Geoscience Reference
In-Depth Information
Chapter 5
Assessing and Modeling the
Urban Climate in Lisbon
5.1. Introduction
Cities cover less than 1.5% of the Earth's land surface. However, urban
populations are currently growing at a much faster rate than the population as a
whole, particularly in developing countries. Furthermore, mega-cities (with
populations of 10 million or more) have brought about serious environmental
problems [BRI 06]. The climate of a city depends on regional and local geographic
characteristics, such as latitude, distance from water bodies, altitude, and
topography, among others. Conversely, urban areas have a strong influence on
natural environment, including climate, by modifying radiative, thermal, moisture
and aerodynamic pre-existent characteristics. Consequently, there is a great variety
of urban climates and a vast number of local and microclimates within each city,
depending on air composition, urban morphology, and land cover (including the
presence of green areas and water bodies). Urban climate casts an imprint on the
surrounding areas, particularly downwind, but the influence of cities on “global”
changes should be brought to attention as a considerable amount
of
greenhouse
gases (GHG) are emitted in the urban environment [GRI 06a; ALC 08].
According to Oke [OKE 06a] there are several “modes” of research or practice
employed by those involved in urban climate studies: 1) conceptualization; 2)
theorization; 3) field observation; 4) modeling (statistical, scale, and numerical); 5)
validation of models; 6) applications in urban design and planning; 7) impact
assessment (post-implementation); 8) policy development and modification.
Geographical Information Systems (GIS) are useful tools for different phases and
levels of the research and application. This chapter will deal with the importance of
geographical “support” in the correct monitoring of urban climate features (mode 3),
in modeling parameters of urban climate at the meso and microscale and in
validating some parameters (4 and 5). The objectives of these studies are to help
implementing modes 6, 7, and 8.
