赴墨西哥考察MILAGRO大气污染观测项目总结

2006年3月20～30日应墨西哥国立大学大气科学中心Darrel Baumgardner博士的邀请，中国气象科学研究院孙俊英博士、陈跃博士、王亚强博士赴墨西哥参观MILAGRO大气污染观测项目的组织、实施、地面观测站、观测飞机、仪器等。现将考察情况汇报如下。     

基于SaaS的区域非职业体育赛事云服务平台的设计与实现

与传统软件架构模式相比,云计算具有综合成本较低、部署快速、规模调整灵活等优势,针对区域非职业体育赛事在信息采集、组织管理、赛果处理与发布等赛事运营、组织、管理等方面存在的不足,从平台构建的可行性、架构与功能等方面,讨论并实现了一种基于SaaS模式的非职业体育赛事云服务平台,最后从使用效益等方面总结该平台对于提升区域非职业体育赛事组织与管理所取得的促进作用。     

PLAM指数跟踪方法对中国沙尘天气过程及其波动变化特征的研究

采用1980-2011年气象台站地面气象要素观测资料、高空探空资料,时间和空间加密气象观测站资料,以及中国气象档案馆原始天气图表等资料,基于沙尘气溶胶浓度（PM₁₀）潜势源地贡献函数PSCF（Potential source contribution function）的沙尘系统追踪方法,发展空气质量气象条件PLAM（……）指数对沙尘天气过程的路径跟踪,给出1980-2011年东北亚沙尘天气过程特征分布;采用Spline趋势分析,讨论沙尘天气系统强度的年变化特征。结果表明：基于气溶胶浓度PSCF函数和气象条件PLAM指数追踪得出,中国和东亚地区沙尘天气过程年际强度变化并非单调减弱,具有历史持续性与转折突变性并存的波状变化趋势,出现准10 a的高低频活动特征。     

大气本底站反应性气体观测数据处理系统功能设计及实现

基于反应性气体多年观测的较为成熟的数据处理和质量控制方法,采用模块化功能结构设计,通过应用Visual Studio开发平台并结合MAP WinGIS等空间和时间显示控件,对反应性气体观测数据处理系统进行了设计和开发.系统实现了观测数据在空间和时间上的可视化显示,实际业务应用表明,具有良好的人机交互和数据处理能力,具备一定的数据统计分析功能.实现了对大气本底站反应性气体观测数据的统一管理和综合处理,已成为大气成分观测数据质量控制业务系统的一个重要组成部分.     

基于机器学习的中国冬季气温影响因子分析及模型估算

使用1951—2021年160个中国国家级气象观测站冬季平均气温及多项大气环流及海温等指数,用机器学习方法研究影响中国冬季气温异常的大气环流及海温等外强迫因子,并建立估算拟合模型,评价筛选出的影响因子组合对中国冬季气温异常分布的贡献。使用最小绝对收缩和选择算子（LASSO）算法提取与冬季气温异常相关的影响因子。为体现特征因子之间非线性关系,使用泰勒公式对筛选后的特征进行多项式增广。使用最小二乘梯度提升决策树（LS-GBDT）算法对筛选出的特征因子与冬季气温异常之间的非线性关系进行估算拟合。结果表明,机器学习方法能够对影响冬季气温异常的特征因子进行合理筛选与重要性分析,建立的估算模型在一定程度上体现了气候系统特征因子与冬季气温距平的非线性联系。本研究为了解中国冬季气温异常分布的影响因素及其模拟与估算提供了新方法和途径。     

Mass Concentration and Mineralogical Characteristics of Aerosol Particles Collected at Dunhuang During ACE-Asia

Measurements were performed in spring 2001 and 2002 to determine the characteristics of soil dust in the Chinese desert region of Dunhuang, one of the ground sites of the Asia-Pacific Regional Aerosol Characterization Experiment (ACE-Asia). The mean mass concentrations of total suspended particle matter during the spring of 2001 and 2002 were 317 μg m?3 and 307 μg m?3, respectively. Eleven dust storm events were observed with a mean aerosol concentration of 1095 μg m?3, while the non-dusty days with calm or weak wind speed had a background aerosol loading of 196 μgm?3 on average in the springtime. The main minerals detected in the aerosol samples by X-ray diffraction were illite, kaolinite, chlorite, quartz, feldspar, calcite and dolomite. Gypsum, halite and amphibole were also detected in a few samples. The mineralogical data also show that Asian dust is characterized by a kaolinite to chlorite (K/C) ratio lower than 1 whereas Saharan dust exhibits a K/C ratio larger than 2. Air mass back-trajectory analysis show that three families of pathways are associated with the aerosol particle transport to Dunhuang, but these have similar K/C ratios, which further demonstrates that the mineralogical characteristics of Asian dust are different from African dust.     

The strong El Niño of 2015/16 and its dominant impacts on global and China's climate

The oceanic and atmospheric conditions and the related climate impacts of the 2015/16 ENSO cycle were analyzed, based on the latest global climate observational data, especially that of China. The results show that this strong El Niño event fully established in spring 2015 and has been rapidly developing into one of the three strongest El Niño episodes in recorded history. Meanwhile, it is also expected to be the longest event recorded, attributable to the stable maintenance of the abnormally warm conditions in the equatorial Pacific Ocean since spring 2014. Owing to the impacts of this strong event, along with climate warming background, the global surface temperature and the surface air temperature over Chinese mainland reached record highs in 2015. Disastrous weather in various places worldwide have occurred in association with this severe El Niño episode, and summer precipitation has reduced significantly in North China, especially over the bend of the Yellow River, central Inner Mongolia, and the coastal areas surrounding Bohai Bay. Serious drought has occurred in some of the above areas. The El Niño episode reached its peak strength during November-December 2015, when a lower-troposphere anomalous anticyclonic circulation prevailed over the Philippines, bringing about abnormal southerlies and substantially increased precipitation in southeastern China. At the same time, a negative phase of the Eurasia-Pacific teleconnection pattern dominated over the mid-high latitudes, which suppressed northerly winds in North China. These two factors together resulted in high concentrations of fine particulate matter (PM_2.5) and frequent haze weather in this region. Currently, this strong El Niño is weakening very rapidly, but its impact on climate will continue in the coming months in some regions, especially in China.     

大气粉尘气溶胶中铁氧化物的光谱分析

首次利用浸反射光谱装置（DRS）对中国大气粉法气溶胶中铁氧化物进行了研究，结果表明，在可见光范围，粉尘样品反射光谱的一阶导数曲线，在435nm和560nm对样品中的针铁矿和赤铁矿有识别指示意义，样品中铁的含量与赤铁矿和针铁矿的一阶导数峰值相关性良好，同时发现，红、登、黄3种颜色的反射率随样品中铁含量的增加而增加，而紫、绿、蓝3种颜色的反射率随样品中铁含量的增加而减少，这表明铁氧化在粉尘气溶胶对可见光的散射和吸收效应中扮演着重要的角色。     

中国粉尘源区表土碳酸盐含量与碳氧同位素组成

在中国的主要沙漠和戈壁等粉尘源区采集了地表沙或土壤(统称为表土)样品,分析了样品的碳酸盐含量和碳酸盐的碳氧同位素组成。结果表明,中国粉尘源区表土碳酸盐含量在空间上随着年降水量的增加而逐渐减少,大致呈现自西向东逐渐降低的趋势;碳酸盐δ^13C值在空间上随着年降水量的增加而逐渐偏负．δ^18O值缺乏规律性;塔克拉玛干沙漠细颗粒物质中碳酸盐含量相对偏高,但不同粒级颗粒中碳酸盐的δ^13C值基本一致,表明风蚀时粒度的分选并不影响源区的同位素组成特征;由于粉尘源区表土碳酸盐含量和δ^13C值均具有区域特征,因此利用大气粉尘的碳酸盐含量和δ^13C值示踪不同的源区是可能的。     

中国大陆黑碳气溶胶排放清单

The detailed high-resolution emission inventory of black carbon (BC) from China in the year 2000 was calculated. The latest fuel consumption data including fossil and biomass fuels, and socio-economic statistics used were obtained from government agencies, mostly at the county level, and some new emission factors (Efs) from local measurements were also used. National and regional summaries of emissions were presented at 0.2°×0.2°resolution. Total BC emission was 1499.4 Gg in 2000, mainly due to the burning of coal and biomass. The BC emission estimated here is higher than those in previous studies, mainly because the emissions from coal burning by rural industries and residences were previously underestimated. More BC aerosols were emitted from eastern China than western China. A strong seasonal dependence was observed for BC emissions, with peaks in January and December and low emissions in July and August; and this seasonality is mainly due to patterns in residential heating and the open burning of crop residues.