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Mark C. Serreze, Jonathan D. Kahl, and Russell C. Schnell


Seasonal and regional variations in characteristics of the Arctic low-level temperature inversion are examined using up to 12 years of twice-daily rawinsonde data from 31 inland and coastal sites of the Eurasian Arctic and a total of nearly six station years of data from three Soviet drifting stations near the North Pole. The frequency of inversions, the median inversion depth, and the temperature difference across the inversion layer increase from the Norwegian Sea eastward toward the Laptev and East Siberian seas. This effect is most pronounced in winter and autumn, and reflects proximity to oceanic influences and synoptic activity, possibly enhanced by a gradient in cloud cover. East of Novaya Zemlya during winter, inversions are found in over 95% of all soundings and tend to be surface based. For all locations, however, inversions tend to he most intense during winter due to the large deficit in surface net radiation. The strongest inversions are found over eastern Siberia, and reflect the effects of local topography. The frequency of inversions is lowest during summer, but is still >50% at all locations. Most summer inversions are elevated, and are much weaker than their winter counterparts. Data from the drifting stations reveal an inversion in every sounding from December to April. The minimum frequency of 85% occurs during August. While the median inversion depth is over 1200 m during March, it decreases to approximately 400 m during August, with median temperature differences across the inversion layer of 12.6° and 2.8°C, respectively. The median depth of the summertime mixed layer below inversions at the drifting stations ranges from 300 to 400 m. Seasonal changes in these inversion characteristics show a strong relationship with seasonal changes in cloud cover.

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Jonathan D. W. Kahl, Brandon R. Selbig, and Austin R. Harris


Wind gusts are common to everyday life and affect a wide range of interests including wind energy, structural design, forestry, and fire danger. Strong gusts are a common environmental hazard that can damage buildings, bridges, aircraft, and trains, and interrupt electric power distribution, air traffic, waterways transport, and port operations. Despite representing the component of wind most likely to be associated with serious and costly hazards, reliable forecasts of peak wind gusts have remained elusive. A project at the University of Wisconsin–Milwaukee is addressing the need for improved peak gust forecasts with the development of the meteorologically stratified gust factor (MSGF) model. The MSGF model combines gust factors (the ratio of peak wind gust to average wind speed) with wind speed and direction forecasts to predict hourly peak wind gusts. The MSGF method thus represents a simple, viable option for the operational prediction of peak wind gusts. Here we describe the results of a project designed to provide the site-specific gust factors necessary for operational use of the MSGF model at a large number of locations across the United States. Gust web diagrams depicting the wind speed– and wind direction–stratified gust factors, as well as peak gust climatologies, are presented for all sites analyzed.

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Jonathan D. Kahl, Mark C. Serreze, Spencer Shiotani, Suzanne M. Skony, and Russell C. Schnell

Two new databases containing Arctic in situ meteorological soundings have been constructed and are now available for distribution to interested researchers. The Historical Arctic Rawinsonde Archive is a comprehensive collection of over 1.2 million rawinsonde soundings north of 65°N. For most stations the record begins in 1958 and extends to 1987; however, for some stations the record begins as early as 1948. The Ptarmigan Dropsonde Archive contains more than 10 000 lower-tropospheric soundings over the Beaufort Sea and western Arctic Ocean during the period 1950–1961.

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Victoria A. Lang, Teresa J. Turner, Brandon R. Selbig, Austin R. Harris, and Jonathan D. W. Kahl


Wind gusts present challenges to operational meteorologists, both to forecast accurately and also, to verify. Strong wind gusts can damage structures and create costly risks for diverse industrial sectors. The meteorologically stratified gust factor (MSGF) model incorporates site-specific gust factors (the ratio of peak wind gust to mean wind speed) with wind speed and direction forecast guidance. The MSGF model has previously been shown to be a viable operational tool that exhibits skill (improvement over climatology) in forecasting peak wind gusts.

This study assesses the performance characteristics of the MSGF model by evaluating peak gust predictions during several types of gust-producing weather phenomena. Peak wind gusts were prepared and verified for 7 specific weather conditions over an 8-year period at 16 sites across the United States. When coupled with two forms of model output statistics (MOS) wind guidance, the MSGF model generally shows skill in predicting peak wind gusts at forecast projections ranging from 6 to 72 hours. The model performed best during high pressure and nocturnal conditions and was also skillful during conditions involving snow. The model did not perform well during the rain with thunder weather type. The MSGF model is a viable tool for the operational prediction of peak gusts for most gust-producing weather types.

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Jonathan D. W. Kahl, Nina A. Zaitseva, V. Khattatov, R. C. Schnell, Dina M. Bacon, Jason Bacon, V. Radionov, and M. C. Serreze

An historical archive of over 25 000 radiosonde observations from the former Soviet “North Pole” series of drifting ice stations has been compiled and made available to interested researchers. This archive is the only long-term set of meteorological sounding data over the Arctic Ocean. The digital archive is a result of the multiyear, collaborative efforts of a group of United States and Russian scientists and keypunch operators working under the auspices of Working Group VIII, an area of study within the United States–Russian Federation Agreement for Protection of the Environment and Natural Resources. The archive contains soundings from 21 drifting stations over the period 1954–90 and is being distributed by the National Snow and Ice Data Center in Boulder, Colorado.

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