海底观测网发展现状及趋势研究

文中详细研究了当前世界上最典型的海底观测网的建设发展规模、形式、设备类型以及我国海底观测网的发展现状,并对国内外海底观测网的发展趋势进行总结。对日本、加拿大、美国及欧洲的海底观测网进行了设备级研究,对我国台湾地区、东海、南海的海底观测网现状进行了研究,并讨论了国外先进观测网对我国的海底观测网建设的借鉴意义。文中总结出海底观测网发展的整体趋势为:单节点网络加速验证新型设备及传感器的水下能力;区域尺度网络用于加速多学科发展并提升灾害预警能力;而浮标平台网络作为补充,铺设在远海区域以降低阶段建设成本。     

ICE Particle Size and Shape Effect on Solar Energy Scattering Angular Distribution

The rare occurrence of te halos produced by cirrus ice crystals in nature has been investigated by modelling the incident solar (visible) light scattering angular distribution using the Monte Carlo/ray tracing method.The results show that the irregular shapes of ice crystals and large population of small ice particles in cirrus are responsible forthe rare occurrence of halos.     

华北和印度夏季风降水变化的对比分析

 利用华北和印度夏季降水资料,采用趋势分析、小波变换等方法,对两地区夏季风降水进行了对比分析。结果表明：1) 华北和印度夏季风降水量都存在线性减少倾向,但华北更为显著,减少达16 mm/10 a;2) 华北和印度夏季风降水变化都以18 a周期为主,近年都有逐渐缩短的趋势,而印度的这种周期缩短得比华北更快,近年降水变化周期接近15 a;3) 华北和印度夏季风降水变化在1956、1976、1992/1993年发生了趋势转折;4) 华北和印度降水量主要集中在6-9月,夏季风降水特征非常明显,但两地变化特征表现不尽相同。     

1979—2014年全球变暖背景下青藏高原气候变化特征

近几十年来全球变暖受到越来越广泛的关注,然而全球变暖从1998年开始趋缓,但青藏高原却呈现加速增暖的趋势。本文基于前人研究,系统回顾了青藏高原气温、积雪、降水和大气热源等四方面在全球变暖背景下的变化,指出高原的加速增温导致了积雪迅速融化,降水明显增多的同时,高原热源却呈现减弱趋势。     

作业调度软件LoadLeveler在气象模式中的应用

西北区域气象中心高性能计算集群使用LoadLeveler调度管理作业,为实现资源利用率和吞吐量的最大化,本文探讨了作业调度管理的作用和方法.通过配置文件关键字定义队列、设置调度算法和调度器调节参数,将作业的处理需求与可用资源进行匹配,依据实际需求定义集群和各种资源的可用性规则,防止作业之间的相互干扰.结合LoadLev...     

Interdecadal variations of cold air activities in Northeast China during springtime

Based on the daily mean temperature data of CN05.2 from 1961 to 2012, cold events (CEs) are first divided into two categories according to their duration: strong cold events (SCEs) and weak cold events (WCEs). Then, the characteristics of CEs, SCEs, and WCEs during springtime are investigated. The results indicate that in the pre-1990s epoch, ENSO and Arctic Oscillation events in the previous winter are closely related to SCEs in the following spring. The multidecadal variations of CEs, SCEs, and WCEs are obvious. The intensity trend for SCEs is significantly negative, but it seems less apparent for WCEs. Further analysis reveals that when both SCEs and WCEs occur, a typical East Asian trough in the 850- hPa wind field, whose northwesterly wind component invades Northeast China (NEC) and causes freezing days, can be found in every decade. For the SCEs, a cold vortex, with its center located over Okhotsk and northeasterly current affecting NEC, is found as an additional feature. For the WCEs, the cold vortex is located in Karafuto and its northwesterly airflow intrudes into NEC. As for the difference between SCEs and WCEs, the northwestern flow is weaker while the northeastern counterpart is stronger during the SCEs, in all decades. In the Takaya–Nakamura flux and divergence fields, for the SCEs, a divergence center exists over NEC; and over its downstream regions, a stronger divergence center appears, not like a wave train. However, the opposite is the case for the WCEs; moreover, the wave train appears clearly during the WCEs, which means that the wave energy can propagate and dissipate more easily during WCEs.     

京津冀地区中α尺度飑线过程中大风特征分析及成因初探

应用常规天气观测资料、地面加密自动气象站资料、大风灾情报资料、京津冀地区7部多普勒天气雷达组网观测资料及VDRAS资料,从多个角度对2013年8月4日京津冀地区一次飑线过程产生的大范围大风天气过程进行了分析,结果显示:此次过程是在高空冷空气南下、低层暖湿气流北上、系统前倾及位势不稳定的有利层结条件下,由多单体风暴演变为中α尺度的强飑线所致。飑线形成于低层垂直切变加强、冷池合并之后;大风主要发生在飑线主体回波中,其次是主体回波前和中前,主体回波后很少发生。大风发生的位置取决于飑线结构中气流的性质,气流的性质与冷池前进的程度和对流的强度关系密切。大风大部分由下沉冷气流产生,少数为近地面上升暖气流导致。大风发生的范围和强度与低层风垂直切变的强度呈正比,大范围低层风垂直切变的加强增强了飑线入流和出流的强度,是大范围大风、局部强风形成的重要原因。大风发生站次与冷池的强度和范围密切相关,冷池的加强和范围的扩大加强了后侧冷入流和前侧暖入流的强度和范围,也是大范围大风形成的重要因素。     

The Interannual Variation of Transboundary Contributions from Chinese Emissions of PM_(2.5) to South Korea

In recent years,several studies pointed out that anthropogenic emission sources in China which significantly contribute to the PM_2.5mass burden was an important cause of particulate pollution in South Korea.However,most studies generally focused upon a single pollution event.It is rare to see comprehensive research that captures those features prone to interannual variations concerning the transboundary pollutant contribution in South Korea using a unified method.In this paper,we establish the emission inventories covering East Asia in 2010,2015,and 2017,and then conduct the source apportionment by applying a coupled regional air quality model called the Integrated Source Apportionment Module(ISAM).Comparison of simulated and observed PM_2.5mass concentration at 165 CNEMC(China National Environmental Monitoring Center)sites suggests that the PM_2.5concentrations are well represented by the modeling system.The model is used to quantitatively investigate the contribution from emission sources in China to PM_2.5concentrations over South Korea and those features found to be prone to interannual variations are then discussed.The results show that the average annual contribution of PM_2.5has dropped significantly from 28.0%in 2010 to 15.7%in 2017,which strongly suggests that China has achieved remarkable results in the treatment of atmospheric particulates.     

Retrieving atmospheric temperature profiles from AMSU-A data with neural networks

Back propagation neural networks are used to retrieve atmospheric temperature profiles from NOAA-16 Advanced Microwave Sounding Unit-A (AMSU-A) measurements over East Asia. The collocated radiosonde observation and AMSU-A data over land in 2002-2003 are used to train the network, and the data over land in 2004 are used to test the network. A comparison with the multi-linear regression method shows that the neural network retrieval method can significantly improve the results in all weather conditions. When an offset of 0.5 K or a noise level of ±0.2 K is added to all channels simultaneously, the increase in the overall root mean square (RMS) error is less than 0.1 K. Furthermore, an experiment is conducted to investigate the effects of the window channels on the retrieval. The results indicate that the brightness temperatures of window channels can provide significantly useful information on the temperature retrieval near the surface. Additionally, the RMS errors of the profiles retrieved with the trained neural network are compared with the errors from the International Advanced TOVS (ATOVS) Processing Package (IAPP). It is shown that the network-based algorithm can provide much better results in the experiment region and comparable results in other regions. It is also noted that the network can yield remarkably better results than IAPP at the low levels and at about the 250-hPa level in summer skies over ocean. Finally, the network-based retrieval algorithm developed herein is applied in retrieving the temperature anomalies of Typhoon Rananim from AMSU-A data.