Characterization of wind fields at a regional scale calculated by means of a diagnostic model using multivariate techniques M.L. Sanchez, M.A. Garcia, A. Calle Laboratory of Atmospheric Pollution, Dpto ABSTRACT In the framework of an extensive programme on photochemical and acidifying regional transport sponsored by the Spanish CICYT Commission, a calculation of the wind fields using an algorithm of interpolation has been applied to the Region of Castile and Leon. Based on the observational data recorded at 10 surface meteorological stations from the I.N.M. in 1990, 158 daily wind fields at 12.00 G.M.T. were calculated in a 20*20 Km grid covering all the Region. In order to establish the prevailing transport of pollutants and to identify the influence of the topographical features under different synoptic situations, a relationship between wind fields and the regional weather patterns was perfomed using a multivariate clustering technique. A satisfactory correspondance between mesoscale circulation flows and specific synoptic situations has been obtained. This paper presents the most common atmospheric mesoscale flows prevailing in the winter and summer period and shows the influence of the topographical features on the wind fields at a regional scale. 1.-INTRODUCTION It is clear from a large number of studies the significance of long range transport of air pollutants in the acidification of natural echosystems. Because of the regional nature of the problem, the assesment of source receptor relationships required for abatement control strategies cannot only derived from observational data. Mesoscale models are useful tools to evaluate quantitatively the impact of emissions on receptors and which precursors have to be reduced by what percentage in order to achieve desired acceptable levels of air quality. Mesoscale models have extensive requirements, such as grided meteorological data, with special emphasis on the determination of wind fields. A great deal of hydrostatic, non-hydrostatic and empirical models based on interpolation algorithms are described in the literature, e.g. Pielke [1]. Among all of them, the latest models are attractive because of their simplicity and they are commonly used as diagnostic models for describing transport of pollutants at a regional scale.
58 Computer Simulation The Region of Castile and Leon is a plateau surrounding by mountains acting as constraining barriers to air mass movements. The surface meteorological network from the INM is extensive since it consists of 10 stations distributed in the Region. Both characteristics offer suitable conditions for the application of interpolation algorithms to determine wind fields. In this paper a diagnostic model based on a interpolation scheme has been applied to calculate the wind fields at a regional scale. The reliability of mesoscale flows obtained under the most common synoptic meteorological situations has been analyzed using multivariate techniques. These statistical techniques are suitable tools for visualization and classification of data and they have been used for different environmental problems with satisfactory results, e.g. Sanchez et al. [2]. In order to establish a relationship between surface mesoscale circulation flows and synoptic atmospheric flows, 158 wind fields at 12 G.M.T., covering winter, spring and summer period of 1990 were calculated. In this study hourly wind speed in the 10 surface meteorological stations and variables related to 850 and 500 hpa contours were chosen and their interdependence was analyzed by means of a divisive Q-clustering algorithm based on the K-means principle. The selected algorithm has the advantage of offering two simultaneous ways to interpret the results. It gives the composition of the variables belonging to each cluster and also information can be obtained about the common attributes of the observations that form each cluster. Therefore, the cluster analysis may contribute to an easier identification of wind fields associated to synoptic atmospheric flows by examining the days belonging to each cluster, and moreover, a quantitative description of their main features can be achieved by analyzing the centroids or mean values of each variable in every cluster. The application of the cluster analysis has permitted us to describe the most common mesoscale wind flows linked to synoptic circulation flows. The purpose of this paper is to present and discuss the most common surface wind flows in the Region, with particular emphasis to the winter and summer seasons. 2.- DATA AND PROCEDURE 2.1.- Meteorological variables The grid considered, covering an extension of 100,800 knf is shown in Figure 1. The Figure also shows the most relevant topographical features and the location of the surface meteorological stations from the INM in the Region. The concurrent observational data in all the stations consisted of wind direction, wind speed and temperature at each 10 min. The data used in this paper are related to the mean hourly values recorded at 12.00 G.M.T. The considered variables include surface wind speed recorded at each meteorological station and variables for the description of the main features of the 850 and 500 hpa contours taken from the Spanish Meteorological National Bulletin.
Computer Simulation 59 Figure 1: Geographic main features and the location of the network of surface meteorological stations. 2.2.- Description of the Diagnostic wind field model The interpolation algorithm chosen to determine wind fields, calculates the wind speed in each grid cell, introducing a weight factor that is inversely proportional to the distance squared, r% between the station in a grid cell and the rest of the meteorological stations. 2.3.- Description of the clustering technique and procedure As we pointed out earlier, the relationship between synoptic situations and mesoscale flows has been established using the K-means divisive cluster. The basis of this algorithm has already been described in a previous paper by Sinchez and Ramos [3]. The objetive of divisive cluster analysis is to separate a set of objects into groups, so that the members of any group differ from one another as little as possible. K-means algorithm starts from a given partition specified by the assignment vector P(K,M), with the M observations (days) allocated to K clusters. In a stepwise manner, the algorithm separates the observations trying to find their optimal location, transferring observations between clusters and looking for the final assignment. The key of the division of the observations into the different clusters is the function error, e, defined as equation (1): e[p(m,k)] = ]T D[I, L( I) ] ^ /]\ where L(I) is the cluster containing the Ith case. D(I, L(I)/ represents the sum of the squared absolute deviations from the cluster centroid (median for each of the variables), over all the observations in the cluster and over all the variables. The number of clusters to be retained has been chosen by analyzing the values of the error function for an increasing number of clusters. Based on the analysis of the function error, six clusters were retained. The centroids, or mean values of each variable in each cluster (C1-C6), are shown in Table 1: The first column shows the variables chosen; Stl-StlO refers to the wind speed (m s') at each meteorological station; h850, t850, h500, and t500 correspond to the height (m) and temperature ( C) of 850 and 500 hpa
60 Computer Simulation contours respectively; and in the last column, the average of the wind speed (m s"*) in each station and other variables of the overall observations, 'Aver' is included. To facilitate the interpretation of the results, we have also written the percentage of observations of the winter (W), spring (SP) and summer (S) seasons. Table 1. Results obtained in each cluster. Van Stl St2 SO St4 St5 St6 St7 St8 St9 StlO h850 t850 h500 t500 %W %SP %S Cl 2.48 2.69 2.23 4.63 3.05 2.20 4.05 2.00 3.87 2.42 1482.33 4.86 5601.98-21.36 25 75 - C2 2.17 2.64 2.01 4.37 2.59 1.86 3.54 1.81 2.42 2.47 1523.63 10.44 5752.20-15.44 14 31 55 C3 5.42 5.99 6.71 8.46 7.09 5.24 10.00 4.69 5.75 5.99 1481.46 3.53 5609.07-20.17 65 35 - C4 2.39 2.62 1.73 3.27 2.58 1.34 2.85 1.31 2.79 2.17 1555.37 17.15 5854.10-10.70 _ - 100 C5 1.08 1.65 0.98 3.86 2.13 1.34 2.14 0.50 2.17 1.83 1587.10 7.29 5764.15-17.87 92 8 - C6 2.53 3.83 4.13 6.21 7.26 3.75 7.06 2.60 3.19 4.27 1540.42 6.92 5720.90-16.83 39 48 13 Aver 2.66 3.10 2.67 4.83 3.75 2.39 4.53 1.99 3.21 2.96 1531.11 8.82 5725.76-16.82 35 37 28 3. RESULTS Cluster 1 mainly contains observations from the spring period, characterized by low temperatures at surface, 850 and 500 hpa contours and topography heigths. Concerning the wind speed recorded at each station, the centroid represents the general feature of the overall data in the Region quite well. The most frequent regional synoptic class at 500 hpa contour which corresponds to a trough located at the NE or E of the Iberian Peninsula is shown in Figure 2a. The typical wind flow circulation, depicted in Figure 2b, shows the effect of Iberic System mountains acting as constraining barriers to the north-south movements of air masses and producing channeling effects at southern Region. Strong winds are recorded in the plateau and in the southwest of the Region where the orography favours the channeling effects. On the contrary, blocking effects on wind speed blowing in the areas located downwind or upwind of the
Computer Simulation 61 major mountains (Stations 2,6,8,10) are visualized. Cluster 2 corresponds to the similar situation for the late spring and summer season. Figure 2a: 500 hpa contour chart at 12 G.M.T. on 27 March 1990. Figure 2b: Wind field at 12 G.M.T. on 27 March 1990. Cluster 3 basically links observations from the winter characterized by low temperatures and strong winds in the Region. The most common synoptic situation corresponds to north troughs located at the north or northwest of the Iberian Peninsula, which is shown in Figure 3a. The north-south meridian circulation of cold maritime or polar air masses usually produces a generalized atmospheric instability in the Region giving as result precipitations. The typical mesoscale wind flow, depicted in Figure 3b, shows similar constraining barrier, blocking and channeling effects to those described in the previous cluster.
62 Computer Simulation Figure 3a: 500 hpa contour chart at 12 G.M.T. on 6 April 1990. Figure 3b: Wind field at 12 G.M.T. on 6 April 1990. Clusters 4 and 5 contain summer and winter observations respectively. Extreme high and low temperatures respectively as well as prevailing slight winds in the Region are their mean features. Figures 4a and 4b show one of the most common synoptic meteorological situation at the surface level during the summer period and the corresponding mesoscale wind field. The observation of Figure 4a clearly shows an thermal low over the Iberian Peninsula. The thermal low is one of the mesoscale effects prevailing in the Iberian Peninsula from the spring to the autumn as a consequence of the diurnal extension of the African semi-permanent low pressure system and its effects are described in detail by Millan et al. [4]. The case studied and presented in this paper corresponds to a low pressure located in the northwest of Spain, which lead to a maximum temperature of 40
Computer Simulation 63 oc in the inland of the Region of Galicia. The most relevant feature of the wind fields is the convergence of air masses towards the thermal low center giving as a result the transport of pollutants from the northeast to the west in the Region of Castile and Leon. Similar efects were observed when the thermal low center was located in central Spain playing an important contribution to intensify the sea breeze regime in Portugal, e.g. Moussiopoulos [5]. This situation presents a clear contrast with that obtained under slow synoptic winds in the winter period where wind flows are governed by the orographical features. Figure 4a: Surface pressure chart showing the thermal low at 12 G.M.T 19 August 1990. on Figure 4b: Wind field at 12 G.M.T. on 19 August 1990.
64 Computer Simulation Finally, the last cluster mainly groups spring and winter observations corresponding to interactions between atlantic and continental ridges and troughs to the west and atlantic anticyclones with a westerly zonal circulation flow in the north of the Iberian Peninsula. The obtained wind flows associated with this cluster correspond to those presented in the first and second synoptic situations and in spite of the slowest wind speed recorded at a regional scale, they do not add any additional noticeable information. 4.- MAIN CONCLUSIONS The reliability of the diagnostic model to calculate mesoscale wind fields under typical synoptic atmospheric situations has been proven throughout simulation cases obtained with strong synoptic winds blowing from the NE and SW at a regional scale. Major mountains, such as Cantabric, Iberic and Central systems act as constraining barriers to the meridian circulation and generate blocking and channeling effects in the surrounding area of the plateau. This result emphasizes the importance of controlling acidic compounds and photochemical oxidants in the Region of Castile and Leon in order to describe the contribution of transboundary pollutants coming from Europe and its possible impact on the main forested areas located at the Iberic and Central systems. The importance of the iberian thermal low on the field winds during the summer period has also been well described, demostrating the important effect of air convergence at the surface towards the thermal low center. This result also has interesting consequences for the interregional transport of pollutants coming from the industrialized area and the power stations located in Northern Spain. ACKNOWLEDGMENTS This paper has been funded by the C.I.C.Y.T., and the regional government of Castile and Leon, to whom the authors wish to express their gratitude. We would also like to thank The Duero Regional Meteorological Centre which supplied the meteorological data to carry out this study. REFERENCES 1. Pielke A. Mesoscale Meteorological Modeling. Academic Press Inc, London, Ltd., 1984. 2. Sanchez M.L., Pascual D., Ramos C. and Perez I. 'Forecasting paniculate pollutant concentrations in a city from meteorological variables and regional weather patterns.' Atmos. Environ., 24A, 1509-1519,1991. 3. Sanchez M.L. and Ramos C. 'Application of cluster analysis to identify sources of airborne particles.' Atmos. Environ. 21, 1521-1527,1987. 4. Millan M.M., Artinano B., Alonso L., Navazo M. and Castro M. The effect of meso-scale flows on regional and long-range atmospheric transport in the western mediterranean area.' Atmos. Environ., 25A, 949-963,1991. 5. Moussiopoulos N.'Air Pollution Modeling in Southern Europe.' Proceedings of the Eurotrac Symposium'94. Garmisch-Partenkirchen, 11-15 April, 1994.