The Storm Studies in the Arctic (STAR) network (2007–2010) conducted a major meteorological field project from 10 October–30 November 2007 and in February 2008, focused on southern Baffin Island, Nunavut, Canada—a region that experiences intense autumn and winter storms. The STAR research program is concerned with the documentation, better understanding, and improved prediction of meteorological and related hazards in the Arctic, including their modification by local topography and land–sea ice–ocean transitions, and their effect on local communities. To optimize the applicability of STAR network science, we are also communicating with the user community (northern communities and government sectors). STAR has obtained a variety of surface-based and unique research aircraft field measurements, high-resolution modeling products, and remote sensing measurements (including Cloudsat) as part of its science strategy and has the first arctic Cloudsat validation dataset. In total, 14 research flights were flown between 5 and 30 November 2007, with eight coinciding with Cloudsat passes. The aircraft was outfitted with many instruments that measure cloud microphysical parameters and three unique Doppler-polarized airborne radars operating in Ka, X and W bands. The project area, instrumentation platforms, real-time forecasts, storm cases, and results thus far are discussed in this article. A number of synoptic and mesoscale features were sampled—such as fronts, upslope/terrain-enhanced precipitation, convective precipitation, and boundary layer clouds/precipitation—as well as targeted Cloudsat missions. One significant and unique event included a research flight into an intense high-latitude storm leftover from Hurricane Noel—an intense tropical and extratropical disturbance that caused many fatalities in the tropics and extensive damage on the eastern North American seaboard. These synoptic and mesoscale features and high-latitude storms will be studied in detail over the next several years. It is anticipated that scientific progress in better understanding the nature of these arctic storms and their hazards will lead to improved conceptual models and improved prediction of such events.

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Department of Environment and Geography, University of Manitoba, Winnipeg, Manitoba, Canada

Department of Earth and Space Science, York University, Toronto, Ontario, Canada

Department of Physics, University of Toronto, Ontario, Toronto, Canada

Department of Geography, University of Western Ontario, London, Ontario, Canada

Cloud Physics and Severe Weather Research Section, Environment Canada, Toronto, Ontario, Canada

Flight Research Laboratory, National Research Council of Canada, Ottawa, Ontario, Canada

Hydrometeorology and Arctic Laboratory, Environment Canada, Edmonton, Alberta, Canada

Prairie and Arctic Storm Prediction Centre, Environment Canada, Edmonton, Alberta, Canada

Department of Atmospheric and Ocean Sciences, McGill University, Montreal, Quebec, Canada