Journal Article•
Winter snow cover on the sea ice of the Arctic Ocean at the Surface Heat Budget of the Arctic Ocean (SHEBA): Temporal evolution and spatial variability : The surface heat budget of arctic ocen (SHEBA)
TL;DR: In this article, the evolution and spatial distribution of the snow cover on the sea ice of the Arctic Ocean was observed during the Surface Heat Budget of Arctic Ocean (SHEBA) project, and two basic types of snow were present: depth hoar and wind slab.
Abstract: [1] The evolution and spatial distribution of the snow cover on the sea ice of the Arctic Ocean was observed during the Surface Heat Budget of the Arctic Ocean (SHEBA) project. The snow cover built up in October and November, reached near maximum depth by mid-December, then remained relatively unchanged until snowmelt. Ten layers were deposited, the result of a similar number of weather events. Two basic types of snow were present: depth hoar and wind slab. The depth hoar, 37% of the pack, was produced by the extreme temperature gradients imposed on the snow. The wind slabs, 42% of the snowpack, were the result of two storms in which there was simultaneous snow and high winds (>10 m s -1 ). The slabs impacted virtually all bulk snow properties emphasizing the importance of episodic events in snowpack development. The mean snow depth (n = 21,169) was 33.7 cm with a bulk density of 0.34 g cm -3 (n = 357, r 2 of 0.987), giving an average snow water equivalent of 11.6 cm, 25% higher than the amount record by precipitation gauge. Both depth and stratigraphy varied significantly with ice type, the greatest depth, and the greatest variability in depth occurring on deformed ice (ridges and rubble fields). Across all ice types a persistent structural length in depth variations of ∼20 m was found. This appears to be the result of drift features at the snow surface interacting with small-scale ice surface structures. A number of simple ways of representing the complex temporal and spatial variations of the snow cover in ice-ocean-atmosphere models are suggested.
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TL;DR: In this article, the authors present the best estimate of the thickness and volume of the Arctic Ocean ice cover from 10 ICESat campaigns that span a 5-year period between 2003 and 2008.
Abstract: [1] We present our best estimate of the thickness and volume of the Arctic Ocean ice cover from 10 Ice, Cloud, and land Elevation Satellite (ICESat) campaigns that span a 5-year period between 2003 and 2008. Derived ice drafts are consistently within 0.5 m of those from a submarine cruise in mid-November of 2005 and 4 years of ice draft profiles from moorings in the Chukchi and Beaufort seas. Along with a more than 42% decrease in multiyear (MY) ice coverage since 2005, there was a remarkable thinning of ∼0.6 m in MY ice thickness over 4 years. In contrast, the average thickness of the seasonal ice in midwinter (∼2 m), which covered more than two-thirds of the Arctic Ocean in 2007, exhibited a negligible trend. Average winter sea ice volume over the period, weighted by a loss of ∼3000 km3 between 2007 and 2008, was ∼14,000 km3. The total MY ice volume in the winter has experienced a net loss of 6300 km3 (>40%) in the 4 years since 2005, while the first-year ice cover gained volume owing to increased overall area coverage. The overall decline in volume and thickness are explained almost entirely by changes in the MY ice cover. Combined with a large decline in MY ice coverage over this short record, there is a reversal in the volumetric and areal contributions of the two ice types to the total volume and area of the Arctic Ocean ice cover. Seasonal ice, having surpassed that of MY ice in winter area coverage and volume, became the dominant ice type. It seems that the near-zero replenishment of the MY ice cover after the summers of 2005 and 2007, an imbalance in the cycle of replenishment and ice export, has played a significant role in the loss of Arctic sea ice volume over the ICESat record.
741 citations
TL;DR: In this paper, the authors investigated basin-scale mechanisms regulating anomalies in freshwater content (FWC) in the Beaufort Gyre (BG) of the Arctic Ocean using historical observations and data collected in 2003-2007.
Abstract: [1] We investigate basin-scale mechanisms regulating anomalies in freshwater content (FWC) in the Beaufort Gyre (BG) of the Arctic Ocean using historical observations and data collected in 2003–2007. Specifically, the mean annual cycle and interannual and decadal FWC variability are explored. The major cause of the large FWC in the BG is the process of Ekman pumping (EP) due to the Arctic High anticyclonic circulation centered in the BG. The mean seasonal cycle of liquid FWC is a result of interplay between the mechanical (EP) and thermal (ice transformations) factors and has two peaks. One peak occurs around June–July when the sea ice thickness reaches its minimum (maximum ice melt). The second maximum is observed in November–January when wind curl is strongest (maximum EP) and the salt input from the growing ice has not yet reached its maximum. Interannual changes in FWC during 2003–2007 are characterized by a strong positive trend in the region varying by location with a maximum of approximately 170 cm a � 1 in the center of EP influenced region. Decadal FWC variability in the period 1950–2000 is dominated by a significant change in the 1990s forced by an atmospheric circulation regime change. The center of maximum FWC shifted to the southeast and appeared to contract in area relative to the pre-1990s climatology. In spite of the areal reduction, the spatially integrated FWC increased by over 1000 km 3 relative to climatology.
445 citations
TL;DR: In this paper, the authors examined the impact of seasonal ice cover on sea ice albedo and found that the shift from a multi-year to seasonal cover has significant implications for the heat and mass budget of the ice and for primary productivity in the upper ocean.
Abstract: [1] There is an ongoing shift in the Arctic sea ice cover from multiyear ice to seasonal ice. Here we examine the impact of this shift on sea ice albedo. Our analysis of observations from four years of field experiments indicates that seasonal ice undergoes an albedo evolution with seven phases; cold snow, melting snow, pond formation, pond drainage, pond evolution, open water, and freezeup. Once surface ice melt begins, seasonal ice albedos are consistently less than albedos for multiyear ice resulting in more solar heat absorbed in the ice and transmitted to the ocean. The shift from a multiyear to seasonal ice cover has significant implications for the heat and mass budget of the ice and for primary productivity in the upper ocean. There will be enhanced melting of the ice cover and an increase in the amount of sunlight available in the upper ocean.
323 citations
TL;DR: In this article, a Subgrid SNOW Distribution (SSNOWD) submodel that explicitly includes subgrid snow-depth and snow-cover variability has been developed to improve the depiction of autumn through spring land-atmosphere interactions and feedbacks within regional and global weather, climate, and hydrologic models.
Abstract: To improve the depiction of autumn through spring land–atmosphere interactions and feedbacks within regional and global weather, climate, and hydrologic models, a Subgrid SNOW Distribution (SSNOWD) submodel that explicitly includes subgrid snow-depth and snow-cover variability has been developed. From both atmospheric and hydrologic perspectives, the subgrid snow-depth distribution is an important quantity to account for within large-scale models. In the natural system, these subgrid snow-depth distributions are largely responsible for the mosaic of snow-covered and snow-free areas that develop as the snow melts, and the impacts of these fractional areas must be quantified in order to realistically simulate grid-averaged surface fluxes. SSNOWD's formulation incorporates observational studies showing that snow distributions can be described by a lognormal distribution and the snow-depth coefficient of variation. Using an understanding of the physical processes that lead to these observed snow-dept...
309 citations
TL;DR: In this paper, retrieved freeboards from four ICESat campaigns (ON05, October/November 2005, FM06, February/March 2006, ON06,October/November 2006, and MA07, March/April 2007) are estimated using constructed fields of daily snow depth and compare them with ice drafts from moored upward-looking sonars.
Abstract: [1] Starting with retrieved freeboards from four ICESat campaigns (ON05, October/November 2005; FM06, February/March 2006; ON06, October/November 2006; and MA07, March/April 2007) we estimate their ice thicknesses using constructed fields of daily snow depth and compare them with ice drafts from moored upward-looking sonars. The methodologies, considerations, and assumptions used in the conversion of freeboard to ice thickness are discussed. The thickness distributions of the Arctic multiyear and seasonal ice covers are contrasted. Broadly, the resulting fields seem seasonally and interannually consistent in terms of thickness, growth and ice production. We find mean thicknesses of 2.15/2.46 m in ON05/FM06 and an overall thinner ice cover of 1.96/2.37 m in ON06/MA07. This represents a growth of ∼0.3 m and ∼0.4 m during the ∼4-month intervals of the ON05-FM06 and ON06-MA07 campaigns, respectively. After accounting for data gaps, we compute overall Arctic Ocean ice volumes of 11,318, 14,075, 10,626, and 13,891 km3 for the ON05, FM06, ON06, and MA07 campaigns, respectively. The higher total volume in ON05 (versus ON06) can be attributed to the higher multiyear ice coverage that fall: 37% versus 31%. However, the higher estimated ice production (less export) during the second year (3265 versus 2757 km3) is likely due to the higher growth rate over the larger expanse of seasonal sea ice during the fall and winter. Inside a 25-km radius of two mooring locations in the Beaufort Sea, the estimated mean ICESat ice drafts from ON05 and FM06 are within 0.5 m of those measured at the moorings.
296 citations
References
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Book•
01 Jan 1973
TL;DR: In this article, a thoroughly revised edition presents important methods in the quantitative analysis of geologic data, such as probability, nonparametric statistics, and Fourier analysis, as well as data analysis methods such as the semivariogram and the process of kriging.
Abstract: From the Publisher:
This thoroughly revised edition presents important methods in the quantitative analysis of geologic data. Retains the basic arrangement of the previous edition but expands sections on probability, nonparametric statistics, and Fourier analysis. Contains revised coverage of eigenvalues and eigenvectors, and new coverage of data analysis methods, such as the semivariogram and the process of kriging.
5,956 citations
Book•
01 Jan 1989TL;DR: In this paper, Krigeage and continuite spatiale were used for interpolation of a variogramme with anisotropic interpolation reference record created on 2005-06-20, modified on 2011-09-01.
Abstract: Keywords: Krigeage ; continuite spatiale ; variogramme ; incertitudes ; anisotropie ; interpolation Reference Record created on 2005-06-20, modified on 2011-09-01
4,371 citations
TL;DR: The Comprehensive Ocean-Atmosphere Data Set (COADS) as mentioned in this paper is the result of a cooperative project to collect global weather observations taken near the ocean surface since 1854, primarily from merchant ships, into a compact and easily used data set.
Abstract: Development is described of a Comprehensive Ocean-Atmosphere Data Set (COADS)—the result of a cooperative project to collect global weather observations taken near the ocean's surface since 1854, primarily from merchant ships, into a compact and easily used data set. As background, a historical overview is given of how archiving of these marine data has evolved from 1854, when systematic recording of shipboard meteorological and oceanographic observations was first established as an international activity. Input data sets used for COADS are described, as well as the processing steps used to pack input data into compact binary formats and to apply quality controls for identification of suspect weather elements and duplicate marine reports. Seventy-million unique marine reports for 1854–1979 were output from initial processing. Further processing is described, which created statistical summaries for each month of each year of the period, using 2° latitude × 2° longitude boxes. Monthly summary products are a...
1,084 citations
TL;DR: In this paper, a one-dimensional thermodynamic model of sea ice is presented that includes the effects of snow cover, ice salinity, and internal heating due to penetration of solar radiation.
Abstract: A one-dimensional thermodynamic model of sea ice is presented that includes the effects of snow cover, ice salinity, and internal heating due to penetration of solar radiation. The incoming radiative and turbulent fluxes, oceanic heat flux, ice salinity, snow accumulation, and surface albedo are specified as functions of time. The model is applied to the central Arctic.
1,058 citations