A. Ezcurra

Experimental study of the scavenging process by means of a sequential precipitation collector, preliminary results

Abstract From January 1986 to July 1989, 103 rain events were sampled with a sequential collector in Vitoria, a moderately industrialized city (Spanish Basque country). Each sample was analysed in terms of pH, conductivity and the ionic concentration of Cl−, NO−3, SO2−4, NH+4, Na+, K+, Ca2+ and Mg2+. On average, the rainwater samples were acid, with a mean pH value of 4.9 the major ions being SO2−4 and Ca2+. Events with highly acid characteristics (pH ⩽ 4.5) represent 14% of the total collected. Analysis of meteorological conditions in relation with the average ionic concentrations points out the influence of anthropogenic sources from southwestern France and from the northern Basque country. The decrease in the wet deposition (in percentage of the total deposition per rainfall event) throughout precipitation is particularly apparent for NH+4 and Ca2+ ions. In precipitation related to the meteorological Local-class, the atmospheric removal appears to be more efficient, especially for Ca2+, and we can also note a precipitation-neutralizing effect. Precipitation scavenging is mainly controlled by the total amount of water precipitated. However, the intensity of the rain modified the deposition rate.

Organic acids in precipitation in the Basque country (North of Spain)

Abstract This paper discusses the results of the measurement of organic anions in precipitation collected since July 1989 in Olaeta, a rural village in the Basque Country (North of Spain). In order to gain a deeper knowledge of the characteristics and acids responsible for the free acidity observed in precipitation, a study was started within the EPOCA programme (Estudios en el Pirineo Occidental de la Contaminacion Acida), for measuring organic anions: formiate, acetate and propionate. These results show that it was possible to observe organic anions in nearly every event, with a 5% contribution to the anionic total, and with an appreciable seasonal variation in concentration. The maximum contribution of organic acids to free acidity (H + ) is 6% in rain events with pH≤5.0. There is significant correlation between acetic acid and inorganic ions of marine origin Cl − , Na + and Mg 2+ which might indicate the importance which the air masses of marine origin are going to have in the concentration of this acid. There is also significant correlation between formic acid and SO 4 2− and H + ions which might indicate the relatively importance contribution of formic acid to free acidity.

Chemical composition of acid rain in the North of Spain: the EPOCA program

Abstract The EPOCA program (Estudios en el Pirineo Occidental sobre Contaminacion Acida), whose main goal is to show the possible effects of an “acid rain” type pollution on the forests of the Spanish Basque country, is presented in this paper. A measurement network comprising two automatic precipitation collectors located at Vitoria and at Llodio has been operating since December 1985. 30% of the events of rainfall were acidic with a pH ⩽5. However, rain with an alkaline character (pH>6) is found in 25% (Vitoria) and 40% (Lldio) of the cases. The statistical analysis of the chemical components confirms that the chemical contents of the acid rain have an anthropogenic character and those of the alkaline rain a soil origin. Both sources play an important part in the temporal trend of pH values and precipitation chemistry.

Reconstruction of sea surface temperature by means of DINEOF: a case study during the fishing season in the Bay of Biscay

The Spanish surface fishery operates mainly during the summer season in the waters of the Bay of Biscay. Sea surface temperature (SST) data recovered from satellite images are being used to improve the operational efficiency of fishing vessels (e.g. reduce search time and increase catch rate) and to improve the understanding of the variations in catch distribution and rate needed to properly manage fisheries. The images used for retrieval of SST often present gaps due to the existence of clouds or satellite malfunction periods. The data gaps can totally or partially affect the area of interest. Within this study, an application of a technique for the reconstruction of missing data called DINEOF (data interpolating empirical orthogonal functions) is analysed, with the aim of testing its applicability in operational SST retrieval during summer months. In this case study, the Bay of Biscay is used as the target area. Three months of SST Moderate Resolution Imaging Spectroradiometer (MODIS) images, ranging from 1 May 2006 to 31 July 2006, were used. The main objective of this work is to test the overall performance of this technique, under potential operational use for the support of the fleet during the summer fishing season. The study is designed to analyse the sensitivity of the results of this technique to several details of the methodology used in the reconstruction of SST, such as the number of empirical orthogonal functions (EOFs) retained, the handling of the seasonal cycle or the length (number of images) of the SST database used. The results are tested against independent SST data from International Comprehensive Ocean–Atmosphere Data Set (ICOADS) ship reports and standing buoys and estimations of the error of the reconstructed SST fields are given. Conclusions show that over this area three months of data are enough for efficient SST reconstruction, which yields four EOFs as the optimal number needed for this case study. An extended EOF experiment with SST and SST with a lag of one day was carried out to analyse whether the autocorrelation of the SST data allows better performance in the SST reconstruction, although the experiment did not improve the results. The validation studies show that the reconstructed SSTs can be trusted, even when the amount of missing data is very high. The mean absolute deviation maps show that the error is greatest near to the coast and mainly in the upwelling areas close to the French and north-western Spanish coasts.

Investigation of a 1000-MW smoke plume by means of a 1.064 μm lidar. II: Determination of diffusion characteristics of the plume particles

A mobile 1.064-μm monostatic lidar was used to study the carbon aerosol particles from a 1000-MW oil-burning system. After part I, describing the lidar calibration procedure from airborne measurements and lidar vertical shots on the ambient aerosol, this paper presents the determination of the field of C particle concentrations in order to study the plume characteristics, such as particle concentration, plume trajectography and dispersion parameters … The method proposed allows the retrieval of particle concentrations in amounts comparable with those measured by direct instrumentation and the verification of the classical diffusion laws as established by, for example, Briggs, in nearly neutral meteorological conditions. In particular, for maximum concentration zone as revealed by the automatic scanning procedure of the lidar system, the plume height Z is related to the ambient wind speed U and the horizontal distance X from the source by the expression Z = C1 F130U−1X13. Finally, the high particle concentration zone, localized upwind, is revealed as the most active one both dynamically and thermodynamically, where more than 80% of the vertical transfer fluxes are accomplished.

Using neural networks for short-term prediction of air pollution levels

The present paper focuses on the prediction of hourly levels up to 8 hours ahead for five pollutants (SO2, CO, NO2, NO and O3) and six locations in the area of Bilbao (Spain. To that end, 216 models based on neural networks (NN) have been built. The database used to fit the NNs has been historical records of the traffic, meteorological and air pollution networks existing in the area corresponding to year 2000. Then, the models have been tested on data from the same networks but corresponding to year 2001. At a first stage, for each of the 216 cases, 100 models based on different types of neural networks have been built using data corresponding to year 2000. The final identification of the best model has been made under the criteria of simultaneously having at a 95% confidence level the best values of R2, d1, FA2 and RMSE when applied to data of year 2001. The number of hourly cases in which due to gaps in data predictions have been possible range from 11% to 38% depending on the sensor. Depending on the pollutant, location and number of hours ahead the prediction is made, different types of models have been selected. The use of these models based on NNs can provide Bilbaos air pollution network originally designed for diagnosis purposes, with short-term, real time forecasting capabilities. The performance of these models at the different sensors in the area range from a maximum value of R2=0.88 for the prediction of NO2 1 hour ahead, to a minimum value of R2=0.15 for the prediction of ozone 8 hours ahead. These boundaries and the limitation in the number of cases that predictions are possible represent the maximum forecasting capability that Bilbaos network can provide in real-life operating conditions.

Investigation of a 1000 MW smoke plume by means of a 1.064 μm lidar—I. Lidar calibration procedure from in situ aerosol measurements and vertical lidar shots

Abstract From airborne measurements on various days, average size distributions of natural aerosol particles for different heights were obtained at our rural experimental site. Using different aerosol refractive indices and a mean particle size distribution, the backscattering and extinction coefficients β and α were computed for a 1.064 μm wavelength. Assuming the mean refractive index of the aerosol particles over a rural site as equal to 1.5−0.005 i and taking into account size and concentration distributionsof aerosol particles with height, a vertical profile of atmospheric returns from the 1.064 μm laser radiation from the ground has been computed as characteristic of the site. From numerous lidar shots on various days, an average vertical profile of lidar returns was also obtained as characteristic of both the experimental site and the whole lidar system using a laser wavelength of 1.064 μm. The relationship between the atmospheric returns and lidar signals could then be set up and used as the calibration function of the lidar. In this way, distributionsof particle concentration could be monitored from lidar shots.

Wave Energy Forecasting at Three Coastal Buoys in the Bay of Biscay

In 2008, the first commercial wave farm came online in Portugal. As with other types of renewable energy, the electricity obtained from waves has the drawback of intermittency. Knowing a few hours ahead how much energy waves will hold can contribute to a better management of the electricity grid. In this work, three types of statistical models have been used to create up to 24-h forecasts of the zonal and meridional components of wave energy flux (WEF) levels at three directional buoys located off the coast in the Bay of Biscay. Each models performance has been compared at a 95% confidence level with the simplest prediction (persistence of levels), along with the forecasts provided by the physics-based WAve Modeling (WAM) wave model at the nearest grid point. The results indicate that for forecasting horizons between 3 and roughly 16 h ahead, the statistical models built on random forests (RFs) outperform the rest, including WAM and persistence.

Multi-objective environmental model evaluation by means of multidimensional kernel density estimators

We propose an extension to multiple dimensions of the univariate index of agreement between Probability Density Functions (PDFs) used in climate studies. We also provide a set of high-performance programs targeted both to single and multi-core processors. They compute multivariate PDFs by means of kernels, the optimal bandwidth using smoothed bootstrap and the index of agreement between multidimensional PDFs. Their use is illustrated with two case-studies. The first one assesses the ability of seven global climate models to reproduce the seasonal cycle of zonally averaged temperature. The second case study analyzes the ability of an oceanic reanalysis to reproduce global Sea Surface Temperature and Sea Surface Height. Results show that the proposed methodology is robust to variations in the optimal bandwidth used. The technique is able to process multivariate datasets corresponding to different physical dimensions. The methodology is very sensitive to the existence of a bias in the model with respect to observations. The performance index based on the area under two PDFs is extended to several dimensions.The evaluation of the performance of models can be done for several variables, resulting in a single skill score.A fast and parallel implementation that allows to apply the method with highly dimensional problems is presented.The method is illustrated with two case-studies.The sensitivity of the results to the bias between models and observations or the bandwidth is presented.

Comparison of the Main Features of the Zonally Averaged Surface Air Temperature as Represented by Reanalysis and AR4 Models

The ability exhibited by seven coupled global climate models of the Climate Model Intercomparison Project 3 used in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change to simulate the meridional profiles of the current daily zonally averaged surface air temperature (ZASAT) is analysed. The expansion in the second order of these profiles of the zonally averaged surface air temperature by Legendre polynomials was compared to the same expansion carried out over the profiles provided by European and American reanalysis from 1961 to 1998. According to the theoretical support provided by the one-dimensional energy balance models, the Legendre coefficients corresponding to the ZASAT profile can be qualitatively interpreted as the independent modes that represent the meridional energy flux from the equator to the poles. Three models may be considered as the models that best reproduce the meridional structure of current zonally averaged surface air temperature although the differences between the models are not really large.