高分辨率模式雷达回波预报能力分析   总被引：1，自引：1，他引：0  

刘静  才奎志  谭政华 《气象》2019,45(12):1710-1717

利用2018年7—8月GRAPES_3 km、东北短临(WRFRUC)高分辨率模式综合雷达回波预报数据和辽宁省SWAN雷达组合反射率(MCR)实况,基于邻域法FSS评分指数,分析模式在台风北上和副热带高压边缘暴雨过程中的雷达回波预报能力。结果表明:两家模式在不同降水过程中对小阈值雷达回波有较好的预报技巧,随着回波量级增大,模式预报FSS逐渐减小,雷达回波55 dBz时,FSS甚至为0。当邻域半径是3时,35 dBz以下的回波预报中GRAPES模式在台风北上暴雨中的预报技巧低于副热带高压边缘,35 dBz则相反。WRFRUC模式始终表现为台风北上暴雨中预报较好。当邻域半径9时,WRFRUC模式在台风暴雨中的FSS评分高于GRAPES模式,GRAPES模式在副热带高压暴雨中的FSS评分始终高于WRFRUC模式。GRAPES和WRFRUC模式的最大FSS评分技巧均出现在邻域半径是11时,分别为0.239和0.195。GRAPES模式中FSS评分在12 h逐小时预报中前3个时次较强,WRFRUC模式则表现为中间时次强,两头弱。  相似文献   

基于SRTM数据的天气雷达探测环境分析研究   总被引：4，自引：3，他引：1       下载免费PDF全文

景号然  谢晓琳  郑伟  彭涛  刘娟  刘宗庆 《气象》2019,45(6):871-876

利用SRTM高程数据作为选址基础数据,结合天气雷达工作方式和探测方法,计算得到天气雷达在0.5°、1.0°、2.4°仰角上地物遮挡情况;利用高程格点数据获得3个仰角的地物剖面数据,提高了SRTM数据利用精度和运算速度;分析中结合地球曲率和电磁波折射影响,改进算法获得站点遮蔽角图,站点上空1 km、海拔3和6 km等射束高度图及数据,该分析结果充分体现了SRTM数据的高分辨率特点。最后将结果数据与GIS地图结合,完成了四川省天气雷达网探测环境分析,并给出了各个台站评估结果。  相似文献   

高度计测距精度对沿轨迹重力异常反演的影响     

李洋  张润宁 《测绘学报》2015,44(4):363-369

应用求解沿轨迹重力异常的垂线偏差法以及求解空间分辨率的交叉谱分析法,建立了高度计测距精度与沿轨迹重力异常反演精度以及空间分辨率的关联性模型。首先依据卫星测高原理,给出了沿轨迹重力异常的误差传播公式,然后以此为基础通过推导交叉谱分析中一致性系数与信噪比的数学表达式,建立了高度计测距精度与空间分辨率的解析关系。数值仿真结果表明:雷达高度计测距精度与沿轨迹重力异常反演精度成正比关系,与空间分辨率成幂函数关系,即高度计测距精度提高m倍,沿轨迹重力异常反演精度提高m倍,全球海域平均空间分辨率提高m0.464 4倍。将数值仿真结果与相关文献中对实际测高数据的处理结果进行比较,验证了理论分析及模型的正确性。  相似文献   

利用Sentinel-1影像监测土地回填导致的地表形变     

杨映新  洪武胜  吴曼乔 《测绘通报》2021,(6):67-70

在机场填海区地表稳定散射的范围内,本文运用合成孔径雷达干涉测量（InSAR）技术对机场地表形变安全性进行了监测分析,反演获得了研究区域范围内的年形变速率数据结果和高分辨率形变时序结果,并以此分析了香港国际机场的地表形变区在监测周期内的形变时空分布特征。为证明监测结果的精度和可靠性,本文采用全球导航卫星系统（GNSS）观测站的垂直位移数据,对InSAR方法反演的结果进行了交叉验证,证明两者具有良好的一致性。  相似文献   

Some Thoughts on the Earthquake Science Experimental Site——The Underground Cloud Map   总被引：1，自引：0，他引：1  

CHEN Yong  XU Yihe  CAI Huiteng  LI Wen 《中国地震研究》2019,33(1):1-8

The Western Yunnan Earthquake Predication Test Site set up jointly by the China Earthquake Administration, the National Science Foundation Commission of America, and United States Geological Survey has played an important role in development of early earthquake research work in China. Due to various objective reasons, most of the predicted targets in the earthquake prediction test site have not been achieved, and the development has been hindered. In recent years, the experiment site has been reconsidered, and renamed the “Earthquake Science Experimental Site”. Combined with the current development of seismology and the practical needs of disaster prevention and mitigation, we propose adding the “Underground Cloud Map” as the new direction of the experimental site. Using highly repeatable, environmentally friendly and safe airgun sources, we could send constant seismic signals, which realizes continuous monitoring of subsurface velocity changes. Utilizing the high-resolution 3-D crustal structure from ambient noise tomography, we could obtain 4-D (3-D space + 1-D time) images of subsurface structures, which we termed the “Underground Cloud Map”. The “Underground Cloud Map” can reflect underground velocity and stress changes, providing new means for the earthquake monitoring forecast nationwide, which promotes the conversion of experience-based earthquake prediction to physics-based prediction.  相似文献   

地基干涉雷达IBIS-S桥跨结构振动变形测量与模态分析   总被引：2，自引：0，他引：2  

王鹏  邢诚  项霞 《测绘通报》2019,(10):35-39

地基雷达干涉测量技术能够以较高的时空采样频率获取线性结构目标整体瞬时变形状态。本文将该技术引入大型桥梁桥跨结构的振动变形测量与模态分析中。对动静载试验过程中的武汉二七长江大桥东岸桥跨结构开展连续变形监测，利用频域分解法计算桥跨结构的自振频率、阻尼比和模态振型。计算结果表明，地基干涉雷达干涉测量技术能够快速探测桥跨结构竖弯模态，特别适用于灾后大型线形结构健康状态的应急检测。  相似文献   

SAR image despeckling with a multilayer perceptron neural network     

Xiao Tang  Lei Zhang  Xiaoli Ding 《International Journal of Digital Earth》2019,12(3):354-374

Speckle noise in synthetic-aperture radar (SAR) images severely hinders remote sensing applications; therefore, the appropriate removal of speckle noise is crucial. This paper elaborates on the multilayer perceptron (MLP) neural-network model for SAR image despeckling by using a time series of SAR images. Unlike other filtering methods that use only a single radar intensity image to derive their parameters and filter that single image, this method can be trained using archived images over an area of interest to self-learn the intensity characteristics of image patches and then adaptively determine the weights and thresholds by using a neural network for image despeckling. Several hidden layers are designed for feedforward network training, and back-propagation stochastic gradient descent is adopted to reduce the error between the target output and neural-network output. The parameters in the network are automatically updated in the training process. The greatest advantage of MLP is that once the despeckling parameters are determined, they can be used to process not only new images in the same area but also images in completely different locations. Tests with images from TerraSAR-X in selected areas indicated that MLP shows satisfactory performance with respect to noise reduction and edge preservation. The overall image quality obtained using MLP was markedly higher than that obtained using numerous other filters. In comparison with other recently developed filters, this method yields a slightly higher image quality, and it demonstrates the powerful capabilities of computer learning using SAR images, which indicate the promising prospect of applying MLP to SAR image despeckling.  相似文献   

Propagation of uncertainties in interpolated rainfields to runoff errors     

Yeboah Gyasi-Agyei 《水文科学杂志》2019,64(5):587-606

Conditional daily rainfields were generated using collocated raingauge radar data by a kriging interpolation method, and disaggregated into hourly rainfields using variants of the method of fragments. A geographic information system (GIS)-based distributed rainfall–runoff model was used to convert the hourly rainfields into hydrographs. Using the complete radar rainfall as input, the rainfall–runoff model was calibrated based on storm events taken from nested catchments. Performance statistics were estimated by comparing the observed and the complete radar rainfall simulated hydrographs. Degradation in the hydrograph performance statistics by the simulated hourly rainfields was used to identify runoff error propagation. Uncertainty in daily rainfall amounts alone caused higher errors in runoff (depth, peak, and time to peak) than those caused by uncertainties in the hourly proportions alone. However, the degradation, which reduced with runoff depth, caused by the combined uncertainties was not significantly different from that caused by the uncertainty of amounts alone.  相似文献   

基于云模型的海岸脆弱性评估 ——以厦门岛为例     

朱正涛  蔡锋  曹超  陈沈良 《海洋通报》2019,38(4):462-471

脆弱性评估很大程度上存在着模糊性和随机性,为有效解决评估过程中定性概念与评估指标按隶属函数定量描述这一不确定转换问题,本文基于云理论本文选取海岸地貌、海岸高程、海岸坡度、海岸缓冲能力、有效波高、道路价值和建筑价值为指标,构建了厦门岛海岸脆弱性评估指标体系,运用云模型评估手段定量测度了厦门岛海岸脆弱性空间分异特征。评估结果与客观情况比较吻合,检验了指标体系的合理性和评估模型的适用性。本文提出了海岸脆弱性综合评估模型,实用有效,可以推广到与厦门岛类似的区域,为海岸管理及规划提供科学指导。  相似文献   

An improved building detection approach using L-band POLSAR two-dimensional time-frequency decomposition over oriented built-up areas     

Lei Deng  Ying He  Zhi-hui Mao  Jie Yu 《地理信息系统科学与遥感》2019,56(1):1-21

The objective of this study is to efficiently extract detailed information about various man-made targets in oriented built-up areas using polarimetric synthetic aperture radar (POLSAR) images. This paper develops an improved approach for building detection by utilizing Two-Dimensional Time-Frequency (2-D TF) decomposition. This method performs outstandingly in distinguishing between man-made and natural targets based on the isotropic behaviors, frequency-sensitive responses, and scattering mechanisms of objects. The proposed method can preserve the spatial resolution and exploit the advantages of TF decomposition; specifically, the exact outlines of buildings can be effectively located, and more types of features (e.g., flat roofs, roads, and walls that are oblique to the radar illumination) can be distinguished from forests in complex built-up areas by 2-D TF decomposition. The coarser-resolution subaperture images that are produced in the azimuth direction, which correspond to different looking angles, are beneficial for detecting man-made structures with main scattering centers oriented at oblique angles with respect to the radar illumination. In the range direction, the obtained subaperture images, which correspond to various observation frequencies, can be helpful in distinguishing flat roofs and roads from forests. This method was successfully implemented to analyze both NASA/JPL L-band AIRSAR and L-band EMISAR data sets. The building detection results of the proposed method exhibit a significant improvement over those of other methods and reach an overall accuracy over 80%, with approximately 20% higher than the accuracies of K-means clustering and the entropy/alpha-Wishart classifier and approximately 10% higher than the accuracy of the support vector machine method. Moreover, building details can be precisely detected, obliquely oriented buildings can be identified, and the distinction between buildings and forests is significantly improved, as both visually and statistically indicated. This method is highly adaptable and has substantial application value.  相似文献