Long‐term monitoring of a mercury contaminated estuary (Ria de Aveiro,Portugal): the effect of weather events and management in mercury transport

The main aim of this research was to assess the mercury transport from an estuarine basin with a background of anthropogenic contamination during a spring tidal cycle (year 2009) and compare it with two previous tidal cycles (years 1994 and 1999), as part of a long‐term monitoring program. Results showed that effective mercury transport occurs both in the dissolved and particulate fractions (0.18 and 0.20 kg per tidal cycle, respectively), and despite an overall decrease in environmental contamination, results more than double previous findings on particulate transport in the system. These findings result essentially from changes in the tidal prism (net export of 2 million m³ of water), given that both dissolved and particulate concentrations did not increase over time. Hydrodynamic simulations were performed to evaluate the effect of physical disturbance (dredging) and weather events (increased freshwater flow) in these processes, and results suggest the increased freshwater flow into the system as the main forcing function for the mercury transport increment. These results highlight the importance of long‐term monitoring programs, since despite an overall improvement in local contamination levels, the enhancement of transport processes through hydrological changes increases environmental pressure away from the contamination source. Copyright © 2012 John Wiley & Sons, Ltd.     

一种基于卫星遥感的临近预报方法

中尺度对流系统（MCS）是形成强对流天气的主要原因，云团在MCS生命周期中的分裂合并问题是临近预报的难点。为解决这一问题，本文提出了FCC方法，该方法使用质心位移和FY-2卫星数据预测多个对流单体的运动轨迹。多个案例分析证明，FCC算法在MCS的各个生命周期均能进行有效的预测，包括初生、成熟和消散阶段。此外，通过列联表方法验证了所提算法的有效性。     

Comprehensive study of the drying behavior of Boom clay: Experimental investigation and numerical modeling

This paper presents a thermo‐hydro‐mechanical framework to model the drying behavior of Boom clay. First, the experimental campaign conducted Noémie Prime is briefly presented because it is used to validate the model. The data acquisition and processing is emphasized because of the use of X‐ray microtomography to be able to more accurately compare experimental and numerical strain fields. The different submodels are introduced. Numerical simulations are performed to illustrate the capability of the proposed model to reproduce the observed behavior. Finally, a comprehensive sensitivity study on several key model parameters associated with the water retention curve, and the permeability of the medium, is performed to get a better understanding of the physics behind the coupled model.     

“6·23”江苏阜宁EF4级龙卷超级单体风暴中尺度结构研究

2016年6月23日14—15时，江苏省阜宁县突遭"增强藤田"4级龙卷、强风、短时强降水和冰雹等强对流天气，致使99人罹难，800多人受伤，属极其罕见的极端天气事件.本文利用加密自动站数据、探空数据、单部雷达观测数据以及双多普勒雷达三维风场反演数据，研究了此次龙卷发生的天气背景、龙卷超级单体的三维结构及其演变特征.研究表明：（1）龙卷发生期间，阜宁处于地面暖湿舌内、地面有γ中尺度气旋和辐合线；环境大气抬升凝结高度很低、中低层有很强的水平风的垂直切变；这有利于龙卷的生成.（2）此次龙卷超级单体左移风暴的低层有钩状回波和入流缺口，有界弱回波区位于垂直剖面中低层、悬垂回波位于风暴前部高层.（3）龙卷发生前，风暴质心高度、最大反射率因子高度和风暴回波顶高度均持续增加，风暴垂直累积液态含水量激增；龙卷发生在上述参数的数值首次同时减小时.（4）双多普勒雷达反演的三维风场揭示，超级单体形成之前的对流风暴内部中低层已经有中尺度气旋形成，中尺度气旋伴随着超级单体的生成、发展和强化的各个阶段.中尺度气旋位于钩状回波顶端、其南端有反气旋，此涡旋偶对于中层动量下传、龙卷生成、发展、加强和触地具有重要作用.     

地面稠密观测资料在强对流天气监测预警中的研究进展

综述国内外数篇论文,从强对流天气监测、预报预警、模式同化3个方面总结分析了近年来地面稠密观测资料的应用与优劣之处。综述表明:地面加密自动站、风廓线雷达、地基GPS、雨滴谱仪等多种观测仪器组成的地面稠密观测网具有时间尺度密集、覆盖面积广泛、能捕捉较多细微变化的优势,通过该观测网所得数据总结出的一系列指示性指标在强对流监测预警中具有重要的指示意义。但因中国地形天气情况复杂多变、数据缺失、仪器造价昂贵等问题,导致该观测网所得指示性指标不能适用于中国全境,应根据该观测网数据分析总结适应本地的预报指标。     

基于大数据分析下的气候模型

为研究全球变暖与极寒天气间的关系，对加拿大13个省代表性测站10年的观测数据进行时空变化趋势分析，采用经验正交函数（EOF）寻找海洋表面温度历史数据的变化规律。另外利用BP神经网络建立了年平均温度、日降水量与地球吸热、散热、海表面温度、当地纬度间的关系，预测未来25年气候的变化，并建立了“极寒天气”与气候变化的关系模型。研究表明：高纬度地区温度、降水量普遍较低，同经度地区的温度差异较小且降水量变化不大；加拿大地区温度呈周期性变化，符合北半球的季节变化特征；北大西洋的东部与其他海洋的温度是反相关的，西太平洋南北回归线附近的海洋表面温度升高；“极寒天气”出现频率与气候变化有一定关系，局地极寒现象与全球变暖的大趋势并不矛盾。本研究为人们认识和理解“全球变暖”提供了一个新的思路。     

风云三号C星SEM高能粒子数据检验及应用

风云三号C星(FY-3C卫星)空间环境监测器(SEM)可监测轨道高度上的高能带电粒子(质子、电子和重离子)辐射环境及其引起的辐射剂量和表面充电等空间天气效应,是空间天气监测预警业务不可或缺的自主数据源之一。为验证FY-3C卫星高能粒子探测数据的有效性,需开展数据的定量检验工作。本文采用与同类卫星同类数据进行交叉比对的方式来进行检验。首先,根据一定的假设条件,对比对数据进行归一化处理,尽量消除不同卫星间观测时间、空间(星下点经、纬度和高度)、方向和能量范围等差异对高能粒子分布的影响,然后进行比对,最后计算比对数据间的相关系数、斜率和标准偏差等统计参数,并据此评价比对数据的一致性。通过空间天气平静期高能质子和高能电子与NOAA-18和FY-3B卫星数据的交叉比对可以看出,FY-3C卫星高能粒子数据与比对卫星数据具有较好的一致性。由于工作原理和技术指标相同,FY-3C与FY-3B卫星高能粒子数据的一致性更好,也证明了载荷技术状态的稳定性。通过对太阳质子事件和高能电子暴的观测实例证明,FY-3C卫星高能粒子数据能够准确地反映空间天气扰动事件的特征和强度。以上结果表明,FY-3C卫星高能粒子数据可信度较高,能够用于空间天气监测、预警以及研究工作。     

不同天气现象下毕节高温特征及预报回归检验分析

利用毕节2010-2019年观测资料,分析不同天气现象下日最高气温特征,建立高温模型,并对近5 a 24 h高温进行检验,得出如下结论:(1)毕节高温日变化在夏季最稳定,春季波动最大。气温日较差晴天最大,阴天最小,多云时略大于阴间多云。(2)毕节8~10成云出现频率高达65.7%,夏季晴天频率波动大,春、夏季多云频率较高,且按天气现象分类统计月平均高温时,其峰值均出现在7月。(3) 24 h高温预报准确率月、季变化特征明显,夏季准确率最高,较最低的冬季高出21.4%,在区别天气现象的情况下,阴雨天时预报准确率最高,多云时最低,其中12月多云时最低为25%。(4)回归模型分析发现不同季节同种天气现象24 h高温预报影响因子权重差异明显,日照时数和平均本站气压对模型影响程度较高。不同季节晴天影响因子差异最大,拟合效果最好时段在夏季,平均估计误差为1.2℃,估计误差最大在冬季,平均估计误差为1.7℃。     

Contributions of Fuqing ZHANG to Predictability,Data Assimilation,and Dynamics of High Impact Weather: A Tribute

This article reviews Fuqing ZHANG’s contributions to mesoscale atmospheric science,from research to mentoring to academic service,over his 20-year career.His fundamental scientific contributions on predictability,data assimilation,and dynamics of high impact weather,especially gravity waves and tropical cyclones,are highlighted.His extremely generous efforts to efficiently transmit to the community new scientific knowledge and ideas through mentoring,interacting,workshop organizing,and reviewing are summarized.Special appreciation is given to his tremendous contributions to the development of mesoscale meteorology in China and the education of Chinese graduate students and young scientists.     

Identification of Convective and Stratiform Clouds Based on the Improved DBSCAN Clustering Algorithm

A convective and stratiform cloud classification method for weather radar is proposed based on the density-based spatial clustering of applications with noise (DBSCAN) algorithm. To identify convective and stratiform clouds in different developmental phases, two-dimensional (2D) and three-dimensional (3D) models are proposed by applying reflectivity factors at 0.5° and at 0.5°, 1.5°, and 2.4° elevation angles, respectively. According to the thresholds of the algorithm, which include echo intensity, the echo top height of 35 dBZ (ET), density threshold, and ε neighborhood, cloud clusters can be marked into four types: deep-convective cloud (DCC), shallow-convective cloud (SCC), hybrid convective-stratiform cloud (HCS), and stratiform cloud (SFC) types. Each cloud cluster type is further identified as a core area and boundary area, which can provide more abundant cloud structure information. The algorithm is verified using the volume scan data observed with new-generation S-band weather radars in Nanjing, Xuzhou, and Qingdao. The results show that cloud clusters can be intuitively identified as core and boundary points, which change in area continuously during the process of convective evolution, by the improved DBSCAN algorithm. Therefore, the occurrence and disappearance of convective weather can be estimated in advance by observing the changes of the classification. Because density thresholds are different and multiple elevations are utilized in the 3D model, the identified echo types and areas are dissimilar between the 2D and 3D models. The 3D model identifies larger convective and stratiform clouds than the 2D model. However, the developing convective clouds of small areas at lower heights cannot be identified with the 3D model because they are covered by thick stratiform clouds. In addition, the 3D model can avoid the influence of the melting layer and better suggest convective clouds in the developmental stage.