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中尺度对流系统（Mesoscale Convective System,MCS）是很多对流性天气的主要致灾体,可导致严重的气象和水文灾害,如雷暴大风、冰雹、龙卷风和山洪。对MCS进行准确的识别和追踪,并根据追踪轨迹及获得的MCS特征实现MCS的分类,对灾害天气的分析和预报有重要意义。基于京津冀地区2010—2019年的雷达组合反射率拼图资料,分别使用支持向量机（SVM）、随机森林（RF）、极度梯度提升决策树（XGBoost）和深度神经网络（DNN）4种机器学习方法,研发了京津冀地区MCS的自动识别算法。使用时、空重叠追踪法对识别的MCS进行追踪匹配,得到包含强度、时间和空间信息的MCS追踪数据资料。在区分线状对流系统和非线状对流系统的基础上,进一步从经典的尾随层云（Trailing Stratiform,TS）、前导层云（Leading Stratiform,LS）和平行层云（Parallel Stratiform,PS）三类准线性MCS的概念模型和结构特征出发,根据追踪轨迹计算MCS的运动方向和MCS近似长轴两侧层状云和强对流云的面积占比,建立准线性MCS的分类算法。MCS的识别属于二分分类问题,以命中率（POD）、虚警率（FAR）、临界成功指数（CSI）和准确率（ACC）为评价指标,综合对比各项指标发现DNN模型较SVM、RF和XGBoost模型对MCS的识别效果更好。使用时、空重叠追踪法对DNN模型识别的MCS进行追踪,结合对两个追踪实例的分析,发现本研究所用的算法取得了很好的追踪结果,也进一步说明了深度学习方法识别MCS的准确性和优势。根据追踪轨迹计算某时刻MCS的运动方向,结合识别的层状云和强对流云的分布位置,准确实现了TS、LS和PS型准线性MCS的分类,为准线性MCS的生命史预测及其致灾天气特别是短时强降水的强度、位置和持续时间的客观预报提供了一种技术思路。 相似文献
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Metamorphism and microstructure of seasonal snow: Single layer tracking in Western Tianshan,China 总被引：1，自引：1，他引：0
Snowpack is a combination of several snow layers. Accordingly, snowpack natural metamorphism is composed of several stages. The aim of this study is to investigate the natural snow metamorphism at the snow layer unit. The field investigation was conducted at the Tianshan Station for Snow Cover and Avalanche Research, Chinese Academy of Sciences(43°16' N, 84°24' E, and 1,776 m a.s.l.), during the winter of 2010-2011. A complete metamorphic procedure and the corresponding microstructure of a target snow layer were tracked. The results indicate that: the ideal and complete metamorphic process and the corresponding predominant snow grain shape have 5 stages: 1) unstable kinetic metamorphism near the surface; 2) unstable kinetic metamorphism under pressure; 3) stable kinetic metamorphism; 4) equilibrium metamorphism; 5) wet snow metamorphism. Snow grain size sharply decreased in the surface stage, and then changed to continuously increase. Rapid increase of grain size occurred in the stable kinetic metamorphism and wet snow metamorphism stage. The characteristic length was introduced to represent the real sizes of depth hoar crystals. The snow grain circularity ratio had a variation of "rapid increase–slow decrease–slow increase", and the snow aggregations continuously increased with time. Snow density grew stepwise and remained steady from the stable kinetic to the equilibrium metamorphism stage. The differences in metamorphism extent and stages among snow layers, led to the characteristic layered structure of snowpack. 相似文献
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Linda J. Young Carol A. Gotway 《Stochastic Environmental Research and Risk Assessment (SERRA)》2007,21(5):589-600
A nationwide Environmental Public Health Tracking program is being created to monitor environmental impacts on human health.
This, and many other efforts to relate environmental and health outcomes, depend largely on the synthesis of existing data
sets; little new data are being generated for this purpose. More often than not, the data available for such synthesis have
been collected for different geographic or spatial units, and any set of these units may be different from the one of interest.
In this paper, we compare and contrast two approaches that can be used within a Geographic Information System to link spatial
data from different sources. The first approach works with centroids of areal units and is commonly used in environmental
health analyses. The second approach honors the spatial support (size, shape and orientation) of the data. Using traditional
regression models and a spatially-varying coefficient regression model, we show that different linkage methods can lead to
different inference. We describe key ideas pertaining to the support of spatial data that are often ignored in many analyses
of environmental health data and present a general analytical approach to change-of-support problems. 相似文献
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用GRACE星间速度恢复地球重力场 总被引：9，自引：2，他引：7
本文首先给出了用星间速度恢复地球重力场的数学模型,然后用GRACE卫星30天的星间速度观测值计算了一个100阶的地球重力场模型DQM2006S2。为了对这一模型的精度进行评述,将它与EGM 96,EIGEN-CHAMP03S和GGM01S3个地球重力场模型作了比较,并用这一模型计算了高程异常与GPS/水准实际观测值进行了比较,结果表明:DQM2006S2模型精度优于EGM 96和EIGEN-CHAMP03S模型精度,但是不及GGM01S模型精度。精度不及GGM01S的原因是GGM01S模型使用了111天的星间速度数据,其数据量约为DQM2006S2模型使用数据量的4倍。 相似文献
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Mathias Versichele Tijs Neutens Matthias Delafontaine Nico Van de Weghe 《Applied geography (Sevenoaks, England)》2012,32(2):208-220
In this paper, proximity-based Bluetooth tracking is postulated as an efficient and effective methodology for analysing the complex spatiotemporal dynamics of visitor movements at mass events. A case study of the Ghent Festivities event (1.5 million visitors over 10 days) is described in detail and preliminary results are shown to give an indication of the added value of the methodology for stakeholders of the event. By covering 22 locations in the study area with Bluetooth scanners, we were able to extract 152,487 trajectories generated by 80,828 detected visitors. Apart from generating clear statistics such as visitor counts, the share of returning visitors, and visitor flow maps, the analyses also reveal the complex nature of this event by hinting at the existence of several mutually different visitor profiles. We conclude by arguing why Bluetooth tracking offers significant advantages for tracking mass event visitors with respect to other and more prominent technologies, and outline some of its remaining deficiencies. 相似文献