Sensitivity analysis of the different land surface parameterization
available in the WRF model
Abstract
One of the challenges in the numerical weather models is the adequate
representation of soil-vegetation-atmosphere interaction at different
spatial scales, including scenarios with heterogeneous land cover and
complex mountainous terrain. The interaction determines the energy, mass
and momentum exchange at the surface and could affect different
variables including precipitation, temperature, and wind. In order to
quantify the long-term climate impact of changes in local land use and
to assess the role of topography, two numerical experiments were
examined. The first experiment allows assessing the continuous growth of
urban areas within the Aburrá Valley, a complex terrain region located
in Colombian Andes. The Weather Research Forecast model (WRF) is used as
the basis of the experiment. The basic setup involves two nested
domains, one representing the continental scale (18 km) and the other
the regional scale (2 km). The second experiment allows drastic
topography modification, including changing the valley configuration to
a plateau. The control run for both experiments corresponds to a
climatological scenario. In both experiments, the boundary conditions
correspond to the climatological continental domain output. Surface
temperature, surface winds, and precipitation are used as the main
variables to compare both experiments relative to the control run. The
results of the first experiment show a strong relationship between land
cover and the variables, especially for surface temperature and wind
speed, due to the strong forcing land cover imposes on the albedo, heat
capacity and surface roughness, changing temperature and wind speed
magnitudes. The second experiment removes the winds spatial variability
related to hill slopes, the direction and magnitude is modulated only by
the trade winds and roughness of land cover.