Analysis of multi-dimensional SAR for determining the thickness of thin sea ice in the Bohai Sea

Flat thin ice (<30 cm thick) is a common ice type in the Bohai Sea, China. Ice thickness detection is important to offshore exploration and marine transport in winter. Synthetic aperture radar (SAR) can be used to acquire sea ice data in all weather conditions, and it is a useful tool for monitoring sea ice conditions. In this paper, we combine a multi-layered sea ice electromagnetic (EM) scattering model with a sea ice thermodynamic model to assess the determination of the thickness of flat thin ice in the Bohai Sea using SAR at different frequencies, polarization, and incidence angles. Our modeling studies suggest that co-polarization backscattering coefficients and the co-polarized ratio can be used to retrieve the thickness of flat thin ice from C- and X-band SAR, while the co-polarized correlation coefficient can be used to retrieve flat thin ice thickness from L-, C-, and X-band SAR. Importantly, small or moderate incidence angles should be chosen to avoid the effect of speckle noise.     

The seasonal foot printing mechanism of spring Arctic sea ice in the Bergen climate models

The influence of spring Arctic sea ice variability on the Pacific Decadal Oscillation(PDO) like sea surface temperature(SST) variability is established and investigated using an Atmosphere Ocean General Circulation Model(AOGCM) of the Bergen Climate Model version 2(BCM2). The spring Arctic sea ice variability affects the mid-latitudes and tropics through the propagation of the anomalous Eliassen-Palm(E-P) flux from the polar region to mid- and low-latitudes during boreal spring. The pathway includes anomalous upward wave activity, which propagates to the high troposphere from near the surface of the polar region, turns southward between 500 h Pa and 200 h Pa and extends downward between 50°N and 70°N, influencing the near surface atmospheric circulation. The alteration of the near surface atmospheric circulation then causes anomalous surface ocean circulation. These circulation changes consequently leads to the SST anomalies in the North Pacific which may persist until the following summer, named seasonal "foot printing" mechanism(SFPM).     

Measurements of sea ice thickness and its subice morphology analysis using ice-penetration radar in the Arctic Ocean

1　IntroductionSeaice ,asanimportantcomponentoftheArcticclimatesystem ,hasdrawnsignifi cantscientificinterest.Seaicethicknessanditsmorphologyhavedramaticimpactsono cean atmosphere iceinteractions(Wadhams 1 994;Barryetal.1 993 ;Dickson 1 999;PadhamsandNorman 2 0 0 0 ) ,whichdirectlyaffecttheexchangeprocessandspeedofheatandmassbetweentheoceanandtheatmosphere ,dominatethephysicalmechanicsfea turesofseaice ,andaffecttheseaicemovement&deformationaswellasicefreezing&meltingprocess(Hollandetal.1 99…     

Linkages between Arctic sea ice cover,large-scale atmospheric circulation,and weather and ice conditions in the Gulf of Bothnia,Baltic Sea

During years 1980/1981–2012/2013, inter-annual variations in sea ice and snow thickness in Kemi, in the northern coast of the Gulf of Bothnia, Baltic Sea, depended on the air temperature, snow fall, and rain. Inter-annual variations in the November—April mean air temperature, accumulated total precipitation, snow fall, and rain, as well as ice and snow thickness in Kemi and ice concentration in the Gulf of Bothnia correlated with inter-annual variations of the Pacific Decadal Oscillation(PDO), Arctic Oscillation(AO), North Atlantic Oscillation(NAO), Scandinavian Pattern(SCA), and Polar / Eurasian Pattern(PEU). The strong role of PDO is a new finding. In general, the relationships with PDO were approximately equally strong as those with AO, but rain and sea ice concentration were better correlated with PDO. The correlations with PDO were, however, not persistent; for a study period since 1950 the correlations were much lower. During 1980/1981—2012/2013, also the Pacific / North American Pattern(PNA) and El Nino–Southern Oscillation(ENSO) had statistical connections with the conditions in the Gulf of Bothnia, revealed by analyzing their effects combined with those of PDO and AO. A reduced autumn sea ice area in the Arctic was related to increased rain and total precipitation in the following winter in Kemi. This correlation was significant for the Pan-Arctic sea ice area in September, October, and November, and for the November sea ice area in the Barents / Kara seas.     

Detection and monitoring of new-ice in the East Greenland Sea using the SeaWinds scatterometer

Space borne radar scatterometers are primarily designed to measure the wind vector over the world ocean; yet they also provide useful information on sea ice type and extent. In this paper, it is shown how the SeaWinds scatterometer can be used to detect new sea ice at the very beginning of its growth. Taking advantage of the very good coverage of the East Greenland Sea by SeaWinds on board the QuickSCAT satellite it has been possible to detect the early stage of formation of the sea ice peninsula, named the Odden, and to monitor its evolution during March 2001. The early sea ice detection has been validated by using RADARSAT Synthetic Aperture Radar scenes. It is also shown that microwave radiometers, such as the Special Sensor Microwave Imager (SSM/I), which are used as standard sensors for sea ice monitoring, do not detect the very early stage of sea ice growth and lag behind new sea ice occurrence by about twelve to twenty four hours.     

Seasonal change of ice algal and phytoplankton assemblages in the Nella Fjord near Zhongshan Station, East Antarctica

The ice algal and phytoplankton assemblages were studied from Nella Fjord near Zhongshan Station, East Antarctica from April 12 to December 30, 1992. Algal blooms occurred about 3 cm thick on the bottom of sea ice in late April and mid November to early December respectively, and a phytoplankton bloom appeared in the underlying surface water in mid December following the spring ice algal bloom. The biomass in ice bottom was 1 to 3 orders of magnitude higher than that of surface water. Amphiprora kjellmanii, Berkeleya sp., Navicula glaciei, Nitzschia barkelyi, N. cylindrus /N. curta, N. lecointei and Nitzschia sp. were common in the sea ice temporarily or throughout the study period. The biomass in a certain ice segment was decreased gradually and the dominant species were usually succeeded as the season went on. Nitzschia sublineata and Dactyliosolen antarctica were two seasonal dominant species only observed in underlying water column. The assemblages between bottom of ice and underlying surface water were different except when spring ice algae bloomed. The evidence shows that the ice algal blooms occurred mainly by in situ growth of ice algae, and the phytoplankton bloom was mostly caused by the release of ice algae.     

Retrieval of Snow Depth on Sea Ice in the Arctic Using the FengYun-3B Microwave Radiation Imager

Snow on sea ice is a sensitive indicator of climate change because it plays an important role regulating surface and near surface air temperatures. Given its high albedo and low thermal conductivity, snow cover is considered a key reason for amplified warming in polar regions. This study focuses on retrieving snow depth on sea ice from brightness temperatures recorded by the Microwave Radiation Imager(MWRI) on board the FengYun(FY)-3 B satellite. After cross calibration with the Advanced Microwave Scanning Radiometer-EOS(AMSR-E) Level 2 A data from January 1 to May 31, 2011, MWRI brightness temperatures were used to calculate sea ice concentrations based on the Arctic Radiation and Turbulence Interaction Study Sea Ice(ASI) algorithm. Snow depths were derived according to the proportional relationship between snow depth and surface scattering at 18.7 and 36.5 GHz. To eliminate the influence of uncertainties in snow grain sizes and sporadic weather effects, seven-day averaged snow depths were calculated. These results were compared with snow depths from two external data sets, the IceBridge ICDIS4 and AMSR-E Level 3 Sea Ice products. The bias and standard deviation of the differences between the MWRI snow depth and IceBridge data were respectively 1.6 and 3.2 cm for a total of 52 comparisons. Differences between MWRI snow depths and AMSR-E Level 3 products showed biases ranging between-1.01 and-0.58 cm, standard deviations from 3.63 to 4.23 cm, and correlation coefficients from 0.61 to 0.79 for the different months.     

Snow and sea ice thermodynamics in the Arctic： Model validation and sensitivity study against SHEBA data

Evolution of the Arctic sea ice and its snow cover during the SHEBA year were simulated by applying a high-resolution thermodynamic snow/ice model （HIGHTSI）. Attention was paid to the impact of albedo on snow and sea ice mass balance, effect of snow on total ice mass balance, and the model vertical resolution. The SHEBA annual simulation was made applying the best possible external forcing data set created by the Sea Ice Model Intercomparison Project. The HIGHTSI control run reasonably reproduced the observed snow and ice thickness. A number of albedo schemes were incorporated into HIGHTSI to study the feedback processes between the albedo and snow and ice thickness. The snow thickness turned out to be an essential variable in the albedo parameterization. Albedo schemes dependent on the surface temperature were liable to excessive positive feedback effects generated by errors in the modelled surface temperature. The superimposed ice formation should be taken into account for the annual Arctic sea ice mass balance.     

Modeling seasonal variations of ocean and sea ice circulation in the Beaufort and Chukchi Seas： A model-data fusion study

A 3.8-kin Coupled Ice-Ocean Model （C1OM） was implemented to successfully reproduce many observed phenomena in the Beaufort and Chukchi seas, including the Bering-inflow-originated coastal current that splits into three branches： Alaska Coastal Water （ACW） , Central Channel, and Herald Valley branches. Other modeled phenomena include the Beaufort Slope Current （BSC） , the Beaufort Gyre, the East Siberian Current （ ESC）, mesoscale eddies, seasonal landfast ice, sea ice ridging, shear, and deformation. Many of these downscaling processes can only be captured by using a high-resolution CIOM, nested in a global climate model. The seasonal cycles for sea ice concentration, thickness, velocity, and other variables are well reproduced with Solid validation by satellite measurements. The seasonal cycles for upper ocean dynamics and thermodynamics are also well reproduced, which include the formation of the cold saline layer due to the injection of salt during sea ice formation, the BSC, and the subsurface upwelling in winter that brings up warm, even more saline Atlantic Water along the shelfbreak and shelf along the Beaufort coast.     

热带次表层海温对中国东部夏季气候的影响

热带海洋热状况是影响中国气候变化的主要因子之一,为了研究热带次表层海温如何影响中国气候,通过相关计算和合成分析等方法讨论了热带太平洋至印度洋次表层海温异常对中国东部夏季降水和温度的影响。结果表明:当冬季赤道东印度洋至西太平洋次表层海温偏暖(偏冷),中印度洋和东太平洋次表层海温偏冷(偏暖),夏季,长江中下游地区降水偏少(偏多),华南、华北和东北大部地区降水偏多(偏少);中国东部大范围高温(低温)。其可能的影响途径为,东亚夏季风环流对热带次表层海温异常的响应导致了其年际变化,进而引起中国东部夏季气候的异常分布。