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.     

Numerical simulation research on multi-electrodes resistivity imaging survey array

Multi-electrodes Resistivity Imaging Survey （MRIS） is an array method of electrical survey. In practice how to choose a reasonable array is the key to get reliable survey results. Based on four methods of MRIS such as Wenner, Schlumberger, Pole-pole and Dipole-dipole the authors established the model, by studying the result of the forward numerical simulation modeling and inverse modeling, and analyzed the differences among the different forms of detection devices.     

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基于CCGIS的三维城市模璎数据生产

立足于生产实际阐述了一种基于CCGIS的三维城市生产工艺,重点说明了三维城市模型数据生产流程和控制,并结合恩施三维信息查询系统为例对该生产工艺进行验证。     

厦门市二调数据成果1980西安坐标转换

根据第二次全国土地调查有关技术文件的要求,各地汇总和提交的成果资料的数学基础必须是1980西安坐标系,而当前许多城市的土地调查工作是基于地方坐标系进行的.本文以厦门市为例,从技术路线、实现方法、精度检查等方面就地方坐标系下的调查成果如何转换为西安坐标系进行了较为详细的探讨,为其他地区的类似工作提供了有益的借鉴.     

A combined model of wind, wave, tide and storm surges

A combined numerical model of wind, wave, tide, and storm surges was built on the basis of the “wind field model in limited sea surface areas”. When used to forecast the sea surface wind, wave height and water level, it can describe them very well. Contribution No. 4108 from the Institute of Oceanology, Chinese Academy of Sciences. This work supported by Stress Project (KZ952-S1-420), Chinese Academy of Sciences; 863 Project (863-818-06-05), and (863-818-Q-07)     

卫星遥感与地球系统的时空耦合关系研究

本文从卫星的小型化、系列化以及信息共享的多样化等方面阐述了卫星遥感的发展趋势及特点,同时,探讨了地球巨系统的内涵及特点,并以干旱区为例,建立了时空耦合的概念模型,最后分析了卫星遥感技术在数字地球研究中的作用及意义.     

论伪距测量的多普勒效应

论述了多普勒效应对 GPS伪距测量的影响 ,建立了 GPS伪距测量多普勒改正的模型。研究表明 ,多普勒效应对伪距观测值的影响与伪距和伪距变化率的积成正比。伪距观测值的多普勒改正的符号与伪距变化率的符号相同。多普勒改正值在卫星升起和降落时最大 ,其最大值可达到 60 m左右 ;在卫星最高位置时最小 ,其值接近于 0。多普勒效应对伪距观测值的影响相对于卫星最高位呈负对称     

Hydrocarbon- Generating Model of the Area Covered With Volcanic Rock

The distribution of Oil & gas fields shows their close relationship with the most active tectonic regions. This is not a coincidence but having a scientific reasons. The crustal active regions, refer to the places where the active natural earthquake, volcanic activities, underground water happened, and the areas of the leaking off of natural gas to the surface of the crust. The magma of volcanic activities brings the organic "kitchen range body" hydrocarbon- generating model and inorganic genetic hydrocarbon to the regions covered by volcanic rock. Underground water brings a catalytic hydrocarbongenerating model for organic matter, and the leaking- off of H2 and CO2 contributes a synthetic hydrocarbon - generating model. Volcanic activities bring the assemblage of Source, Reservoir and Seal formed by the sediments and magma the sedimentary basins, and the hydrocarbon - generating system with a "water - volcano" binary structure is formed. All these conditions are favorable and excellent for the formation of oil & gas fields. The distribution of American oil & gas fields have very close relationship with the mines of Fe, Mn, Ct, Mo, W and V, deposits of Zn, Cu, V, Pb, Al and Hg, and the deposits of fluorite, sulfur, potassium salt, phosphate and halite, and the distribution of sulfate- chloride of river water. The reason why few oil & gas fields discovered in the regions covered by volcanic rock in western America maybe because of the view of "inconsistency between petroleum and volcano". Further more, It's very difficult to carry out a geophysical exploration in such kinds of regions.This paper examined a few hydrocarbon-generating models (systems) mentioned above and came up with some fresh ideas on the exploration in the areas covered with volcanic rocks.