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Atmospheric Modeling

The local environment modifies the conditions in the thin air stratum above the ground, generally referred to as the atmospheric boundary layer. As humans alter the character of the natural landscape in the city-building process, they affect and impact local energy exchanges that take place within the boundary layer. The end result from this modification of the landscape influences the local (microscale), mesoscale, and potentially even the macroscale climate. That is why it is important to run atmospheric models which include urban area data (surface type, surface temperature, surface terrain). Meteorological models are designed to simulate atmospheric processes of various spatial and temporal scales. The models used in urban heat island mitigation simulations are of mesoscale extent, on the order of 300 x 300 km, with increased differentiation around areas of interest, e.g., urban areas or regions where surface modifications are assumed to occur.

Over the years, the Lawrence Berkley National Laboratory (LBNL) has developed, obtained, updated, and used several advanced computer models and tools to simulate the meteorological and air quality impacts of various surface-change and urbanization scenarios. In recent years, LBNL has modified these models to utilize input from remotely-sensed data, (e.g., satellite or aircraft data) more effectively, in an effort to better differentiate between urban and non-urban land uses and land covers, and improve upon the simulation of changes in surface properties such as urban albedo and afforestation. LBNL has also developed several parameterizations to enhance the simulation of processes of interest to urban heat island mitigation, (e.g., cooling in vegetative canopies). The updated models were used in a variety of applications to simulate meteorological conditions for any region in the U.S. (and the world) and for any particular time or scale.

Typical input to meteorological models includes a description of the initial weather conditions, related boundary conditions as the weather system evolves, and a detailed description of the surface. The latter includes topography, water surfaces, vegetation, albedo, roughness, and other thermophysical properties such as density, specific heat, thermal diffusivity, and so on. The surface albedo and vegetation fraction are best characterized through the use of remotely-sensed data. For the UHIPP (Urban Heat Island Pilot Project), LBNL uses AVHRR or Landsat Thematic Mapper (TM) and Multispectral Scanner (MSS) satellite data to develop gridded input fields of albedo and vegetation cover to the mesoscale meteorological models. Part of this data will be obtained and transferred to LBNL by NASA. In addition, LBNL relies on land-use/land-cover (LULC) data to further characterize the surface and develop urban heat island mitigation schemes for albedo and vegetative cover. Observational data from regional meteorological-stations networks are used to drive the models and test the validity of the results to establish the model's performance.

Typical output from meteorological models includes four-dimensional (space and time) fields of variables such as air temperature, moisture, wind speed, wind direction, boundary-layer heights, and so on. For the purpose of urban heat island mitigation modeling, the most important output variable to examine is air temperature. This variable is critical in identifying urban heat islands (if any) and assessing the energy-use and air-quality benefits of urban heat island mitigation strategies (e.g., through effects of reduced air temperature).

Additional Information - LBNL

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Last Updated: August 5, 1999