A global wave parameter database for geophysical applications. Part 1: Wave-current–turbulence interaction parameters for the open ocean based on traditional parameterizations

Ocean surface mixing and drift are influenced by the mixed layer depth, buoyancy fluxes and currents below the mixed layer. Drift and mixing are also functions of the surface Stokes drift U_ss, volume Stokes transport T_S, a wave breaking height scale H_swg, and the flux of energy from waves to ocean turbulence Φ_oc. Here we describe a global database of these parameters, estimated from a well-validated numerical wave model, that uses traditional forms of the wave generation and dissipation parameterizations, and covers the years 2003–2007. Compared to previous studies, the present work has the advantage of being consistent with the known physical processes that regulate the wave field and the air–sea fluxes, and also consistent with a very large number of in situ and satellite observations of wave parameters. Consequently, some of our estimates differ significantly from previous estimates. In particular, we find that the mean global integral of Φ_oc is 68 TW, and the yearly mean value of T_S is typically 10–30% of the Ekman transport, except in well-defined regions where it can reach 60%. We also have refined our previous estimates of U_ss by using a better treatment of the high frequency part of the wave spectrum. In the open ocean, U_ss  0.013U₁₀, where U₁₀ is the wind speed at 10 m height.     

防海胆食害藻礁的设计及实验研究

人工藻礁是进行藻场建设的重要手段,但由于海胆等食藻类生物的摄食,将会影响藻类的生长,从而影响人工藻场的建设效果.为解决人工藻场建设中海胆的食害问题,从礁体自身设计出发,实验设计了8种不同形状的藻礁,选用光棘球海胆和中间球海胆为实验对象,观察比较了不同形状藻礁对海胆攀爬的阻碍效果,实验发现:侧周面为锯齿形或侧周面缠挂多孔柔性材料的礁型可有效阻止海胆攀爬,起到防止海胆摄食礁顶藻类的目的.研究结果为人工藻礁的设计提供了参考依据.     

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 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.     

Effects of nutritional factors on the growth and heterotrophic eicosapentaenoic acid production of diatom <Emphasis Type="Italic">Nitzschia laevis</Emphasis>

The effects of several nutritional factors on the growth and eicosapentaenoic acid (EPA) production of diatom Nitzschia laevis were studied. 4 LDM (quadrupled concentration of the nutrient salt) was the optimal concentration of nutrient salt for the growth and EPA production of N. laevis. The growth of N. laevis was inhibited when the glucose concentration was either lower than 10 gL⁻¹ or higher than 15 gL⁻¹. Both sodium nitrate and urea were good nitrogen sources for the growth and EPA production, while ammonium chloride seriously decreased the dry cell weight (DW) and the EPA content. Silicate seriously influenced the growth of N. laevis. The maximum DW of 2.34 gL⁻¹ was obtained in the presence of 150 mgL⁻¹ Na₂SiO₃·9H₂O. The EPA content remained almost the same when the silicate concentration was lower than 150 mgL⁻¹; however, higher silicate concentrations resulted in a steady decrease of EPA content. Low medium salinity (⩽29) did not seem to influence the DW of N. laevis, and high salinity resulted in a decrease of DW. The highest EPA content (4.08%) and yield (110 mgL⁻¹) were observed at the salinity of 36 and 29, respectively.     

Study on the isotherms of the interaction between suspended particles and Cu (II) in the Huanghe River

The isotherms of the interaction between the suspended particles and Cu²⁺, and the effects of lysine and asparaginic acid on the isotherms in the Huanghe (Yellow) River were studied by applying the theory and method of interfacial stepwise ion/coordination particle exchange. We obtained a new stepped river isotherm, formed by two curves joined together with a “plateau” in the middle. The adsorption equilibrium constantsK ₁ andK ₂ were calculated by using the isothermal equation of surface stepwise ion exchange. Amino acid in small amount promotes exchange adsorption of the suspended particles with Cu²⁺. The degree of promotive action relates to the isoelectric point of amino acid. The promotive effect of lysine is bigger than that of asparaginic acid. Project 29361001 supported by NSFC.     

EXERCISE IN DOWNSCALING ON SEA SURFACE TEMPERATURE ALONG CHINESE COAST

ＩＮＴＲＯＤＵＣＴＩＯＮＴｈｅｍｏｎｓｏｏｎｈａｓａｃｉｒｃｕｌａｔｉｏｎｆｅａｔｕｒｅｔｈａｔｉｓｐｌａｎｅｔａｒｙｉｎｓｃａｌｅａｎｄａｎｉｄｅｎｔｉｆｉａｂｌｅｓｉｇｎａｌｒｅｇａｒｄｉｎｇｉｔｓｓｕｂｓｅｑｕｅｎｔｉｎｔｅｎｓｉｔｙｓｏｍｅｎｉｎｅｍｏｎｔｈｓｐｒｉｏｒｔｏｔｈｅａｃｔｉｖｅｓｔａｇｅｏｆｔｈｅｓｕｍｍｅｒｍｏｎｓｏｏｎ(ＷｅｂｓｔｅｒａｎｄＹａｎｇ,1992).Ｆｕｒｔｈｅｒｍｏｒｅ,ｔｈｅｍａｇｎｉｔｕｄｅｏｆｔｈｅｍｏｎｓｏｏｎｖａｒｉａｂｉｌｉｔｙｉｓｓｕｂｓｔａｎｔｉａ…     

Total lipid and fatty acid composition of eight strains of marine diatoms

Fatty acid composition and total lipid content of 8 strains of marine diatoms (Nitzschia frustrula, Nitzschia closterium, Nitzschia incerta, Navicula pelliculosa, Phaeodactylum tricornutum, Synedra fragilaroides) were examined. The microalgae were grown under defined conditions and harvested at the late exponential phase. The major fatty acids in most strains were 14∶0 (1.0%–6.3%), 16∶0 (13.5–26.4%), 16∶1n−7 (21.1%–46.3%) and 20∶5n−3 (6.5%–19.5%). The polyunsaturated fatty acids 16∶2n−4, 16∶3n−4, 16∶4n−1 and 20∶4n−6 also comprised a significant proportion of the total fatty acids in some strains. The characteristic fatty acid composition of diatoms is readily distinguishable from those of other microalgal groups. Significant concentration of the polyunsaturated fatty acid 20∶5n−3 (eicosapentaenoic acid) was present in each strain, with the highest proportion in B222 (19.5%). Project supported by the Hi-Tech “863” Programs of the China Ministry of Science and Technology (863-819-02-01).     

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.     

Transition Periods Between Sea Ice Concentration and Sea Surface Air Temperature in the Arctic Revealed by an Abnormal Running Correlation

This study used the synthetic running correlation coefficient calculation method to calculate the running correlation coefficients between the daily sea ice concentration(SIC) and sea surface air temperature(SSAT) in the Beaufort-Chukchi-East Siberian-Laptev Sea(BCEL Sea), Kara Sea and southern Chukchi Sea, with an aim to understand and measure the seasonally occurring changes in the Arctic climate system. The similarities and differences among these three regions were also discussed. There are periods in spring and autumn when the changes in SIC and SSAT are not synchronized, which is a result of the seasonally occurring variation in the climate system. These periods are referred to as transition periods. Spring transition periods can be found in all three regions, and the start and end dates of these periods have advancing trends. The multiyear average duration of the spring transition periods in the BCEL Sea, Kara Sea and southern Chukchi Sea is 74 days, 57 days and 34 days, respectively. In autumn, transition periods exist in only the southern Chukchi Sea, with a multiyear average duration of only 16 days. Moreover, in the Kara Sea, positive correlation events can be found in some years, which are caused by weather time scale processes.