| Summary: | The atmosphere is a complex system with an infinite number of independent variables. The best approximations of the atmosphere are made using numerical models. The use of such models provides an invaluable tool for studying the atmospheric system. In the atmosphere, narrow bands of strong winds at upper levels, called jet streams, impact the underlying large-scale weather conditions. In this Ph.D. thesis, I have studied jet stream variability from reanalyses and climate models. The regional climate model RCA4 simulations over South Asia reveal a good agreement between model results and reanalysis for jet stream representation. Lateral boundary data sources are believed to contribute to discrepancies over the mountainous regions. Currently, the weather forecasts have an upper limit of around 10 days. The atmospheric variability between 10 to 40 days is known as low frequency variability (LFV). This Ph.D. thesis also examined the LFV from a non-linear perspective, which indicated the existence of multiple recurring atmospheric conditions. The North Atlantic eddy-driven jet, which explains a major part of the winter variability over the North Atlantic region, has three preferred latitudinal positions situated south, closest to, and north of its climatological mean position. These positions represent, respectively, Greenland blocking, a low-pressure system over the North Atlantic, and a high-pressure system over the North Atlantic. An improved representation of this jet is reported from CMIP5 GCMs. However, the existence of three preferred latitudinal positions remains a challenge for these models. The statistical properties of recurring atmospheric conditions can potentially enhance current weather and climate predictions. Techniques from dynamical system theory, like unstable periodic orbits, can be employed to reconstruct such statistical properties. This has been demonstrated, for the first time, in a three-level baroclinic model, of intermediate complexity, for the Northern Hemisphere winter. In the Northern ...
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