Structure of a Multi-Year Pressure Ridge

Three transverse profiles across a large pressure ridge located in the Beaufort Sea are presented. The ridge sail extended 4m. above sea level and the ridge keel 13 m. below. The cross-sections of the ridge keel can be described as roughly semi-circular. This suggests that form drag coefficients for flow transverse to the long axes of multi-year ridges may be as high as 0.8. Examination of several salinity, temperature and brine-volume profiles shows that much of the ice in the ridge has a very low salinity and is quite strong. All the inter-block voids that initially existed in the ridge at the time of its formation have been completely filled with ice. These observations, coupled with icebreaking experience indicate that multi-year ridges are, indeed, significant obstacles to even the largest icebreaking ship and should be avoided if possible. A very large first year ridge with a sail height of 12.8 m. is also described. This is the largest free-floating ridge yet measured

Cryosphere and climate

This chapter will discuss two main issues related to the cryosphere and climate. One is the effect of sea ice and salinity gradients on ocean circulation, and in particular the possible role of sea ice transport on the ocean conveyer belt. The other is the effect of the cryosphere on climate, and in particular in high-latitude warming under increased CO2. In understanding the role of the cryosphere in both cases, it is useful to elucidate two types of toy sea ice models. Neither of these represents reality, but both are useful for illustrating the archetypal features of sea ice that control much of its large-scale behavior. The first model is a simple slab thermodynamic sea ice model as presented by Thorndike. In this model there are no dynamical effects and the thickness of ice is determined by surface heat budget and oceanic heat flux considerations, with the thickness of the ice critically affecting the effective conductivity whereby heat is transferred from the bottom ice boundary to the upper ice boundary. In this model all of the sea ice characteristics are controlled by the vertical heat fluxes from the atmosphere and ocean into the ice. The thickness is controlled by the ice's becoming an effective insulator as it thickens, thus reducing conductive heat loss to the atmosphere. A second model emphasizes the effects of dynamics. It considers the ice pack to be a collection of floes moving in response to synoptic wind fields and ocean currents. These motions create semipermanent leads (open areas) over which ice can grow rapidly

Modeling transport and fate of riverine dissolved organic carbon in the Arctic Ocean

Author Posting. © American Geophysical Union, 2009. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Global Biogeochemical Cycles 23 (2009): GB4006, doi:10.1029/2008GB003396.The spatial distribution and fate of riverine dissolved organic carbon (DOC) in the Arctic may be significant for the regional carbon cycle but are difficult to fully characterize using the sparse observations alone. Numerical models of the circulation and biogeochemical cycles of the region can help to interpret and extrapolate the data and may ultimately be applied in global change sensitivity studies. Here we develop and explore a regional, three-dimensional model of the Arctic Ocean in which, for the first time, we explicitly represent the sources of riverine DOC with seasonal discharge based on climatological field estimates. Through a suite of numerical experiments, we explore the distribution of DOC-like tracers with realistic riverine sources and a simple linear decay to represent remineralization through microbial degradation. The model reproduces the slope of the DOC-salinity relationship observed in the eastern and western Arctic basins when the DOC tracer lifetime is about 10 years, consistent with published inferences from field data. The new empirical parameterization of riverine DOC and the regional circulation and biogeochemical model provide new tools for application in both regional and global change studies.I.M.M. and M.J.F. are grateful to National Science Foundation for financial support

Levels of Abnormal Prion Protein in Deer and Elk with Chronic Wasting Disease

Infected deer may pose a higher risk than elk for disease transmission

Study of the impact of ice formation in leads upon the sea ice pack mass balance using a new frazil and grease ice parameterization

Leads are cracks in sea ice that often form because of deformation. During winter months, leads expose the ocean to the cold atmosphere, resulting in supercooling and the formation of frazil ice crystals within the mixed layer. Here the authors investigate the role of frazil ice formation in leads on the mass balance of the sea ice pack through the incorporation of a new module into the Los Alamos sea ice model (CICE). The frazil ice module considers an initial cooling of leads followed by a steady-state formation of uniformly distributed single size frazil ice crystals that precipitate to the ocean surface as grease ice. The grease ice is pushed against one of the lead edges by wind and water drag that the authors represent through a variable collection thickness for new sea ice. Simulations of the sea ice cover in the Arctic and Antarctic are performed and compared to a model that treats leads the same as the open ocean. The processes of ice formation in the new module slow down the refreezing of leads, resulting in a longer period of frazil ice production. The fraction of frazil-derived sea ice increases from 10% to 50%, corresponding better to observations. The new module has higher ice formation rates in areas of high ice concentration and thus has a greater impact within multiyear ice than it does in the marginal seas. The thickness of sea ice in the central Arctic increases by over 0.5 m, whereas within the Antarctic it remains unchanged

Sea level variability in the Arctic Ocean from AOMIP models

Author Posting. © American Geophysical Union, 2007. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 112 (2007): C04S08, doi:10.1029/2006JC003916.Monthly sea levels from five Arctic Ocean Model Intercomparison Project (AOMIP) models are analyzed and validated against observations in the Arctic Ocean. The AOMIP models are able to simulate variability of sea level reasonably well, but several improvements are needed to reduce model errors. It is suggested that the models will improve if their domains have a minimum depth less than 10 m. It is also recommended to take into account forcing associated with atmospheric loading, fast ice, and volume water fluxes representing Bering Strait inflow and river runoff. Several aspects of sea level variability in the Arctic Ocean are investigated based on updated observed sea level time series. The observed rate of sea level rise corrected for the glacial isostatic adjustment at 9 stations in the Kara, Laptev, and East Siberian seas for 1954–2006 is estimated as 0.250 cm/yr. There is a well pronounced decadal variability in the observed sea level time series. The 5-year running mean sea level signal correlates well with the annual Arctic Oscillation (AO) index and the sea level atmospheric pressure (SLP) at coastal stations and the North Pole. For 1954–2000 all model results reflect this correlation very well, indicating that the long-term model forcing and model reaction to the forcing are correct. Consistent with the influences of AO-driven processes, the sea level in the Arctic Ocean dropped significantly after 1990 and increased after the circulation regime changed from cyclonic to anticyclonic in 1997. In contrast, from 2000 to 2006 the sea level rose despite the stabilization of the AO index at its lowest values after 2000.This research is supported by the National Science Foundation Office of Polar Programs (under cooperative agreements OPP- 0002239 and OPP- 0327664) with the International Arctic Research Center, University of Alaska Fairbanks, and by the Climate Change Prediction Program of the Department of Energy’s Office of Biological and Environmental Research. The development of the UW model is also supported by NASA grants NNG04GB03G and NNG04GH52G and NSF grants OPP-0240916 and OPP-0229429

A model of the Arctic Ocean carbon cycle

Author Posting. © American Geophysical Union, 2011. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 116 (2011): C12020, doi:10.1029/2011JC006998.A three dimensional model of Arctic Ocean circulation and mixing, with a horizontal resolution of 18 km, is overlain by a biogeochemical model resolving the physical, chemical and biological transport and transformations of phosphorus, alkalinity, oxygen and carbon, including the air-sea exchange of dissolved gases and the riverine delivery of dissolved organic carbon. The model qualitatively captures the observed regional and seasonal trends in surface ocean PO4, dissolved inorganic carbon, total alkalinity, and pCO2. Integrated annually, over the basin, the model suggests a net annual uptake of 59 Tg C a−1, within the range of published estimates based on the extrapolation of local observations (20–199 Tg C a−1). This flux is attributable to the cooling (increasing solubility) of waters moving into the basin, mainly from the subpolar North Atlantic. The air-sea flux is regulated seasonally and regionally by sea-ice cover, which modulates both air-sea gas transfer and the photosynthetic production of organic matter, and by the delivery of riverine dissolved organic carbon (RDOC), which drive the regional contrasts in pCO2 between Eurasian and North American coastal waters. Integrated over the basin, the delivery and remineralization of RDOC reduces the net oceanic CO2 uptake by ~10%.This study has been carried out as part of ECCO2 and SASS (Synthesis of the Arctic System Science) projects funded by NASA and NSF, respectively. MM and MJF are grateful for support from the National Science Foundation (ARC-0531119 and ARC-0806229) for financial support. MM also acknowledges NASA for providing computer time, the use of the computing facilities at NAS center and also the Scripps post-doctoral program for further financial support that helped to complete the manuscript. RMK also acknowledges NOAA for support (NA08OAR4310820 and NA08OAR4320752).2012-06-1

No association of vitamin D metabolism-related polymorphisms and melanoma risk as well as melanoma prognosis: a case–control study

Melanoma is one of the most aggressive human cancers. The vitamin D system contributes to the pathogenesis and prognosis of malignancies including cutaneous melanoma. An expression of the vitamin D receptor (VDR) and an anti-proliferative effect of vitamin D in melanocytes and melanoma cells have been shown in vitro. Studies examining associations of polymorphisms in genes coding for vitamin D metabolism-related proteins (1α-hydroxylase [CYP27B1], 1,25(OH)2D-24hydroxylase [CYP24A1], vitamin D-binding protein [VDBP]) and cancer risk are scarce, especially with respect to melanoma. Mainly VDR polymorphisms regarding melanoma risk and prognosis were examined although other vitamin D metabolism-related genes may also be crucial. In our hospital-based case–control study including 305 melanoma patients and 370 healthy controls single nucleotide polymorphisms in the genes CYP27B1 (rs4646536), CYP24A1 (rs927650), VDBP (rs1155563, rs7041), and VDR (rs757343, rs731236, rs2107301, rs7975232) were analyzed for their association with melanoma risk and prognosis. Except VDR rs731236 and VDR rs2107301, the other six polymorphisms have not been analyzed regarding melanoma before. To further improve the prevention as well as the treatment of melanoma, it is important to identify further genetic markers for melanoma risk as well as prognosis in addition to the crude phenotypic, demographic, and environmental markers used in the clinic today. A panel of genetic risk markers could help to better identify individuals at risk for melanoma development or worse prognosis. We, however, found that none of the polymorphisms tested was associated with melanoma risk as well as prognosis in logistic and linear regression models in our study population

Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical-biogeochemical models

The relative skill of 21 regional and global biogeochemical models was assessed in terms of how well the models reproduced observed net primary productivity (NPP) and environmental variables such as nitrate concentration (NO3), mixed layer depth (MLD), euphotic layer depth (Zeu), and sea ice concentration, by comparing results against a newly updated, quality-controlled in situ NPP database for the Arctic Ocean (1959-2011). The models broadly captured the spatial features of integrated NPP (iNPP) on a pan-Arctic scale. Most models underestimated iNPP by varying degrees in spite of overestimating surface NO3, MLD, and Zeu throughout the regions. Among the models, iNPP exhibited little difference over sea ice condition (ice-free vs. ice-influenced) and bottom depth (shelf vs. deep ocean). The models performed relatively well for the most recent decade and towards the end of Arctic summer. In the Barents and Greenland Seas, regional model skill of surface NO3 was best associated with how well MLD was reproduced. . Regionally, iNPP was relatively well simulated in the Beaufort Sea and the central Arctic Basin, where in situ NPP is low and nutrients are mostly depleted. Models performed less well at simulating iNPP in the Greenland and Chukchi Seas, despite the higher model skill in MLD and sea ice concentration, respectively. iNPP model skill was constrained by different factors in different Arctic Ocean regions. Our study suggests that better parameterization of biological and ecological microbial rates (phytoplankton growth and zooplankton grazing) are needed for improved Arctic Ocean biogeochemical modeling