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in mean wind speeds over time, daily mean wind speeds show a significant change in sample variance, the frequency of wind speeds within and above specific thresholds has significantly changed over time, and the frequency and intensity of blowing-snow days have significantly changed over time. a. In situ data Alpine-region in situ stations may more accurately represent wind speed trends because of fewer anthropogenic changes (e.g., station relocation, urban development, and land-use/land-cover
in mean wind speeds over time, daily mean wind speeds show a significant change in sample variance, the frequency of wind speeds within and above specific thresholds has significantly changed over time, and the frequency and intensity of blowing-snow days have significantly changed over time. a. In situ data Alpine-region in situ stations may more accurately represent wind speed trends because of fewer anthropogenic changes (e.g., station relocation, urban development, and land-use/land-cover
was occurring over most of Wilkes Land, Antarctica. An analysis of CALIOP and MODIS data over the period 8–14 October 2010 showed that the storm began late in the day on 9 October 2010 and continued for 3–4 days. The false-color MODIS image shown in Fig. 3 illustrates the large area covered by this storm at 0550 UTC 12 October 2010. In this image, the snow- and ice-covered surface is blue, while clouds are a bright white. Blowing snow is indicated by the grayish-white areas that cover most of
was occurring over most of Wilkes Land, Antarctica. An analysis of CALIOP and MODIS data over the period 8–14 October 2010 showed that the storm began late in the day on 9 October 2010 and continued for 3–4 days. The false-color MODIS image shown in Fig. 3 illustrates the large area covered by this storm at 0550 UTC 12 October 2010. In this image, the snow- and ice-covered surface is blue, while clouds are a bright white. Blowing snow is indicated by the grayish-white areas that cover most of
during 1901–2005 ( Lynch et al. 2016 ). Simulations agree that both global and northeastern U.S. regional temperatures will continue to increase over the coming century ( Pachauri et al. 2014 ) with Northeast winters projected to warm 0.712°C decade −1 through 2100, according to CMIP5 projections using the 8.5 W m −2 representative concentration pathway scenario, or RCP8.5 ( Lynch et al. 2016 ). By the end of the century, northern New England is projected to lose 25%–50% of its snow-covered days
during 1901–2005 ( Lynch et al. 2016 ). Simulations agree that both global and northeastern U.S. regional temperatures will continue to increase over the coming century ( Pachauri et al. 2014 ) with Northeast winters projected to warm 0.712°C decade −1 through 2100, according to CMIP5 projections using the 8.5 W m −2 representative concentration pathway scenario, or RCP8.5 ( Lynch et al. 2016 ). By the end of the century, northern New England is projected to lose 25%–50% of its snow-covered days
1. Introduction What does it mean for a winter to be “snowy”? In the scientific literature, several metrics of “snowiness” exist ( Hewer and Gough 2020 ). These include the direct measurement of snowfall, that is, the measurement of precipitation that is intercepted at Earth’s surface in the form of snow ( Groisman and Easterling 1994 ; Ueda et al. 2015 ); snow cover, that is, the spatial extent of snow that remains as ground cover ( Farmer et al. 2009 ; Fernandes et al. 2014 ); and snow
1. Introduction What does it mean for a winter to be “snowy”? In the scientific literature, several metrics of “snowiness” exist ( Hewer and Gough 2020 ). These include the direct measurement of snowfall, that is, the measurement of precipitation that is intercepted at Earth’s surface in the form of snow ( Groisman and Easterling 1994 ; Ueda et al. 2015 ); snow cover, that is, the spatial extent of snow that remains as ground cover ( Farmer et al. 2009 ; Fernandes et al. 2014 ); and snow
1. Introduction Adverse cold weather conditions, most notably snow and ice, threaten surface transportation nationwide and impact roadway safety, mobility, and maintenance costs [ Pisano et al. 2008 ; Black and Mote 2015a , b ; Road Weather Management Program (RWMP) 2018 ]. During the period from 2005 to 2014, weather-related vehicular crashes accounted for 22% (1 258 978) of all reported crashes, resulting in 16% (5897) of crash fatalities and 19% (445 303) of crash injuries ( RWMP 2018
1. Introduction Adverse cold weather conditions, most notably snow and ice, threaten surface transportation nationwide and impact roadway safety, mobility, and maintenance costs [ Pisano et al. 2008 ; Black and Mote 2015a , b ; Road Weather Management Program (RWMP) 2018 ]. During the period from 2005 to 2014, weather-related vehicular crashes accounted for 22% (1 258 978) of all reported crashes, resulting in 16% (5897) of crash fatalities and 19% (445 303) of crash injuries ( RWMP 2018
FEBRUAI~Y 1984CORRESPONDENCE341CORRESPONDENCEComments on "An Apparent Relationship between Eurasian Spring Snow Coverand the Advance Period of the Indian Summer Monsoon"CHESTER F. ROPELEWSKICAC, NMC, NWS, NOAA, Washington, DC 20233ALAN ROBOCKDepartment of Meteorology, University of Maryland, College Park, MD 20742MICHAEL MATSONNESDIS, NOAA, Washington, DC 202337 November 1983Dey and Bhanu Kumar (1982) find a relationshipbetween Eurasian spring snow cover and the "advanceperiod" of the Indian
FEBRUAI~Y 1984CORRESPONDENCE341CORRESPONDENCEComments on "An Apparent Relationship between Eurasian Spring Snow Coverand the Advance Period of the Indian Summer Monsoon"CHESTER F. ROPELEWSKICAC, NMC, NWS, NOAA, Washington, DC 20233ALAN ROBOCKDepartment of Meteorology, University of Maryland, College Park, MD 20742MICHAEL MATSONNESDIS, NOAA, Washington, DC 202337 November 1983Dey and Bhanu Kumar (1982) find a relationshipbetween Eurasian spring snow cover and the "advanceperiod" of the Indian
al. 2001 ; Clements et al. 2003 ; Dorninger et al. 2011 ). In winter in snow-covered regions, the nocturnal air temperature distribution is more strongly influenced by topographic and boundary layer conditions than by microsite conditions (near-surface moisture, canopy, and exposure) because the ground surface is covered with thick snowpack ( Yazaki et al. 2013b ). Theoretically, the energy near the ground surface is lost when the temperature and longwave radiation in the boundary layer are low
al. 2001 ; Clements et al. 2003 ; Dorninger et al. 2011 ). In winter in snow-covered regions, the nocturnal air temperature distribution is more strongly influenced by topographic and boundary layer conditions than by microsite conditions (near-surface moisture, canopy, and exposure) because the ground surface is covered with thick snowpack ( Yazaki et al. 2013b ). Theoretically, the energy near the ground surface is lost when the temperature and longwave radiation in the boundary layer are low
Introduction About 98% of the global seasonal snow cover is located in the Northern Hemisphere ( Armstrong and Brodzig 2001 ), with a mean maximum extent of nearly 50% of the land surface area ( Robinson et al. 1993 ). In large areas, snowmelt is a significant contribution to the surface water supply and is the main cause of flooding. Variability in snow cover causes dramatic changes in surface albedo and, as a consequence, in the land surface energy budget. Therefore, global snow depth and
Introduction About 98% of the global seasonal snow cover is located in the Northern Hemisphere ( Armstrong and Brodzig 2001 ), with a mean maximum extent of nearly 50% of the land surface area ( Robinson et al. 1993 ). In large areas, snowmelt is a significant contribution to the surface water supply and is the main cause of flooding. Variability in snow cover causes dramatic changes in surface albedo and, as a consequence, in the land surface energy budget. Therefore, global snow depth and
made over two northern Minnesota bog cover types. Two Kipp and Zonenpyranometers were cycled over black spruce [Picea rnariana (Mill.) B.S.P.] and sphagnum-sedge bogcanopies within a one year period. During the snow-free seasonal periods black spruce had a 6-8% albedo and did not exhibit a response tonew shoot growth and maturation. Albedo increased to 8.2% with an 80% bog surface snow cover in lateNovember while a 100% bog surface snow cover increased the albedo to 10.5% in February
made over two northern Minnesota bog cover types. Two Kipp and Zonenpyranometers were cycled over black spruce [Picea rnariana (Mill.) B.S.P.] and sphagnum-sedge bogcanopies within a one year period. During the snow-free seasonal periods black spruce had a 6-8% albedo and did not exhibit a response tonew shoot growth and maturation. Albedo increased to 8.2% with an 80% bog surface snow cover in lateNovember while a 100% bog surface snow cover increased the albedo to 10.5% in February
Introduction Large changes in snow cover extent can result in the modification of atmospheric conditions through the earth’s lower troposphere due to the radiative effects of snow. In reflecting large amounts of incident shortwave radiation and absorbing heat through melting, it has been indicated that snow cover can lower surface air temperatures over timescales of days to months (e.g., Namias 1962 ; Dewey 1977 ). Snow cover has also been shown to affect the circulation of the atmosphere on
Introduction Large changes in snow cover extent can result in the modification of atmospheric conditions through the earth’s lower troposphere due to the radiative effects of snow. In reflecting large amounts of incident shortwave radiation and absorbing heat through melting, it has been indicated that snow cover can lower surface air temperatures over timescales of days to months (e.g., Namias 1962 ; Dewey 1977 ). Snow cover has also been shown to affect the circulation of the atmosphere on
