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81.
中国地球气候系统模式的发展及其模拟和预估 总被引:4,自引:0,他引:4
周天军 陈梓明 邹立维 陈晓龙 俞永强 王斌 包庆 鲍颖 曹剑 何编 胡帅 李立娟 李建 林岩銮 马利斌 乔方利 容新尧 宋振亚 唐彦丽 吴波 吴统文 辛晓歌 张贺 张明华 《气象学报》2020,78(3):332-350
地球气候系统模式是开展多学科、多圈层集成研究的重要平台,其发展是国际地学领域特别是全球变化领域竞争的前沿。中国的地球气候系统模式研发工作始于20世纪80年代,最近10年得到快速发展。研发格局上已经形成中国科学院、有关部委和高校三足鼎立的局面。文中在简要回顾中国地球气候系统模式早期发展历史的基础上,总结了中国参加第6次耦合模式比较计划的9个地球气候系统模式的技术特点,初步评估了中国4个模式对全球和东亚气候模拟的基本性能,分析了其在4种共享社会经济路径情景下对全球降水与温度的预估变化及其与平衡态气候敏感度的联系。最后,结合国际态势,从发展的角度提出未来中国气候模式研发工作需要加强的8个方向。 相似文献
82.
采用岩心分析数据与测井曲线相结合的方法,引入泥质含量参数配合声波时差进行多元线性回归分析。建立鄂尔多斯盆地研究区低孔低渗储层渗透率测井解释模型。根据泥质含量特征二次分类后进行多元线性回归,建立两个渗透率测井解释模型相关性良好,对应于研究区两种不同的沉积微相特征;测井解释渗透率与岩心实测渗透率匹配良好,解释模型满足研究区精度要求。在沉积微相背景约束条件下,对研究区储层选择合理参数多元线性回归建立渗透率测井解释模型,可以使低孔低渗储层渗透率解释达到良好应用效果。 相似文献
83.
土壤侵蚀量预报模型研究进展 总被引:38,自引:0,他引:38
土壤侵蚀模型是定量评价水土资源发展动态、指导综合治理规划、评价治理方案和措施的技术工具。根据建模的手段和方法,土壤侵蚀量预报模型有经验模型和物理成因模型两大类。根据建模对象的不同,土壤侵蚀模型又有坡面土壤侵蚀模型和流域土壤侵蚀模型之分。主要从这4个方面入手,介绍了国内外土壤侵蚀量预报模型研究的主要成就,指出了现有模型的不足。在总结前人工作的基础上,提出了我国土壤侵蚀模型今后的发展方向。 相似文献
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受海拔高、空气稀薄、气候无常、高差较大等自然条件的影响,高海拔地区进行测量作业与低海拔地区有很大差别。根据高海拔地区矿山特点,结合多年矿山控制测量、特别是高海拔矿山控制测量经验,讨论在高海拔地区矿山因地制宜地建立测量控制网的方法。 相似文献
87.
Jiafei Xiao Jingyang He Haiying Yang Chengquan Wu Jianbin Xu Yantao Li 《Resource Geology》2019,69(3):227-248
The Datangpo‐type manganese ore deposits, which formed during the Nanhuan (Cryogenian) period and are located in northeastern Guizhou and adjacent areas, are one of the most important manganese resources in China, showing good prospecting potential. Many middle‐to‐large deposits, and even super‐large mineral deposits, have been discovered. However, the genesis of manganese ore deposits is still controversial and remains a long‐standing source of debate; there are several viewpoints including biogenesis, hydrothermal sedimentation, gravity flows, cold‐spring carbonates, etc. Geochemical data from several manganese ore deposits show that there are positive correlations between Al2O3 and TiO2, SiO2, K2O, and Na2O, and strong negative correlations between Al2O3 and CaO, MgO, and MnO in black shales and manganese ores. U, Mo, and V show distinct enrichment in black shales and inconspicuous enrichment in Mn ores. Ba and Rb show strong positive correlations with K2O in manganese ores. Cu, Ni, and Zn show clear correlations with total iron in both manganese ores and black shales. ∑REE of manganese ores has a large range with evident positive Ce anomalies and positive Eu anomalies. The Post Archean Australian Shale (PAAS) normalized rare earth element (REE) distribution patterns of manganese ores present pronounced middle rare earth element (MREE) enrichment, producing “hat‐shaped” REE plots. ∑REE of black shales is more variable compared with PAAS, and the PAAS‐normalized REE distribution patterns appear as “flat‐shaped” REE plots, lacking evident anomaly characteristics. δ13C values of carbonate in both manganese ores and the black shales show observable negative excursions. The comprehensive analysis suggests that the black shales formed in a reducing and quiet water column, while the manganese ores formed in oxic muddy seawater, which resulted from periodic transgressions. There was an oxidation–reduction cycle of manganese between the top water body and the bottom water body caused by the transgressions during the early Datangpo, which resulted in the dissolution of manganese. Through the exchange of the euphotic zone water and the bottom water, and episodic inflow of oxygenated water, the manganese in the bottom water was oxidized to Mn‐oxyhydroxides and rapidly buried along with algae. In the early diagenetic stage, Mn‐oxyhydroxides were reduced and dissolved in the anoxic pore water and then transformed into Mn‐carbonates by reacting with HCO3? from the degradation of organic matter or from seawater. In the intervals between transgressions, continuous supplies of terrigenous clastics and the high productive rates of organic matter in the euphotic zone resulted in the deposition of the black shales enriched in organic matter. 相似文献
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The abilities of typhoon (TC) track prediction by a medium-range forecast model T213L31 at National Meteorological Center are analyzed and its ability to improve its TC forecasts is discussed. The results show that about 57% of the TCs could be predicted by T213L31 but the initial position errors are large.The 43% area without the prediction of TC tracks is concentrated between 13°N and 20°N and east of 120°E and lack of conventional observation data is the main reason for the absence of TC prediction in this area.The adding of bogus TC could improve the ability of TC track prediction when there is no TC vortex in the analysis field, but could only have positive effects on the short-range TC track prediction when there is TC vortex in the T213L31 analysis field. 相似文献
90.
The North Atlantic oscillation simulated by versions 2 and 4 of IAP/ LASG GOALS Model 总被引:6,自引:0,他引:6
The capabilities of two versions of the Global-Ocean-Atmosphere-Land-System model (i.e. GOALS-2 and GOALS-4) developed at State Key Laboratory of Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), are validated in terms of the simulations of the winter North Atlantic Oscillation (NAO), which is currently the subject of considerable scientific interest. The results show that both GOALS-2 and GOALS-4 exhibit a realistic NAO signal associated with relatively reasonable spatial pat-terns of sea level pressure, surface air temperature, and precipitation. Generally speaking, the associated pat-terns of precipitation in GOALSs match better with the observation in comparison with the case of surface temperature. For the imprint of NAO on the ocean, or perhaps a coupling between the two fluids, the asso-ciated tripole patterns of the North Atlantic SST anomaly are presented distinctly in GOALS-2, for GOALS-4 however, this is not the case. Spatially, the models’ main deficiencies appear to be that the simu-lated Icelandic lows shift northward apparently, which in turn result in the blemish of GOALSs in repro-ducing the accompanied surface wind anomalies. For the interannual and even longer time scale variations of DJF sea level pressure (SLP) over the North Atlantic region. GOALSs reproduce the center with the strongest variability rationally, but the intensities are far weaker than the observation. 相似文献