Data assimilation in a system with two scales—combining two initialization techniques

An ensemble Kalman filter (EnKF) is used to assimilate data onto a non-linear chaotic model, coupling two kinds of variables. The first kind of variables of the system is characterized as large amplitude, slow, large scale, distributed in eight equally spaced locations around a circle. The second kind of variables are small amplitude, fast, and short scale, distributed in 256 equally spaced locations. Synthetic observations are obtained from the model and the observational error is proportional to their respective amplitudes. The performance of the EnKF is affected by differences in the spatial correlation scales of the variables being assimilated. This method allows the simultaneous assimilation of all the variables. The ensemble filter also allows assimilating only the large-scale variables, letting the small-scale variables to freely evolve. Assimilation of the large-scale variables together with a few small-scale variables significantly degrades the filter. These results are explained by the spurious correlations that arise from the sampled ensemble covariances. An alternative approach is to combine two different initialization techniques for the slow and fast variables. Here, the fast variables are initialized by restraining the evolution of the ensemble members, using a Newtonian relaxation toward the observed fast variables. Then, the usual ensemble analysis is used to assimilate the large-scale observations.     

朝鲜半岛及华北上元古界-古生界沉积序列与碎屑锆石年代学记录及其构造属性分析

通过地层结构、沉积序列与碎屑锆石年代学记录等三方面的成因分析和区域对比,本文进一步探究了中-朝地块新元古代-古生代的构造属性及演化信息。研究指出,朝鲜半岛平南盆地、太白山盆地以及华北地块内部,其地层结构-沉积相序主要以寒武-奥陶系内陆架碳酸盐岩沉积、志留-泥盆系缺失、中上石炭统-二叠系海陆交互相含煤沉积为特征,并具有可对比的1.85Ga、2.5Ga以及1.15Ga、1.6Ga等碎屑锆石年龄峰值。而在临津江带、沃川带以及华北东南缘,则以泥盆-石炭系泥岩/片岩、中基性火山岩及火山碎屑岩、碳酸盐岩(透镜体)混杂发育为特征,总体显示外陆架沉积环境,且具有可对比的与地层时代接近的最小碎屑锆石年龄,这也是对沉积期较强构造-岩浆活动的反映。综合地层结构、相序、碎屑锆石年龄组成以及聚煤记录,提出朝鲜半岛与华北应属于统一的一级构造单元,即"中-朝板块";但朝鲜半岛西南部及华北东南缘毗邻板块边缘,因此其地层-沉积记录与板内存在差异,简单的一致性模式并不适用。     

Analysis of mass concentration of atmospheric particulate matter in a sandstorm course and its affecting factors in the Taklimakan Desert

During the course of a major sandstorm from April 17 to April 23, 2008 in the Taklimakan Desert, data pertaining to the mass concentrations of different-sized atmospheric particulate matter were observed continuously with Grimm 1.108, Thermo RP 1400a, TSP, and CAWS-600 instruments. The results showed that: (1) during the entire sandstorm process there were some differences between the daily mean particle concentration peaks and the hourly mean particle concentration peaks because the actual sandstorm lasted for only about 4 hr, whereas more particles were accumulated in the floating dust days before and after the actual sandstorm; (2) the intensity of the sandstorm was enhanced with the increase of wind speed, and this was related to the peak mass concentrations of atmospheric particulate matter; the wind speed directly affected the concentration of atmospheric particulate matter: the higher the wind speed, the higher the mass concentration (>0.23 μm was 39,496.5 μg/m³, and >20.0 μm was 5,390.7 μg/m³); (3) the concentration changes of PM₁₀ and TSP were also related to the course and intensity of the sandstorm; and (4) the mass concentration of atmospheric particulate matter had the following sequence during the dust weather: clear day < floating dust < floating and blowing dust < sandstorm. Temperature, relative humidity, and barometric pressure are important factors affecting the strength of storms, which could also indirectly affect the concentration change of atmospheric particulate matter.     

A Machine Learning-based Cloud Detection Algorithm for the Himawari-8 Spectral Image

Cloud Masking is one of the most essential products for satellite remote sensing and downstream applications. This study develops machine learning-based (ML-based) cloud detection algorithms using spectral observations for the Advanced Himawari Imager (AHI) onboard the Himawari-8 geostationary satellite. Collocated active observations from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) are used to provide reference labels for model development and validation. We introduce both daytime and nighttime algorithms that differ according to whether solar band observations are included, and the artificial neural network (ANN) and random forest (RF) techniques are adopted for comparison. To eliminate the influences of surface conditions on cloud detection, we introduce three models with different treatments of the surface. Instead of developing independent ML-based algorithms, we add surface variables in a binary way that enhances the ML-based algorithm accuracy by ~5%. Validated against CALIOP observations, we find that our daytime RF-based algorithm outperforms the AHI operational algorithm by improving the accuracy of cloudy pixel detection by ~5%, while at the same time, reducing misjudgment by ~3%. The nighttime model with only infrared observations is also slightly better than the AHI operational product but may tend to overestimate cloudy pixels. Overall, our ML-based algorithms can serve as a reliable method to provide cloud mask results for both daytime and nighttime AHI observations. We furthermore suggest treating the surface with a set of independent variables for future ML-based algorithm development.     

硫酸盐渍土膨胀规律的综合影响因素的试验研究

对含氯化钠硫酸盐渍土的膨胀规律作了综合影响因素的研究，首次提出了５因素盐胀率的计算公式，并得出了盐胀率的单因素和交互作用影响的规律；另外找出了某些因素的定量指标。     

Temporal vP/vS variation characteristics in different zones of China’s Capital Circle area before and after Wen’an earthquake

On July 4, 2006, an earthquake of MS5.1 took place in Wen’an, Hebei Province, just at the south center of China’s Capital Circle area digital seismograph network. It is the strongest event recorded ever since the network went into operation in 2002. We processed the vast amounts of phase data yielded by the 107 digital seismic stations between 2002~2007 using Wadati method. In order to improve the precision and stability of shear and compressional wave velocities (vP/vS) calculation, we impose a number of restrictions on the computation environment and condition, e.g., the earthquakes are densely concentrated, selected stations are limited in range, the number of stations in- volved in the computation is larger than 5 and linear fitting features high precision and small error. Under these restrictions, the study shows that vP/vS in and around Wen’an and Tangshan underwent a normal-low-normal proc- ess one year before Wen’an earthquake, vP/vS became obviously low and the low ratio lasted for about one year, meanwhile, little variation of vP/vS was seen in Xingtai, northwest of Beijing, southwest of Beijing, Beijing-Tianjin and Beijing; after the quake, the vP/vS returned normal in Wen’an and Tangshan. Error and stability analysis of the calculated result for vP/vS shows it is convincible that anomaly appeared in and around Wen’an and Tangshan be- fore Wen’an earthquake.     

Data Assimilation (4D-VAR) for Shallow-Water Flow: The Case of the Chicoutimi River

This is a web presentation of the work presented at the 10th Annual Conference of the CFD Society of Canada, “CFD 2002”, at the University of Windsor on June 9-11, 2002. This discussion paper presents the four-dimensional variational data assimilation (4D-VAR) technique as a tool to forecast floods. This discussion will be limited to hydrological forecast. We assume that the weather, here a large rainstorm, had already been forecasted by the meteorological services. In the 4D-VAR technique, we need to minimize, in the sense of Lagrange, a cost function which measures the difference between the forecast and the observations. The physical equations acts as a set of constraints. Here, the model is the shallow-water equations modified to include sediment transport. The minimum was found by using the steepest descent algorithm. This is made possible because the gradient of the cost function can be calculated analytically by using the adjoint equations of the model. To illustrate the 4D-VAR technique, the bypass of a simple theoretical dam as well as the more complex overflowing of the Chicoutimi River at the Chute-Garneau dam (during the 1996 flood) are investigated.     

Unconventional geometric phase gate and multiqubit entanglement for hot ions with a frequency-modulated field

We present an alternative scheme for implementing the unconventional geometric two-qubit phase gate and preparing multiqubit entanglement by using a frequency-modulated laser field to simultaneously illuminate all ions. Selecting the index of modulation yields selective mechanisms for coupling and decoupling between the internal and the external states of the ions. By the selective mechanisms, we obtain the unconventional geometric two-qubit phase gate, multiparticle Greenberger--Horne--Zeilinger states and highly entangled cluster states. Our scheme is insensitive to the thermal motion of the ions.