Characterizing the response of simulated Atmospheric Boundary Layers to stochastic cloud radiative forcingRobert Tardif, NCAR and Howard Bondell, SAMSI
The Atmospheric Boundary Layer (ABL) is defined as the layer of the lower atmosphere directly influenced by the presence of the Earth's surface. The forecasting of the diurnal evolution of conditions within the ABL (temperature, humidity and wind) is of concern in a wide spectrum of activities such as agriculture (occurrence of frost), transportation (fog formation), air quality and public safety (transport and dispersion of pollutants and contaminants) and wind energy production. The evolution of the ABL over land is determined in large part by the energy budget at the surface, involving radiative and turbulent fluxes. The temporal and spatial variability of the ABL is therefore affected by the character of surface conditions (roughness, soil moisture, etc.) and their influence on the transfer of energy from the surface to the atmosphere. Another important factor is the presence of clouds. They influence the distribution (spatial and temporal) of the available radiative energy at the surface through their modulation of incoming solar and thermal radiation. A significant variability is observed in macro and microphysical characteristics of clouds, leading to variability in radiative fluxes and therefore in the evolution of ABL properties.
This study seeks to characterize the response of the ABL to variability in the macro-physical properties of clouds (cloud height and amount of water in the cloud). The focus is on warm fair-weather clouds found above the ABL and their influence on the diurnal evolution of the wind profile. Idealized ensemble simulations of the ABL are performed with a single column model (SCM) incorporating a subset of the WRF physical parameterizations. The SCM is coupled to a stochastic model designed to represent the temporal variability in cloud properties. The stochastic model has been derived from measurements taken at the Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) in the Southern Great Plains (SGP). Individual members of the SCM ensemble are defined by different realizations of the stochastic cloud model used as input, with the statistical properties of the ensemble results providing a basis for the investigation of the ABL sensitivity to cloud radiative effects. The rationale for this research will be illustrated in the presentation and the dataset of cloud properties described. The statistical properties of fair-weather clouds and the methodology used in the design of the stochastic model will be presented. Finally, preliminary results from SCM simulations will be discussed.
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