渭河盆地地温场分布规律及其控制因素

本文以渭河盆地地温场为研究对象,在收集补充新地热井资料及分析测试样品的基础上,通过盆地深部结构、构造特征、地温场特征、热储层特征、地热资源量等分析,建立了盆地不同岩性岩石热导率与深度关系图版,确定了盆地地温场变化规律及地热田控制因素,提出了渭河盆地地热田形成模式。评价了盆地地热资源有利区,为盆地后续的开发利用提供了理论支持。研究认为渭河盆地热地温梯度分布在2.34～5.85℃/100m之间,平均地温梯度为3.50℃/100m,代表性大地热流68.33mw/m²,地温梯度及不同深度地层温度具有东高西低、南高北低的特点。热导率总体上具有随深度的增加,逐渐增大的规律,热导率随深度增加主要受压实程度增强控制。相同深度条件下泥岩热导率最低,砂岩热导率居中、白云岩热导率最高。渭河盆地主要为层状地热田,盆地内地热通过热传导及热对流两种方式进行传递,以热传导为主。渭河盆地地热资源丰富,热储层可分为三种类型:①新生界砂岩孔隙型;②下古生界碳酸盐岩岩溶型;③断裂型。渭河盆地地热资源有利区主要分布于西安凹陷、固市凹陷。盆地地温场及地热田分布与莫霍面、软流圈上隆、岩石圈厚度减薄的深部背景...     

沉积盆地中恢复地层剥蚀量的新方法

主要介绍了磷灰石裂变径迹分析法,沉积波动过程分析法和宇宙成因核素分析法等３种恢复和计算地层剥蚀量的新方法。它们的优点是不但给出一个剥蚀面造成的地层总的剥蚀量,还能详细刻画整个剥蚀过程,从而能计算出每一期构造抬升引起的地层剥蚀量。     

Non-Newtonian topographic relaxation on Europa

Models of topographic support on Europa by lateral shell thickness variations have previously assumed a Newtonian ice viscosity. Here I show that using a more realistic stress-dependent viscosity gives relaxation times which can be significantly different. Topography of wavelength 100 km cannot be supported by lateral shell thickness variations for ∼50 Myr, unless the shell thickness is <10 km or the ice grain size >10 mm. Shorter wavelength topography would require even thinner shells, but may be supported elastically. Global-scale variations in shell thickness, however, can be supported for geological timescales if the shell thickness is O(10 km).     

利用地基土应力分布原理确定砂垫层厚度

软弱土层场地若采用天然地基不能满足建筑物所需强度与沉降要求,采用换土撼砂法就可以提高地基的承载力。运用应力分布原理合理确定撼砂层厚度不仅可保证工程稳固性,并可节约投资和缩短工期。     

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.     

海冰形变对北极冬季CICE模式冰厚模拟结果的影响

海冰数值模式是研究海冰动力热力状态参量及之间联系的有效途径。目前对冰厚数值模拟结果的分析远远少于对海冰范围/面积和密集度的研究,对冰速与海冰形变对冰厚分布影响的研究也尚欠缺。本文利用Los Alamos sea ice model（CICE）海冰模式模拟了1980−2018年的北极海冰变化,并使用遥感、同化冰厚数据进行比对验证,分析了模拟冰速和海冰形变对冰厚的影响,计算了冰速的散度和切变偏差对冰厚偏差的贡献。结果显示,CICE对北极70°N以北区域平均冰厚和冰速的年际变化模拟基本合理,但模拟的平均冰厚和冰速多年变化趋势均小于同化数据的变化率;模拟和观测冰厚的空间分布差异与冰速和形变率的偏差有密切联系,主要表现为波弗特海的正偏差和北极中央区至弗拉姆海峡的负偏差。泛北极区域散度和切变偏差在3月之前对冰厚偏差的贡献在13%～16%之间变化,3−4月则由16%跃变至27%。散度偏差主导了11月、12月波弗特海区域的冰厚正偏差,切变偏差主导了冬季加拿大群岛以北海域和穿极流区域的冰厚负偏差。     

渤海海冰特征厚度分析

通过海冰生消机理和数值试验,讨论了渤海海冰特征厚度的存在条件;对不同厚度的海冰表面温度、冰面热量收支、冰面下热传导和太阳辐射透射量进行了对比分析,分析了渤海海冰向特征冰厚的动态演化过程;在不同气温、风速、相对湿度和海洋热通量等气象和水文条件下,对渤海特征冰厚进行了计算;讨论了海冰生消的动态平衡过程,分析了1997/1998年冬季辽东湾JZ20-2海域实测冰厚与特征冰厚的相互关系。对渤海特征冰厚分析将有助于渤海海冰数值模拟工作的开展和对不同重现期设计冰厚的推算。     

基于CMIP6数据的北极海冰未来分布和变化趋势分析

文章基于第六次国际耦合模式比较计划（CMIP6）的情景模式比较子计划的4种强迫情景,利用6个模式的输出数据对北极海区海冰密集度和海冰厚度的未来空间分布和长期变化趋势进行分析,并结合海面气温分析了其对海冰变化的可能影响。结果表明,不同强迫情景下2030年、2040年和2050年北极大部分海域海冰密集度均超过50%,海冰厚度约为1.5 m左右,其中东格陵兰海、巴伦支海、喀拉海和楚科奇海部分海域海冰密集度和厚度相对较小。2015—2050年两者整体均呈现下降的特征,部分海区的海冰密集度在高强迫情景下每年降低最大可超1%。2050年高强迫情景的季节变化结果显示,大部分海区冬春季海冰密集度超过90%,且各月均呈现下降趋势。海冰厚度方面,冬春夏大部分海区海冰厚度超过1 m,而秋季大部分海区海冰厚度小于等于0.5 m。12月至翌年5月全域海冰厚度以减小为主,其余月份却出现小范围海冰厚度增加的区域。至2100年的长期变化趋势方面,北冰洋中心区、东格陵兰海和楚科奇海海冰密集度和海冰厚度均随时间增加而减小,其中北冰洋中心区减小速率最大,同时三个海区海面气温将在未来持续增温。此外,海面气温的空间分布和长期变化趋势均与海冰密集度间存在较明显的相反变化特征,说明了气温对海冰的可能影响。本研究可为未来北极海冰在不同的强迫情景下的变化特征提供一定的参考。     

赤道东印度洋和孟加拉湾障碍层厚度的年际变化及其影响机制

Interannual variability(IAV) in the barrier layer thickness(BLT) and forcing mechanisms in the eastern equatorial Indian Ocean(EEIO) and Bay of Bengal(BoB) are examined using monthly Argo data sets during 2002–2017. The BLT during November–January(NDJ) in the EEIO shows strong IAV, which is associated with the Indian Ocean dipole mode(IOD), with the IOD leading the BLT by two months. During the negative IOD phase, the westerly wind anomalies driving the downwelling Kelvin waves increase the isothermal layer depth(ILD). Moreover, the variability in the mixed layer depth(MLD) is complex. Affected by the Wyrtki jet, the MLD presents negative anomalies west of 85°E and strong positive anomalies between 85°E and 93°E. Therefore, the BLT shows positive anomalies except between 86°E and 92°E in the EEIO. Additionally, the IAV in the BLT during December–February(DJF) in the BoB is also investigated. In the eastern and northeastern BoB, the IAV in the BLT is remotely forced by equatorial zonal wind stress anomalies associated with the El Ni?o-Southern Oscillation(ENSO). In the western BoB, the regional surface wind forcing-related ENSO modulates the BLT variations.