鲁西北连续两次强降水过程对比分析

利用各种观测资料和NCEP/NCAR 1×1°再分析资料,对2012年7月30日夜间和31日夜间鲁西北连续两天强降雨天气进行诊断和对比分析。结果表明:强降水产生在西风槽前和副热带高压边缘的偏南暖湿气流中,西风槽稳定少动,台风在东南沿海北上,副高加强北抬,为鲁西北连续两天的强降水提供了天气尺度背景。925hPa及以下的低层,来自于渤海的偏东气流和来自于华东沿海的东南气流同时向鲁西北强降水区输送水汽,低层比湿大,CAPE和K指数较高。第1次强降水产生在偏南气流的暖区中,降水强度大,维持时间短。第2次强降水期间,低层有冷空气锲入,把暖湿气流抬升,前期为对流性降水,中后期转为稳定性降水,降水强度小,维持时间较长。850hPa及以下倒槽式切变线和中尺度低涡环流是造成强降水的中尺度影响系统,近地面层来自于渤海的东北气流与来自于东南沿海的东南暖湿气流形成中尺度涡旋,产生气旋式辐合上升,触发对流不稳定能量释放。对流云团在鲁西北形成长形的中尺度对流系统(MCS),稳定少动,有明显的列车效应和后向传播特征。强降水具有较强的日变化,夜间发展增强,白天减弱。     

2016年6月海南一次龙卷过程分析

利用19612015年陕西省70个气象观测站的逐日降水资料,采用线性倾向估计、趋势分析及Mann Kendall等方法,分析了陕西省不同等级降水量、降水日数及降水强度的气候变化特征。结果表明：无论是降水量、降水日数,还是降水强度,均呈现出南多北少的分布特征,且随着降水级别的逐级增加,地区分布差异逐渐增大;整体上降水量和降水日数呈现出减少趋势,其中降水日数的下降趋势均非常显著,全省年均降水日数的气候倾向率达到了-3.83天·10a-1,通过了0.01的显著性检验,降水强度的增加趋势通过了0.05的显著性检验,每10 a全省年均降水强度增加0.15 mm·d-1;陕西降水量及降水日数的减少主要体现在春秋两季小雨及中雨的减少上,小雨降水强度在夏、秋两季的气候倾向率分别为0.05和0.04 mm·d-1·10a-1,其上升趋势分别通过了0.01和0.1的显著性检验,这是年均降水强度上升的主要原因;陕西年均降水量及降水日数自1984年出现了突变性下降,而降水强度的突变则出现在2004年,之后一直呈现持续的上升趋势。     

临沂冰雹发生规律及预警技术研究

利用常规观测资料和多普勒雷达探测资料,对临沂地区冰雹的时空分布特征、冰雹天气的预警参数和指标进行分析研究。结果表明:20世纪60-80年代是临沂冰雹高发期,90年代后明显减少,下降趋势十分明显。5-6月是临沂降雹最集中的时段。山地和丘陵地区降雹频次明显比平原地区的高。发生冰雹天气与环境参数有密切关系,出现大冰雹过程要求更为适宜的0℃层高度,在强垂直风切变环境下出现大冰雹的可能性更大。大部分地面开始降雹都是在C-VIL跃增后2~3个体扫和强反射率因子核心快速下降之时,这两个特征在冰雹预报预警工作中有一定的参考价值,对于冰雹预警的发布具有10~20 min的时间提前量。强回波中心最大值及其所在高度和有界弱回波区BWER或弱回波区WER的范围等都是判断降雹潜势的关键指标。季节性的预警指标在实际业务工作中有一定的参考价值,能够有效提高冰雹预警的准确率。     

风云三号C星微波全球地表温度产品精度评估

地表温度是衡量地表水热平衡的关键参数,微波地表温度因其范围大、全天候等独特的优势,在气候、农业和环境等领域得到广泛应用。基于经质量控制的MODIS地表温度产品对风云三号卫星C星的微波地表温度日产品和月平均产品进行验证评估,结果显示:FY-3C卫星升轨(夜晚)和降轨(白天)微波地表温度日产品平均分别高估8. 7 K、低估13. 2 K,月平均产品平均分别高估7. 9 K、低估12. 0 K,日产品和月平均产品的反演误差都在15K以内。在全球空间分布上,升轨(夜晚)和降轨(白天)月产品误差分别呈现高估和低估,热带雨林区和沙漠、荒漠区域在夜晚分别高估5 K以内和30 K以内,白天则分别低估10 K以内和10～30 K。不同土地覆盖类型间FY-3C微波地表温度反演精度存在差异,总体上升轨(夜晚)比降轨(白天)的精度高,反演精度最高和最低的土地类型分别是常绿阔叶林和荒漠、稀疏植被,不同土地覆盖类型间的地表温度反演精度在季节上存在明显差异。根据分析结果,改进FY-3C微波地表温度的反演算法,可进一步提高微波地表温度的反演精度。     

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。     

恩施“6·24”暴雨中尺度系统特征分析

利用常规观测资料、自动区域站雨量、卫星TBB资料、雷达资料,对恩施州2016年6月24—25日发生的一次大范围暴雨过程进行分析。结果表明:本次强降水,具有典型的两槽一脊"单阻型"梅雨环流特征,在有利的大尺度环流背景下,在高空槽、低层低涡切变、西南急流、地面中尺度辐合线等中尺度天气系统的共同影响、相互作用下,形成了此次大范围强降水。此次暴雨空间上分布不均,局地性强,表现为明显的中尺度对流性特征,雷达回波图上降水性质表现为混合型降水,暴雨的直接影响系统是中β尺度对流系统,且中β尺度对流系统在多个中尺度对流云团合并后加强,时间尺度约为5 h。此次暴雨过程是在上干冷下暖湿强的大气层结不稳定条件下,梅雨锋、边界层辐合线和地形槽的触发作用将前期积累的能量释放产生的强对流天气,同时,副高外围西南气流将南海和西太平洋的水汽向恩施输送,为暴雨的发生提供了有利的条件。     

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.     

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.