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After 5 years in orbit, the Global Precipitation Measurement (GPM) mission has produced enough quality-controlled 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. [ABSTRACT FROM AUTHOR]

Ensembles of numerical model forecasts are of interest to operational early warning forecasters as the spread of the ensemble provides an indication of the uncertainty of the alerts, and the mean value is deemed to outperform the forecasts of the individual models. This paper explores two ensembles on a severe weather episode in Spain, aiming to ascertain the relative usefulness of each one. One ensemble uses sensible choices of physical parameterizations (precipitation microphysics, land surface physics, and cumulus physics) while the other follows a perturbed initial conditions approach. The results show that, depending on the parameterizations, large differences can be expected in terms of storm location, spatial structure of the precipitation field, and rain intensity. It is also found that the spread of the perturbed initial conditions ensemble is smaller than the dispersion due to physical parameterizations. This confirms that in severe weather situations operational forecasts should address moist physics deficiencies to realize the full benefits of the ensemble approach, in addition to optimizing initial conditions. The results also provide insights into differences in simulations arising from ensembles of weather models using several combinations of different physical parameterizations. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a spatial analysis of the results in the general elections of contemporary Spain (1977–2007). By using electoral data at municipal level, we have traced back the evolution of the vote at high spatial resolution, thus providing a more accurate overview of the evolution of modern Spanish politics and offering empirical evidence on the nationalization thesis. We demonstrate that this approach reveals several processes that remain hidden when aggregated data are used, especially the clustering patterns in the smooth transition from dictatorship to full democracy (the so-called Spanish Transition). We found a statistical normalization process of the left/right dynamics with a growing number of balanced municipalities with a similar number of votes for left and right parties. The tendency towards a Gaussian histogram centered on a value of 50% for the left vote is an indication of political normalization after 40 years of dictatorship. [Copyright &y& Elsevier]

Abstract: Previous studies of the role of regional airports in the Spanish economy have focused on calculating efficiency using air traffic as the output and airport infrastructure data as the input. We present an alternative quantitative analysis based upon the geographical structure within the airport''s market basin. We formulate a ‘geographical efficiency’ model that considers territorial variables within the airport hinterland. Input data for our model include the socio-economic structure of the population, intermodal transport links, industrial and tourism potential and existing leisure-related services. The output is the annual number of passengers associated with such constraints. The result is a relative efficiency estimate that shows uneven patterns of geographical efficiency amongst Spain''s regional airports and also provides insights into opportunities for expanding some of these critical items of infrastructure. They suggest that some of Spain''s regional airports may be better placed than others to compete in a liberalized market that exhibits a clear tendency in favor of coastal, tourism-based airports. [Copyright &y& Elsevier]

The article offers a multisource analysis of Hurricane Vince, the first tropical cyclone on record to make landfall in continental Spain, of 2005. According to the research, the rare storm originated and developed 800 kilometers east-southwest of the Azores in an area with a relatively cold sea surface temperature. The analysis data from the Global Forecast System and the European Center for Medium Range Weather Forecasts both shows a similar initial situation, stating that: initial development of Vince was due to the organization of an area of low pressure between October 5 and 8, 2005.

This study presents the methodology followed in the land use mapping at scale 1:50,000 for the Functional Area of Segovia, Spain. The study is included in the regional planning directives for Segovia, and makes a comprehensive use of the remote sensing techniques developed during the second half of the 1990s. The methodological precedents in this respect are analyzed, mainly the CORINE land cover project, together with the data sources and the techniques that were used to obtain the thematic information searched for. The less known methods are described and a complete methodological sequence of the work is offered. The main characteristics of the methodology are the high degree of automation, objectivity, possibility of direct contrasting and its capacity for quick updating. Diverse data sources have been used, such as cartographic vector information and satellite imagery. LANDSAT-TM and IRS-1D Pan were used as well as aerial oblique photography. All information was integrated into a Geographic Information System (GIS; named SIGIM-TD). Data fusion methods were also widely used to improve the spatial resolution of the images. A neural network was generated to provide an appropriate classification method. Results of the neural network-based classification are shown and a classification-fieldwork correlation of 0.887 was obtained, in contrast with coefficients of 0.334, 0.432, 0.234 and 0.678 achieved through other techniques. Graphic results of the work are presented together with the data sources used for the map elaboration. Finally, a discussion on the advances that these techniques represent is done. [Copyright &y& Elsevier]

Major floods in Spain in September 9–13, 2019 resulted in seven casualties and massive losses to agriculture, property and infrastructure. This paper investigates the utility of satellite data to: (1) characterize the event when input into a hydrological model, and to provide an accurate picture of the evolution of the floods; and (2) inform meteorologists in real time in order to complement model forecasts. It is shown that the precipitation estimates from the Global Precipitation Measurement (GPM) Core Observatory (GPM-CO, available since 2014) and the merged satellite estimates provide an extraordinary improvement over previous technologies to monitor severe hydrometeorological episodes in near real time. In spite of known biases and errors, these new satellite precipitation estimates can be of broad practical interest to deal with emergencies and long-term readiness, especially for semi-arid areas potentially affected by ongoing global warming. Comparisons of satellite data of the September event with model outputs and more direct observations such as rain gauges and ground radars reinforce the idea that satellites are fundamental for an appropriate management of hydrometeorological events. • The IMERG product is useful for monitoring severe storms in the Mediterranean. • Integration of satellite precipitation data into models can save lives and assists planning. • The integration of satellite estimates with numerical forecasts seems unavoidable. • More research on the effects of deep convection over land is required. [ABSTRACT FROM AUTHOR]

Uncertainties and non-linearities between processes involved in rural dynamics pose a challenge to planners and policymakers. Numerical models minimize the risk of making an inappropriate decision and assist planners with making informed policy decisions. In this paper, we present a quantitative analysis of the social, economic and demographic dimensions of rural dynamics using a system dynamics approach. The resulting model (RUSEM: RUral Socio-Economic Model) consists of four main modules that reproduce the main characteristics of the rural areas, with a focus for the European case. The economic module contains the most important variables in the dynamics of local economies - for example, the provision of key services, the availability of public services, and local economic structure. The social and demographic modules use large age groups to analyse the labour market and population dynamics. The attractiveness module summarises push-pull factors affecting rural migration. The model is used to evaluate thirty-six socio-economic scenarios of rural Spain. The results show that very small villages could be incapable to stop rural decline because the absence of "critical mass" while mid-sized villages require targeted actions to reinforce the positive feedbacks of local economy. RUSEM has two goals: to offer computational support enabling robust decision-making in policy formulation in conditions of deep uncertainty and to integrate the socio-economic dimension into Earth System Models (ESMs) providing a numerical model that can be embedded into ESMs at a relatively cheap computational cost. • RUSEM is a socio-economic model of rural dynamics based on system dynamics theory. • It offers computational support enabling robust decision-making in policy formulation. • It can be embedded into ESMs improving the representation of anthropogenic processes. • Output data showed the existence of 'critical mass' thresholds in small communities. [ABSTRACT FROM AUTHOR]

Precipitation is one of the most relevant fields in atmospheric modeling because of its environmental, social and economic implications. However, precipitation validation from weather model outputs presents substantial challenges, such as measurement uncertainties, use of gridded datasets vs. direct observations, and the selection of statistical goodness-of-fit measures. The main difficulty of working with precipitation is that it can be spatially irregular, especially in extreme events. High temporal aggregation smooths the field and reduces verification uncertainty. For this reason, validations are usually focused on a daily scale. However, many extreme events occur on shorter periods, for which a sub-daily precipitation assessment is required. In this paper, hourly precipitation verification of the Weather Research and Forecasting (WRF) model is explored for 45 extreme precipitation events (EPEs) recorded in northeastern Spain. For this, stations with recorded EPEs were classified according to the hourly distribution of precipitation. WRF simulations were established considering three microphysics and two planetary boundary layer (PBL) parameterizations. Finally, several statistical goodness-of-fit measures and spatial and temporal precipitation distributions were used for evaluating WRF performance. The results showed that microphysics were more important than PBL parameterizations. Goddard and Thompson together with Mellor-Yamada-Nakanishi and Nino PBL gave better results for most of the analyzed characteristics. However, an optimal combination of parameterizations was not obtained for all EPEs, because event characteristics had important effects on model performance. • Hourly precipitation verification of the WRF model has been explored. • We selected 965 stations where extreme precipitation was recorded. • Three microphysics and two planetary boundary layer parameterizations were tested. • Goddard and Thompson together with Mellor-Yamada-Nakanishi and Nino gave better results. [ABSTRACT FROM AUTHOR]