pattern, with the west being positive and the east negative.
A peaks-over-threshold (POT) approach is used to study trends in extreme rainfall over the Iberian Peninsula (IP) at a daily scale. Records from 52 observatories regularly distributed over Iberia with no missing data were available for the common period from 1958 to 2004. The POT approach was used because it is particularly effective at extracting information concerning true extreme events. A generalized Pareto distribution fit was made to the data involving time-dependent parameters to account for possible temporal changes in the frequency distribution. These parameters were analyzed for trends in the return-level period, of importance for engineering purposes. A time-varying threshold was defined and an automatic declustering scheme was used to select independent extreme events exceeding the threshold. The results indicate a high variability of extreme events over the coastline of the IP, greater over the Mediterranean coast than over the Atlantic coast. The calculation of the trends for the 2-yr return level yielded a large proportion of negative trends for all three seasons considered: 58% for winter, 63% for spring, and 69% for autumn. The parametric approach also revealed an increase in the area with a positive trend of the 20-yr return level relative to the 2-yr return period, especially in autumn in the east of the IP.
In this work, the capacity of the one-dimensional approximation to describe the linear dynamics of liquid bridges is studied in detail. The frequency and damping rate that characterize the first oscillation mode of a cylindrical liquid bridge are calculated from the one-dimensional models and the Navier–Stokes equations. The results are systematically compared varying Λ and C. This comparison allows one to observe the accuracy of the 1-D models and to select the most suitable one for any given values of Λ and C. This selection is expected to be correct for non-cylindrical equilibrium shapes as well. For the sake of illustration, the 1-D models are also solved numerically for non-cylindrical axisymmetric equilibrium shapes.