天气雷达组合风场显示产品的检验评估

采用绝对误差、相对误差、皮尔逊相关系数、样本数量分布图等统计方法对中国气象局气象探测中心下发的2012年8月至2017年7月天气雷达组合风场显示产品进行质量评估,结果表明:①该产品与探空风场有较高的相关性,两种资料没有系统性差异,风向相关性优于风速;②随高度升高,该产品和探空资料的相关系数变差,500hPa以下高度的风场数据可用性较高;③产品质量与降水有着密切的关系,天气尺度的稳定性降水有利于提高风场反演质量,非气象回波、强对流天气情况下雷达反演风场质量均会下降。④产品质量与地形复杂程度有一定的关系。     

福建省暴雨洪涝灾害风险评估与管理

利用安徽省1961—2016年81个国家级地面气象观测站雨量、2006—2016年1 162个地面自动观测站小时雨量、1961—2016年安徽省民政厅灾情和2006—2016年《安徽省气象灾害年鉴》收录的227个暴雨过程灾情数据,采取气候平均、广义极值、概率密度函数、百分位分布等方法,统计暴雨过程的持续天数、区域、范围、平均日降水量和小时雨量对暴雨灾害的影响,划分安徽省暴雨灾害预警等级。结果表明：（1）安徽省暴雨灾害预警等级可分为Ⅳ级（轻度）、Ⅲ级（中度）、Ⅱ级（重度）、Ⅰ级（特重）四个等级;（2）从Ⅳ级到Ⅰ级,暴雨过程的持续天数指标从1—4 d,范围指标根据暴雨区占区域总面积的百分比确定,从Ⅳ级的20%上升至Ⅰ级的80%;（3）根据暴雨过程的区域差异,将安徽分为沿淮淮北、大别山区及皖南山区、沿江及江淮之间三个区域,分别建立降水量与暴雨灾情的定量关系,并在每个区域设置相应的平均日降水量和小时雨量指标;（4）利用上述暴雨灾害预警等级,对1981—2018年安徽省致灾的149个暴雨过程进行回代检验,并将其用于2020年6—7月安徽省暴雨灾害预警,暴雨灾害预警发布周期为Ⅳ级（轻度）0.66~0.82 a、Ⅲ级（中度）1.15~1.90 a、Ⅱ级（重度）3.16~3.80 a、Ⅰ级（特重）9.5~12.6 a,符合安徽暴雨灾情实际,可以为气象部门启动暴雨应急响应提供参考。

     

6种数值模式在安徽区域天气预报中的检验

本文检验了从2006年6月到2008年12月,Grapes、MM5、WRF、T213、JMA和Germany共6个模式对安徽区域72 h内降水量、风速和气温的预报。降水量TS评分显示,从小雨到大雨,JMA的参考价值较高,从大雨到大暴雨则是MM5和WRF比较好;Germany和T213的评分均处于中间水平,而Grapes评分最低。冬夏季各模式的预报较好,其他季节预报较差。风速,24 h JMA和T213的预报较好,48、72 h MM5和WRF的参考价值较高。气温,24、48 h MM5和WRF预报较好,而72 h则是MM5和T213好。Grapes对风速和气温的预报相对较差。上述检验结果不仅有助于预报员更好地利用数值模式制作天气预报,而且为数值天气预报的解释应用提供科学依据。     

中国南方暴雨野外试验中尺度气象分析场的建立及其质量评估

利用武汉暴雨研究所从美国引进的LAPS中尺度分析系统,将2008年和2009年5-7月中国南方暴雨野外科学试验(SCHeREX)中所采集的观测资料进行融合、同化,生成了华南、华中、江淮和长江三角洲4个观测区的空间分辨为5 km、时间分辨为3 h的SHCeREX中尺度气象分析场.文中从两方面对SCHeREX中尺度分析场的...     

Machine learning reveals the influences of grain morphology on grain crushing strength

Acta Geotechnica - Grain morphology has significant impacts on the mechanical behaviors of granular materials. However, its influences on grain breakage are still poorly understood due to the...     

夏季江淮地区降水的气候变化研究进展

针对夏季江淮地区降水的气候变化进行了文献综述和展望。首先回顾了中国大陆东部夏季降水进退研究情况,然后重点概述了中国大陆东部降水气候变化的研究成果、江淮梅雨气候变化和该地区夏季极端降水的研究成果、中国大陆中东部对流降水与层状降水的气候变化研究现状,随后对引起江淮地区夏季降水气候变化的影响机理研究做了回顾。文章最后指出未来要加强五个方面的研究,即江淮地区降水气候变化的综合机理研究、天气学研究、大气污染作用研究、云物理学研究和观测技术方法研究。     

底板突水预测与评价的专家系统方法研究

突水预报是一个涉及到水文地质、工程地质、开采条件、岩石力学等诸多因素的复杂问题,借助于防治水领域知名专家的实践经验和防治水知识,运用合理的推理方法,考虑影响底板突水的多方面因素,建立一种底板突水预测与评价的专家系统方法,一方面可以总结、运用和推广现场实践经验,另一方面,采用规则的形式来表示预测专家的判断性知识,运用可信度值来反映专家经验的不确定性,又能提高预测预报的成功率与准确性,为受底板水威胁矿区的安全生产提供保证.     

Application and Verification of Joint Probability Method in Potential Forecast for Severe Convective Weather in Anhui Province

In consideration of large uncertainties in severe convective weather forecast, ensemble forecasting is a dynamic method developed to quantitatively estimate forecast uncertainty. Based on ensemble output, joint probability is a post-processing method to delineate key areas where weather event may actually occur by taking account of the uncertainty of several important physical parameters. An investigation of the environments of little rainfall convection and strong rainfall convection from April to September (warm season) during 2009-2015 was presented using daily disastrous weather data, precipitation data of 80 stations in Anhui province and NCEP Final Analysis (FNL) data. Through ingredients-based forecasting methodology and statistical analysis,four convective parameters characterizing two types of convection were obtained, respectively, which were used to establish joint probability forecasting together with their corresponding thresholds. Using the ECMWF ensemble forecast and observations from April to September during 2016-2017, systematic verification mainly based on ROC and case study of different weather processes were conducted. The results demonstrate that joint probability method is capable of discriminating little rainfall convection and non-convection with comparable performance for different lead times, which is more favorable to identifying the occurrence of strong rainfall convection. The joint probability of little rainfall convection is a good indication for the occurrence of regional or local convection, but may produce some false alarms. The joint probability of strong rainfall convection is good at indicating regional concentrated short-term heavy precipitation as well as local heavy rainfall. There are also individual missing reports in this method, and in practice, 10% can be roughly used as joint probability threshold to achieve relative high TS score. Overall, ensemble-based joint probability method can provide practical short-term probabilistic guidance for severe convective weather.     

High-resolution mesoscale analysis data from the South China heavy rainfall experiment (SCHeREX): Data generation and quality evaluation

In this study, the observational data acquired in the South China Heavy Rainfall Experiment (SCHeREX) from May to July 2008 and 2009 were integrated and assimilated with the US National Oceanic and Atmospheric Administration’s (NOAA) Local Analysis and Prediction System (LAPS; information available online at ). A high-resolution mesoscale analysis dataset was then generated at a spatial resolution of 5 km and a temporal resolution of 3 h in four observational areas: South China, Central China, Jianghuai area, and Yangtze River Delta area. The quality of this dataset was evaluated as follows. First, the dataset was qualitatively compared with radar reflectivity and TBB image for specific heavy rainfall events so as to examine its capability in reproduction of mesoscale systems. The results show that the SCHeREX analysis dataset has a strong capability in capturing severe mesoscale convective systems. Second, the mean deviation and root mean square error of the SCHeREX mesoscale analysis fields were analyzed and compared with radiosonde data. The results reveal that the errors of geopotential height, temperature, relative humidity, and wind of the SCHeREX analysis were within the acceptable range of observation errors. In particular, the average error was 45 m for geopotential height between 700 and 925 hPa, 1.0–1.1°C for temperature, less than 20% for relative humidity, 1.5–2.0 m s⁻¹ for wind speed, and 20°–25° for wind direction. The above results clearly indicate that the SCHeREX mesoscale analysis dataset is of high quality and sufficient reliability, and it is applicable to refined mesoscale weather studies.     

行车荷载作用下冲填土变形特性试验研究

本文以上海临港新城冲填土地层分布区的道路在车辆振动荷载作用下路基变形为研究对象,以一定的动应力、不同的振动频率来模拟车辆振动荷载,进行了振动三轴试验研究,试验结果表明:在固结比相同,振动幅值相同的情况下,轴向应变随着振动次数的增加呈线性增大;轴向应变随孔隙水压力的增加先缓慢增长,当孔压比达到一定值后,轴向应变会迅速增加,直到破坏;轴向应变与剪应变和径向应变呈良好的线性关系。