A NUMERICAL MODEL-BASED METHOD FOR ESTIMATING WIND SPEED REGIME IN OUTDOOR AND SEMI-OUTDOOR SITES IN THE URBAN ENVIRONMENT

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1 Proceedings of the 13 th International Conference on Environmental Science and Technology Athens, Greece, 5-7 September 2013 A NUMERICAL MODEL-BASED METHOD FOR ESTIMATING WIND SPEED REGIME IN OUTDOOR AND SEMI-OUTDOOR SITES IN THE URBAN ENVIRONMENT CHARALAMPOPOULOS* I., TSIROS* I., CHRONOPOULOU-SERELI* A., AND MATZARAKIS** A. *Lab. of General and Agricultural Meteorology, Agricultural University of Athens, Iera Odos 75, 11855, Athens, Greece **Chair of Meteorology and Climatology, Alberts-Ludwigs-University Freiburg, Hebelstr.27, D Freiburg, Germany ABSTRACT The wind speed is a substantial parameter for the assessment of the urban microclimatic conditions and the human thermal comfort which formed in open space. The estimation of this factor, especially at pedestrian level, is often inaccurate or inexplicit due to the complexity of the environment. The present study deals with a methodology for wind speed estimations in urban outdoor sites. The methodology is implemented in the ENVImet 3D micro-scale boundary layer urban microclimatic model. The model adopts microscale numerical simulation of surface plant air interactions inside open spaces, especially the feedback between artificial surfaces like buildings and vegetation inside street canyons or greens areas. It can then simulate hard wind field modifications (solid boundaries) like walls as well as soft modifications (porous shelters) like vegetation. The proposed methodology combines simulation results with simple regression models. The output of the proposed methodology is a specific mathematical function that relates wind speed values recorded at a reference meteorological station to wind speed values at selected adjacent sites. The focal point of this methodology is the accuracy of such a non-hydrostatic incompressible Navier Stokes equations model for reproducing the aerodynamic effects of trees, buildings and other obstacles in the urban environment based on the prediction of wind environment at pedestrian level. For the purposes of the study, various urban design configurations were considered in the simulation procedure including a building atrium, an atrium with vegetation and a vegetated open site. The output regression functions indicate striking correlation between measured and estimated values of the wind speed with R 2 > 0.9 for all the examined urban design configurations. In addition, results indicate that there is a new ability of overcoming the difficulties on estimating the wind speed near the ground, utilizing reliable 3D microclimatic numerical models. KEYWORDS: Wind speed estimation, urban environment, outdoor site, semi-outdoor site, numerical model 1. INTRODUCTION The thermal comfort and bioclimate of human beings depends on several meteorological parameters (Mayer and Höppe, 1987., Fröhlich and Matzarakis, 2013., Charalampopoulos et al., 2012). According to Mayer (1993), some of these parameters are strongly influenced by the surroundings [e.g., wind speed and the different radiation fluxes that strongly influence thermal bioclimate (Matzarakis 2001)]. Therefore the

2 knowledge of the input parameters for thermal comfort estimation is very important and has to be dealed carefully and appropriate. The most common problem biometeorologists are faced with is the lack of in-situ data, especially wind speed. This is mainly due to the fact that the only equipment sensitive enough to record accurately winds speed below 1.5 m s -1 (typical values for the urban environment) are the ultrasonic anemometers. In view of such lack of enough data, several assumptions need to be considered in both microclimate (e.g. Shashua-Bar et al., 2010) and bioclimate ansalysis (e.g. Shashua-Bar et al., 2012). In addition, even in cases where appropriate instrumentations available, it is not frequent to find available and safe place to mount the appropriate equipment at pedestrian level (Johnson and Hunter, 1998.; Blocken and Carmeliet, 2004.; Finnigan et al., 2007). The need of expertised installment and the high cost of the ultrasonic anemometer, drive to implementation of computational methods via computational fluid dynamics (CFD) software. The methodology that is introduced in this study is a simplified approach for utilizing wind speed data derived by simulations using ENVI-met software. 2. STUDY AREA AND SELECTED SITES For the purposes of this study, six outdoor sites were selected. Those sites are located in the Agricultural University of Athens (AUA) campus (37 o 59 N, 23 o 42 E, and 36 m altitude) in the western part of Athens. The campus is almost 26 ha covered by buildings for education and research as well as green areas (gardens, experimental crops and arboriculture). The criteria for site selection were site s configuration (the proportion of green coverage and built area, the type of vegetation and the geometry of the nearby obstacles). More specifically: Site 1 (k1) is located inside the automatic meteorological station of Agricultural University of Athens in a planar area free of vegetation and other obstacles like buildings and trees. In this site, a fully equipped automatic meteorological station is mounted which records the wind speed at 1.5 m above the ground. This site will be the reference for the purpose of this study. Site 2 (k2) is in the middle of an open atrium of a 10-m-height building constructed of concrete; the atrium shape reduces significantly the sunshine duration at k2. Site 3 (k3) is located inside the AUA botanical garden in a green atrium with ground irrigated grass and the surrounding trees to reach almost 10 m height. Site 4 (k4) is in the middle of the experimental arboricultural field of AUA. The fifth site (k5) is inside a small park, with medium height (~3 m) and linear planted trees. Finally, site 6 (k6) is in sparse vegetated garden in front of a wide and medium height (10 m) building. 3. CFD Model Overview For the purpose of this study, the 3D micrometeorological model ENVI-met, version 3.1, was used. The model is a CFD (computational fluid dynamics) application capable to reproduce the major processes in the atmosphere that affect the microclimate, including the simulation of wind flows, turbulence, radiation fluxes, temperature and humidity, on a well-founded physical basis (i.e. the fundamental laws of fluid dynamics and thermodynamics). The model simulates the microclimatic dynamics within a daily cycle (or other time span) in complex structures, i.e. buildings with various shapes and heights as well as vegetation. Its high spatial and temporal resolution enables a fine understanding of the microclimate at street level. Important advantages of this model are the adequate and detailed representation of the surface exchanges since the vegetation and soil are treated in a multi-layer configuration, and also the possibility of using small horizontal and vertical grid boxes down to 1-m size (Samaali et al., 2007). A full description of the model and the equations are given in (Bruse and Fleer, 1998).

3 4. RESULTS AND DISCUSSION 4.1 Numerical results In order to achieve higher spatial resolution, each separate specific site s model was appropriately represented in the model. The site s model consists of position and height of buildings, position and leaf area of plants, distribution of surface materials and soil types, geographic position of the location on earth. Then, for each site s configuration the model employed for more than 400 initial atmospheric conditions. More specifically, the model was run for initial wind speed from 0.1 m s -1 to 5.0 m s -1 (increment step 0.1 m s -1 ) and for each direction from 0 o to 360 o (increment step 45 o ). The wind speed spatial distribution for each case study can then be evaluated. An illustrative example is given in figure 1. Figure 1. Wind speed spatial distribution over the site k2 and the sampling pair (reference site k1 and the building atrium k2). Finally, numerical data sampling was performed, i.e., for each wind speed spatial distribution a pair data (reference site and the selected site 1 ) was selected. Thus, for every site s pair, a two-column data file was created respectively. The first column includes the wind speed value at the reference site (k1) and the second one, the corresponding wind speed at the selected site. 4.2 Regression analysis results Regression analysis was performed to provide estimates of the wind speed at the selected sites (k2,k3,k4,k5,k6). Calculations were separated in sampling numerical pairs (k1 vs k2, k1 vs k3, k1 vs k4, k1 vs k5, k1 vs k6). The criteria for choosing the appropriate equation type (linear, polynomial etc), derived by the regression analysis, were the value of R 2 and the physical meaning of the derived equations. The calculation process is shown in figure 2. 1 Selected sites are k2,k3,k4,k5,k6

4 Figure 2. Workflow diagram. Table 1 shows the statistics of the regression results whereas in figures 3, 4 and 5 the regression are presented for the various sites as scatterplots. As shown in Table 1, in order to describe the wind speed mathematical relationship between the reference site (k1) and the building atrium (k2) the most appropriate equation was found to be a 4 th order polynomial equation. The building atrium tents to behave as a solid wind-barrier and the main air motion inside this area is a function of turbulence. This behavior depicted more clearly in figure 3. Table 1. The regression analysis results Description Equation R 2 k1 vs k2 y= x x x x + k1=x, k2=y R²=0.982* k1 vs k3 k1=x, k3=y y= x k1 vs k4 k1=x, k4=y y= x k1 vs k5 k1=x, k5=y y= x k1 vs k6 k1=x, k6=y y= x *=Significant at p<0.05 R²=0.995* R²=0.997* R²=0.995* R²=0.997* As figures 4&5 illustrate, the appropriate equations for the description of the relation between references site (k1) and the selected sites (k4, k5 and k6), are linear. Those sites are planted with medium-height trees, thus the most effective wind modifications caused by porous shelters. The absence of solid boundaries (buildings) leads to present a striking linear pattern in sites k3 to k6. The sparse planted sites (k4 and k6) seem to have a narrow distribution as the scatterplots illustrate (fig. 4B and fig. 5B). On the other

5 hand the densely planted sites (k3 and k5) present widely spread scatterplots as a function of increased turbulence (fig. 4A and fig. 5A). Figure 3. Scatter plot of the wind speed values at the reference site (k1) and at the building atrium (k2). A B Figure 4. A: Scatter plot of the wind speed values at the reference site (k1) and at the green atrium (k3). B: Scatter plot of the wind speed at the reference site (k1) and at the experimental arboricultural field (k4). A B Figure 5. A: Scatter plot of the wind speed at the reference site (k1) and at the small park (k5). B: Scatter plot of the wind speed at the reference site (k1) and at the garden (k6).

6 5. CONCLUDING REMARKS AND FUTURE STEPS The simple equations derived by the proposed numerical-based methodology, may be considered as alternatives to overcome the strong difficulties of estimating the wind speed at pedestrian level, especially in urban sites with complexities. The proposed methodology is simple and easily applicable. Moreover, having the final equations derived, the estimation of the wind speed distribution is fast and focused on each selected site. A future study should focus on the validation of the modeled results against experimental data. Such a study is underway for all of the examined sites using an ultrasonic anemometer under various weather conditions. It is expected that the main parameters for model calibration are the grid size, the Leaf Area Density (LAD) profile and the initial roughness Length z0 at reference point. REFERENCES 1. Blocken B. and Carmeliet J. (2004) Pedestrian Wind Environment around Buildings: Literature Review and Practical Examples, Journal of Thermal Envelope and Building Science 28(2): Bruse M. and Fleer H. (1998) Simulating surface-plant-air interactions inside urban environments with a three dimensional numerical model, Environmental Modelling and Software 13(3-4): Charalampopoulos I., Tsiros I., Chronopoulou-Sereli A., Matzarakis A. (2012). Analysis of thermal bioclimate in various urban configurations in Athens, Greece, Urban Ecosystems: DOI /s Finnigan J. (2007). The turbulent Wind in Plant and Forest Canopies. Plant Disturbance Ecology. Burlington, Academic Press: Fröhlich D. and Matzarakis A. (2013) Modeling of changes in thermal bioclimate: examples based on urban spaces in Freiburg, Germany, Theoretical and Applied Climatology 111(3-4): Johnson G. and Hunter L. (1998) Urban wind flows: wind tunnel and numerical simulations-- a preliminary comparison, Environmental Modelling and Software 13(3-4): Matzarakis A. (2001) Die thermische Komponente des Stadtklimas. Ber. Meteorol. Inst. Univ. Freiburg Nr Mayer H. (1993) Urban bioclimatology, Experientia 49(11): Mayer H. and Höppe P. (1987) Thermal comfort of man in different urban environments, Theoretical and Applied Climatology 38(1): Samaali M., Courault D., Bruse M., Olioso A., Occelli R. (2007) Analysis of a 3D boundary layer model at local scale: Validation on soybean surface radiative measurements, Atmospheric Research 85(2): Shashua-Bar L., Tsiros I. and Hoffman M. (2010) A modeling study for evaluating passive cooling scenarios in urban streets with trees. Case study: Athens, Greece, Building and Environment 45(11): Shashua-Bar L., Tsiros I. and Hoffman M. (2012) Passive cooling design options to ameliorate thermal comfort in urban streets of a Mediterranean climate (Athens) under hot summer conditions, Building and Environment 57: