Optimal deployment of the Antarctic surface weather observing network

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The Antarctic continent, its surrounding ocean and atmosphere are a vastly under observed region of the planet. Environmental observing systems have often historically been sited on largely subjective grounds, including logistic convenience and simple accessibility. As environmental observing networks such as those Antarctic Automated Weather Stations (AAWS) are increasingly being relied upon for operational (e.g. numerical weather prediction), weather research (e.g. mesoscale meteorology, ecosystem change) and climate (e.g. ice mass balance; climate variability and change) studies, more objective considerations are needed for the economical and effective retention or expansion of limited observing assets. Emerging theory from network design offers the basis for some objective guidance in this area. Gridded data from (archived) Antarctic Mesoscale Prediction Systems (AMPS) will be used by University of Washington and NCAR researchers to optimize the spatial correlation length scales for the existing AWS network via ensemble sensitivity theory. These predictions of optimal station placement will in turn be subject to observing systems experiments (OSE) and observing system simulation experiments (OSSE), using both data denial and reconfiguration approaches. Results of this research may inform the placement of the most spatially representative locations of AWS stations for both meteorology (e.g. NWP) and climate related studies. A graduate student and a post-doctoral associate will be involved in this interdisciplinary problem.