Katabatic Flows and Their Relation to the Formation of Convective Clouds—Idealized Case Studies
(2012)
The formation of a convective cloud system as a result of a katabatic-induced surface cold front at the eastern Andes Mountains of South America was investigated in a numerical model study. The occurrence of this cloud system is hypothesized to be a consequence of converging cold-air drainage from slopes and valleys resulting from the concave shape of the terrain. Simplified terrain configurations were applied to three different atmospheric experiments to determine the influence of the terrain and the ambient stratification on the underlying processes. The simulation demonstrated the occurrence of a convective cloud, but not in every simulation. The initial stable stratification experiment did not initiate convective activity. Further analysis of the development of the convective cells confirmed the terrain’s impact, but it also showed a dependence on atmospheric conditions. The katabatic flows and the surface fluxes from which they are induced are sensitive to the ambient stratification, which was seen when only a weak cold front developed in response to a decrease in the surface inversion and the downslope velocity. On the basis of specific characteristics of katabatic flows and the heat-exchange budget, the presence of these flows and their significance as the driving force behind the cloud-formation process were confirmed.
A New Class of Quality Controls for Micrometeorological Data in Complex Tropical Environments
(2015)
Quality control is a particularly demanding problem for micrometeorological studies in complex environments. With the transition to electronic sensing and storage of climate data in high temporal resolution, traditional approaches of homogenization are insufficient for addressing the small-scale variability and spatial heterogeneity of the data. This problem can be successfully addressed by introducing a new class of control procedures based on the physical and climatological relations between different climate variables. The new approach utilizes knowledge about the interdependency of air temperature, precipitation, radiation, relative air humidity, cloud cover, and visibility to develop empirical functions for determining the probability margins for the co-occurrence of specific conditions in tropical mountains and deserts. It can also be applied to other geographic settings by adjusting the parameters derived from the data itself. All procedures are integrated into a processing chain with feedback loops and combined with conventional logical and statistical checks, which enables it to detect small errors that normally pass unnoticed. The algorithms are also adapted to incorporate the short time steps of the original data to retain the potential for detailed process analyses.