Simulation of tropical cyclone activity over the western North Pacific based on CMIP5 models

Based on the Coupled Model Inter-comparison Project 5 (CMIP5) models, the tropical cyclone (TC) activity in the summers of 1965–2005 over the western North Pacific (WNP) is simulated by a TC dynamically downscaling system. In consideration of diversity among climate models, Bayesian model averaging (BMA) and equal-weighed model averaging (EMA) methods are applied to produce the ensemble large-scale environmental factors of the CMIP5 model outputs. The environmental factors generated by BMA and EMA methods are compared, as well as the corresponding TC simulations by the downscaling system. Results indicate that BMA method shows a significant advantage over the EMA. In addition, impacts of model selections on BMA method are examined. To each factor, ten models with better performance are selected from 30 CMIP5 models and then conduct BMA, respectively. As a consequence, the ensemble environmental factors and simulated TC activity are similar with the results from the 30 models’ BMA, which verifies the BMA method can afford corresponding weight for each model in the ensemble based on the model’s predictive skill. Thereby, the existence of poor performance models will not particularly affect the BMA effectiveness and the ensemble outcomes are improved. Finally, based upon the BMA method and downscaling system, we analyze the sensitivity of TC activity to three important environmental factors, i.e., sea surface temperature (SST), large-scale steering flow, and vertical wind shear. Among three factors, SST and large-scale steering flow greatly affect TC tracks, while average intensity distribution is sensitive to all three environmental factors. Moreover, SST and vertical wind shear jointly play a critical role in the inter-annual variability of TC lifetime maximum intensity and frequency of intense TCs.     

基于深度学习的高分辨率遥感影像土地覆盖自动分类方法

土地覆盖变化是全球变化研究的核心,而精准分类是开展土地覆盖变化研究的基础。高分辨率遥感卫星技术的快速发展对地表分类的速度和精度提出了双重挑战,近年来人工智能等新技术的发展为图像自动分割提供了实现途径,而以卷积神经网络为代表的深度学习方法在遥感图像分类领域也具有独特的优势。为对比深度学习模型设计对高分辨率图像分类结果的影响,本文以郑州市2019年高分1号影像作为输入,对比研究了基于UNet模型改进的4种不同深度学习网络模型在高分辨率影像土地覆盖自动分类应用中的差异,探讨了残差网络、模型损失函数、跳层连接和注意力机制模块等编码和解码设定对于分类精度的影响机制。研究发现：同时加入多尺度损失函数、跳层连接和注意力机制模块的MS-EfficientUNet模型对郑州市土地覆盖分类结果最优,基于像元评价的整体分类精度可达0.7981。通过在解码器中引入多尺度损失函数可有效提高林地、水体和其他类别的分类精度;而对编码器进行改进,加入跳层连接和注意力机制可进一步提高草地、水体和其他类别地物的分类精度。研究结果表明,深度学习技术在高分辨率遥感影像自动分类中具有潜在应用价值,但分类结果精度的进一步提高和多级别大范围的精细分类方法仍是下一步研究的重点。     

Decadal Variations of Intense Tropical Cyclones over the Western North Pacific during 1948–2010简

Using Joint Warning Typhoon Center （JTWC） best track data during the period 1948-2010, decadal and interdecadal changes of annual category 4 and 5 tropical cyclone （TC） frequency in the western North Pacific basin were examined. By allowing all of the observed TCs in the JTWC dataset to move along the observed TC tracks in a TC intensity model, the annual category 4 and 5 TC frequency was simulated. The results agreed well with observations when the TC intensity prior to 1973 was adjusted based on time-dependent biases due to changes in measurement and reporting practices. The simulated and adjusted time series showed significant decadal （12-18 years） variability, while the interdecadal （18-32 years） variability was found to be statistically insignificant. Numerical simulations indicated that changes in TC tracks are the most important factor for the decadal variability in the category 4 and 5 TC frequency in the western North Pacific basin, while a combined effect of changes in SST and vertical wind shear also contributes to the decadal variability. Further analysis suggested that the active phase of category 4 and 5 TCs is closely associated with an eastward shift in the TC formation locations, which allows more TCs to follow a longer journey, favoring the development of category 4 and 5 TCs. The active phase corresponds with the SST warming over the tropical central and eastern Pacific and the eastward extension of the monsoon trough, thus leading to the eastward shift in TC formation locations.     

基于同震库仑应力变化的汶川地震余震频次研究

在计算同震静态库仑应力变化的基础上,基于速率-状态摩擦定律及与同震静态库仑应力变化相关的余震频次估计方法,研究了汶川地震余震区及附近不同区域内与汶川地震同震静态库仑应力触发相关的"直接"余震频次。结果显示,主震破裂带尤其是主震破裂带南段的"直接"余震频次明显低于实际情况,其原因在于同震库仑应力变化导致的主震破裂面上应力水平的降低。研究结果还显示,汶川地震同震库仑应力变化对余震活动持续时间的影响与震级下限有关。对ML4.0以上余震,持续时间约为震后15~16个月;对ML3.5以上余震,接近60个月。在上述时段内,与同震库仑应力变化相关的"直接"余震占全部余震的比例为44.7%~48.6%。这表明,即使在同震库仑应力变化的"有效"作用时段内,主震破裂面上也大约有50%的余震活动不是缘于同震库仑应力变化的影响,这可能与震后余滑及粘弹松弛等时间相关因素的影响有关。     

地震空间分布因子Zk及其在唐山地区的应用

根据空间距离方法,给出了地震空间分布因子Z_1的统计计算方法,并指出地震空间分布因子Z_1可以较好地判断地震空间分布类型。利用唐山地区的地震资料,对地震空间分布因子Z_1在地震预报中的实际应用进行了探讨,指出Z_1对中强地震具有一定的震兆反应能力。本文还就不同的序列处理方式及不同的震级下限对地震空间分布因子Z_1的影响,进行了深入的探讨。     

Experiments of Brittle-Plastic Transition and Instability Modes of Juyongguan Granite at Different Temperatures and Pressures

INTRODUCTIONAlargenumberofstudiesindicatethatthelithosphericstresslimit (peakstrength)iscoincidentwiththefocaldepthofstrongearthquakes (Goetzeetal.,1 979;Braceetal.,1 980 ;Kirby ,1 980 ;Meissner ,etal.,1 982 ;Sibson ,1 982 ;Chenetal.,1 983;Smithetal.,1 984 ;andMeissner,1 996 ) ,whicharelocatedinrelativelyhigh velocityzonesabovelow velocityzonesinthecrust.Butthereexistsdifferenttheoriesconcerningthereasonsforthecoincidence ,especiallyconcerningthecontrollingfactorsaboutthefocaldepthofstr…     

雁列式断层组合变形过程中的声发射活动特征

着重研究拉张或挤压型雁列式断层标本变形过程中声发射(简称AE，下同)的时空演化特征. 结果表明，预置构造对AE空间分布格局具有较强的控制作用，随着差应力的增加，AE首先在两个端点附近丛集，之后向两端点连线附近集中，出现明显的破裂局部化现象，较大事件还通常集中于某一端点附近反复发生. 前期微破裂丛集图象指示后期宏观破裂的扩展方向及扩展范围. 拉张和挤压型雁列区宏观破裂方向分别与轴向应力方向垂直和平行. 雁列式断层标本变形过程中，破裂前的弱化阶段相对较长、弱化过程明显. 微破裂事件累积频次指数增长可能是系统失稳前的典型征兆之一，而雁列区宏观破裂之后，AE数量逐渐减少、应变释放相对减弱. 摩擦滑动过程中，大的粘滑失稳前未见有AE活动前兆性的增强过程.雁列区的b值变化在失稳前显示趋势性降低——快速回升这一典型的变化过程，b值降低一般发生在差应力增强过程之中，并有可能延续至弱化阶段，而快速回升则一般发生在破裂失稳前的短时期内. 对比研究表明，构造差异所导致的b值差异远大于b值随差应力的增加而产生的变化量，而对同一构造标本，力学状态的改变会导致AE序列时序特征的急剧变化，较高的加载速率对应较高的应变能释放及明显的低b值. 先期破碎带由于较低的破坏强度，其对差应力的微小变化具有特殊敏感性，从而成为源、兆分离、窗口或敏感点效应等地震活动性前兆现象的一种可能的原因.      

多通道SAR影像中道路的探测

提出了一种探测多通道SAR影像中道路的新方案。首先阐述了从边缘探测器中建构线状探测器。然后,介绍了应用到SAR影像中的多参数统计假设检验方法。利用传统的亮线提取过程对初期结果进行了矢量化。实验表明:该方法应用到全极化SAR影像中的道路的提取中效果较好。     

基于RMAPS的一次局地强降水过程成因分析

2017年8月8日午夜,天津北辰区出现局地短时强降水,小时雨强超过70mm·h~(-1)。利用RMAPS(Rapidrefresh Multi-scale Analysis and Prediction System)和观测资料,通过多种资料叠加、雷达回波参数量化和低层风场反演等方法分析了降水成因,结果表明:①降水是由M_βCS(Meso-β-scale Convective System)后向传播过程中尾部的多单体雷暴造成的,传播过程中单体合并对雷暴系统的结构及增强有重要影响,合并后系统的回波体积参数V_(40)(反射率≥40dBz的体积)增长了23.3%,在V_(40)增长之前,变率参数F_(V40-up6)(6km以上40dBz回波体积6min的变化)出现了"突降",这对雷暴系统即将发展有预警意义;②冷池出流与地面东南风形成的辐合线是对流系统维持的关键,中低层切变线也为对流的发生发展提供了有利的动力条件;伴随着强降水,对流有效位能CAPE由峰值急速下降,低层垂直风切变指数α骤增,这揭示了不稳定能量、垂直风切变与对流过程之间的关系;③降水落区与不稳定参数SWEAT的大值区对应,预警时间3h,来自渤海的地面暖湿带与假相当位温密集带的交汇处也是落区临近预报的关注点。