Fine-resolution simulation of surface current and sea ice in the Arctic Mediterranean Seas

A fine-resolution model is developed for ocean circulation simulation in the National Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Chinese Academy of Sciences, and is applied to simulate surface current and sea ice variations in the Arctic Mediterranean Seas. A dynamic sea ice model in elastic-viscous-plastic rheology and a thermodynamic sea ice model are employed. A 200-year simulation is performed and a dimatological average of a 10-year period (141st-150th) is presented with focus on sea ice concentration and surface current variations in the Arctic Mediterranean Seas. The model is able to simulate well the East Greenland Current, Beaufort Gyre and the Transpolar Drift, but the simulated West Spitsbergen Current is small and weak. In the March climatology, the sea ice coverage can be simulated well except for a bit more ice in east of Spitsbergen Island. The result is also good for the September scenario except for less ice concentration east of Greenland and greater ice concentration near the ice margin. The extra ice east of Spitsbergen Island is caused by sea ice current convergence forced by atmospheric wind stress.     

The changes of pigment contents and their environmental implications in the lake sediments of Ny-(A)lesund, Svalbard, the Arctic

According to palaeoclimatic and modern instrumental data, numerous studies have indicated that the Arctic climate has undergone a significant warming during the past 100 years, and this may lead to significant impact on the fragile lake ecosystem. In this study, we collected a lake sediment core from the Ny-(A)lesund of Svalbard and determined the concentrations of four pigments including chlorophyll derivatives, total carotenoids, oscillaxanthin and myxoxanthophyll in the sediments. Combined with other physical and chemical proxies such as calcium carbonate, total organic carbon, biogenic silicon etc., we have reconstructed the historical changes of lacustrine primary productivity in Ny-(A)lesund, especially for the past 100 years. The results showed that during the period of Little Ice Age (LIA), the climate was unfavorable for the growth of the lake algae, and thus the lacustrine productivity declined. This result was supported by the relatively low contents of pigment and biogenic silica in the sediments. In contrast, the contents of total organic carbon (TOC) and sediment pigments increased significantly in the upper 5 cm (~1890AD), reflecting the rapid growth of the lake algae, thus the great increase of lacustrine primary productivity, corresponding to the warming climate after LIA. However, the biogenic silica in the upper sediments still had a relatively low level, and this might be related to the growth competition with other algae species. Over the past 100 years, the ratio of Osc/Myx in the sediments decreased continuously, indicative of durative increase of myxoxanthophyll in blue-green algal pigments, and this might imply that the human activity had enhanced the nutrition level of the lake in the Arctic region.     

Ice concentration assimilation in a regional ice-ocean cou- pled model and its application in sea ice forecasting

A reasonable initial state of ice concentration is essential for accurate short-term forecasts of sea ice using ice-ocean coupled models. In this study, sea ice concentration data are assimilated into an operational ice forecast system based on a com- bined optimal interpolation and nudging scheme. The scheme produces a modeled sea ice concentration at every time step, based on the difference between observational and forecast data and on the ratio of observational error to modeled error. The impact and the effectiveness of data assimilation are investigated. Significant improvements to predictions of sea ice extent were obtained through the assimilation of ice concentration, and minor improvements through the adjustment of the upper ocean properties. The assimilation of ice thickness data did not significantly improve predictions. Forecast experiments show that the forecast accuracy is higher in summer, and that the errors on five-day forecasts occur mainly around the marginal ice zone.     

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.     

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…     

A coupled multi-category sea ice model and POM for Baffin Bay and the Labrador Sea

An overview of the seasonal variation of sea-ice cover in Baffin Bay and the Labrador Sea is given. A coupled ice-ocean model, CECOM, has been developed to study the seasonal variation and associated ice-ocean processes. The sea-ice component of the model is a multi-category ice model in which mean concentration and thickness are expressed in terms of a thickness distribution function. Ten categories of ice thickness are specified in the model. Sea ice is coupled dynamically and thermodynamically to the Princeton Ocean Model. Selected results from the model including the seasonal variation of sea ice in Baffin Bay, the North Water polynya and ice growth and melt over the Labrador Shelf are presented.     

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.     

A coupled ice-ocean ecosystem model for 1-D and 3-D applications in the Bering and Chukchi Seas

Primary production in the Bering and Chukchi Seas is strongly influenced by the annual cycle of sea ice. Here pelagic and sea ice algal ecosystems coexist and interact with each other. Ecosystem modeling of sea ice associated phytoplankton blooms has been understudied compared to open water ecosystem model applications. This study introduces a general coupled ice-ocean ecosystem model with equations and parameters for 1-D and 3-D applications that is based on 1-D coupled ice-ocean ecosystem model development in the landfast ice in the Chukchi Sea and marginal ice zone of Bering Sea. The biological model includes both pelagic and sea ice algal habitats with 10 compartments： three phytoplankton （pelagic diatom, flagellates and ice algae： D, F, and Ai） , three zooplankton （copepods, large zooplankton, and microzooplankton ： ZS, ZL, ZP） , three nutrients （ nitrate ＋ nitrite, ammonium, silicon ： NO3 , NH4, Si） and detritus （Det）. The coupling of the biological models with physical ocean models is straightforward with just the addition of the advection and diffusion terms to the ecosystem model. The coupling with a multi-category sea ice model requires the same calculation of the sea ice ecosystem model in each ice thickness category and the redistribution between categories caused by both dynamic and thermodynamic forcing as in the physical model. Phytoplankton and ice algal self-shading effect is the sole feedback from the ecosystem model to the physical model.     

A method of catchments health assessment under value-pressure model and its application in urbanized river network area: A case study in Shanghai,China

Catchments health assessment is fundamental to effective catchments management. Generally, an as-sessment method should be selected to reflect both the purpose of assessment and local characteristics. A trial in Shanghai was conducted to test the method for catchments health assessment in urbanized river network area. Seven indicators that described four dimensions of river, river network, land use and function, and local feature were used to assess catchments values; while possible change rate of urbanization and industrialization in the next 3 years were chosen for catchments pressure assessment in the value-pressure model. Factors related to catchments classi-fication, indicators measurement and protection priority have been considered in the development strategies for catchments health management. The results showed that value-pressure assessment was applicable in urbanized catchments health management, particularly when both human and catchments had multiple demands. As a result of over 30-year rapid urbanization, more than 70% of Shanghai river network area was still in a healthy condition with high catchments values, among them, 39.3% was under high pressure. Poor water quality, simplified river system and weakened local feature of river pattern had largely affected catchments health in Shanghai. Lack of long-term monitoring data would seriously restrict the development and validity of catchments health assessment.