A 3D multi-threshold,region-growing algorithm for identifying dust storm features from model simulations

Dust storms cause significant damage to health, property, and the environment worldwide every year. To help mitigate the damage, dust forecast models simulate and predict upcoming dust events, providing valuable information to scientists, decision makers, and the public. These simulation outputs are in four-dimensions (i.e., latitude, longitude, elevation, and time) and represent spatially heterogeneous dust storm features and their evolution over space and time. This research investigates and proposes an automatic multi-threshold, region-growing-based algorithm to identify critical dust storm features from 3D dust storm simulations. A multi-threshold scheme is defined for the identification of dust storm features with different dust concentrations. Based on the multi-thresholds, dust storm features are iteratively identified by developing a region-growing algorithm that splits a clustered dust storm feature into multiple sub-features. The proposed approach is compared with three commonly used methods in image processing and thunderstorm identification. The proposed approach outperforms the other three methods in sensitivity and quantitative/qualitative accuracy. This research approach may also be slightly adjusted to identify critical 3D features from simulation outputs for other severe weather and geographical phenomena.     

Rock warming and drying under simulated intertidal conditions,part II: weathering and biological influences on evaporative cooling and near‐surface micro‐climatic conditions as an example of biogeomorphic ecosystem engineering

The way in which rocks and engineering materials heat‐up and dry‐out in the intertidal zone is of relevance to both weathering and ecology. These behaviours can be measured in the laboratory under controlled conditions designed to replicate those occurring in the field. Previous studies have demonstrated differences in thermal behaviours between rock types and through time as a result of soiling in terrestrial environments, but the influence of weathering and colonization on rock behaviours in the intertidal zone has not been previously assessed. We measured the warming and drying of blocks of rock (limestone and granite) and marine concrete during ‘low‐tide’ events simulated in the laboratory, before and after a period of exposure (eight months) on rock platforms in Cornwall, UK. As well as differences between the material types, temperatures of control (unexposed) and field‐exposed blocks differed in the order of 1 to 2 °C. Drying behaviours were also different after field exposure. Differences during the first few hours of exposure to air and heat were attributed to discolouration and albedo effects. Over longer periods of time, changes in the availability of near‐surface pore water as a result of micro‐scale bioerosion of limestone and the development of bio‐chemical crusts on marine concrete [observed using scanning electron microscopy (SEM)] are suggested as mechanisms enhancing and reducing, respectively, the efficiency of evaporative cooling. The retention of moisture by epilithic biofilms may also influence thermal and drying behaviours of granite. These observations represent one of the first examples of cross‐scalar biogeomorphic linkages in the intertidal zone. The significance of the results for the subsequent efficiency of weathering, and near‐surface micro‐climatic conditions experienced by colonizing organisms is discussed. The involvement of microorganisms in the creation of more (or less) ecologically stressful conditions through the alteration of substratum geomorphic properties and behaviours is suggested as an example of ‘biogeomorphic ecosystem engineering’. Copyright © 2011 John Wiley & Sons, Ltd.     

初值及物理过程对\

利用国防科技大学全球中期数值天气预报模式（YinHe Global Spetral model,YHGS）产品驱动WRF对2018年7月4日华中地区暴雨过程进行模拟,并与ERA-interim资料作初始场模拟结果对比,评估YHGS模式产品在此次暴雨过程预报中的应用能力。结果表明：（1）WRF-YHGS对2018年7月4日华中地区暴雨过程有一定的预报能力,其模拟的大尺度环流形势、水汽收支量变化趋势与WRF-ERA有着很好的一致性,YHGS模式产品驱动中尺度数值预报是可行的。（2）WRF-YHGS模拟效果较WRF-ERA差,但大雨量级WRF-ERA湿偏差较大,两组试验各物理量模拟结果存在一定差距,且随着积分时间的增加差异逐渐增大。（3）WRF-YHGS、WRF-ERA模拟结果的差异主要来自YHGS与ERA初始场中差异较大的次天气尺度运动和YHGS全球模式预报场误差两个方面。

     

1951—2008年北京极端天气事件分析

采用湖南14个地市州所在地国家气象站1980—2013年逐分钟降雨资料, 分别利用模糊识别法、芝加哥法、Pilgrim & cordery法及同频率法对各地短历时60 min、90 min、120 min、150 min、180 min以5 min为单位时段的暴雨雨型进行了识别和推求, 结果表明:推求的各地暴雨雨型基本以峰值在前部的单峰型为主; 芝加哥、Pilgrim & cordery计算的峰值、强度相当, 推求的各历时暴雨雨型基本一致, 也更接近实际, 同频率法相对来说效果较差些。

     

2017年洞庭湖特大洪水分析

2017年6月22日至7月1日,湖南省大部分地区发生了持续性强降雨过程。暴雨在湘水、资江、沅水及洞庭湖区来回摆动,三水(湘、资、沅)及湖区周边洪水接近于同时入湖,造成了洞庭湖历史罕见的特大洪水,入湖洪峰出湖洪峰均为1954年以来最大。     

3维场景植被冠层多波段模拟研究进展

植被冠层辐射散射信号中蕴含了丰富的植被信息,通过构建植被冠层辐射散射模型,可以实现植被结构等生物物理参数的遥感定量反演。迄今为止,可见光/近红外、热红外、微波波段均已发展了大量的模型,这些模型在参数反演方面各具优势,但不同波段的模型又有其自身的局限性。跨波段的联合模拟可以实现模型间的优势互补,进而提高地表参数的反演精度,近年来已有学者专注于可见光/近红外与热红外模型,热红外与微波模型,主被动微波模型,以及可见光/近红外与微波模型的联合模拟和协同反演,但多是两两联合,且主要是基于经验模型或解析模型。基于3维场景的植被冠层辐射散射特性模拟模型可以细致刻画不同组分的结构和空间分布特征,对于由植被结构引起的多次散射和组分比例变化的考虑具有优势。本文主要介绍了3维模拟模型在可见光/近红外、热红外和微波波段,以及跨波段联合模拟方面的研究进展,从模型机理、场景统一、以及组分理化参数的统一的角度,探讨了构建多波段3维模拟系统的可行性,展望了多波段3维模拟模型的发展趋势。     

地面数字化测图模拟与仿真平台的三维可视化

介绍地面数字化测图模拟与仿真平台三维建模的基本思想,给出了地面数字化测图模拟与仿真平台三维建模过程和建模中相关问题的解决办法,达到了平台在GIS软件中多方位的动态三维可视化效果。     

复杂地区机载SAR数据获取航线规划

本文主要论述机载SAR数据获取航线规划,提出了适合于地形复杂地区机载SAR航摄的航线规划方案。详细说明了航线设计方法,并引入低分辨率的DEM数据,对航线规划结果进行了模拟;最后对机载合成孔径雷达航摄进行三维模拟,以期更好地显示并检验航线规划结果。     

《海洋数值模拟》课程建设的探索

《海洋数值模拟》是淮海工学院面向海洋技术专业本科生开设的专业选修课程。以培养海洋科学专业学生的数值模拟技能为目标,以研究海洋环境动力机制为导向,研究了《海洋数值模拟》课程的教学案例,提出了关于该课程建设上的思考,教学实践表明,学生的基本技能得到明显提高,学习兴趣普遍增强。     

Quantifying uncertainty in remote sensing-based urban land-use mapping

Land-use/land-cover information constitutes an important component in the calibration of many urban growth models. Typically, the model building involves a process of historic calibration based on time series of land-use maps. Medium-resolution satellite imagery is an interesting source for obtaining data on land-use change, yet inferring information on the use of urbanised spaces from these images is a challenging task that is subject to different types of uncertainty. Quantifying and reducing the uncertainties in land-use mapping and land-use change model parameter assessment are therefore crucial to improve the reliability of urban growth models relying on these data. In this paper, a remote sensing-based land-use mapping approach is adopted, consisting of two stages: (i) estimating impervious surface cover at sub-pixel level through linear regression unmixing and (ii) inferring urban land use from urban form using metrics describing the spatial structure of the built-up area, together with address data. The focus lies on quantifying the uncertainty involved in this approach. Both stages of the land-use mapping process are subjected to Monte Carlo simulation to assess their relative contribution to and their combined impact on the uncertainty in the derived land-use maps. The robustness to uncertainty of the land-use mapping strategy is addressed by comparing the most likely land-use maps obtained from the simulation with the original land-use map, obtained without taking uncertainty into account. The approach was applied on the Brussels-Capital Region and the central part of the Flanders region (Belgium), covering the city of Antwerp, using a time series of SPOT data for 1996, 2005 and 2012. Although the most likely land-use map obtained from the simulation is very similar to the original land-use map – indicating absence of bias in the mapping process – it is shown that the errors related to the impervious surface sub-pixel fraction estimation have a strong impact on the land-use map's uncertainty. Hence, uncertainties observed in the derived land-use maps should be taken into account when using these maps as an input for modelling of urban growth.