Simulation of Wind Field in Tehran Using Hybrid Diagnostic and Prognostic Models
M. Shafie-Pour, Y. Rashidi and M. Ardestani
DOI : 10.3844/ajessp.2008.512.521
American Journal of Environmental Sciences
Volume 4, Issue 5
This article concentrates on Wind Field Simulation in a mega city such as Tehran which is home to nearly 10 million inhabitants. The necessity of having a comprehensive knowledge about the wind field in a certain zone is significant for different reasons; the most important of all would be surveying on the emission and dispersion of pollutants. The wind models can be classified as: Dynamic and Kinematics. In this article the authors have developed a Kinematics model based on Continuity Equation. The final version of the equation being solved is a elliptic partial differential equation. The lateral boundary Conditions are first kind and those for top and bottom are the second kind. In order to initializing the model, the data gathered by two meteorological towers set up in Tehran and also the data of the upper layer atmosphere from Mehrabad Airport have been used. The result of the wind field simulation reveals when the velocity of the synoptic scale wind is low, the condition of the wind flow is entirely affected by the local system of mountain-valley. During the day, the flow is towards the valley to the mountains, while at night it is from the mountain to the valley. The local systems of wind circulation such as mountain-valley and land-sea are closed systems that trigger in removing of the pollutants, their accumulation and their chemical changes in a definite area. It should be noted that wind field simulation, by means of diagnostic (Kinematic) models, depend entirely on the existing data and considering the time we cannot forecast wind field over the observed data. The results of wind field simulation using combination of diagnostic and prognostic (Dynamic) models are significantly improved.
© 2008 M. Shafie-Pour, Y. Rashidi and M. Ardestani. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.