Title: Valley-floor snowfall in Taylor Valley, Antarctica, from 1995 to 2017: spring, summer and autumn
Abstract We present an analysis of the 20 year snowfall dataset in Taylor Valley and the results of a new snow cover monitoring study. Snowfall has been measured at four sites in Taylor Valley from 1995 to 2017. We focus on valley-floor snowfall when wind does not exceed 5 m s -1 , and we exclude winter from our analysis due to poor data quality. Snowfall averaged 11 mm water equivalent (w.e.) from 1995 to 2017 across all stations and ranged from 1 to 58 mm w.e. Standard deviations ranged from 3 to 17 mm w.e., highlighting the strong interannual variability of snowfall in Taylor Valley. During spring and autumn there is a spatial gradient in snowfall such that the coast received twice as much snowfall as more central and inland stations. We identified a changepoint in 2007 from increasing snowfall (3 mm w.e. yr -1 ) to decreasing snowfall (1 mm w.e. yr -1 ), which coincides with a shift from decreasing temperature to no detectable temperature trend. Daily camera imagery from 2007 to 2017 augments the snowfall measurements. The camera imagery revealed a near tripling of the average number of days with snow cover from 37 days between 2006 and 2012 to 106 days with snow cover between 2012 and 2017. more »« less
Boisrame, Gabrielle; Rakhmatulina, Ekaterina; Thompson, Sally; Stephens, Scott
(, Hydroshare)
CUAHSI
(Ed.)
This dataset is part of a project studying the effects of wildfire on the Illilouette Creek Basin, a watershed within Yosemite National Park. Three temporary weather stations were installed under distinct types of vegetation cover. Each station measures air temperature, relative humidity, rainfall (the rain gage is not heated, so only the portion of snowfall that melts within the gage is measured), wind speed and direction, solar radiation, and both soil moisture and temperature at three depths. These measurements are recorded every 10 minutes, beginning in the summer of 2015 through June 2021. Snow depths and percent cover were estimated from time lapse imagery up to four times per day, and field measurements of snow depth and density were conducted up to two times each winter. The west-facing hillside where these stations are located most recently burned in 2004 and 2017 (Empire Fire). Photos are included of the stations both before and after the Empire Fire. For descriptions of the data format and units, see the included WeatherStnMetadata.xlsx file.
Bergstrom, Anna; Gooseff, Michael N.; Myers, Madeline; Doran, Peter T.; Cross, Julian M.
(, The Cryosphere)
Abstract. The McMurdo Dry Valleys (MDVs) of Antarctica are a polar desertecosystem consisting of alpine glaciers, ice-covered lakes, streams, andexpanses of vegetation-free rocky soil. Because average summer temperaturesare close to 0 ∘C, theMDV ecosystem in general, and glacier melt dynamics in particular, are both closely linked to the energy balance. A slightincrease in incoming radiation or change in albedo can have large effects onthe timing and volume of meltwater. However, the seasonal evolution orspatial variability of albedo in the valleys has yet to fully characterized.In this study, we aim to understand the drivers of landscape albedo changewithin and across seasons. To do so, a box with a camera, GPS, andshortwave radiometer was hung from a helicopter that flew transects four to fivetimes a season along Taylor Valley. Measurements were repeated over threeseasons. These data were coupled with incoming radiation measured at sixmeteorological stations distributed along the valley to calculate thedistribution of albedo across individual glaciers, lakes, and soilsurfaces. We hypothesized that albedo would decrease throughout the australsummer with ablation of snow patches and increasing sediment exposure on theglacier and lake surfaces. However, small snow events (<6 mm waterequivalent) coupled with ice whitening caused spatial and temporalvariability of albedo across the entire landscape. Glaciers frequentlyfollowed a pattern of increasing albedo with increasing elevation, as well asincreasing albedo moving from east to west laterally across the ablationzone. We suggest that spatial patterns of albedo are a function of landscapemorphology trapping snow and sediment, longitudinal gradients in snowfallmagnitude, and wind-driven snow redistribution from east to west alongthe valley. We also compare our albedo measurements to the MODIS albedo productand found that overall the data have reasonable agreement. The mismatch inspatial scale between these two datasets results in variability, which isreduced after a snow event due to albedo following valley-scale gradients ofsnowfall magnitude. These findings highlight the importance of understandingthe spatial and temporal variability in albedo and the close coupling ofclimate and landscape response. This new understanding of landscape albedocan constrain landscape energy budgets, better predict meltwater generationon from MDV glaciers, and how these ecosystems will respond to changingclimate at the landscape scale.
Clark, Craig A.; Metz, Nicholas D.; Goebbert, Kevin H.; Ganesh-Babu, Bharath; Ballard, Nolan; Blackford, Andrew; Bottom, Andrew; Britt, Catherine; Carmer, Kelly; Davis, Quenten; et al
(, Frontiers in Water)
The Laurentian Great Lakes have substantial influences on regional climatology, particularly with impactful lake-effect snow events. This study examines the snowfall, cloud-inferred snow band morphology, and environment of lake-effect snow days along the southern shore of Lake Michigan for the 1997–2017 period. Suitable days for study were identified based on the presence of lake-effect clouds assessed in a previous study and extended through 2017, combined with an independent classification of likely lake-effect snow days based on independent snowfall data and weather map assessments. The primary goals are to identify lake-effect snow days and evaluate the snowfall distribution and modes of variability, the sensitivity to thermodynamic and flow characteristics within the upstream sounding at Green Bay, WI, and the influences of snowband morphology. Over 300 lake-effect days are identified during the study period, with peak mean snowfall within the lake belt extending from southwest Michigan to northern Indiana. Although multiple lake-effect morphological types are often observed on the same day, the most common snow band morphology is wind parallel bands. Relative to days with wind parallel bands, the shoreline band morphology is more common with a reduced lower-tropospheric zonal wind component within the upstream sounding at Green Bay, WI, as well as higher sea-level pressure and 500-hPa geopotential height anomalies to the north of the Great Lakes. Snowfall is sensitive to band morphology, with higher snowfall for shoreline band structures than for wind parallel bands, especially due south of Lake Michigan. Snowfall is also sensitive to thermodynamic and flow properties, with a greater sensitivity to temperature in southwest Michigan and to flow properties in northwest Indiana.
Wagner, David N.; Shupe, Matthew D.; Cox, Christopher; Persson, Ola G.; Uttal, Taneil; Frey, Markus M.; Kirchgaessner, Amélie; Schneebeli, Martin; Jaggi, Matthias; Macfarlane, Amy R.; et al
(, The Cryosphere)
Abstract. Data from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition allowed us to investigate the temporal dynamics of snowfall, snow accumulation and erosion in great detail for almost the whole accumulation season (November 2019 to May 2020). We computed cumulative snow water equivalent (SWE) over the sea ice based on snow depth and density retrievals from a SnowMicroPen and approximately weekly measured snow depths along fixed transect paths. We used the derived SWE from the snow cover to compare with precipitation sensors installed during MOSAiC. The data were also compared with ERA5 reanalysis snowfall rates for the drift track. We found an accumulated snow mass of 38 mm SWE between the end of October 2019 and end of April 2020. The initial SWE over first-year ice relative to second-year ice increased from 50 % to 90 % by end of the investigation period. Further, we found that the Vaisala Present Weather Detector 22, an optical precipitation sensor, and installed on a railing on the top deck of research vessel Polarstern, was least affected by blowing snow and showed good agreements with SWE retrievals along the transect. On the contrary, the OTT Pluvio2 pluviometer and the OTT Parsivel2 laser disdrometer were largely affected by wind and blowing snow, leading to too high measured precipitation rates. These are largely reduced when eliminating drifting snow periods in the comparison. ERA5 reveals good timing of the snowfall events and good agreement with ground measurements with an overestimation tendency. Retrieved snowfall from the ship-based Ka-band ARM zenith radar shows good agreements with SWE of the snow cover and differences comparable to those of ERA5. Based on the results, we suggest the Ka-band radar-derived snowfall as an upper limit and the present weather detector on RV Polarstern as a lower limit of a cumulative snowfall range. Based on these findings, we suggest a cumulative snowfall of 72 to 107 mm and a precipitation mass loss of the snow cover due to erosion and sublimation as between 47 % and 68 %, for the time period between 31 October 2019 and 26 April 2020. Extending this period beyond available snow cover measurements, we suggest a cumulative snowfall of 98–114 mm.
Jones, Erin A.; Lang, Carrie E.; Laird, Neil F.
(, Frontiers in Water)
In the Great Lakes region, total cold-season snowfall consists of contributions from both lake-effect systems (LES) and non-LES snow events. To enhance understanding of the regional hydroclimatology, this research examined these separate contributions with a focus on the cold seasons (October–March) of 2009/2010, a time period with the number of LES days substantially less than the mean, and 2012/2013, a time period with the number of LES days notably greater than the mean, for the regions surrounding Lakes Erie, Michigan, and Ontario. In general, LES snowfall exhibited a maximum contribution in near-shoreline areas surrounding each lake while non-LES snowfall tended to provide a more widespread distribution throughout the entire study regions with maxima often located in regions of elevated terrain. The percent contribution for LES snowfall to the seasonal snowfall varied spatially near each lake with localized maxima and ranged in magnitudes from 10% to over 70%. Although total LES snowfall amounts tended to be greater during the cold season with the larger number of LES days, the percent of LES snowfall contributing to the total cold-season snowfall was not directly dependent on the number of LES days. The LES snowfall contributions to seasonal totals were found to be generally larger for Lakes Erie and Ontario during the cold season with a greater number of LES days; however, LES contributions were similar or smaller for areas in the vicinity of Lake Michigan during the cold season with a smaller number of LES days.
Myers, Madeline E., Doran, Peter T., and Myers, Krista F. Valley-floor snowfall in Taylor Valley, Antarctica, from 1995 to 2017: spring, summer and autumn. Retrieved from https://par.nsf.gov/biblio/10416098. Antarctic Science 34.4 Web. doi:10.1017/S0954102022000256.
Myers, Madeline E., Doran, Peter T., & Myers, Krista F. Valley-floor snowfall in Taylor Valley, Antarctica, from 1995 to 2017: spring, summer and autumn. Antarctic Science, 34 (4). Retrieved from https://par.nsf.gov/biblio/10416098. https://doi.org/10.1017/S0954102022000256
@article{osti_10416098,
place = {Country unknown/Code not available},
title = {Valley-floor snowfall in Taylor Valley, Antarctica, from 1995 to 2017: spring, summer and autumn},
url = {https://par.nsf.gov/biblio/10416098},
DOI = {10.1017/S0954102022000256},
abstractNote = {Abstract We present an analysis of the 20 year snowfall dataset in Taylor Valley and the results of a new snow cover monitoring study. Snowfall has been measured at four sites in Taylor Valley from 1995 to 2017. We focus on valley-floor snowfall when wind does not exceed 5 m s -1 , and we exclude winter from our analysis due to poor data quality. Snowfall averaged 11 mm water equivalent (w.e.) from 1995 to 2017 across all stations and ranged from 1 to 58 mm w.e. Standard deviations ranged from 3 to 17 mm w.e., highlighting the strong interannual variability of snowfall in Taylor Valley. During spring and autumn there is a spatial gradient in snowfall such that the coast received twice as much snowfall as more central and inland stations. We identified a changepoint in 2007 from increasing snowfall (3 mm w.e. yr -1 ) to decreasing snowfall (1 mm w.e. yr -1 ), which coincides with a shift from decreasing temperature to no detectable temperature trend. Daily camera imagery from 2007 to 2017 augments the snowfall measurements. The camera imagery revealed a near tripling of the average number of days with snow cover from 37 days between 2006 and 2012 to 106 days with snow cover between 2012 and 2017.},
journal = {Antarctic Science},
volume = {34},
number = {4},
author = {Myers, Madeline E. and Doran, Peter T. and Myers, Krista F.},
}
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