Factors influencing the climatological mixed layer depth in the South China Sea: numerical simulations

The mixed layer depth (MLD) in the upper ocean is an important physical parameter for describing the upper ocean mixed layer. We analyzed several major factors influencing the climatological mixed layer depth (CMLD), and established a numerical simulation in the South China Sea (SCS) using the Regional Ocean Model System (ROMS) with a high-resolution (1/12°×1/12°) grid nesting method and 50 vertical layers. Several ideal numerical experiments were tested by modifying the existing sea surface boundary conditions. Especially, we analyzed the sensitivity of the results simulated for the CMLD with factors of sea surface wind stress (SSWS), sea surface net heat flux (SSNHF), and the difference between evaporation and precipitation (DEP). The result shows that of the three factors that change the depth of the CMLD, SSWS is in the first place, when ignoring the impact of SSWS, CMLD will change by 26% on average, and its effect is always to deepen the CMLD; the next comes SSNHF (13%) for deepening the CMLD in October to January and shallowing the CMLD in February to September; and the DEP comes in the third (only 2%). Moreover, we analyzed the temporal and spatial characteristics of CMLD and compared the simulation result with the ARGO observational data. The results indicate that ROMS is applicable for studying CMLD in the SCS area.     

Effects of the attitude of dominant joints on the mobility of translational landslides

Landslides - Geological structures and ground undulation affect the mobility of translational landslides. Combining field investigation, back-analysis, and numerical simulation, we explore the role...     

An Economical Approach to Four-dimensional Variational Data Assimilation

Four-dimensional variational data assimilation (4DVar) is one of the mostpromising methods to provide optimal analysis for numerical weatherprediction (NWP). Five national NWP centers in the world have successfullyapplied 4DVar methods in their global NWPs, thanks to the increment methodand adjoint technique. However, the application of 4DVar is still limited bythe computer resources available at many NWP centers and researchinstitutes. It is essential, therefore, to further reduce the computationalcost of 4DVar. Here, an economical approach to implement 4DVar is proposed,using the technique of dimension-reduced projection (DRP), which is called``DRP-4DVar. The proposed approach is based on dimension reduction usingan ensemble of historical samples to define a subspace. It directly obtainsan optimal solution in the reduced space by fitting observations withhistorical time series generated by the model to form consistent forecaststates, and therefore does not require implementation of the adjoint oftangent linear approximation.To evaluate the performance of the DRP-4DVar on assimilating different typesof mesoscale observations, some observing system simulation experiments areconducted using MM5 and a comparison is made between adjoint-based 4DVar andDRP-4DVar using a 6-hour assimilation window.     

青海乌兰盆地东缘断裂带的新活动特征

在青海乌兰盆地东缘山前冲洪积扇上新发现了一条长约 2 2km的逆冲断裂带 ,该断裂带是NNW向的鄂拉山右旋走滑断裂带北段西侧的次级挤压构造。其新活动受主断裂带的制约和影响 ,地貌上表现为明显的正向断层陡坎。晚更新世以来其垂直滑动速率为 0 11～ 0 17mm/a ,全新世晚期的垂直滑动速率为 0 35mm/a。综合探槽剖面及断层陡坎年代可以确定四次古地震事件 ,其年代分别为距今 2 4 6 5 0± 85 0a、 14 2 0 0± 70 0a、 5 2 0 0±5 2 0a和 2 2 5 0± 380a ,古地震活动具有不均匀性。     

西秦岭北缘断裂带特征地震平均复发间隔的确定和地震危险性评价

时间相依的地震危险性概率评估方法是最近10a来逐渐发展起来的，是一种将已获得的定量地质资料运用于活动断裂中—长期地震潜势概率评估的方法，从而使得在缺乏历史记载或仪器记录资料，但已获得断层平均滑动速率、同震位错、古地震年代序列等资料的活动断裂段上评估未来的发震概率成为可能。在定量计算活动断裂未来地震危险性的过程中，作为输入参数之一的特征地震平均复发间隔是一个至关重要的参数，它的确定将直接影响到概率计算的结果。对研究断裂上已获得的历史地震资料(H)、地质资料(G)和古地震资料(P)，笔采用了时间可预报(T)和准周期(Q)两种模式分别计算其平均复发间隔，比单一的只假定一种复发模式计算更具有完善性和可靠性。在叙述该方法的同时，以西秦岭北缘断裂为例，详细阐述了该断裂上特征地震平均复发间隔的确定，并在此基础上对西秦岭北缘断裂未来地震潜势作了定量评估。     

冷水坑矿田层状富铅锌矿赋矿围岩——铁锰碳酸岩角砾岩物质来源及成因分析

冷水坑矿田具有浅部斑岩型矿体与深部层状矿体的复杂组合,深部层状矿体赋存于上侏罗统打鼓顶组晶屑凝灰岩所夹的(铁锰)碳酸岩角砾岩层中。从(铁锰)碳酸岩角砾岩的基本地质特征入手,论述和分析了(铁锰)碳酸岩角砾岩的主要物质成分组成、分布、产状及与矿体关系等特点,结合矿物X-射线粉晶分析、碳-氧同位素和氢-氧同位素佐证,认为(铁锰)碳酸岩角砾岩为深水湖泊相火山-沉积成因,与层状矿体形成密切相关,后期斑岩岩浆就位及其流体活动对早期火山沉积碳酸岩层叠加改造,从而形成了与斑岩具有成因联系的层状富铅锌银矿床。     

The Structure of Background-error Covariance in a Four-dimensional Variational Data Assimilation System: Single-point Experiment

A four dimensional variational data assimilation (4DVar) based on a dimension-reduced projection (DRP-4DVar) has been developed as a hybrid of the 4DVar and Ensemble Kalman filter (EnKF) concepts. Its good flow-dependent features are demonstrated in single-point experiments through comparisons with adjoint-based 4DVar and three-dimensional variational data (3DVar) assimilations using the fifth-generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5). The results reveal that DRP-4DVar can reasonably generate a background error covariance matrix (simply B-matrix) during the assimilation window from an initial estimation using a number of initial condition dependent historical forecast samples. In contrast, flow-dependence in the B-matrix of MM5 4DVar is barely detectable. It is argued that use of diagonal estimation in the B-matrix of the MM5 4DVar method at the initial time leads to this failure. The experiments also show that the increments produced by DRP-4DVar are anisotropic and no longer symmetric with respect to observation location due to the effects of the weather trends captured in its B-matrix. This differs from the MM5 3DVar which does not consider the influence of heterogeneous forcing on the correlation structure of the B-matrix, a condition that is realistic for many situations. Thus, the MM5 3DVar assimilation could only present an isotropic and homogeneous structure in its increments.     

A new method for multi-point pollution source identification

对于污染源源项特征(数量,位置及排放强度)的快速且精确估计是污染事件应急响应的关键.与单点源估计相比,多点源的重建更具挑战性.本文提出了一种新的针对于多点源污染事件的两步反演算法,该算法通过结合大气化学模式与有限的浓度观测数据以实现对于未知数量的多点源的准确估计.在其计算过程中,无需任何未知量的先验信息,且可以自动识别污染源的数量,并确定每一个污染源的位置及强度.本文通过使用若干组理想试验验证了算法的适用性,试验结果表明,该算法可准确估计单点源,两点源和三点源的个数及位置,强度的估计误差可基本忽略.且该算法的估计精度和计算效率不会随着点源个数的增加而减弱.     

Application and Characteristic Analysis of the Moist Singular Vector in GRAPES-GEPS

The singular vector(SV) initial perturbation method can capture the fastest-growing initial perturbation in a tangent linear model(TLM). Based on the global tangent linear and adjoint model of GRAPES-GEPS(Global/Regional Assimilation and Prediction System—Global Ensemble Prediction System), some experiments were carried out to analyze the structure of the moist SVs from the perspectives of the energy norm, energy spectrum, and vertical structure. The conclusions are as follows: The evolution of ...     

Application of the Hilbert–Huang Transform to the Estimation of Air-Sea Turbulent Fluxes

The Hilbert–Huang transform (HHT) is applied to analyzing the turbulent time series obtained within the atmospheric boundary layer over the ocean. A method based on the HHT is introduced to reduce the influence of non-turbulent motions on the eddy-covariance based flux by removing non-turbulent modes from the time series. The scale dependence of the flux is examined and a gap mode is identified to distinguish between turbulent modes and non-turbulent modes. To examine the effectiveness of this method it is compared with three conventional methods (block average, moving-window average, and multi-resolution decomposition). The data used are from three sonic anemometers installed on a moored buoy at about 6, 4 and 2.7 m height above the sea surface. For each method, along-wind and cross-wind momentum fluxes and sensible heat fluxes at the three heights are calculated. According to the assumption of a constant-flux layer, there should be no significant difference between the fluxes at the three heights. The results show that the fluxes calculated using HHT exhibit a smaller difference and higher correlation than the other methods. These results support the successful application of HHT to the estimation of air-sea turbulent fluxes.