A baroclinic planetary boundary-layer model, and its application to the Wangara data
β Scribed by S. Venkatesh; G. T. Csanady
- Publisher
- Springer
- Year
- 1974
- Tongue
- English
- Weight
- 777 KB
- Volume
- 5
- Category
- Article
- ISSN
- 0006-8314
No coin nor oath required. For personal study only.
β¦ Synopsis
Nondimensional parameters characteristic of the outer part of the planetary boundary layer have been determined by fitting a simple, Ekman-type theory to a number of averaged, observed velocity distributions, using the Wangara data of Clarke et al. (1971). The theoretical model is based on constant eddy viscosity in the outer layer and a linear variation of the geostrophic wind with height. At the lower boundary of the outer layer, the condition is applied that stress and velocity are parallel. This yields an equation for the cross-isobar angle as a function of drag coefficient, depth coefficient and nondimensional thermal wind.
The data could be sorted into three well-defined, distinct groups, each characterized by a more or less constant value of the depth coefficient. The group with the lowest value of this parameter contains most of the nighttime data, the middle group the remaining nighttime data and most of the daytime ones, and the group with the largest depth, daytime data with cold air advection. The difference between the lowest and highest depth coefficients found here is about a factor of three. Within each group separately, the theoretically derived cross-isobar angle agrees remarkably well with the observed one, as a function of thermal wind.
Boundary-Layer
Meteorology S (1974) 459-473.
π SIMILAR VOLUMES
## Abstract The efficacy of a simple encroachment model of mixedβlayer growth is explored by simulating two disparate days of the Wangara Experiment. The inclusion of thermal winds is shown to be essential if temperature, height and vector wind of the mixed layer are to be predicted with accuracy.
## Abstract This study investigates the LargeβEddy Simulation (LES) technique in the diurnally varying atmospheric boundary layer in conditions of realistic environmental forcing. The initial settings of meteorological fields are obtained by βingestingβ into the LES domain the vertical profiles of
## Abstract We present a forecasting model based on fuzzy pattern recognition and weighted linear regression. In this model fuzzy pattern recognition is used to find homogeneous fuzzy classes in a heterogeneous data set. It is assumed that the classes represent typical situations. For each class a