Impact of 4DVAR assimilation of rainfall data on the simulation of mesoscale precipitation systems in a mei-yu heavy rainfall event

The multi-scale weather systems associated with a mei-yu front and the corresponding heavy precipitation during a particular heavy rainfall event that occurred on 4 5 July 2003 in east China were successfully simulated through rainfall assimilation using the PSU/NCAR non-hydrostatic, mesoscale, numerical model （MM5） and its four-dimensional, variational, data assimilation （4DVAR） system. For this case, the improvement of the process via the 4DVAR rainfall assimilation into the simulation of mesoscale precipitation systems is investigated. With the rainfall assimilation, the convection is triggered at the right location and time, and the evolution and spatial distribution of the mesoscale convective systems （MCSs） are also more correctly simulated. Through the interactions between MCSs and the weather systems at different scales, including the low-level jet and mei-yu front, the simulation of the entire mei-yu weather system is significantly improved, both during the data assimilation window and the subsequent 12-h period. The results suggest that the rainfall assimilation first provides positive impact at the convective scale and the influences are then propagated upscale to the meso- and sub-synoptic scales.
Through a set of sensitive experiments designed to evaluate the impact of different initial variables on the simulation of mei-yu heavy rainfall, it was found that the moisture field and meridional wind had the strongest effect during the convection initialization stage, however, after the convection was fully triggered, all of the variables at the initial condition seemed to have comparable importance.     

Conversion of kinetic energy from synoptic scale disturbance to low-frequency fluctuation over the Yangtze River valley in the summers of 1997 and 1999

In order to investigate the conversion of kinetic energy from a synoptic scale disturbance （SSD; period≤seven days） to a low-frequency fluctuation （LFF; period〉seven days）, the budget equation of the LFF kinetic energy is derived. The energy conversion is then calculated and analyzed for the summers of 1997 and 1999. The results show that the energy conversion from the SSD to the LFF is obviously enhanced in the middle and lower troposphere during the heavy rainfall, suggesting this to be one of mechanisms inducing the heavy rainfall, although the local LFF kinetic energy may not be enhanced.     

珠穆朗玛峰地区雪冰中重金属浓度与季节变化

对2005 年9 月采自珠穆朗玛峰北坡海拔6523 m 的东绒布冰川积累区一批雪坑样品中重金属Ba, Co, Cu, Zn 和Pb 的浓度利用电感耦合等离子体质谱仪进行了测试, 重金属浓度范围分别为(pg/ml); Ba2~227、Co2.8~15.7、Cu 10~120、Zn29~4948、Pb14~142。并利用气体稳 定同位素质谱仪MAT-252 对样品稳定氧同位素比率(δ¹⁸O) 进行了测试, 雪坑样品对应的时间为2004 年夏到2005 年秋, δ¹⁸O和重金属元素的浓度都存在着季节变化特征。在夏季风期间δ¹⁸O 值和重金属元素的浓度都很低,而在非夏季风期间δ¹⁸O值和重金属元素浓度升高,反映了不同的水汽来源对重金属浓度季节变化的影响及其环境意义。Co, Cu, Pb, Zn 的地壳富集系数(EF_c) 分别为: 3.6、27、33、180, 表明该地区Pb, Cu, Zn 已经受到了人类活动的污染, 其中Zn 受到的污染最大。     

武汉市汤逊湖沉积物重金属垂向变化的磁响应特征及环境意义

对武汉汤逊湖湖泊沉积物T06-1样芯进行了磁性测量、重金属分析和粒度分析,探讨了利用磁参数追踪、指示城市湖泊重金属污染的可行性.结果表明,低矫顽力的亚铁磁矿物主导了沉积物的磁性特征.磁参数χ,SIRM和ARM与重金属Cr,Zn,Cu和Pb呈现较为一致的垂向变化特征:55cm之下,磁参数值和重金属的含量均较低且稳定;在50～10 cm之间,两者基本呈现随深度的减小而增加的趋势,其中在20～10 cm区间,出现小范围内波动;而10cm至表层,元素含量和磁参数值随深度减小而急剧增加.选取粘土(＜4μm)对沉积物中Cr,Zn,Cu和Pb进行粒度校正的结果显示:校正后元素的变化趋向于平稳,但在表层的10cm处Cr,Pb,Zn和Cu的含量仍然较高,表明了表层沉积物中金属元素的含量主要受人类活动的影响.相关分析也表明了磁参数χ,SIRM和ARM与重金属Cr,Pb,Zn和Cu之间均呈显著相关关系(0.62≤R≤0.86),表明磁参数可以用于追踪和指示汤逊湖湖泊沉积物重金属污染.     

土壤剖面的磁学特征及其对交通污染的指示意义——以北京首都机场高速公路为例

对北京首都机场高速公路旁采集的土壤柱状T01剖面的磁学参数和金属元素分析,探讨了研究区内现代交通导致的土壤磁学性质的变化及其对环境污染的响应.结果表明,磁参数(χ,ARM和SIRM)与重金属含量呈同步垂向变化趋势.来源于交通运输排放的污染物是土壤剖面上部(0～8 cm)磁性和金属含量增强的主要原因,8cm以下,土壤基本未受到污染,磁性矿物和重金属含量较低,磁性颗粒变化稳定,基本代表了该地区土壤的自然背景.尽管土壤岩石磁学分析表明剖面上下部受污染和未受污染样品的磁载体均是粒度较粗的多畴磁铁矿,但是结合磁参数比值曲线,说明底部样品的磁颗粒的粒度较顶部偏细.磁性矿物的含量变化没有影响磁颗粒的粒度特征.指标聚类等相关分析表明,土壤磁参数(χ,ARM和SIRM)与重金属元素(Pb,Zn和Cu)含量显著相关;结合模糊聚类分析,磁参数可用于追踪、识别交通污染物质在土壤剖面中的富集、迁移状态,揭示不同深度土壤的污染程度.     

灌河口潮滩重金属累积特征及污染评价

河口地区潮滩是重金属重要的"汇"。测定了灌河口(燕尾港)潮滩高中低滩的33个表面样粒度、重金属数据,研究了4根柱状样的重金属和粒度特征,利用地累积指数法、潜在生态危害指数法及富集指数法等评价指标,对灌河口重金属的污染状况进行了评价,并对其结果进行了相互比较和印证。分析结果显示,灌河口潮滩重金属的分布主要受水动力影响,特别是受粘土分布的控制。Cd与粒径Ф值相关性不显著,相关系数只有0.099,而与粘土含量呈明显正相关关系,Hg的变化趋势恰恰相反,其含量随着距离河口距离的加大反而有增加的趋势;其他元素的变化趋势不明显。重金属元素Zn、Pb、Cu、Hg含量变化走势基本相同,用Li作归一化标准元素归一化后,所有重金属元素的归一化值变化波动范围均比重金属含量值明显收窄,波峰和波谷有后延的趋势。灌河口滩涂总体重金属环境尚可,但存在一定程度的Hg、Cu污染富集。柱状样Hg、Cu的地累积污染指数总体上均呈现随深度增加而降低的趋势。     

江西两种典型强对流天气的雷达回波特征分析

选取江西12次典型强对流天气过程,从7个方面对冰雹、雷雨大风和短时强降水2种强对流天气的多普勒天气雷达回波特征进行对比分析。分析结果表明,江西冰雹、雷雨大风天气45～55 dBz强回波平均高度为12.6 km,≥-25℃等温层的高度,比短时强降水天气高5.7 km。弱回波区或有界弱回波区、三体散射长钉、持续高垂直积分液态水含量、中气旋、下湿上干和强风垂直切变等,都是冰雹、雷雨大风天气的典型特征;相对平均径向速度图上“S”形暖平流及表现强低空急流的“牛眼”、深厚的湿度层等,则是短时强降水天气的主要特征。     

Sensitivity Analysis of the Super Heavy Rainfall Event in Henan on 20 July (2021) Using ECMWF Ensemble Forecasts

An unprecedented heavy rainfall event occurred in Henan Province, China, during the period of 1200 UTC 19-1200 UTC 20 July 2021 with a record of 522 mm accumulated rainfall. Zhengzhou, the capital city of Henan, received 201.9 mm of rainfall in just one hour on the day. In the present study, the sensitivity of this event to atmospheric variables is investigated using the ECMWF ensemble forecasts. The sensitivity analysis first indicates that a local YellowHuai River low vortex(YHV) in the southe...     

Characteristics of Radar Echo Parameters and Microphysical Structure Simulation of a Short-Time Heavy Precipitation Supercell

By using the conventional observations, radar data, NCEP/NCAR FNL 1°×1° reanalysis data and numerical simulation data and with the construction and calculation of radar echo parameters, this paper presents the structural characteristics and physical processes of a short-time heavy precipitation supercell that occurred in the squall line process in Shanxi Province on 24 June 2020. The results show that this squall line event occurred in front of a surface cold front,combined with infiltration of ...     

特征变量选择结合SVM的耕地土壤Hg含量高光谱反演

为探讨应用高光谱数据反演耕地土壤重金属汞(Hg)含量,对原始光谱进行10 nm重采样和SG平滑处理,用不同光谱变换数据与土壤重金属Hg含量进行相关性分析,采用IRIV、Random Frog和PCC提取光谱特征波段,分别建立SVM与GWO-SVM土壤Hg含量高光谱反演模型,获取Hg含量最优反演路径。研究表明,一阶微分变换光谱后土壤光谱特征更明显;上述特征提取方法在不同程度上减少光谱数据冗余,保留有效变量信息;经灰狼算法优化后支持向量机模型反演精度提高,IRIV结合GWO-SVM预测精度更高,其验证集R²为0.894,RMSE为0.082,MAE为0.016。研究成果可为类似土壤重金属含量的反演提供借鉴。