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
Return to Urban Studies
Responsible Official: Dr. Steven J. Goodman (steven.goodman@nasa.gov)
Page Curator: Diane Samuelson (diane.samuelson@msfc.nasa.gov)
Last Updated: August 5, 1999
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