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In a military context, situational awareness, i.e., an understanding of how well you can see and how well you can be seen, is crucial. Turbulence degrades image quality and absorption by aerosols reduces contrast, which reduces the maximum distance at which you can see. In my research, I focus on a small-scale description of atmospheric flow processes, with emphasis on turbulence. For this, we use a series of numerical (weather prediction) tools from coarse to high resolution. This framework is used to model the dispersion of aerosols, in particular those generated at the sea surface, in the lower atmosphere while taking into account the features of the heterogeneous terrain (land-sea transition, orography, etc.). It is our ambition to understand the necessary and sufficient detail of this numerical modeling to optimize computational requirements and the physical footprint that can be handled.
Within TNO, this work is predominantly embedded within DSS but it also relates to other TNO areas: turbulence degrades the quality of (laser) communication systems, and aerosols are important to climate and air quality.
My work has primarily resulted in a better understanding of the possibilities and limitations of numerical weather codes in applications related to optical turbulence and propagation. Algorithms to generate optical parameters have been coupled to numerical weather codes. Model results are compared to experimental data that was obtained in long-term (international) field trials. This provides an “anywhere, anytime” capability in assessing situational awareness.
Specific results include a case study of sea breeze for the Quiberon region in Brittany, a refinement of the aerosol production function for the Mediterranean in terms of wave age, the compilation of turbulence intensity maps for larger areas, the description of the False Bay (South Africa) environment in terms of atmosphere and propagation, and an assessment of aerosol effects on the propagation of (high-energy) laser beams.