Agencia Estatal De Meteorologia Research Articles

Utilidad de las proyecciones climáticas generadas por AEMET para estudios de impacto del cambio climático sobre avenidas a escala nacional

<p class="Resumen">La evaluación preliminar del riesgo de inundación deberá tener en cuenta el efecto del cambio climático en la incidencia de inundaciones, según la Directiva de Inundaciones. La Agencia Estatal de Meteorología (AEMET) española ha regionalizado algunas variables suministradas por varios modelos climáticos globales en España, mediante dos métodos de regionalización estadística. La utilidad de esta regionalización, en cuanto a las precipitaciones, reside en el ajuste que tengan a los datos observados en el periodo de control (1961-2000). Para ello, se ha realizado una comparación en base a una serie de estadísticos. Los resultados muestran que, aunque el ajuste es bueno para valores medios anuales, los valores máximos anuales de precipitación para ambas regionalizaciones no son adecuados, ya que los modelos simulan un clima con precipitaciones máximas anuales inferiores, menor variabilidad de los extremos y una gran incertidumbre en la caracterización de los valores más extremos.</p>

Influence of climate change on flood magnitude and seasonality in the Arga River catchment in Spain

Climate change projections suggest that extremes, such as floods, will modify their behaviour in the future. Detailed catchment-scale studies are needed to implement the European Union Floods Directive and give recommendations for flood management and design of hydraulic infrastructure. In this study, a methodology to quantify changes in future flood magnitude and seasonality due to climate change at a catchment scale is proposed. Projections of 24 global climate models are used, with 10 being downscaled by the Spanish Meteorological Agency (Agencia Estatal de Meteorologia, AEMET) and 14 from the EURO-CORDEX project, under two representative concentration pathways (RCPs) 4.5 and 8.5, from the Fifth Assessment Report provided by the Intergovernmental Panel on Climate Change. Downscaled climate models provided by the AEMET were corrected in terms of bias. The HBV rainfall-runoff model was selected to simulate the catchment hydrological behaviour. Simulations were analysed through both annual maximum and peaks-over-threshold (POT) series. The results show a decrease in the magnitude of extreme floods for the climate model projections downscaled by the AEMET. However, results for the climate model projections downscaled by EURO-CORDEX show differing trends, depending on the RCP. A small decrease in the flood magnitude was noticed for the RCP 4.5, while an increase was found for the RCP 8.5. Regarding the monthly seasonality analysis performed by using the POT series, a delay in the flood timing from late-autumn to late-winter is identified supporting the findings of recent studies performed with observed data in recent decades.

Reducing Data Uncertainty in Surface Meteorology Using Data Assimilation: A Comparison Study

Data assimilation in weather forecasting is a well-known technique used to obtain an improved estimation of the current state of the atmosphere (analysis). The Meteorological Service of Catalunya (SMC) is seeking for a real time high resolution analysis of surface parameters over Catalonia (north-east of Spain), in order to know the current weather conditions at any point of that region. For this purpose, a comparative study among several data assimilation experiments based on LAPS (Local Analysis and Prediction System) and STMAS (Space-Time Multiscale Analysis System) and multi-regression technique designed at SMC, has been performed to determine which one delivers best results. The comparison has been done using as true state independent observational data provided by the Spanish Meteorological State Agency (Agencia Estatal de METeorologia, AEMET). The results show that the multi-regression technique provides more accurate analyses of temperature and relative humidity than the LAPS/STMAS experiments, mainly due to the fact that multi-regression methodology only uses observations and consequently the model biases are avoided.

Comparing different profiles to characterize the atmosphere for three MODIS TIR bands

Accurate land surface temperature (LST) retrievals from sensors aboard orbiting satellites are dependent on the corresponding atmospheric correction, especially in the thermal infrared (TIR) spectral domain (8–14μm). To remove the atmospheric effects from at-sensor measured radiance in the TIR range it is needed to characterize the atmosphere by means of three specific variables: the upwelling path and the hemispherical downwelling radiances plus the atmospheric transmissivity. Those variables can be derived from the previous knowledge of vertical atmospheric profiles of air temperature and relative humidity at different geo-potential heights and pressures.In this work, the above mentioned atmospheric variables were analyzed for three specific weather station sites located in Spain, at three different altitudes. These variables were calculated with atmospheric profiles retrieved from three different sources: The National Centers for Environmental Prediction (NCEP) web-tool atmospheric profiles calculator, the MODIS (MOD07) product and the radiosoundings available on the web of the University of Wyoming (WYO), which are launched by the Agencia Estatal de Meteorologia (AEMET), in the particular case of Spain. Atmospheric profiles from 2010 to 2013 were obtained to carry out the present study.Results from comparison of these three different atmospheric profiles show that the NCEP profiles characterize the atmosphere in a better manner than MOD07. Average result values of the three MODIS spectral bands 29, 31 and 32 show a BIAS of 0.06Wm−2μm−1sr−1 and RMSE of ±0.2Wm−2μm−1sr−1 for upwelling radiance, a BIAS of 0.13Wm−2μm−1sr−1 and RMSE of ±0.3Wm−2μm−1sr−1 for the donwelling radiance and a BIAS of −0.008 and RMSE of ±0.03 for the atmospheric transmissivity.In terms of simulated LST, these errors yield a deviation of ±0.9K when applying a single-channel method.

Transforming meteorological data into Linked Data

We describe the AEMET meteorological dataset, which makes available some data sources from the Agencia Estatal de Meteorologia AEMET, Spanish Meteorological Office as Linked Data. The data selected for publication are generated every ten minutes by approximately 250 automatic weather stations deployed across Spain and made available as CSV files in the AEMET FTP server. These files are retrieved from the server, processed with Python scripts, transformed to RDF according to an ontology network which reuses the W3C SSN Ontology, published in a triple store and visualized using Map4RDF.

Species distribution models in climate change scenarios are still not useful for informing policy planning: an uncertainty assessment using fuzzy logic

We compared the effect of general circulation models and greenhouse gas emission scenarios on the uncertainty associated with models predicting changes in areas favourable to animal species. Given that mountain species are particularly at risk due to climate warming, we selected one amphibian (Baetic midwife toad), one reptile (Lataste's viper), one bird (Bonelli's eagle), and one mammal (Iberian wild goat) present in Spanish mountains to model their distributional response to climate change during this century. Climate forecasts for the whole century were provided by the Agencia Estatal de Meteorología (AEMET; National Meteorological Agency) of Spain, which adapted the general circulation models CGCM2 and ECHAM4 and produced expected temperature and precipitation values for Spain according to the A2 and B2 emission scenarios. We constructed separate models of the species response to spatial, topographic, human, and climate variables using current values of the corresponding variables. We predicted future areas favourable to the species by replacing the current climate values with those expected according to each climate change scenario, while keeping spatial, topographic and human variables constant. Fuzzy logic was used to compute the coincidence between predictions for different emission scenarios in the same global circulation model, and the consistency between predictions for the same emission scenario applying different general circulation models. In general, coincidences were higher than consistencies and, thus, discrepancies between predictions were more attributable to uncertainty in global circulation models, i.e. our insufficient knowledge concerning the effect of the oceans and atmosphere on climate, than to the putative effect of different emission scenarios on future climates. Our conclusion is that species distribution models in climate warming scenarios are still not useful for informing emission policy planning, although they have great potential as tools once consistencies become higher than coincidences.

Long-term rainfall monthly shortage in Spain: spatial patterns, statistical models and time trends

Several patterns of the monthly rainfall shortage in Spain are investigated by using long-term series of monthly rain amounts, which were recorded at 34 observatories and compiled by the Agencia Estatal de Meteorologia, AEMET (Spanish Ministry of Environment). Owing to the strong variability of the pluviometric regime along the year, the median of the empirical monthly rain amounts is estimated for every month of the year. A monthly shortage is then defined as the difference between the corresponding monthly median and the monthly rain amount. A spell of monthly shortage is a set of consecutive months with amounts below the corresponding monthly medians. Five magnitudes are defined to characterize the rainfall shortage: (1) the spell length, L (months); (2) the average monthly shortage of a spell, (mm); (3) the largest monthly shortage in a spell, SM (mm); (4) the total rainfall shortage for every spell, CS (mm) and (5) the rainfall amount for every shortage spell, CR. The whole number of spells, N, and the number of spells as a function of shortage lengths, N(L), are compared with those deduced from the distribution theory of runs (TR). Instead of a geometric distribution, a Markov chain of first order with two states becomes a better option for the probability density function of L. Although the empirical distributions of , SM and CS are well fitted by a Pearson-type III model for most gauges, the generalized Pareto (GP) distribution is sometimes a better choice. The distribution of CR is well fitted by gamma and especially Poisson-gamma models. Besides these statistical analyses, an interpretation of the rainfall shortage is attempted by looking for links between the distributions of cumulative monthly shortage (CMS), and cumulative number of months (CNM) with rainfall deficit. Both distributions generate normalized shortage curves (NSC), which follow similar laws to the normalized rainfall curves (NRC), used, for instance, in the study of daily rainfall amounts. Finally, statistical significance of local and field time trends of , SM and CS are evaluated. Copyright © 2009 Royal Meteorological Society

Wind forcing of the coastal circulation off north and northwest Iberia: Comparison of atmospheric models

Comparisons between observed winds and winds from reanalysis (National Centers for Environmental Prediction (NCEP) Reanalysis 1 and 2) and forecast meteorological models (High‐Resolution Limited Area Model (HIRLAM)‐Agencia Estatal de Meteorologia 0.2° and Atmospheric Research Mesoscale Model version 5‐MeteoGalicia with 30 km and 10 km resolution) have been performed for the coastal region around northwest and north Iberia during a typical autumn downwelling period (September–December 2002). Observations at buoys and coastal stations and QuikSCAT‐derived winds were employed. The analyzed period was dominated by southerly and southwesterly winds associated to the passage of low‐pressure systems. Our results show that the westward component is higher on the north coast than on the west coast and that winds are intensified at the western north coast. In this situation, the performance is similar in all model products in general terms, but only HIRLAM represents the reduction of winds in the Cantabrian Sea and NCEP and MM5 overestimate the magnitude of south‐southwest winds. Spatial differences in winds are also obtained for upwelling favorable events, associated either with a high‐pressure system north from Iberia at the beginning of the autumn transition (northeasterly winds) or with conditions after the passage of a low‐pressure system (northwesterly winds). The existence of sea surface temperature (SST) gradients in the coastal region implies that higher‐resolution boundary SST products for meteorological models are necessary. Finally, the effect of these wind products on the coastal circulation was assessed with a 3‐D numerical simulation. Differences in the expansion/confinement of river plumes and the surface speed of the slope current are induced by differences in wind patterns over the shelf and slope area among atmospheric models.