Model experiments on snow and ice thermodynamics in the Arctic Ocean with CHINARE 2003 data

Abstract

[1] Snow and ice thermodynamics over the Arctic Ocean were simulated applying a one-dimensional model. A number of numerical experiments in synoptic (10 days in early autumn) and seasonal (May-September) scales were carried out to investigate the impact of external forcing, snow physics, and the model resolution: the number of layers in both snow and ice ranged from 3 to 40. The model forcing was based on in situ observations carried out in 2003 during the Chinese National Arctic Research Expedition (CHINARE) as well as on forecasts and analyses of the European Centre for MediumRange Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR). The model results were compared against the results of the ECMWF and NCEP/NCAR sea ice schemes. The ECMWF operational precipitation forecasts yielded realistic seasonal snowfall, while the precipitation in NCEP/NCAR reanalysis was unrealistically large. A good result on snow thickness evolution also strongly depended on the accuracy of modeled snowmelt. A time-dependent surface albedo parameterization was critical for the seasonal evolution of snow and ice thickness. Application of 15-20 model levels in snow and ice is recommended as it (1) ensured good reproduction of the vertical snow/ice temperature profile also when solar radiation was large, (2) decreased the sensitivity of snow and ice mass balance to changes in surface albedo, (3) enabled the calculation of subsurface melting of snow and ice, and (4) reasonably reproduced the superimposed ice formation and onset of ice melt. In autumn, however, the accuracy of atmospheric forcing was more important than the model resolution.

Spatial and temporal variability in summer snow pack in Dronning Maud Land, Antarctica

“…The penetration depth (0.20-0.25 m) of the diurnal temperature cycle was close to that obtained by at Svea in January 1993, by Jordan et al (1989) for seasonal snow in New Hampshire, USA, in February, and by Cheng et al (2008a, b) for snow on the Arctic sea ice in summer. In all of these studies, the diurnal range of the solar zenith angle was between 36 • and 43 • .…”

“…This is supported by Takahashi and Kameda (2007), who suggested that snow density at the base of the snow stake should be used to estimate water equivalent surface mass balance from stake measurements. Our data set also provides possibilities for the validation of snow thermodynamic models from the point of view of the dependence of thermal conductivity on density (Brandt and Warren, 1997) and penetration of solar radiation into the snow pack (Cheng et al, 2008a).…”

A new pattern of the moisture transport for precipitation related to the drastic decline in Arctic sea ice extent

“…However, anomalous moisture transport can result in anomalous precipitation, and in this case, the relation between enhanced moisture transport and diminished SIE is unclear because changes in precipitation are not always related to SIE in the same way, depending on the type of precipitation and the season. Snowfall on sea ice enhances thermal insulation and thus reduces sea ice growth in winter (Leppäranta, 1993), but increases the surface albedo and thus reduces melt in spring and summer (Cheng et al, 2008). In contrast, rainfall is generally related to sea ice melt, and for both snowfall and rainfall, flooding over the ice favours the formation of superimposed ice and potentially increases in the Arctic sea ice thickness.…”

“…As, according to These results are coherent with any of the mechanisms referred in the introduction. Thus, (i) a lower MTP in early summer (as occurred since 2003) implies lower precipitation (in this season mainly as snowfall), which would result in a decrease in the surface albedo and thus increasing melt (Cheng et al, 2008); (ii) a lower MTP in late summer (as has occurred since 2003) could be due to a less probability of occurrence of rainfall storms with possible flooding over the ice, which would favour the formation of superimposed ice and consequently is consistent with increasing melt; (iii) a higher MTP in early autumn (September) (as has occurred since 2003) implies higher precipitation (in this season mainly as rainfall), something generally related to sea ice melt; (iv) a higher MTP in late autumn and early winter (as has occurred since 2003) implies higher precipitation (in this season mainly as snowfall), enhancing thermal insulation and thus reducing sea ice growth in (Leppäranta, 1993). The rigorous checking of these implications merits further analysis but it is out of the scope of this paper since it would imply knowing details over the precipitation form (snow or rain) for the different Arctic regions with good temporal and geographical resolution, and even to analyse specific precipitation episodes to know if these are responsible for flooding or not.…”

Advances in understanding and parameterization of small-scale physical processes in the marine Arctic climate system: a review

“…This requires, however, a good vertical resolution. Climate and NWP models have traditionally used a single snowpack layer, but a high vertical resolution in snow and ice models has been revealed to be important for correctly simulating light scattering coefficients , surface albedo , the onset of ice melt (Cheng et al, 2008b), sub-surface grain metamorphism and melt (Dadic et al, 2008;Cheng et al, 2008a, b), the vertical profile of thermal conductivity (Dadic et al, 2008), and deep snowpack conditions (Dutra et al, 2012). The increase in vertical resolution has yielded a fundamental improvement in the treatment of the penetration of shortwave radiation in snow and sea ice (Briegleb and Light, 2007;Light et al, 2008).…”