降水现象对大气消光系数和能见度的影响

大气中各种粒子对大气消光系数和能见度有不同程度影响,除气溶胶粒子外,降水粒子对能见度影响也不可忽视。为了解降水粒子对能见度的影响,确定能见度变化与降水现象之间的关系,该文在分析降水粒子的大小、速度、形状、谱分布、光学特性等特征的基础上,忽略气溶胶粒子的影响,建立基于实测谱分布的降水与能见度的理论模型,讨论不同类型降雨、降雪对大气消光系数和能见度的影响。同时选取Parsivel降水粒子谱仪在南京地区的降雨和降雪观测记录,利用实测数据来对比验证本文所建立的降水-能见度理论模型。结果表明:能见度随着降水强度的增大呈指数降低;受降水粒子特性和天气条件等多种因素影响,能见度与降水强度之间的关系并不是唯一对应的;降雨和降雪对能见度的影响各不相同,相比而言,降雨对能见度的影响比较容易确定,而降雪对能见度的影响比较复杂,主要因为雪花或冰晶的类型复杂多变,对大气消光系数有不同程度的影响。结合理论分析和实测数据对比验证,降水现象对能见度的影响得到了证实。     

Mapping 3D visibility in an urban street environment from mobile LiDAR point clouds

ABSTRACT

Visibility determination is a key requirement in a wide range of national and urban applications, such as national security, landscape management, and urban design. Mobile LiDAR point clouds can depict the urban built environment with a high level of details and accuracy. However, few three-dimensional visibility approaches have been developed for the street-level point-cloud data. Accordingly, an approach based on mobile LiDAR point clouds has been developed to map the three-dimensional visibility at the street level. The method consists of five steps: voxelization of point-cloud data, construction of lines-of-sight, construction of sectors of sight, construction of three-dimensional visible space, and calculation of volume index. The proposed approach is able to automatically measure the volume of visible space and openness at any viewpoint along a street. This approach has been applied to three study areas. The results indicated that the proposed approach enables accurate simulation of visible space as well as high-resolution (1 m × 1 m) mapping of the visible volume index. The proposed approach can make a contribution to the improvement of urban planning and design processes that aim at developing more sustainable built environments.     

郑州市市区风环境模拟研究

城市风环境是城市微气候研究的一个重要方向,对分析城市热岛效应、空气流通等具有重要意义。本文以郑州市市区为例,使用1971—2018年气象观测数据、2018年建筑分布数据（OSM）和2016年资源三号卫星数据作为数据源,通过运用气象学和GIS技术结合的方法,探究潜在通风廊道,科学量化城市形态对风环境的影响。研究首先借助WindNinja软件,对城市背景风环境进行模拟分析,该计算方法提高了风道定位的精度。然后利用卫星遥感数据制作了数字高程模型（DSM）,结合OSM计算下垫面地表粗糙度。进一步借助ArcGIS软件,利用最小成本路径法（LCP）确定城市潜在通风廊道的位置。结果表明：① 郑州市近年来平均风速缓慢下降,平均每10年下降0.26 m/s;全年主导风向东北风进入城市后受城市形态影响在京广铁路线附近以西逐渐转为东北偏东风,其中在京广快速路以东风速较高,在京广快速路以西风速较低;② 金水区西部、中原区、二七区以及管城区的地表粗糙度较高,通风环境较差;金水区东部和惠济区的地表粗糙度较低,通风环境较好;③根据盛行风向模拟的潜在通风廊道,其共同特点是趋向于低粗糙度的地区。     

天津港秋冬季低能见度数值释用预报研究

本文利用近5年(2009—2013年)天津港资料,分析了该地区大气能见度的分级特征。采用7年秋、冬季NCEP(2006—2012年)和地面资料,通过相关分析给出了对港口低能见度天气有高影响的高、低空物理量因子;排除沙尘和降水天气,针对不同区间的能见度样本,利用BP神经网络方法分类训练了3个统计模型;并与WRF天气模式产品对接,采用分步筛选法,研发了天津港秋、冬季72 h时效的逐时能见度BP释用预报产品。经过3年业务运行,检验结果表明:对逐时能见度而言,BP释用预报对10 km以下低能见度比WRF模式的预报技巧显著提高,达到10.5%~35.4%;其中对0.5 km大雾的预报技巧总体相当,但当WRF预报有降水时,WRF模式预报结果略优;对0.5~1 km的大雾预报,WRF模式的预报技巧1%,BP释用预报提高到了14%~21%。日最低能见度的检验表明:对小于1 km的大雾过程,BP释用预报的TS评分平均达到75%,比WRF预报技巧提高了24%;对1~10 km的低能见度过程,比WRF的预报技巧平均提高了60%。     

基于全视野数字图像的能见度估算方法

基于全视野数字图像的能见度估算方法是将全视野图像大气透射率与大气能见度通过曲线拟合方法建立联系,得到估算模型进行能见度估算。首先通过历史全视野图像和对应时刻的大气能见度建立样本数据集,再利用暗原色先验理论获取全视野图像大气透射率,通过多项式拟合方法建立离散样本数据集中大气透射率与对应时刻大气能见度的关系,即全视野图像能见度估算模型,最终将所需估算时刻的数字图像输入估算模型进行能见度估算,得到大气能见度数值。结果表明:建立的基于全视野数字图像能见度估算模型在环境光照均匀时大气能见度估算值与能见度实测值有较好的一致性,可作为前向散射仪的补充观测方法,弥补其采样存在的局限性。     

基于WRF模式的青岛近海能见度算法比较研究

采用GFS背景场资料和ADAS资料同化系统,使用WRF模式对2014—2016年青岛近海17个海雾个例进行了模拟,分析了3种能见度算法的预报效果。结果表明, FSL（Forecast Systems Laboratory）算法对于沿海站、岸基站雾的预报较SW99（Steolinga and Warner 1999）算法有优势;对于海岛站而言,SW99算法则优于FSL算法。混合算法CVIS（Combined Visibility）较单一算法预报雾准确率有所提高。3种能见度算法基本上是高估能见度的,SW99算法能见度预报均方根误差最大。另外,SW99算法对沿海站、岸基站雾开始时间预报较实况多偏晚,结束时间预报较实况多偏早,持续时间预报较实况多偏短。     

呼伦贝尔市大气能见度影响因子及一次低能见度个例分析

为探寻呼伦贝尔市大气能见度、低能见度特征及其影响因子,揭示"冰晶雾"天气成因,利用呼伦贝尔市大气能见度资料及地面气象要素资料对4个代表站的能见度进行统计分析,并对一次典型低能见度事件进行分析,结果表明:(1)整个地区大气能见度的气候特征在空间分布及时间演变上均存在较大的不一致性,牧区能见度优于农区;(2)大气能见度与相对湿度和气压呈负相关,与气温和风速以正相关为主;(3)大气低能见度出现的集中时段是冬季,伴随最多的天气现象为结冰、积雪和霜;(4)2 m温度低于零下36℃,对于浓雾的产生具有指示意义。     

2011—2015年安徽省高速公路低能见度变化特征

利用2011—2015年安徽省高速公路自动气象观测站观测的能见度资料,分析了安徽省低能见度年、日变化及其与降水的关系,结果表明：受降雨影响,大别山区和皖南山区部分站点低能见度出现频率最高时段在汛期（5—9月）,其他地区主要出现在10月和11月。低能见度出现时间存在明显日变化,夜间出现频率高于白天,19：00以后开始逐渐增多,日出前后达到最大,之后迅速减少。7—8月的13：00—17：00出现与降水相关的低能见度频率较高。不同季节里,各站低能见度出现最多的时间和频率存在一定差异,春季和秋季最低能见度主要出现在日出前后,冬季主要出现在夜间到日出之前,夏季江淮之间北部和淮北地区主要出现在日出前后,江淮之间南部到江南在一天各时间段内出现频率较为均匀。     

COMPREHENSIVE ANALYSIS OF THE MACRO- AND MICRO-PHYSICAL CHARACTERISTICS OF DENSE FOG IN THE AREA SOUTH OF THE NANLING MOUNTAINS

Using the composite field observational data collected in the area south of the Nanling Mts. and numerical modeling, the seasonal features of dense fog and visibility, fog drop spectrum and physical concept of fog forming have been analyzed. The occurring frequency of low visibility（≤200 m） is very high with a mean of 24.7%, a maximum of 41.8% from the end of autumn to winter and next spring. The fog processes that occur in the area south of the Nanling Mts. in spring and winter result from the interactions of complicated micro-physical processes, the local terrain, water vapor transportation and the influencing weather system. The fog processes are arisen from advection or windward slope, which is much different from the radiation fog. Cooling condensation due to the air lifted by the local mountain plays an important role in fog formation. Windward slope of the mountain is favorable to the fog formation. Dense fog can occur at lower altitudes in the windward slope of mountain, resulting in the lower visibility. The fog is mainly of small-drop spectrum with smaller number-density than that of urban fog, and its drop spectrum has descending trend in the section of smaller diameter. The inverse relationship between fog water content and visibility is the best among several relationships of micro-variables. In addition to micro-physical processes of fog body itself, the motion of irregular climbing and crossing over hillside while the fog body is being transported by the wind are also important reasons for the fluctuation of micro-physical parameters such as fog water content.     

Using visibility analysis to improve point density and processing time of SfM-MVS techniques for 3D reconstruction of landforms

Image network geometry, including the number and orientation of images, impacts the error, coverage, and processing time of 3D terrain mapping performed using structure-from-motion and multiview-stereo (SfM-MVS). Few studies have quantified trade-offs in error and processing time or ways to optimize image acquisition in diverse topographic conditions. Here, we determine suitable camera locations for image acquisition by minimizing the occlusion produced by topography. Viewshed analysis is used to select the suitable images, which requires a preliminary digital elevation model (DEM), potential camera locations, and sensor parameters. One aerial and two ground-based image collections were used to analyse differences between SfM-MVS models produced using: (1) all available images (ALL); (2) images selected using conventional methods (CON); and (3) images selected using the viewshed analysis (VIEW). The resulting models were compared with benchmark point clouds acquired by a terrestrial laser scanner (TLS) and TLS-derived DEMs. The VIEW datasets produced denser point clouds (28–32% more points) and DEMs with up to 66% reduction in error compared with CON datasets due to reduction of gaps in the DEM. VIEW datasets reduced processing time by 37–76% compared with ALL, with no reduction in coverage or increase in error. DEMs produced with ALL and VIEW datasets had similar slope and roughness, while slight differences that may be locally important were observed for the CON dataset. The new method helps optimize SfM-MVS image collection strategies that significantly reduce the number of images required with minimal loss in coverage or accuracy over complex surfaces. © 2020 John Wiley & Sons, Ltd.