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Qiang Huang, John Hanesiak, Sergiy Savelyev, Tim Papakyriakou, and Peter A. Taylor

using wind speed, air temperature, and time since last snowfall as predictors. This technique is more practical than other visibility models and achieved a critical success index as high as 66%. In our present research, visibility, snow particle drift density, and standard meteorological data over Arctic sea ice were collected during blowing snow events to investigate the relationship between visibility, snow particle counter readings, and wind speed. The purpose is to provide an empirical set of

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Yanyun Liu, Wanqiu Wang, and Arun Kumar

1. Introduction Sea ice plays an important role in the global climate system through its impact on the water and energy budgets ( McBean et al. 2005 ; Budikova 2009 ; Guemas et al. 2016 ). Sea ice reflects most of the incident solar radiation through high albedo, thus reducing the amount of energy absorbed by the surface. It also modulates the exchange of moisture and heat fluxes between the ocean and the atmosphere. The Arctic sea ice has changed dramatically over the past few decades and is

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William Gregory, Michel Tsamados, Julienne Stroeve, and Peter Sollich

1. Introduction Passive microwave satellite observations since 1979 have shown a consistent decline in pan-Arctic sea ice extent (SIE) for all months of the year, in direct accordance with a warming planet as a result of anthropogenic CO 2 emissions ( Notz and Stroeve 2016 ). Across all months, September SIE has shown the fastest decline ( Overland and Wang 2013 ; Serreze and Stroeve 2015 ) as well as the largest interannual variability ( Stroeve and Notz 2018 ). Significant anomalies such as

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Adrienne Tivy, Bea Alt, Stephen Howell, Katherine Wilson, and John Yackel

1. Introduction One of the key findings of the Arctic Climate Impact Assessment (ACIA) is that reductions in Arctic sea ice, both past observed and future projected, will very likely increase marine transport in the north ( ACIA 2004 ). Annual average sea ice extent in the Arctic has decreased approximately 8% since the beginning of the satellite record in the late 1970s ( Cavalieri et al. 1997 , 2003 ; Parkinson et al. 1999 ; Parkinson and Cavelieri 2002 ) and 15%–20% reductions in minimum

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Thomas F. Lee, Susan Atwater, and Charles Samuels

SEPTEMBER 1993 NOTES AND CORRESPONDENCE 369Sea Ice-Edge Enhancement Using Polar-Orbiting Environmental Satellite Data THOMAS F. LEENaval Research Laboratory, Marine Meteorology Division, Monterey, CaliforniaSUSAN ATWATER AND CHARLES SAMUELSFairweather Forecasting, Anchorage, Alaska11 January 1993 and 26 April 1993ABSTRACT The authors develop and discuss satellite image enhancements of sea ice

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Robert W. Grumbine

SEPTEMBER 1994 NMC NOTES 453NMC NOTESA Sea-Ice Albedo Experiment with the NMC Medium Range Forecast Model*ROBERT W. GRUMBINENational Meteorological Center, Camp Springs, Maryland23 November 1993 and 31 March 1994ABSTRACT The sea-ice albedo treatment currently used in the National Meteorological Center Medium Range ForecastModel was a carryover from earlier models. A more modern treatment

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Sheldon Drobot

1. Introduction While considerable advances have been made in seasonal forecasts over tropical and extratropical regions during the last two decades (e.g., Goddard et al. 2001 ), capabilities in seasonal forecasts for Arctic regions have not advanced correspondingly. For instance, the National Ice Center's (NIC; see the appendix for a list of acronyms) seasonal outlook for the Beaufort Sea ( Fig. 1 ), the region of interest in this study, continues to use a pair of surface pressure

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William L. Chapman and John E. Walsh

JUNE 1991 WILLIAM L. CHAPMAN AND JOHN E. WALSH 271Long-Range Prediction of Regional Sea Ice Anon~alies in the Arctic WILLIAM L. CHAPMAN AND JOHN E. WALSHDepartment of Atmospheric Sciences, University of lllinois, Urbana, Illinois(Manuscript received 30 September 1990, in final form 25 November 1990)ABSTRACT Gridded fields of sea ice concentration are used to evaluate weekly and monthly anomalies of sea ice coveragein 22 Arctic

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Robert W. Grumbine

1. Introduction Since at least the time of Nansen (1902) , it has been common to think of sea ice drifting at some fraction of the wind speed, and at some angle to the wind. This is the drift rule. Nansen’s values, based on observation of ice floe drift during the cross-polar drift of the Maud (1893–96) were 1.8% and 28° to the right of the wind. This included about 949 floe-days of observations (7 November 1893–27 June 1896) from a single point. 1 In the time since then, two things have

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James E. Overland

and forecasting experience. When sea temperatures are <2-3-C above the saltwater freezingpoint there is the likelihood of supercooling of the spray during its trajectory and extreme ice accretion ontopside structures. The NOAA algorithm shows excellent results when compared to a new cold-water datasetfrom the Labrador Sea (mean sea temperature of-l.3-C), even though the algorithm was developed from anAlaskan dataset with a mean sea temperature of 3.6-C. A rederived algorithm from the combined

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