scholarly journals The effects of snow and salt on ice table stability in University Valley, Antarctica

2017 ◽  
Vol 30 (1) ◽  
pp. 67-78 ◽  
Author(s):  
K.E. Williams ◽  
J.L. Heldmann ◽  
Christopher P. McKay ◽  
Michael T. Mellon

AbstractThe Antarctic Dry Valleys represent a unique environment where it is possible to study dry permafrost overlaying an ice-rich permafrost. In this paper, two opposing mechanisms for ice table stability in University Valley are addressed: i) diffusive recharge via thin seasonal snow deposits and ii) desiccation via salt deposits in the upper soil column. A high-resolution time-marching soil and snow model was constructed and applied to University Valley, driven by meteorological station atmospheric measurements. It was found that periodic thin surficial snow deposits (observed in University Valley) are capable of drastically slowing (if not completely eliminating) the underlying ice table ablation. The effects of NaCl, CaCl2 and perchlorate deposits were then modelled. Unlike the snow cover, however, the presence of salt in the soil surface (but no periodic snow) results in a slight increase in the ice table recession rate, due to the hygroscopic effects of salt sequestering vapour from the ice table below. Near-surface pore ice frequently forms when large amounts of salt are present in the soil due to the suppression of the saturation vapour pressure. Implications for Mars high latitudes are discussed.

2005 ◽  
Vol 18 (8) ◽  
pp. 1174-1189 ◽  
Author(s):  
Andrew J. Monaghan ◽  
David H. Bromwich ◽  
Jordan G. Powers ◽  
Kevin W. Manning

Abstract In response to the need for improved weather prediction capabilities in support of the U.S. Antarctic Program’s Antarctic field operations, the Antarctic Mesoscale Prediction System (AMPS) was implemented in October 2000. AMPS employs a limited-area model, the Polar fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5), optimized for use over ice sheets. Twice-daily forecasts from the 3.3-km resolution domain of AMPS are joined together to study the climate of the McMurdo region from June 2002 to May 2003. Annual and seasonal distributions of wind direction and speed, 2-m temperature, mean sea level pressure, precipitation, and cloud fraction are presented. This is the first time a model adapted for polar use and with relatively high resolution is used to study the climate of the rugged McMurdo region, allowing several important climatological features to be investigated with unprecedented detail. Orographic effects exert an important influence on the near-surface winds. Time-mean vortices occur in the lee of Ross Island, perhaps a factor in the high incidence of mesoscale cyclogenesis noted in this area. The near-surface temperature gradient is oriented northwest to southeast with the warmest temperatures in the northwest near McMurdo and the gradient being steepest in winter. The first-ever detailed precipitation maps of the region are presented. Orographic precipitation maxima occur on the southerly slopes of Ross Island and in the mountains to the southwest. The source of the moisture is primarily from the large synoptic systems passing to the northeast and east of Ross Island. A precipitation-shadow effect appears to be an important influence on the low precipitation amounts observed in the McMurdo Dry Valleys. Total cloud fraction primarily depends on the amount of open water in the Ross Sea; the cloudiest region is to the northeast of Ross Island in the vicinity of the Ross Sea polynya.


Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 217
Author(s):  
Jiangping Zhu ◽  
Aihong Xie ◽  
Xiang Qin ◽  
Yetang Wang ◽  
Bing Xu ◽  
...  

The European Center for Medium-Range Weather Forecasts (ECMWF) released its latest reanalysis dataset named ERA5 in 2017. To assess the performance of ERA5 in Antarctica, we compare the near-surface temperature data from ERA5 and ERA-Interim with the measured data from 41 weather stations. ERA5 has a strong linear relationship with monthly observations, and the statistical significant correlation coefficients (p < 0.05) are higher than 0.95 at all stations selected. The performance of ERA5 shows regional differences, and the correlations are high in West Antarctica and low in East Antarctica. Compared with ERA5, ERA-Interim has a slightly higher linear relationship with observations in the Antarctic Peninsula. ERA5 agrees well with the temperature observations in austral spring, with significant correlation coefficients higher than 0.90 and bias lower than 0.70 °C. The temperature trend from ERA5 is consistent with that from observations, in which a cooling trend dominates East Antarctica and West Antarctica, while a warming trend exists in the Antarctic Peninsula except during austral summer. Generally, ERA5 can effectively represent the temperature changes in Antarctica and its three subregions. Although ERA5 has bias, ERA5 can play an important role as a powerful tool to explore the climate change in Antarctica with sparse in situ observations.


2012 ◽  
Vol 58 (209) ◽  
pp. 529-539 ◽  
Author(s):  
Shin Sugiyama ◽  
Hiroyuki Enomoto ◽  
Shuji Fujita ◽  
Kotaro Fukui ◽  
Fumio Nakazawa ◽  
...  

AbstractDuring the Japanese-Swedish Antarctic traverse expedition of 2007/08, we measured the surface snow density at 46 locations along the 2800 km long route from Syowa station to Wasa station in East Antarctica. The mean snow density for the upper 1 (or 0.5) m layer varied from 333 to 439 kg m-3 over a region spanning an elevation range of 365-3800 ma.s.l. The density variations were associated with the elevation of the sampling sites; the density decreased as the elevation increased, moving from the coastal region inland. However, the density was relatively insensitive to the change in elevation along the ridge on the Antarctic plateau between Dome F and Kohnen stations. Because surface wind is weak in this region, irrespective of elevation, the wind speed was suggested to play a key role in the near-surface densification. The results of multiple regression performed on the density using meteorological variables were significantly improved by the inclusion of wind speed as a predictor. The regression analysis yielded a linear dependence between the density and the wind speed, with a coefficient of 13.5 kg m-3 (m s-1)-1. This relationship is nearly three times stronger than a value previously computed from a dataset available in Antarctica. Our data indicate that the wind speed is more important to estimates of the surface snow density in Antarctica than has been previously assumed.


2017 ◽  
Vol 56 (8) ◽  
pp. 2239-2258 ◽  
Author(s):  
Jonathan D. Wille ◽  
David H. Bromwich ◽  
John J. Cassano ◽  
Melissa A. Nigro ◽  
Marian E. Mateling ◽  
...  

AbstractAccurately predicting moisture and stability in the Antarctic planetary boundary layer (PBL) is essential for low-cloud forecasts, especially when Antarctic forecasters often use relative humidity as a proxy for cloud cover. These forecasters typically rely on the Antarctic Mesoscale Prediction System (AMPS) Polar Weather Research and Forecasting (Polar WRF) Model for high-resolution forecasts. To complement the PBL observations from the 30-m Alexander Tall Tower! (ATT) on the Ross Ice Shelf as discussed in a recent paper by Wille and coworkers, a field campaign was conducted at the ATT site from 13 to 26 January 2014 using Small Unmanned Meteorological Observer (SUMO) aerial systems to collect PBL data. The 3-km-resolution AMPS forecast output is combined with the global European Centre for Medium-Range Weather Forecasts interim reanalysis (ERAI), SUMO flights, and ATT data to describe atmospheric conditions on the Ross Ice Shelf. The SUMO comparison showed that AMPS had an average 2–3 m s−1 high wind speed bias from the near surface to 600 m, which led to excessive mechanical mixing and reduced stability in the PBL. As discussed in previous Polar WRF studies, the Mellor–Yamada–Janjić PBL scheme is likely responsible for the high wind speed bias. The SUMO comparison also showed a near-surface 10–15-percentage-point dry relative humidity bias in AMPS that increased to a 25–30-percentage-point deficit from 200 to 400 m above the surface. A large dry bias at these critical heights for aircraft operations implies poor AMPS low-cloud forecasts. The ERAI showed that the katabatic flow from the Transantarctic Mountains is unrealistically dry in AMPS.


2021 ◽  
Author(s):  
Xiaocheng Liu ◽  
Chenming Zhang ◽  
Yue Liu ◽  
David Lockington ◽  
Ling Li

&lt;p&gt;Estimation of evaporation rates from soils is significant for environmental, hydrological, and agricultural purposes. Modeling of the soil surface resistance is essential to estimate the evaporation rates from bare soil. Empirical surface resistance models may cause large deviations when applied to different soils. A physically-based soil surface model is developed to calculate the surface resistance, which can consider evaporation on the soil surface when soil is fully saturated and the vapor flow below the soil surface after dry layer forming on the top. Furthermore, this physically-based expression of the surface resistance is added into a numerical model that considers the liquid water transport, water vapor transport, and heat transport during evaporation. The simulation results are in good agreement with the results from six soil column drying experiments.&amp;#160; This numerical model can be applied to predict or estimate the evaporation rate of different soil and saturation at different depths during evaporation.&lt;/p&gt;


2021 ◽  
Author(s):  
Jeremy Carter ◽  
Amber Leeson ◽  
Andrew Orr ◽  
Christoph Kittel ◽  
Melchior van Wessem

&lt;p&gt;Understanding the surface climatology of the Antarctic ice sheet is essential if we are to adequately predict its response to future climate change. This includes both primary impacts such as increased ice melting and secondary impacts such as ice shelf collapse events. Given its size, and inhospitable environment, weather stations on Antarctica are sparse. Thus, we rely on regional climate models to 1) develop our understanding of how the climate of Antarctica varies in both time and space and 2) provide data to use as context for remote sensing studies and forcing for dynamical process models. Given that there are a number of different regional climate models available that explicitly simulate Antarctic climate, understanding inter- and intra model variability is important.&lt;/p&gt;&lt;p&gt;Here, inter- and intra-model variability in Antarctic-wide regional climate model output is assessed for: snowfall; rainfall; snowmelt and near-surface air temperature within a cloud-based virtual lab framework. State-of-the-art regional climate model runs from the Antarctic-CORDEX project using the RACMO, MAR and MetUM models are used, together with the ERA5 and ERA-Interim reanalyses products. Multiple simulations using the same model and domain boundary but run at either different spatial resolutions or with different driving data are used. Traditional analysis techniques are exploited and the question of potential added value from more modern and involved methods such as the use of Gaussian Processes is investigated. The advantages of using a virtual lab in a cloud based environment for increasing transparency and reproducibility, are demonstrated, with a view to ultimately make the code and methods used widely available for other research groups.&lt;/p&gt;


2016 ◽  
Vol 62 (234) ◽  
pp. 714-724 ◽  
Author(s):  
SHELLEY MACDONELL ◽  
MARTIN SHARP ◽  
SEAN FITZSIMONS

ABSTRACTCryoconite holes can be important sources and stores of water and nutrients on cold and polythermal glaciers, and they provide a habitat for various forms of biota. Understanding the hydrological connectivity of cryoconite holes may be the key to understanding the transport of nutrients and biological material to the proglacial areas of such glaciers. This paper aims to characterize and explain spatial variability in the connectivity of ice-lidded cryoconite holes on a small, piedmont glacier in the McMurdo Dry Valleys through geochemical analysis of cryoconite hole waters. Solute concentrations in both surface and near-surface ice and cryoconite holes, vary greatly along the glacier centerline, and all sample types displayed similar spatial patterns of variability. Using chloride as a tracer, we estimated variations in cryoconite hole connectivity along the glacier centerline. We found that a previously used mass transfer method did not provide reliable estimates of the time period for which cryoconite hole waters had been isolated from the atmosphere. We attribute this to spatial variability in both the chloride content of the surface ice and surface ablation rates. The approach may, however, be used to qualitatively characterize spatial variations in the hydrological connectivity of the cryoconite holes. These results also suggest that ice-lidded cryoconite holes are never truly isolated from the near-surface drainage system.


2014 ◽  
Vol 8 (4) ◽  
pp. 1205-1215 ◽  
Author(s):  
J.-C. Gallet ◽  
F. Domine ◽  
J. Savarino ◽  
M. Dumont ◽  
E. Brun

Abstract. On the Antarctic plateau, precipitation quantities are so low that the surface mass budget is for an important part determined by exchanges of water vapor between the snow surface and the atmosphere surface. At Dome C (75° S, 123° E), we have frequently observed the growth of crystals on the snow surface under calm sunny weather. Here we present the time variations of specific surface area (SSA) and density of these crystals. Using the detailed snow model Crocus, we conclude that the formation of these crystals was very likely due to the nighttime formation of surface hoar crystals and to the daytime formation of sublimation crystals. These latter crystals form by processes similar to those involved in the formation of frost flowers on young sea ice. The formation of these crystals impacts the albedo, mass and energy budget of the Antarctic plateau. In particular, the SSA variations of the surface layer can induce an instantaneous forcing at the snow surface up to −10 W m−2 at noon, resulting in a surface temperature drop of 0.45 K. This result confirms that snow SSA is a crucial variable to consider in the energy budget and climate of snow-covered surfaces.


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