Wavelet analysis of coastal-trapped waves along the China coast generated by winter storms in 2008

This study applies the wavelet analysis to the tidal gauge records, alongshore winds, atmospheric temperature and pressure along the China coast in winter 2008. The analysis results show three events of sea level oscillations （SLOs） on the shelf induced by winter storms. The first event occurred from January 9 to 21. The SLO periods were double-peaked at 1.6-5.3 and 7.0-16.0 d with the power densities of 0.04-0.05 and 0.10-0.15 m^2.d, respectively. The second event occurred from February 5 to 18. The SLO period was single-peaked at 2.3-3.5 d with power density of 0.03-0.04 m^2.d. The third event occurred from February 20 to March 8. The SLO periods were double- peaked at 1.5-4.3 and 6.1-8.2 d with the power densities of 0.08-0.11 and 0.02-0.08 me.d, respectively. The SLOs propagated along the coast from Zhejiang in north to Guangdong in south. The phase speeds ranged about 9-29 m/s from Kanmen to Pingtan, 5-11 m/s from Xiamen to Huizhou and 11-22 m/s from Huizhou to Shuidong. The dispersion relation of the SLOs shows their nature of coastal-trapped wave.

An investigation of the effects of dust storms on rat lung using HRCT and blood gas analysis

The increasing intensity and frequency of sand-dust storms in China has led to greater prominence of associated environmentaland health issues. Many studies have focused on the health effects of air particulate contaminants, but fewformal investigations have studied the effects of sand-dust storms on human and animal health. The aim of this study wasto investigate the effects of dust storms on rat lung by using high resolution computed tomography （HRCT） and blood gasanalysis through a wind tunnel simulating. We found that the rat lung damage effects can be detected by the HRCT imagingafter exposure to sand-dust storm environments, but had no obvious result through blood gas analysis. Exposure durationspositively correlated with the damage degree to lung tissue. These will provide some evidence for clinical diagnosis ofnon-occupational pneumoconiosis.

ANALYSIS OF “BIMODAL PATTERN” STORM ACTIVITY CHARACTERISTICS OF THE BAY OF BENGAL

Storms that occur at the Bay of Bengal(Bo B) are of a bimodal pattern, which is different from that of the other sea areas. By using the NCEP, SST and JTWC data, the causes of the bimodal pattern storm activity of the Bo B are diagnosed and analyzed in this paper. The result shows that the seasonal variation of general atmosphere circulation in East Asia has a regulating and controlling impact on the Bo B storm activity, and the "bimodal period" of the storm activity corresponds exactly to the seasonal conversion period of atmospheric circulation. The minor wind speed of shear spring and autumn contributed to the storm, which was a crucial factor for the generation and occurrence of the"bimodal pattern"storm activity in the Bo B. The analysis on sea surface temperature(SST) shows that the SSTs of all the year around in the Bo B area meet the conditions required for the generation of tropical cyclones(TCs). However,the SSTs in the central area of the bay are higher than that of the surrounding areas in spring and autumn, which facilitates the occurrence of a "two-peak"storm activity pattern. The genesis potential index(GPI) quantifies and reflects the environmental conditions for the generation of the Bo B storms. For GPI, the intense low-level vortex disturbance in the troposphere and high-humidity atmosphere are the sufficient conditions for storms, while large maximum wind velocity of the ground vortex radius and small vertical wind shear are the necessary conditions of storms.

Brain Storm Optimization Based Clustering for Learning Behavior Analysis

Recently,online learning platforms have proven to help people gain knowledge more conveniently.Since the outbreak of COVID-19 in 2020,online learning has become a mainstream mode,as many schools have adopted its format.The platforms are able to capture substantial data relating to the students’learning activities,which could be analyzed to determine relationships between learning behaviors and study habits.As such,an intelligent analysis method is needed to process efficiently this high volume of information.Clustering is an effect data mining method which discover data distribution and hidden characteristic from uncharacterized online learning data.This study proposes a clustering algorithm based on brain storm optimization(CBSO)to categorize students according to their learning behaviors and determine their characteristics.This enables teaching to be tailored to taken into account those results,thereby,improving the education quality over time.Specifically,we use the individual of CBSO to represent the distribution of students and find the optimal one by the operations of convergence and divergence.The experiments are performed on the 104 students’online learning data,and the results show that CBSO is feasible and efficient.

Analysis of Heavy Rain Process in South Liaoning Province Caused by No. 1105 Tropical Storm "Meari"

[ Objective] The aim was to study the heavy rainstorm by tropical storm ＂Meari＂ in Liaoning. [ Method] Based on the ground data, radar data, numerical report data, encrypted automatic station and NCEP reanalysis data, the heavy rain process by tropical storm ＂ Meari＂ was ana- lyzed. The changes of each physical quantity were discussed while the tropical storm moving northward. [ Result] The subtropical high pressure and Mainland high pressure jointed and maintained, forced ＂ Meari＂ turned northwest. The low-level southeast jet by ＂Meari＂ provided full water trans- mission and layer unstable conditions. The heavy rain mainly distributed in the tongue area of high energy, and the total energy was a key index to predict the rainfall area. [ Condusion] The study provided reference for the report business.

The dynamical and thermodynamical analysis of the oceanic response to storm

In this paper, the discussion is made on the problem of the oceanic response caused by air-sea interaction under storm. First, the perturbation differential equations for the problem are given, and the interaction functions are supposed to be the solving conditions. Next, the nonlinear diffusion equations of the problem are solved by using the method of the given variable transforms and the specific variable power series. Finally, the response disturbances to the circular intense storm is calculated so as to discribe quantitatively the evolution processes of the oceanic response.

Comprehensive Risk Analysis of Storm Surge Flood Based on WebGIS

The comprehensive risk analysis of storm surge flood is vital to the safety management of sea embank- ment, the scientific assessment of storm surge disaster and the improvement of emergent treatment in storm surge haz- ard. Based on the research of disaster-causing, disaster-pregnant and disaster-bearing factors, the influencing factors of storm surge risk are concluded to be flood natural risk, embankment position, embankment width and height. The membership degree of the factors of storm surge risk is firstly determined by storm surge flood evolution based on WebGIS, and the comprehensive risk membership and risk grade of each influencing factor are obtained. Then the effects of a single factor on comprehensive risk and sensitivity analysis are discussed, and the storm surge flood risk map is obtained. Finally, the storm surge of Tianjin Binhai New Area is taken as a case. The results show that the in- fluencing degree of the factors on the comprehensive risk membership is in decreasing order of flood natural risk, em- bankment position, embankment width and height. The flood risk map of the case is drawn, which is useful to decrease losses caused by storm surge disaster.

MESOSCALE ANALYSIS OF YUNNAN SUCCESSIVE HEAVY PRECIPITATION AROUSED BY THE STORM OVER THE BAY IN EARLY SUMMER

By using regular meteorological data, physical quantity fields, satellite pictures and Doppler radarecho data, we analyze the mesoscale features and the conditions of 4 successive heavy precipitation processes inYunnan aroused by the storm over the Bay in the early summer. The results show that the life of the storm overthe Bay is usual 2 or 3 days and the cloud top temperature of the storm is always below -65°C. The storm overthe Bay affects Yunnan by mesoscale convective cloud clusters, cloud system in peripheral or weaken itselfmoving to the northeast. The Tibetan Plateau shear lines and vortexes, NE-SW convergence channels andsouthwest wind convergence supply favorable circulation background and dynamical conditions. There are manycommon features about Doppler radar echoes, the flocculent echoes with intensity about 35-45 dBZ move to theeast to produce successive precipitation in Yunnan, and the mesoscale features of southwest jet and wind veeringwith altitude not only are favorable to transport warm and moist airflow brought to the north by the storm overthe Bay, but also are favorable to convective development.

3D Simulation of Storm Surge Disaster Based on Scenario Analysis

The occurrence of storm surge disaster is often accompanied with floodplain, overflow, dike breach and other complex phenomena, while current studies on storm surge flooding are more concentrated on the 1D/2D numerical simulation of single disaster scenario(floodplain, overflow or dike breach), ignoring the composite effects of various phenomena. Therefore, considering the uncertainty in the disaster process of storm surge, scenario analysis was firstly proposed to identify the composite disaster scenario including multiple phenomena by analyzing key driving forces, building scenario matrix and deducing situation logic. Secondly, by combining the advantages of k-ω and k-ε models in the wall treatment, a shear stress transmission k-ω model coupled with VOF was proposed to simulate the 3D flood routing for storm surge disaster. Thirdly, risk degree was introduced to make the risk analysis of storm surge disaster. Finally, based on the scenario analysis, four scenarios with different storm surge intensity(100-year and 200-year frequency) were identified in Tianjin Binhai New Area. Then, 3D numerical simulation and risk map were made for the case.

Sedimentary record of a late Holocene storm event in Laizhou Bay,Bohai Sea,China

The Bohai Sea is influenced by numerous extreme oceanic wave events in history.However,it is often difficult to determine the types of these events due to the lack of detailed historical records,causing uncertainty in the reconstruction of historical coastal disasters.We investigated an anomalous sand layer in the Xiliyu Village by the coast of Laizhou Bay,Shandong,from which an extreme event deposit was identified using a multi-proxy approach including grain size distribution,geochemistry,and magnetic susceptibility.This event was dated 2700–3100 a bp,and caused inundation of a large coastal area of Laizhou Bay.By comparing historical records with instrumental data,we believe that the event deposit was generated by a severe storm surge with wind speed of>34.9 m/s.

Response of the North Pacific Storm Track Activity in the Cold Season to Multi-scale Oceanic Variations of Kuroshio Extension System: A Statistical Assessment

In this paper,a statistical method called Generalized Equilibrium Feedback Analysis(GEFA)is used to investigate the responses of the North Pacific Storm Track(NPST)in the cold season to the multi-scale oceanic variations of the Kuroshio Extension(KE)system,including its large-scale variation,oceanic front meridional shift,and mesoscale eddy activity.Results show that in the cold season from the lower to the upper troposphere,the KE large-scale variation significantly weakens the storm track activity over the central North Pacific south of 30°N.The northward shift of the KE front significantly strengthens the storm track activity over the western and central North Pacific south of 40°N,resulting in a southward shift of the NPST.In contrast,the NPST response to KE mesoscale eddy activity is not so significant and relatively shallow,which only shows some significant positive signals near the dateline in the lower and middle troposphere.Furthermore,it is found that baroclinicity and baroclinic energy conversion play an important role in the formation of the NPST response to the KE multi-scale oceanic variations.

OBJECTIVE CLASSIFICATION OF THE TRACKS OF TROPICAL STORMS IN THE BAY OF BENGAL

An objective analysis of tropical cyclone tracks is performed, with which the tracks of 131 tropical storms(TSs) in 1972-2011 are separated into three types that move west-, north- and northwestward, denoted as Types A, B and C, respectively. Type A(21 TSs and 16% of total) has the origin in the southwestern Bay of Bengal, with the TS in a unimodal distribution as its seasonal feature, occurring mainly in autumn; 18 of the 21 TSs(taking up 90%) land mostly on the western Bay coast(west of 85°E); 5% of Type-A TSs attains the wind speed of >42.7 to 48.9 m/s. Type A has little or no effect on Tibet. Type B(74 TSs, 56.6% of the total) has its preferable origin in the central Bay of Bengal, with the TS in a bimodal distribution as its seasonal pattern. This type denotes the travel in the north in spring,with the landfall of 67 of the 74 TSs(accounting for 91%) mainly on the middle coast of the Bay(85° to 95°E), and19% of the TSs reaching the wind velocity of >42.7 to 48.9 m/s, which exert great effect on Tibet and it is this TS track that gives strong precipitation on its way through this region. Type C(36 TSs, 27.5% of the total) has its main origin in the southern part of the bay, and these TSs are formed largely in autumn, moving in the northwest direction,and 23 of the 36 TSs(64%) land mostly on the western Bay coast, lasting for a longer time, with almost no impact upon Tibet.

Statistical study on interplanetary drivers behind intense geomagnetic storms and substorms

Geomagnetic storms and substorms play a central role in both the daily life of mankind and in academic space physics.The profiles of storms,especially their initial phase morphology and the intensity of their substorms under different interplanetary conditions,have usually been ignored in previous studies.In this study,97 intense geomagnetic storms(Dstmin≤–100 nT)between 1998 and 2018 were studied statistically using the double superposed epoch analysis(DSEA)and normalized superposed epoch analysis(NSEA)methods.These storms are categorized into two types according to different interplanetary magnetic field(IMF)Bz orientations:geomagnetic storms whose IMF is northward,both upstream and downstream relative to the interplanetary shock,and geomagnetic storms whose upstream and downstream IMF is consistently southward.We further divide these two types into two subsets,by different geomagnetic storm profiles:Type Ⅰ/Type Ⅱ—one/two-step geomagnetic storms with northward IMF both upstream and downstream of the interplanetary shock;Type Ⅲ/TypeⅣ—one/two-step geomagnetic storms with southward IMF both upstream and downstream of the interplanetary shock.The results show that:(1)geomagnetic storms with northward IMF both upstream and downstream of the interplanetary shock have a clear initial phase;geomagnetic storms with southward IMF in both upstream and downstream of the interplanetary shock do not;(2)the IMF is an important controlling factor in affecting the intensity characteristics of substorms.When Bz is positive before and after the interplanetary shock arrival,the Auroral Electrojet(AE)index changes gently during the initial phase of geomagnetic storms,the median value of AE index is maintained at 500–1000 nT;(3)when Bz is negative before and after the interplanetary shock arrival,the AE index rises rapidly and reaches its maxmum value about one hour after storm sudden commencements(SSC),although the time is scaled between reference points and the maximum value of AE is usually greater than 1,000 nT,representing intense substorms;(4)for most cases,the Dst0 usually reaches its minimum at least one hour after Bz.These results are useful in improving contemporary space weather models,especially for those that address geomagnetic storms and substorms.

Two Modes and Their Seasonal and Interannual Variation of the Baroclinic Waves/Storm Tracks over the Wintertime North Pacific

In this study,a newly developed method,termed moving empirical orthogonal function analysis（MEOF）,is applied to the study of midlatitude baroclinic waves over the wintertime North Pacific from 1979 to 2009.It is shown that when the daily,high-pass filtered（2–10 days） meridional wind at 250 h Pa is chosen as the variable of the MEOF analysis,typical features of baroclinic waves/storm tracks over the wintertime North Pacific can be well described by this method.It is found that the first two leading modes of the MEOF analysis,MEOF1 and MEOF2,assume quite different patterns.MEOF1 takes the form of a single wave train running in the east–west direction along 40°N,while MEOF2 is a double wave train pattern running in the east–west direction along 50°N and 30°N,respectively.The shift composites of various anomalous fields based on MEOF1 and MEOF2 assume typical baroclinic wave features.MEOF1 represents a primary storm track pulsing with an intrinsic time scale of two days.It shows significant ＂midwinter suppression＂ and apparent interannual variability.It is stronger after the mid-1990 s than before the mid-1990 s.MEOF2 represents a double-branch storm track,also with an intrinsic time scale of approximately two days,running along 50°N and 30°N,respectively.It shows no apparent seasonal variation,but its interannual and decadal variation is quite clear.It oscillates with larger amplitude and longer periods after the mid-1990 s than before the mid-1990 s,and is heavily modulated by El Ni n°o–Southern Oscillation（ENSO）.

基于Kafka和Storm的车辆套牌实时分析存储系统

城市机动车数量、出行量的增加,使得车辆套牌现象屡禁不止.交管部门为了解决套牌监测的难题,采用传统的识别方式(如基于人工识别、基于牌照识别、基于射频识别等).然而面对海量的日志记录,这些方式普遍存在效率低、实时性差的问题.为此引入大数据技术,提出一个基于Kafka和Storm的车辆套牌实时分析存储系统.Kafka可以作为中间件进行缓存,提高数据采集和数据分析的同步性,还能避免数据丢失;Storm框架可以实现日志信息的实时计算,然后将套牌车辆信息存入指定文档中.整个系统具有实时、分布式存储、稳定、可扩展等特性.

基于Storm的实时用户日志管理系统

研究并开发了具有实时响应的大数据用户日志管理分析平台。采用Storm流式计算框架,完成用户日志分析的实时处理平台架构;采用Elastic Search作为实时搜索引擎,完成实时响应处理;使用Flume、Kafka技术完成海量日志采集、聚合和传输等功能。以某城市监狱管理系统的用户日志信息为实验数据,系统取得了良好的实验效果。为同时处理海量数据和实时响应用户请求的系统提供了可行性解决方案。

一种基于Storm及Hadoop的海量日志安全分析系统

针对海量日志流安全分析的问题,设计一种海量日志安全分析系统。该系统将开源框架Storm与Hadoop进行整合,通过正则表达联动检测机制和基于FP-Growth算法的离线关联分析来探测日志流中的网络安全事件,实现识别安全事件无需人工干预。实验结果表明,该系统对各类网络安全事件具有较好的识别效果。

INFLUENCE ON NORTHERN PACIFIC STORM TRACK OF EQUATO-RIAL CENTRAL AND EASTERN PACIFIC SSTA DURING WINTER

Singular value decomposition (SVD) is conducted of 15 winter tropical Pacific SST with 500 hPa filtered potential height variance over the northern Pacific storm track. It is shown that the first coupled mode obtained depicts the effect on the track of SSTA over equatorial central and eastern Pacific. Further com-posite analysis indicates that the SSTA over there during winter can give rise to or invigorate PNA teleconnec-tion response pattern in 500 hPa height field which, in turn, exerts crucial influence on the interannual variabil-ity in vigor and east-west displacement of the Pacific storm track, especially over its central and eastern part.

Cytokine storm promoting T cell exhaustion in severe COVID-19 revealed by single cell sequencing data analysis

Background:Evidence has suggested that cytokine storms may be associated with T cell exhaustion(TEX)in COVID-19.However,the interaction mechanism between cytokine storms and TEX remains unclear.Methods:With the aim of dissecting the molecular relationship of cytokine storms and TEX through single-cell RNA sequencing data analysis,we identified 14 cell types from bronchoalveolar lavage fluid of COVID-19 patients and healthy people.We observed a novel subset of severely exhausted CD8 T cells(Exh T_CD8)that co-expressed multiple inhibitory receptors,and two macrophage subclasses that were the main source of cytokine storms in bronchoalveolar.Results:Correlation analysis between cytokine storm level and TEX level suggested that cytokine storms likely promoted TEX in severe COVID-19.Cell–cell communication analysis indicated that cytokines(e.g.CXCL10,CXCL11,CXCL2,CCL2,and CCL3)released by macrophages acted as ligands and significantly interacted with inhibitory receptors(e.g.CXCR3,DPP4,CCR1,CCR2,and CCR5)expressed by Exh T_CD8.These interactions formed the cytokine–receptor axes,which were also verified to be significantly correlated with cytokine storms and TEX in lung squamous cell carcinoma.Conclusions:Cytokine storms may promote TEX through cytokine-receptor axes and be associated with poor prognosis in COVID19.Blocking cytokine-receptor axes may reverse TEX.Our finding provides novel insights into TEX in COVID-19 and new clues for cytokine-targeted immunotherapy development.

基于Storm的海量数据实时聚类

针对现有平台处理海量数据实时响应能力普遍较差的问题,引入Storm分布式实时计算平台进行大规模数据的聚类分析,设计了基于Storm框架的DBSCAN算法。该算法将整个过程分为数据接入、聚类分析、结果输出等阶段,在框架预定义的组件中分别编程实现,各组件通过数据流连通形成任务实体,提交到集群运行完成。通过对比分析和性能监测,验证了所提方案具有低延迟和高吞吐量的优势,集群运行状况良好,负载均衡。实验结果表明Storm平台处理海量数据实时性较高,能够胜任大数据背景下的数据挖掘任务。