Estimation of Sea Ice Thickness from SARAL/AltiKa in Drifting Orbit Phase

Abstract

Intra and inter-annual variations in the sea ice thickness are highly sensitive indicators of climatic variations undergoing in the earth’s atmosphere and oceans. This paper describes the method of estimating sea ice thickness using radar waveforms data acquired by SARAL/Altika mission during its drifting orbit phase from July 2016 onwards yielding spatially dense data coverage. Based on statistical analysis of return echoes, classification of the surface has been carried out in three different types, viz. floe, lead and mixed. Time delay correction methods were suitably selected and implemented to make corrections in altimetric range measurements and thereby freeboard. By assuming hydrostatic equilibrium, freeboard data were converted into sea ice thickness. Results show that sea ice thickness varies from 4 to 5?m near ice shelves and 1 to 2.5?m in the marginal sea ice regions. Freeboard and sea ice thickness estimates were also validated using NASA’s Operation Ice Bridge (OIB) datasets. Freeboard measurements show very high correlation (0.97) having RMSE of 0.13. Overestimation of approximately 1–2?m observed in the sea ice thickness, which could be attributed to distance between AltiKa footprint and OIB locations. Moreover, sensitivity analysis shows that snow depth and snow density over sea ice play crucial role in the estimation of sea ice thickness.     

Sea Ice Leads Detection Using SARAL/AltiKa Altimeter

Sea ice leads play an essential role in ocean-ice-atmosphere exchange, in ocean circulation, geochemistry, and in ice dynamics. Their precise detection is crucial for altimetric estimations of sea ice thickness and volume. This study evaluates the performance of the SARAL/AltiKa (Satellite with ARgos and ALtiKa) altimeter to detect leads and to monitor their spatio-temporal dynamics. We show that a pulse peakiness parameter (PP) used to detect leads by Envisat RA-2 and ERS-1,-2 altimeters is not suitable because of saturation of AltiKa return echoes over the leads. The signal saturation results in loss of 6–10% of PP data over sea ice. We propose a different parameter—maximal power of waveform—and define the threshold to discriminate the leads. Our algorithm can be applied from December until May. It detects well the leads of small and medium size from 200 m to 3–4 km. So the combination of the high-resolution altimetric estimates with low-resolution thermal infra-red or radiometric lead fraction products could enhance the capability of remote sensing to monitor sea ice fracturing.     

Concurrent Use of OSCAT and AltiKa to Characterize Antarctic Ice Surface Features

Radar altimetry provides an important geophysical parameter, backscatter coefficient (σ₀), which is useful in studying target surface characteristics. Ku-band (Oceansat-2 scatterometer- OSCAT) and Ka-band (SARAL-AltiKa altimeter) data are concurrently used to characterize polar surface features over the Antarctic region. Maximum-likelihood classification has been employed to classify combined data set (AltiKa and OSCAT) for discrimination among sea ice, open water, and ice sheet (interior and exterior). The sea ice region obtained using the current approach has been compared with sea ice boundary derived from passive microwave data.     

Upper Ocean Four-Dimensional Variational Data Assimilation in the Arabian Sea and Bay of Bengal

A regional ocean circulation model with four-dimensional variational data assimilation scheme is configured to study the ocean state of the Indian Ocean region (65°E–95°E; 5°N–20°N) covering the Arabian Sea (AS) and Bay of Bengal (BoB). The state estimation setup uses 10 km horizontal resolution and 5 m vertical resolution in the upper ocean. The in-situ temperature and salinity, satellite-derived observations of sea surface height, and blended (in-situ and satellite-derived) observations of sea surface temperature alongwith their associated uncertainties are used for data assimilation with the regionally configured ocean model. The ocean state estimation is carried out for 61 days (1 June to 31 July 2013). The assimilated fields are closer to observations compared to other global state estimates. The mixed layer depth (MLD) of the region shows deepening during the period of assimilation with AS showing higher MLD compared to the BoB. An empirical forecast equation is derived for the prediction of MLD using the air–sea forcing variables as predictors. The surface and sub-surface (50 m) heat and salt budget tendencies of the region are also investigated. It is found that at the sub-surface, only the advection and diffusion temperature and salt tendencies are important.     

Recent satellite-derived sea ice volume flux through the Fram Strait: 2011–2015

The Fram Strait(FS) is the primary region of sea ice export from the Arctic Ocean and thus plays an important role in regulating the amount of sea ice and fresh water entering the North Atlantic seas. A 5 a(2011–2015) sea ice thickness record retrieved from Cryo Sat-2 observations is used to derive a sea ice volume flux via the FS. Over this period, a mean winter accumulative volume flux(WAVF) based on sea ice drift data derived from passivemicrowave measurements, which are provided by the National Snow and Ice Data Center(NSIDC) and the Institut Francais de Recherche pour d'Exploitation de la Mer(IFREMER), amounts to 1 029 km~3(NSIDC) and1 463 km~3(IFREMER), respectively. For this period, a mean monthly volume flux(area flux) difference between the estimates derived from the NSIDC and IFREMER drift data is –62 km~3 per month(–18×10~6 km~2 per month).Analysis reveals that this negative bias is mainly attributable to faster IFREMER drift speeds in comparison with slower NSIDC drift data. NSIDC-based sea ice volume flux estimates are compared with the results from the University of Bremen(UB), and the two products agree relatively well with a mean monthly bias of(5.7±45.9) km~3 per month for the period from January 2011 to August 2013. IFREMER-based volume flux is also in good agreement with previous results of the 1990 s. Compared with P1(1990/1991–1993/1994) and P2(2003/2004–2007/2008), the WAVF estimates indicate a decline of more than 600 km~3 in P3(2011/2012–2014/2015). Over the three periods, the variability and the decline in the sea ice volume flux are mainly attributable to sea ice motion changes, and second to sea ice thickness changes, and the least to sea ice concentration variations.     

Discussion/comments regarding “Trends in<Emphasis Type="Italic"> p</Emphasis>CO<Subscript>2</Subscript> and sea–air CO<Subscript>2</Subscript> flux over the global open oceans for the last two decades” by Y. Iida,A. Kojima,Y. Takatani,T. Nakano,H. Sugimoto,T. Midorikawa,M. Ishii

A paper by Iida et al. that was recently published in this journal (J Oceanogr 17:637–661, 2015) presented trends in the partial pressure of carbon dioxide in surface seawater and the estimated sea–air carbon dioxide flux over the global open oceans for the last two decades. The purpose of the present discussion is to demonstrate that the formula used by Iida et al. in their assessments can also be employed to estimate the sea–air carbon dioxide flux based on long-term wind statistics, i.e., based on data showing how the mean wind speed 10 m above the sea surface has varied over a long period. Examples of the application of this approach are given here, based on long-term wind statistics for the northern North Sea and the North West Shelf of Australia.     

基于HY-2A散射计数据的极区海冰范围反演方法及其评估

A sea ice extent retrieval algorithm over the polar area based on scatterometer data of HY-2A satellite has been established.Four parameters are used for distinguishing between sea ice and ocean with Fisher's linear discriminant analysis method.The method is used to generate polar sea ice extent maps of the Arctic and Antarctic regions of the full 2013–2014 from the scatterometer aboard HY-2A(HY-2A-SCAT) backscatter data.The time series of the ice mapped imagery shows ice edge evolution and indicates a similar seasonal change trend with total ice area from DMSP-F17 Special Sensor Microwave Imager/Sounder(SSMIS) sea ice concentration data.For both hemispheres,the HY-2A-SCAT extent correlates very well with SSMIS 15% extent for the whole year period.Compared with Synthetic Aperture Radar(SAR) imagery,the HY-2A-SCAT ice extent shows good correlation with the Sentinel-1 SAR ice edge.Over some ice edge area,the difference is very evident because sea ice edges can be very dynamic and move several kilometers in a single day.     

Rapid decrease in Antarctic sea ice in recent years

A 41-year Antarctic sea ice concentration(SIC) dataset derived from satellite passive microwave radiometers during the period of 1979–2019 has been used to analyze sea ice changes in recent decades. The trends of SIC and sea ice extent(SIE) are calculated during the periods of 1979–2019, 1979–2013, and 2014–2019. The trends show regionally dependent features. The SIC shows an increasing trend in most of the regions except the Bellingshausen Sea and Amundsen Sea(BA) during 1979–2019 and 1979–2013. The SIE trend shows a decreasing or decelerating trend in the period of 1979–2019((6 835±2 210) km2/a) compared with the 1979–2013 period((18 600±2 203) km~2/a). In recent years(2014–2019), the SIC and SIE have exhibited decreasing trends(–(34 567±3 521) km~2/month), especially in the Weddell Sea(WS) and Ross Sea(RS) during summer and autumn. The trends are related to regionally dependent causes. The analyses show that the SIC and SIE decreased in response to the warming trend of 2 m air temperature(T_(a-2m)) and have exhibited a good relationship with T_(a-2m) in summer and autumn in recent years. The sea ice decrease in the Antarctic is mainly caused by increases in absorbed energy and southward energy transportation in recent years, such as the increase in gained solar radiation and moist static energy from the south, which demonstrate notable regional characteristics. In the WS region, the local positive feedback from the additional absorbed solar radiation, resulting in warmer air and reduced sea ice, is the main reason for the sea ice decrease in recent years. The increase in southward energy transport has also favored a decrease in sea ice. In the RS region, the increase in southward-transported moist static energy has contributed to the decrease in sea ice, and the increases in cloud cover and longwave radiation have prevented sea ice growth.     

Interaction of an anticyclonic eddy with sea ice in the western Arctic Ocean: an eddy-resolving model study

The dramatic decline of summer sea ice extent and thickness has been witnessed in the western Arctic Ocean in recent decades, which hasmotivated scientists to search for possible factors driving the sea ice variability. An eddy-resolving, ice-ocean coupled model covering the entire Arctic Ocean is implemented, with focus on the western Arctic Ocean. Special attention is paid to the summer Alaskan coastal current (ACC), which has a high temperature (up to 5℃ ormore) in the upper layer due to the solar radiation over the open water at the lower latitude. Downstream of the ACC after Barrow Point, a surface-intensified anticyclonic eddy is frequently generated and propagate towards the Canada Basin during the summer season when sea ice has retreated away from the coast. Such an eddy has a warm core, and its source is high-temperature ACC water. A typical warm-core eddy is traced. It is trapped just below summer sea ice melt water and has a thickness about 60 m. Temperature in the eddy core reaches 2-3℃, and most water inside the eddy has a temperature over 1℃. With a definition of the eddy boundary, an eddy heat is calculated, which can melt 1 600 km² of 1mthick sea ice under extreme conditions.     

Dimethylsulphide and dimethylsulphoniopropionate in Antarctic sea ice and their release during sea ice melting

This study presents concentrations of dimethylsulphide (DMS) and its precursor compound dimethylsulphoniopropionate (DMSP) in a variety of sea ice and seawater habitats in the Antarctic Sea Ice Zone (ASIZ) during spring and summer. Sixty-two sea ice cores of pack and fast ice were collected from twenty-seven sites across an area of the eastern ASIZ (64°E to 110°E; and the Antarctic coastline north to 62°S). Concentrations of DMS in 81 sections of sea ice ranged from < 0.3 to 75 nM, with an average of 12 nM. DMSP in 60 whole sea ice cores ranged from 25 to 796 nM and showed a negative relationship with ice thickness (y = 125x^− 0.8). Extremely high DMSP concentrations were found in 2 cores of rafted sea ice (2910 and 1110 nM). The relationship of DMSP with ice thickness (excluding rafted ice) suggests that the release of large amounts of DMSP during sea ice melting may occur in discrete areas defined by ice thickness distribution, and may produce ‘hot spots’ of elevated seawater DMS concentration of the order of 100 nM. During early summer across a 500 km transect through melting pack ice, elevated DMS concentrations (range 21–37 nM, mean 31 nM, n = 15) were found in surface seawater. This band of elevated DMS concentration appeared to have been associated with the release of sea ice DMS and DMSP rather than in situ production by an ice edge algal bloom, as chlorophyll a concentrations were relatively low (0.09–0.42 μg l^− 1). During fast ice melting in the area of Davis station, Prydz Bay, sea ice DMSP was released mostly as extracellular DMSP, since intracellular DMSP was negligible in both hyposaline brine (5 ppt) and in a melt water lens (4–5 ppt), while extracellular DMSP concentrations were as high as 149 and 54 nM, respectively in these habitats. DMS in a melt water lens was relatively high at 11 nM. During the ice-free summer in the coastal Davis area, DMS concentrations in surface seawater were highest immediately following breakout of the fast ice cover in late December (range 5–14 nM), and then remained at relatively low concentrations through to late February (< 0.3–6 nM). These measurements support the view that the melting of Antarctic sea ice produces elevated seawater DMS due to release of sea ice DMS and DMSP.     

Sediment transport by sea ice in the Chukchi and Beaufort Seas: Increasing importance due to changing ice conditions?

Sediment-laden sea ice is widespread over the shallow, wide Siberian Arctic shelves, with off-shelf export from the Laptev and East Siberian Seas contributing substantially to the Arctic Ocean's sediment budget. By contrast, the North American shelves, owing to their narrow width and greater water depths, have not been deemed as important for basin-wide sediment transport by sea ice. Observations over the Chukchi and Beaufort shelves in 2001/02 revealed the widespread occurrence of sediment-laden ice over an area of more than 100,000 km² between 68 and 74°N and 155 and 170°W. Ice stratigraphic studies indicate that sediment inclusions were associated with entrainment of frazil ice into deformed, multiple layers of rafted nilas, indicative of a flaw-lead environment adjacent to the landfast ice of the Chukchi and Beaufort Seas. This is corroborated by buoy trajectories and satellite imagery indicating entrainment in a coastal polynya in the eastern Chukchi Sea in February of 2002 as well as formation of sediment-laden ice along the Beaufort Sea coast as far eastward as the Mackenzie shelf. Moored upward-looking sonar on the Mackenzie shelf provides further insight into the ice growth and deformation regime governing sediment entrainment. Analysis of Radarsat Synthetic Aperture (SAR) imagery in conjunction with bathymetric data help constrain the water depth of sediment resuspension and subsequent ice entrainment (>20 m for the Chukchi Sea). Sediment loads averaged at 128 t km^–2, with sediment occurring in layers of roughly 0.5 m thickness, mostly in the lower ice layers. The total amount of sediment transported by sea ice (mostly out of the narrow zone between the landfast ice edge and waters too deep for resuspension and entrainment) is at minimum 4×10⁶ t in the sampling area and is estimated at 5–8×10⁶ t over the entire Chukchi and Beaufort shelves in 2001/02, representing a significant term in the sediment budget of the western Arctic Ocean. Recent changes in the Chukchi and Beaufort Sea ice regimes (reduced summer minimum ice extent, ice thinning, reduction in multi-year ice extent, altered drift paths and mid-winter landfast ice break-out events) have likely resulted in an increase of sediment-laden ice in the area. Apart from contributing substantially to along- and across-shelf particulate flow, an increase in the amount of dirty ice significantly impacts (sub-)ice algal production and may enhance the dispersal of pollutants.     

基于卫星观测的2003-2013年北极海冰体积变化估算

北极海冰正处于快速减退时期,北极海冰体积变化是全球气候变化的重要指示因子。本文利用两种卫星高度计数据（ICESat和CryoSat-2）反演得到的海冰厚度数据,结合星载辐射计提取的海冰密集度数据以及海冰年龄数据,估算了近期的北极海冰体积以及一年冰和多年冰体积变化。CryoSat-2观测时段（2011-2013年）与ICESat观测时段（2003-2008年）相比,北极海冰体积在秋季（10-11月）和冬季（2-3月）分别减少了1 426 km3和412 km3。其中,秋季和冬季的一年冰的体积增加了702 km3和2 975 km3。相反,多年冰分别减少了2 108 km3和3 206 km3。多年冰的大量流失是造成北极海冰净储量下降的主要原因。     

基于MODIS热红外数据的渤海海冰厚度反演

Level ice thickness distribution pattern in the Bohai Sea in the winter of 2009–2010 was investigated in this paper using MODIS night-time thermal infrared imagery.The cloud cover in the imagery was masked out manually.Level ice thickness was calculated using MODIS ice surface temperature and an ice surface heat balance equation.Weather forcing data was from the European Centre for Medium-Range Weather Forecasts(ECMWF) analyses.The retrieved ice thickness agreed reasonable well with in situ observations from two off-shore oil platforms.The overall bias and the root mean square error of the MODIS ice thickness are –1.4 cm and 3.9 cm,respectively.The MODIS results under cold conditions(air temperature –10°C) also agree with the estimated ice growth from Lebedev and Zubov models.The MODIS ice thickness is sensitive to the changes of the sea ice and air temperature,in particular when the sea ice is relatively thin.It is less sensitive to the wind speed.Our method is feasible for the Bohai Sea operational ice thickness analyses during cold freezing seasons.     

Assessing the Measurement Consistency Between the Jason-2/AMR and SARAL/AltiKa/DFMR Microwave Radiometers Using Simultaneous Nadir Observations

SARAL/AltiKa has a Dual Frequency Microwave Radiometer (DFMR), and Jason-2 has an Advanced Microwave Radiometer (AMR). Both microwave radiometer sensors include a 23.8 GHz primary water sensing channel. The measurement consistencies between DFMR and AMR are important for establishing a consistent altimetry data set between SARAL/AltiKa and Jason-2 in order to accurately assess sea level rise in a long-term time series. This study investigates the measurement consistency in the 23.8 GHz channel between DFMR and AMR at the Simultaneous Nadir Overpasses (SNO's) between the two satellites and also at coldest ocean brightness temperature locations. Preliminary results show that while both instruments show no significant trends over the one year since the launch of SARAL, a consistent relative bias of 2.88 K (DFMR higher than AMR) with a standard deviation of 0.98 K is observed. The relative bias at the lowest brightness temperature from the SNO method (-3.82 K) is consistent with that calculated from coldest ocean method (-3.74 K). The relative bias exhibits strong latitude (and scene temperature) dependency, changing from -3.82 K at high latitudes to -0.92 K near the equator. There also exists an asymmetry between the northern and southern hemisphere. The relative bias increases toward the lower end of brightness temperature.     

Halocarbons associated with Arctic sea ice

Short-lived halocarbons were measured in Arctic sea–ice brine, seawater and air above the Greenland and Norwegian seas (~81°N, 2–5°E) in mid-summer, from a melting ice floe at the edge of the ice pack. In the ice floe, concentrations of C₂H₅I, 2-C₃H₇I and CH₂Br₂ showed significant enhancement in the sea ice brine, of average factors of 1.7, 1.4 and 2.5 times respectively, compared to the water underneath and after normalising to brine volume. Concentrations of mono-iodocarbons in air are the highest ever reported, and our calculations suggest increased fluxes of halocarbons to the atmosphere may result from their sea–ice enhancement. Some halocarbons were also measured in ice of the sub-Arctic in Hudson Bay (~55°N, 77°W) in early spring, ice that was thicker, colder and less porous than the Arctic ice in summer, and in which the halocarbons were concentrated to values over 10 times larger than in the Arctic ice when normalised to brine volume. Concentrations in the Arctic ice were similar to those in Antarctic sea ice that was similarly warm and porous. As climate warms and Arctic sea ice becomes more like that of the Antarctic, our results lead us to expect the production of iodocarbons and so of reactive iodine gases to increase.     

基于卫星高度计的北极海冰厚度变化研究

A modified algorithm taking into account the first year(FY) and multiyear(MY) ice densities is used to derive a sea ice thickness from freeboard measurements acquired by satellite altimetry ICESat(2003–2008). Estimates agree with various independent in situ measurements within 0.21 m. Both the fall and winter campaigns see a dramatic extent retreat of thicker MY ice that survives at least one summer melting season. There were strong seasonal and interannual variabilities with regard to the mean thickness. Seasonal increases of 0.53 m for FY the ice and 0.29 m for the MY ice between the autumn and the winter ICESat campaigns, roughly 4–5 month separation, were found. Interannually, the significant MY ice thickness declines over the consecutive four ICESat winter campaigns(2005–2008) leads to a pronounced thickness drop of 0.8 m in MY sea ice zones. No clear trend was identified from the averaged thickness of thinner, FY ice that emerges in autumn and winter and melts in summer. Uncertainty estimates for our calculated thickness, caused by the standard deviations of multiple input parameters including freeboard, ice density, snow density, snow depth, show large errors more than 0.5 m in thicker MY ice zones and relatively small standard deviations under 0.5 m elsewhere. Moreover, a sensitivity analysis is implemented to determine the separate impact on the thickness estimate in the dependence of an individual input variable as mentioned above. The results show systematic bias of the estimated ice thickness appears to be mainly caused by the variations of freeboard as well as the ice density whereas the snow density and depth brings about relatively insignificant errors.     

Performance evaluation of active wireline heave compensation systems in marine well logging environments

The basic functionality and performance of a new Schlumberger active wireline heave compensation system on the JOIDES Resolution was evaluated during the sea trial and a 3-year period of the IODP Phase II operations. A suite of software programs was developed to enable real-time monitoring of the dynamics of logging tools, and assess the efficiency of wireline heave compensation during downhole operations. The evaluation of the system effectiveness was performed under normal logging conditions as well as during stationary tests. Logging data were analyzed for their overall quality and repeatability, and to assess the reliability of high-resolution data such as formation microscanner (FMS) electrical images. This revealed that the system reduces 65–80 % of displacement or 88–98 % variance of downhole tool motion in stationary mode under heave conditions of ±0.2–1.5 m and water depths of 300–4,500 m in open holes. Under similar water/heave conditions, the compensator system reduces tool displacement by 50–60 %, or 75–84 % variance in downhole tool motion during normal logging operations. Such compensation efficiency (CE) is comparable to previous compensation systems, but using advanced and upgradeable technologies, and provides 50–85 % heave motion and heave variance attenuation. Moreover, logging down/up at low speeds (300–600 m/h) reduces the system’s CE values by 15–20 %, and logging down at higher speeds (1,000–1,200 m/h) eliminates CE values by 55–65 %. Considering the high quality of the logging data collected, it is concluded that the new system can provide an improved level of compensation over previous systems. Also, if practically feasible, future integration of downhole cable dynamics as an input feedback into the current system could further improve its compensation efficiency during logging operations.     

Bayesian classification of the ice cover of the Arctic seas

A classification of sea ice in the Arctic by age (multiyear; first-year; and first-year deformed ice, nilas, etc.) is developed based on the Bayesian approach using satellite radar data and taking into account regional peculiarities of these types of ice for different sectors of the Arctic. Estimations of a priori probabilities for each ice type, which are required for the use of the Bayesian classification, are obtained by the analysis of ice charts in the Arctic seas developed at the AARI in 2008–2013 using satellite data. A posterior probabilities are estimated visually by an expert. Types of sea ice distinguished by the expert on satellite images make it possible to create sample values of the radar-scattering cross section (RSCS). Examples of the proposed Bayesian classification of ice in the Laptev Sea according to Envisat satellite data are given.     

<Emphasis Type="Italic">In-situ</Emphasis> measured primary productivity of ice algae in Arctic sea ice floes using a new incubation method

Recent changes in climate and environmental conditions have had great negative effects such as decreasing sea ice thickness and the extent of Arctic sea ice floes that support ice-related organisms. However, limited field observations hinder the understanding of the impacts of the current changes in the previously ice-covered regions on sea ice algae and other ice-related ecosystems. Our main objective in this study was to measure recent primary production of ice algae and their relative contribution to total primary production (ice plus pelagic primary production). In-situ primary productivity experiments with a new incubation system for ice algae were conducted in 3 sea ice cores at 2 different ice camps in the northern Chukchi Sea, 2014, using a ¹³C and ¹⁵N isotope tracer technique. A new incubation system was tested for conducting primary productivity experiments on ice algae that has several advantages over previous incubation methods, enabling stable carbon and nitrogen uptake experiments on ice algae under more natural environmental conditions. The vertical C-shaped distributions of the ice algal chl-a, with elevated concentrations at the top and bottom of the sea ice were observed in all cores, which is unusual for Arctic sea ice. The mean chl-a concentration (0.05 ± 0.03 mg chl-a m^?3) and the daily carbon uptake rates (ranging from 0.55 to 2.23 mg C m^?2 d^?1) for the ice algae were much lower in this study than in previous studies in the Arctic Ocean. This is likely because of the late sampling periods and thus the substantial melting occurring. Ice algae contributed 1.5–5.7% of the total particulate organic carbon (POC) contents of the combined euphotic water columns and sea ice floes. In comparison, ice algae contributed 4.8–8.6% to the total primary production which is greater than previously reported in the Arctic Ocean. If all of the ice-associated productions were included, the contributions of the sea ice floes to the total primary production would be greater in the Arctic Ocean and their importance would be greater in the arctic marine ecosystems.     

The physical structures of snow and sea ice in the Arctic section of 150°-180°W during the summer of 2010

The physical structures of snow and sea ice in the Arctic section of 150°-180°W were observed on the basis of snow-pit, ice-core, and drill-hole measurements from late July to late August 2010. Almost all the investigated floes were first-year ice, except for one located north of Alaska, which was probably multi-year ice transported from north of the Canadian Arctic Archipelago during early summer. The snow covers over all the investigated floes were in the melting phase, with temperatures approaching 0℃ and densities of 295-398 kg/m3 . The snow covers can be divided into two to five layers of different textures, with most cases having a top layer of fresh snow, a round-grain layer in the middle, and slush and/or thin icing layers at the bottom. The first-year sea ice contained about 7%-17% granular ice at the top. There was no granular ice in the lower layers. The interior melting and desalination of sea ice introduced strong stratifications of temperature, salinity, density, and gas and brine volume fractions. The sea ice temperature exhibited linear cooling with depth, while the salinity and the density increased linearly with normalized depth from 0.2 to 0.9 and from 0 to 0.65, respectively. The top layer, especially the freeboard layer, had the lowest salinity and density, and consequently the largest gas content and the smallest brine content. Both the salinity and density in the ice basal layer were highly scattered due to large differences in ice porosity among the samples. The bulk average sea ice temperature, salinity, density, and gas and brine volume fractions were-0.8℃, 1.8, 837 kg/m3 , 9.3% and 10.4%, respectively. The snow cover, sea ice bottom, and sea ice interior show evidences of melting during mid-August in the investigated floe located at about 87°N, 175°W.