基于MODE对模式预报强风风场的检验分析

基于专业气象服务领域十分关注的模式强风预报性能的客观检验和致灾性强风预警服务效果的合理性判别问题,利用一次强风过程对电网专业气象预警服务效果的检验示范,探讨基于目标(面向对象)的诊断检验方法(Method for ObjectBased Diagnostic Evaluation,MODE)对强风事件检验的适用性。通过对强风空间检验的各个关键参数的选择确定、匹配分析,发现:(1)MODE检验的卷积半径、诊断量权重和匹配阈值等参数的选择,将影响检验目标的适度聚焦和误差表达的客观性,因此需要综合考虑预报和实况场的水平分辨率、用户对该类强天气预报误差的空间和时间冗余度等;(2)MODE检验可较好地量化给出模式预报的整体效果,包括:强风落区的范围大小和位置偏差、强风过程的时间相位差等,从而可量化判别出模式在各个时刻的空报和漏报区域以及对强风过程移动速度和生命周期长度的预报性能。     

武汉城市区域水陆风环流的形成与转化特征研究

大气细颗粒物PM_2.5污染引起的雾霾天气既与本地污染物排放密切有关,也受局地特殊的风场影响.本文以武汉城市区域为研究对象,分别研究了长江沿岸的江陆风环流、东湖沿岸湖陆风环流的形成与转化特征,发现江风、湖风开始时间均为07：00-08：00,一年中最大风速均能达到2 m/s左右,而春夏季江风的持续时间高于秋冬季,夏季湖风的持续时间高于春季.同时发现区域附近温度和相对湿度之间有明显的相关性,湿度变化趋势大体上跟温度变化趋势相反,且温度对相对湿度的影响存在一定的滞后性,延迟时间大约为1 h.     

关于带有协作/竞争机制时变积分器网络一致性的收敛速率

本文探讨了时变无向网络达到状态一致过程中的收敛速率问题.首先基于一般的时变无向网络展开研究,证明了其收敛速率随耦合权重的增加而提高.同时,给出了收敛速率的明确下界,并指出这个下界是耦合权重的线性函数.基于这些结论,本文研究了带符号网络的收敛速率问题,发现只要带有正权值的边具有（δ,T）连通性,就可以增大这些边的权重而保持其余边（带有负权值）不变,使一致性以指数的速率达到.本文的证明过程主要基于完全一致可观这一概念.另外,本文也得到了这样的结论：一致性误差值可以从系统一段时间内的相对状态值中重建.这对于分布式网络中滤波器的状态估计有一定的借鉴意义.     

吉林省最高最低气温非对称变化时空演变特征

利用吉林省45个气象站1970-2014年逐日的最高、最低气温资料,分析吉林省最高、最低气温不对称变化在年、季尺度上的时空演变特征。采用经验模态分解法(EMD)分解年、季最高、最低气温序列,分析变化趋势。结果表明:近45年年平均最高、最低气温均呈增加趋势,且最低气温增幅是最高气温的两倍。四季的最高、最低气温变化形式与年变化一致;不同地区之间最高气温的增幅差异不大,最低气温增幅存在一定区别,东部最低气温增幅小于中、西部。相对稳定的增温区出现在西部和中部,不同季节的增温幅度不同,春、夏要强于秋、冬。经验模态分解(EMD)结果显示吉林省年平均最高、最低气温均为增加趋势,而春、冬季中最高气温趋势分量的倾向率与原始序列不同,为负值。夏、秋季中最高气温及四季中最低气温趋势分量序列与原始数据序列的倾向率一致,均为正值但大小存在差异。     

乌鲁木齐机场一次寒潮多相态降水过程分析

利用常规观测资料及新疆区域自动站、乌鲁木齐风廓线雷达、多普勒雷达资料,针对2015年2月13日发生在乌鲁木齐地区的一次雨雪天气过程,从大气背景环境、风温垂直结构、冷暖平流及雨、雪相态转换成因等方面进行分析。结果表明:此次寒潮降水天气的大尺度环流背景是中亚地区高空脊向极区发展,脊顶北风引导极地冷空气南下,在西西伯利亚地区发展成大槽。大槽东移进入新疆地区后,槽后冷空气与北上的西南暖湿气流在天山山区汇合造成此次寒潮降水天气。乌鲁木齐机场出现雪转雨再转雪等相态转换,是由于先受冷平流控制,随着地面冷锋前部暖平流临近,低空暖层厚度加大,降雪粒子在降落过程中融化为雨滴,地面降水相态转为雨夹雪和雨,冷锋系统进入后,再次处于冷平流控制下,降水相态再由雨转为雪。风廓线雷达风场资料的分析结果表明,空中冷暖平流的性质和转换与降水相态变化有较好的对应关系;风廓线垂直速度显示,降雪粒子与雨滴粒子相比,垂直速度较小且雨滴粒子主要集中在1000 m以下。利用多普勒雷达产品分析地面冷锋的移动、空中冷暖平流的变化,有助于对降水相态变化的预报。     

衡阳风变化及风能蕴藏量评估

利用衡阳9站1970—2016年测风数据,通过气候倾向率分析风速年、年代际变化,M-K检验风速突变年份,运用有效风能密度评估各区域风能蕴藏量,其结论如下:衡阳风速总体呈下降趋势,衡山减少最明显,风速减少极显著区域未出现突变;低海拔区风速集中在0～3. 4 m/s(85. 8%),1991—2016年风频两极分化,低速及高速区增多,中间出现断层。南岳山风速范围广,2005—2016年强风频区有缺失,主风频在3～5区间;2010年全面采用高灵敏度自动测风仪,低海拔区静风迅速减少;按照有效风能密度定义,南岳山风能丰富,低海拔区未达到可利用标准。     

Field determination for roughness length above the different non-erodible surfaces

Non-erodible elements, for its disturbance to the near-surface airflow, have been widely used in arid and semi-arid regions to protect the surface from wind erosion. Roughness length was usually used to evaluate the protection effect of non-erodible elements from wind erosion. In this study, the wind profiles above five types of non-erodible surfaces including gravel, wheat straw checkerboard barriers, cotton stem checkerboard barriers, shrubs, and herbs were measured and analyzed. The wind velocities above these surfaces increased with height approximately in logarithmic functions. The roughness length of different non-erodible surfaces was calculated by the functions of wind profiles. The results reveal that:(1) Roughness length increased with wind velocity in given wind velocity ranges. (2) On vegetative surfaces, wind did not effectively bend the stems. The threshold wind velocity for bending the stems of Achnatherum splendens was 4 m/s, 10 m/s for Agropyron cristatum, and for Artemisia ordosica, no obvious bending of stems even for wind velocity reaching 12 m/s. (3) Correlation analysis results show that the vegetation''s coverage and frontal area affect the roughness length more significantly than the other parameters. (4) The protective results of these non-erodible elements were evaluated. The checkerboard sand barriers made of cotton stem could provide more effective protection than that made of wheat straw. In the same coverage conditions, vegetation could provide more effective protection from wind erosion than gravel, and the blending of different non-erodible elements especially the combination of blending of vegeation and checkerboard sand barriers could provide more effective protection to the surface.     

A GIS-based fire spread simulator integrating a simplified physical wildland fire model and a wind field model

??This article discusses the integration of two models, namely, the Physical Forest Fire Spread (PhFFS) and the High Definition Wind Model (HDWM), into a Geographical Information System-based interface. The resulting tool automates data acquisition, preprocesses spatial data, launches the aforementioned models and displays the corresponding results in a unique environment. Our implementation uses the Python language and Esri’s ArcPy library to extend the functionality of ArcMap 10.4. The PhFFS is a simplified 2D physical wildland fire spread model based on conservation equations, with convection and radiation as heat transfer mechanisms. It also includes some 3D effects. The HDWM arises from an asymptotic approximation of the Navier–Stokes equations, and provides a 3D wind velocity field in an air layer above the terrain surface. Both models can be run in standalone or coupled mode. Finally, the simulation of a real fire in Galicia (Spain) confirms that the tool developed is efficient and fully operational.     

Factors controlling the seasonality of the Madden-Julian Oscillation

By analyzing observational data, previous studies have indicated that the tropical Madden-Julian Oscillation (MJO) is active during the boreal winter but relatively weak during the boreal summer. However, the factors that control seasonal MJO variation are not clear. To quantitatively understand the relative contributions of the occurrence frequency of enhanced MJO events and their averaged strength and lifespan to seasonal MJO amplitude, we defined the MJO events of 1979–2014 and analyzed their features in different seasons by using the Real-time Multivariate MJO (RMM) index and the newly proposed RMM-r index. The results indicate that the MJO events show a higher frequency of occurrence, a stronger intensity and a longer duration during the boreal winter (Dec.–Feb.) and spring (Mar.–May). However, the frequency, strength and lifespan of MJO events are all reduced during the boreal summer (Jun.–Aug.) and autumn (Sep.–Nov.). The enhanced MJO events in winter–spring also show a large ratio of variance for eastward to westward components. To elucidate how large-scale background fields affect seasonal MJO variation, a series of sensitivity experiments was conducted by using a 2.5-layer model that can simulate MJO-like features. It is found that the variation in low-level moisture (vertical wind shear) is the key large-scale factor affecting the seasonal variation in MJO strength (in propagation). In comparison with the summer–autumn seasons when the MJO is relatively weakened, the relatively abundant low-level moisture near the equator during boreal winter–spring may strengthen the development of MJO convection and circulation, whereas the relatively weak easterly shear (or the westerly shear anomaly) is conducive to the enhancement of an eastward-propagating MJO component.     

不同天气条件下脉冲激光风廓线仪测风性能

将2012年5月21日-8月16日广东省湛江市东海岛气象观测站内脉冲激光风廓线仪WINDCUBE V2与气象站内的100 m测风塔进行同步观测试验,在经过观测数据同步性调整、有效性检验和代表性样本筛选基础上,分大小风和有无降雨天气过程,对杯式测风仪、超声风速仪与激光风廓线仪的同步测风数据进行比较,结果显示:脉冲激光风廓线仪与杯式测风仪测量水平风参数的相关性较好,10 min平均风速、风向的线性拟合度均大于0.99,3 s阵风风速的拟合度大于0.96,湍流强度的拟合度大于0.67,风速标准差的拟合度大于0.79;大风情况下,激光风廓线仪对风参数的测量效果更佳。无降雨情况下,激光风廓线仪的测量效果较降雨时略好,10 min降水量小于15 mm的降雨对这款激光风廓线仪的风速、风向、湍流强度、3 s阵风风速的测量没有显著影响,对风速标准差有一定影响。当水平风速增大和有降雨时,激光风廓线仪对垂直速度的测量效果欠佳。该对比分析可为激光风廓线仪观测数据的可靠性提供参考。