基于Sentinel-1B SAR数据的洪水提取和监测

洪涝灾害是我国最严重的气象灾害之一,及时准确的洪灾监测是防灾减灾的重要前期工作和基础。本文利用sentinel-1B雷达数据,以黑瞎子岛为研究区,联合使用OSTU阈值分割法和随机森林面向对象分类法针对像素统计单波形、双波形、多波形SAR影像提取洪水要素,实现对洪灾淹没面积的时序监测,为灾情监测提供数据和技术支撑。     

随机森林算法在全球干旱评估中的应用

干旱是发生频率最高,造成社会、经济损失和生态破坏最严重、最广泛的自然灾害之一,因此对干旱进行可靠、有效的评估十分重要.本文以月平均降水、月平均温度、月最高温度、月最低温度、土壤湿度、蒸散发、NDVI、叶绿素荧光等作为解释变量,以基于SPI的干旱等级作为目标变量,采用随机森林算法,以2007-2012年的数据作为训练数据...     

随机激励下非线性海洋结构物响应分析方法研究进展

对在随机载荷作用下非线性海洋结构物的运动响应分析的各种方法进行了综述,对有些方法的基本原理做了阐述,并指出一些最新的研究进展和今后进一步研究的方向。     

一种准确通用的台风路径预报模式

应用天气学理论,对台风云图的晴空区轴线制约台风移动的规律进行物理解释。根据台风云团与晴空区之间存在的干、湿梯度力和推动台风前进的惯性力的互相关系,建立台风移向预报方程和轨迹预报方程,分析论证了台风移向变化的物理过程,把影响台风移动的复杂因子转化为单一的预报因子。     

基于FY-4A卫星和随机森林算法的西藏山南市雷电短临预报方法

针对青藏高原地区雷电短临预报缺乏雷达资料的问题,采用FY-4A卫星多通道数据、欧洲中心第5代再分析资料(ERA5)中的对流指数、闪电定位仪资料等多源监测数据,根据雷电的发生、发展机理,提出了18个关键预报因子,利用随机森林算法建立了适用于西藏山南地区的雷电短临预报模型。统计分析各预报因子在有无雷电天气样本中的概率密度分布与随机森林模型得到的特征重要度指标,结果表明提出的预报因子物理意义明确,建立的模型可信度较高。利用随机森林算法分别对未来10 min、20 min、30 min建立雷电预报模型,并与光流外推预报方法进行对比检验,结果表明：随机森林模型预报效果命中率(POD)、临界成功指数(CSI)均高于光流法,空报率(FAR)也相对较低;未来20 min的随机森林预报模型CSI评分最高,整体预报效果最佳。     

Distribution of the nonlinear random ocean wave period

Because of the intrinsic difficulty in determining distributions for wave periods, previous studies on wave period distribution models have not taken nonlinearity into account and have not performed well in terms of describing and statistically analyzing the probability density distribution of ocean waves. In this study, a statistical model of random waves is developed using Stokes wave theory of water wave dynamics. In addition, a new nonlinear probability distribution function for the wave period is presented with the parameters of spectral density width and nonlinear wave steepness, which is more reasonable as a physical mechanism. The magnitude of wave steepness determines the intensity of the nonlinear effect, while the spectral width only changes the energy distribution. The wave steepness is found to be an important parameter in terms of not only dynamics but also statistics. The value of wave steepness reflects the degree that the wave period distribution skews from the Cauchy distribution, and it also describes the variation in the distribution function, which resembles that of the wave surface elevation distribution and wave height distribution. We found that the distribution curves skew leftward and upward as the wave steepness increases. The wave period observations for the SZFII-1 buoy, made off the coast of Weihai (37°27.6′ N, 122°15.1′ E), China, are used to verify the new distribution. The coefficient of the correlation between the new distribution and the buoy data at different spectral widths (ν=0.3−0.5) is within the range of 0.968 6 to 0.991 7. In addition, the Longuet-Higgins (1975) and Sun (1988) distributions and the new distribution presented in this work are compared. The validations and comparisons indicate that the new nonlinear probability density distribution fits the buoy measurements better than the Longuet-Higgins and Sun distributions do. We believe that adoption of the new wave period distribution would improve traditional statistical wave theory.     

大马士革非正式聚落的讨论(英文)

Toadies cities are accumulating the global population in their territories,occurring formally and informally.The in-crease of urban informality is the most significant trend shaping the 21st century world.Furthermore,the urban informality theory should be considered in urbanization courses and development studies.With the rapid economic market development,changes mapped the major Syrian cities.Damascus is in the midst of a profound transformation of architectural and planning changes.Damascus urbanization i...     

A real-time, event-triggered storm surge forecasting system for the state of North Carolina

A new real-time, event-triggered storm surge prediction system has been developed for the State of North Carolina to assist emergency managers, policy-makers and other government officials with evacuation planning, decision-making and resource deployment during tropical storm landfall and flood inundation events. The North Carolina Forecast System (NCFS) was designed and built to provide a rapid response assessment of hurricane threat, accomplished by driving a high-resolution, two-dimensional, depth-integrated version of the ADCIRC (Advanced Circulation) coastal ocean model with winds from a synthetic asymmetric gradient wind vortex. These parametric winds, calculated at exact finite-element mesh node locations and directly coupled to the ocean model at every time step, are generated from National Hurricane Center (NHC) forecast advisories the moment they are inserted into the real-time weather data stream, maximizing the number of hours of forecast utility. Tidal harmonic constituents are prescribed at the open water boundaries and applied as tidal potentials in the interior of the ocean model domain. A directional surface roughness parameterization that modulates the wind speed at a given location based on the types of land cover encountered upwind, a forest canopy sheltering effect, and a spatially varying distribution of Manning’s–n friction coefficient used for computing the bottom/channel bed friction are also included in the storm surge model. Comparisons of the simulated wind speeds and phases against their real meteorological counterparts, of model elevations against actual sea surface elevations measured by NOAA tide gauges along the NC coast, and of simulated depth-averaged current velocities against Acoustic Doppler Current Profiler (ADCP) data, indicate that this new system produces remarkably realistic predictions of winds and storm surge.     

Nonlinear random wave-induced drag force on a vegetation field

This paper provides a practical method by which the drag force on a vegetation field beneath nonlinear random waves can be estimated. This is achieved by using a simple drag formula together with an empirical drag coefficient given by Mendez et al. (Mendez, F.J., Losada, I.J., Losada, M.A., 1999. Hydrodynamics induced by wind waves in a vegetation field. J. Geophys. Res. 104 (C8), 18383–18396). Effects of nonlinear waves are included by using Stokes second order wave theory where the basic harmonic motion is assumed to be a stationary Gaussian narrow–band random process. An example of calculation is also presented.     

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