重庆城区浓雾的基本特征

统计分析沙坪坝1951～2002年间发生的浓雾事件，结合2001年12月重庆市雾的外场试验资料，探索重庆市主城区浓雾的基本特征。重庆主城区浓雾随年代演变有减缓趋势；主城区浓雾是自然雾与烟尘等的混合物，河谷及城市效应使雾更浓；城市中出现浓雾的大气边界层特征是在近地面层有逆温及增湿降温现象；高浓度气溶胶的净辐射效应阻碍白天混合层发展，使大气边界层趋于稳定，它是重庆连续几天有雾的原因之一；浓雾具有一定的湿沉降作用，能有限地清洁空气；有浓雾的天气条件下，建议降低污染物的排放总量，以避免严重大气污染事件发生。     

云南省Internet网络天气预报会商系统

云南省基于Internet网络的天气预报会商系统覆盖云南省、地 (州 )、县三级。系统采用了Internet网络技术、数据库技术 ,实现了省、地 (州 )、县天气预报发布及浏览查询、预报讨论BBS、天气预报会商室、系统管理 ,在线短消息互发等功能。     

相控阵天气雷达监测预警龙卷风的过程剖析

天气雷达作为龙卷风监测预警的重要手段之一,应用具有超高时空分辨率的X波段双极化相控阵天气雷达系统,较好地捕获并提前预警龙卷风。以2022年6月19日07时发生在广东佛山南海的一次龙卷风为例,详细剖析龙卷生消及雷达监测预警过程。借助雷达智能预警软件,利用X波段双极化相控阵天气雷达的双偏振量和超高时空分辨率数据,实时反演三维风场和分析龙卷碎片(TVS)特征,能够显著提高龙卷风监测预警水平。实例表明,本次成功地提前18分钟预警龙卷,进一步说明了X波段双极化相控阵天气雷达在强对流天气探测方面具有较强的生命力。     

贵州省地质灾害气象预警预报

贵州复杂和脆弱的地质环境使地质灾害频发,危害民生,影响国民经济的健康发展,引起社会的重视。选用适合的地质灾害气象预警预报方法,是主动防灾减灾的手段之一。几年来的预警预报工作证明,效果总体较好。对其重要性、影响、作用、改进的意义做了解读。     

华家岭2008年电线积冰的变化特征与气象条件分析

利用华家岭气象站不同高度、不同方向、不同导线直径的电线积冰观测资料,分析了电线积冰在不同高度、不同方向、不同导线的变化特征,以及与气温、水汽压、风速等气象要素的关系。分析表明,电线积冰量随高度增加而增加,随电线直径增大而增大;在相同高度、相同导线上,不同方向的积冰量与风向有关。电线积冰量与水汽压、风速分别呈正相关和反相关。在一定阈值内,电线积冰量和气温存在较好的相关性。     

邕宁夏季高温天气分析

对邕宁2004年夏季一次高温天气过程进行了阐述,对高温天气发生的原因进行了初步分析,结果发现,稳定的副热带高压与热带风暴共同影响是本次高温过程的主要特点,持续稳定的下沉气流,也是造成高温天气的另一重要原因。     

A Case study of a snowstorm at the Great Wall Station,Antarctica

A case of a snowstorm at the Great Wall Station was studied using data of NCEP (National Centers for Environmental Prediction) analysis, in situ observations and surface weather charts. The storm occurred on August 29th,2006, and brought high winds and poor horizontal visibility to the region.It was found that the storm occurred under the synoptic situation of a high in the south and a low in the north. A low-level easterly jet from the Antarctic continent significantly decreased the air temperature and humidity.Warm air advection at high level brought sufficient vapor from lower latitudes for the snowstorm to develop.The dynamic factors relating to strong snowfall and even the developmentof a snowstorm were deep cyclonic vorticity at middle and low levels,the configuration of divergence at high level and convergence at low level, and strong verticaluplift. There was an inversion layer in the low-level atmosphere during the later phase of the storm.This vertical structure of cold air at low levels and warm air at high levels may have been important to the longevity of the snowstorm.     

Application of ICTs in Airspace Management and Collaborative Decision-Making—Analyzing the Risk Avoidance in the Condition of Risky Weather as an Example

The application of ICTs makes structural change of the development and effective utilization of airspace. Next generation air transportation system (NextGen) includes new automation concepts with automated information to support the traffic control decision-making. As a result, in the field of academia and industry, air traffic controllers integrate information automatically while making decisions to change the previous manually integrated and decided pattern. The safety ability of airspace is reduced and airspace system is endangered under risky weather conditions of airspace. So there is an urgent demand for new information and communication technologies. The paper is an overview of the information constitution and support of NextGen and provides the study of the development of technique of airspace collaborative decision-makings to confirm the new features based on ICTs. It contains basic application-the input of data and output of the routes of airspace management and collaborative decision-making, and general application-the choose of probability nets of avoiding risky weather, and special application-the affection in the management of the air routes, which are made up of position and direction. The research shows the accurate schedule characteristics of airspace management and collaborative decision-making based on ICTs, which made the space accurate by time accurate. Second, the visualization of airspace management and collaborative decision-making based on ICTs made the maps of flight path under mobile data quickly generated. This could make the fully development and utilization of national airspace, ensure safety, and reduce air traffic controllers’ workload and the costs in delaying and operating in risky weather.     

A Study of the Extended-range Forecast for the Low Frequency Temperature and High Temperature Weather over the Lower Reaches of Yangtze River Valley in Summer

Based on the observational data, the variations of Intraseasonal Oscillation (ISO) of the daily temperatures and its relationships to the high temperature in summer over the lower reaches of the Yangtze River Valley (LYRV) were studied for the period of 1979-2011. It is found that the daily temperatures over LYRV in May-August was mainly of periodic oscillations of 1525, 3060 and 6070 days, and the interannual variation of the intensity of its 3060-day oscillation had a strongly positive correlation with the number of days with daily highest temperature over 35 ℃ in July-August. Low frequency components of daily temperature in the LYRV, and the principal components of the Eastern Asian 850 hPa low frequency temperature, over a time period ranging from 1979 to 2000, were used to establish the Extended Complex Autoregressive model (ECAR) on an extended-range forecast of the 3060-day low frequency temperature over the LYRV. A 11-year independent real-time extended-range forecast was conducted on the extended-range forecast of low frequency component of the temperature over the LYRV in May-August, for the period ranging from 2001 to 2011. These experimental results show that this ECAR model, which is based on a data-driven model, has a good forecast skill at the lead time of approximately 23 days, with a forecast ability superior to the traditional autoregressive (AR) model. Hence, the development and variation of the leading 3060-day modes for the Eastern Asian 850 hPa low frequency temperatures and temporal evolutions of their relationships to low frequency components of the temperature over the LYRV in summer are very helpful in predicting the persistent high temperature over the LYRV at a 20 to 25 days lead.