MEASURING URBAN SURFACES ’ THERMAL INERTIA

Through their control on surface properties such as thermal inertia, surface roughness, and albedo, cities exert a significant impact on local climate. As a consequence, the correct representation of urban surfaces in regional-scale atmospheric models is of paramount importance, i.e., in applications such as numerical weather prediction, atmospheric dispersionmodeling, or model-based assessment of the urban effect in temperature time series used in the context of global warming studies. However, the representation of urban surfaces in these models constitutes a particular difficulty. Among the least known parameters, thermal conductivity and heat capacity are notoriously difficult to measure at the kilometer scale that is typically used in regional atmospheric models. Another poorly known quantity is the thermal roughness length, which regulates the exchange of heat between the surface and the atmosphere, becoming extremely small for surfaces constituted of so-called bluff-rough elements such as buildings. This contribution aims at reducing these knowledge gaps by retrieving the parameters mentioned above using an approach that combines satellite remote sensing and atmospheric modeling. The methodology relies on the minimization of the difference between simulated and retrieved urban surface temperature ( UST). Model simulations were carried out by means of the ARPS model, a 3-D prognostic atmospheric model that contains an advanced land surface-atmosphere exchange scheme and, the Spinning Enhanced Visible and Infra Red Imager ( SEVIRI) thermal imageries were used to retreive the UST.