Data on the main working conditions with influence on the development of hearing loss amongst the occupational population in Spain

Obtaining reliable and objective data on certain working conditions is necessary to analyse the causes and variables that can influence the development of hearing loss amongst the working population. Objective occupational data have been collected from a heterogeneous sample of 1418 workers in Spain, see “How activity type, time on the job and noise level on the job affect the hearing of the working population. Using Bayesian networks to predict the development of hipoacusia” (Barrero et al., 2018) [1]. Among the main factors analysed are the noise levels to which these workers are exposed, measured at their respective workstations, and the assessment of their hearing status, evaluated by audiometric medical tests. These factors provide information to predict the development of hypoacusia

Spatiotemporal characterization of Ensemble Prediction Systems – the Mean-Variance of Logarithms (MVL) diagram

We present a novel approach to characterize and graphically represent the spatiotemporal evolution of ensembles using a simple diagram. To this aim we analyze the fluctuations obtained as differences between each member of the ensemble and the control. The lognormal character of these fluctuations suggests a characterization in terms of the first two moments of the logarithmic transformed values. On one hand, the mean is associated with the exponential growth in time. On the other hand, the variance accounts for the spatial correlation and localization of fluctuations. In this paper we introduce the MVL (Mean-Variance of Logarithms) diagram to intuitively represent the interplay and evolution of these two quantities. We show that this diagram uncovers useful information about the spatiotemporal dynamics of the ensemble. Some universal features of the diagram are also described, associated either with the nonlinear system or with the ensemble method and illustrated using both toy models and numerical weather prediction systems

Spatio-temporal error growth in the multi-scale Lorenz’96 model

The influence of multiple spatio-temporal scales on the error growth and predictability of atmospheric flows is analyzed throughout the paper. To this aim, we consider the two-scale Lorenz’96 model and study the interplay of the slow and fast variables on the error growth dynamics. It is shown that when the coupling between slow and fast variables is weak the slow variables dominate the evolution of fluctuations whereas in the case of strong coupling the fast variables impose a non-trivial complex error growth pattern on the slow variables with two different regimes, before and after saturation of fast variables. This complex behavior is analyzed using the recently introduced Mean-Variance Logarithmic (MVL) diagram

Dificultades para la incorporación de la Realidad Aumentada en la enseñanza universitaria: visiones desde los expertos

“Augmented reality” (AR) is presented as technology that harmonizes, in real time and with user collaboration, digital information with physical information through different technological supports. Such are AR possibilities, that when it is incorporated into teaching, students show high satisfaction rates and positive attitudes for its use, but at the same time, a series of limitations and obstacles can be noticed. As an attempt to investigate the technical, curricular and organizational difficulties of AR incorporation in training contexts, an instrument “AR obstacle questionnaire” (CORA) was designed, which in turn was administered to a total of 264 subject experts for validation through the Delphi method, subsequently applying the “K coefficient” (K = ½ Kc (knowledge coefficient) + Ka (argumentation coefficient)), selecting those experts who obtained a ≥ 0,8 score in the coefficient. Among the results obtained in the study we manage to point out the main obstacles involving AR implementation into university education: the lack of teacher training and improvement, the few educational experiences found, lack of conceptual foundation, limited educational research and lack of institutional support.La “realidad aumentada” (RA) se presenta como una tecnología que armoniza, en tiempo real y con la colaboración del usuario, información digital con información física a través de diferentes soportes tecnológicos. Tales son sus posibilidades, que cuando se incorpora a la enseñanza, los alumnos muestran altos niveles de satisfacción y actitudes positivas para su utilización, pero a la misma vez, presenta una serie de limitaciones y obstáculos. Bajo el objetivo de indagar sobre las dificultades técnicas, curriculares y organizativas de la incorporación de la RA en los contextos formativos, se diseño un instrumento un “Cuestionario de obstáculos RA” (CORA), que fue administrado a un total de 264 expertos en la materia para su validación a través de método Delphi, aplicando posteriormente el “Coeficiente K” (K = ½ Kc (coeficiente de conocimiento) + Ka (coeficiente de argumentación)), seleccionando aquellos expertos que en el resultado del coeficiente obtuvieron una puntuación ≥ a 0,8. Entre los resultados obtenidos en el estudio podemos señalar que los principales obstáculos con que nos encontramos para la incorporación de la RA a la formación universitaria, gira en torno a: la falta de formación y perfeccionamiento del profesorado, las pocas experiencias educativas que nos encontramos, la falta de fundamentación conceptual, la limitada investigación educativa y la falta de apoyo institucional.Ministry of Economy and Competitiveness of Spain, Spain. Funder Identifier: http://dx.doi.org/10.13039/50110000332

Regional climate projections over Spain: atmosphere. Future climate projections

Special Issue on climate over the Iberian Peninsula: an overview of CLIVAR-Spain coordinated science

Using WRF to generate high resolution offshore wind climatologies

Ponencia presentada en: VIII Congreso de la Asociación Española de Climatología celebrado en Salamanca entre el 25 y el 28 de septiembre de 2012.Recently, the demand of gridded wind datasets over sea areas has increased due to the ongoing development of offshore wind farms. Currently available reanalysis datasets do not have enough resolution to deal with complex coastlines and coastal topography, and these do interact with the winds and meteorological systems well into the open sea. Here we present the main characteristics of a high resolution wind climatology that has been produced using the Weather Research and Forecasting model to downscale the ERA-INTERIM reanalysis. The simulations were carried out in a domain covering the Mediterranean basin and most of Europe, and thus areas with different wind regimes. The model has been kept close to the driving reanalysis by restarting it daily, as this running mode provided better results than nudging techniques. Results show that WRF is able to produce realistic offshore wind climatologies, probabilistic wind distributions and annual cycle. It also reproduces well-known regional winds remarkably well.This paper is a contribution to the financed projects by the Spanish government CORWES (CGL2010-22158-C02-01), WRF4G (CGL2010-22158-C02-01), EXTREMBLES (CGL2010-21869), C3E (200800050084091), iMar21 (CTM201015009) and MARUCA (E17/08), and was partially funded by projects ‘MAREN’ (Atlantic Area Transnational Programme) and ‘CoCoNet’ (FP7-OCEAN-2011)

Development and analysis of a 50-year high-resolution daily gridded precipitation dataset over Spain (Spain02)

In this paper, we present a new publicly available high-resolution daily precipitation gridded dataset developed for peninsular Spain and the Balearic islands using 2756 quality-controlled stations (this dataset is referred to as Spain02 ). The grid has a regular 0.2° (approx. 20 km) horizontal resolution and spans the period from 1950 to 2003. Different interpolation methods were tested using a cross-validation approach to compare the resulting interpolated values against station data: kriging, angular distance weighting, and thin plane splines. Finally, the grid was produced applying the kriging method in a two-step process. First, the occurrence was interpolated using a binary kriging and, in a second step, the amounts were interpolated by applying ordinary kriging to the occurrence outcomes. This procedure is similar to the interpolation method used to generate the E-OBS gridded data – the state-of-the-art publicly available high-resolution daily dataset for Europe – which was used in this study for comparison purposes. Climatological statistics and extreme value indicators from the resulting grid were compared to those from the 25 km E-OBS dataset using the observed station records as a reference. Spain02 faithfully reproduces climatological features such as annual precipitation occurrence, accumulated amounts and variability, whereas E-OBS has some deficiencies in the southern region. When focusing on upper percentiles and other indicators of extreme precipitation regimes, Spain02 accurately reproduces the amount and spatial distribution of the observed extreme indicators, whereas E-OBS data present serious limitations over Spain due to the sparse data used in this region. As extreme values are more sensitive to interpolation, the dense station coverage of this new data set was crucial to get an accurate reproduction of the extremes

Evaluation and projection of daily temperature percentiles from statistical and dynamical downscaling methods

ABSTRACT. The study of extreme events has become of great interest in recent years due to their direct impact on society. Extremes are usually evaluated by using extreme indicators, based on order statistics on the tail of the probability distribution function (typically percentiles). In this study, we focus on the tail of the distribution of daily maximum and minimum temperatures. For this purpose, we analyse high (95th) and low (5th) percentiles in daily maximum and minimum temperatures on the Iberian Peninsula, respectively, derived from different downscaling methods (statistical and dynamical). First, we analyse the performance of reanalysisdriven downscaling methods in present climate conditions. The comparison among the different methods is performed in terms of the bias of seasonal percentiles, considering as observations the public gridded data sets E-OBS and Spain02, and obtaining an estimation of both the mean and spatial percentile errors. Secondly, we analyse the increments of future percentile projections under the SRES A1B scenario and compare them with those corresponding to the mean temperature, showing that their relative importance depends on the method, and stressing the need to consider an ensemble of methodologies

Can gridded data represent extreme precipitation events?

Póster presentado en: 11IMSC - International Meeting on Statistical Climatology celebrado del 12 al 16 de Julio de 2010 en EdimburgoThe analysis and characterization of extreme precipitation at regional scale requires data at high temporal and spatial resolution due to the abrupt variations of this variable in time and space. In recent years there has been an increasing demand for comprehensive regular high-resolution (both in time and space) gridded datasets from different sectors, including hydrology, agriculture and health which are severely affected by extreme events. One of the main shortcomings of gridded datasets is that extreme events can be smoothed during the interpolation process. Heavy rainfall events can be very local and, hence, interpolation with neighboring stations may lead to an underestimation of the precipitation amounts. In this work we study the capability of a high-resolution daily precipitation gridded dataset over Spain (we refer to this dataset as Spain02, Herrera et al 2010) to characterize extreme precipitation. A dense network of 2756 quality-controlled stations was selected to develop the Spain02 grid with a regular 0.2º horizontal resolution covering the period from 1950 to 2003. We study both upper percentiles and the extreme indicators commonly used to characterize extreme precipitation regimes. We also show the performance of the gridded dataset to capture both the intensity and the spatial structure of severe precipitation episodes which constitute characteristic ephemerides of extreme weather in the Iberian peninsula. The results are compared to the 25 Km E-OBS grid (Haylock et al 2008) developed in the ENSEMBLES project, which is the best daily dataset for the whole Europe to date