Meteorology in Canada: A reaction to the rose report

The methods used in an earlier study focusing on the province of Ontario, Canada, were adapted for this current study to expand the study area over eastern Canada where the infrastructure is at risk of being impacted by freezing rain. To estimate possible impacts of climate change on future freezing rain events, a three-step process was used in the study: (1) statistical downscaling, (2) synoptic weather typing, and (3) future projections. A regression-based downscaling approach, constructed using different regression methods for different meteorological variables, was used to downscale the outputs of eight general circulation models to each of 42 hourly observing stations over eastern Canada. Using synoptic weather typing (principal components analysis, a clustering procedure, discriminant function analysis), the freezing rain-related weather types under historical climate (1958–2007) and future downscaled climate conditions (2016–2035, 2046–2065, 2081–2100) were identified for all selected stations. The potential changes in the frequency of future daily freezing rain events can be projected quantitatively by comparing future and historical frequencies of freezing rain-related weather types.

The modelled results show that eastern Canada could experience more freezing rain events late this century during the coldest months (i.e., December to February) than the averaged historical conditions. Conversely, during the warmest months of the study season (i.e., November and April in the southern regions, October in the northern regions), eastern Canada could experience less freezing rain events late this century. The increase in the number of daily freezing rain events in the future for the coldest months is projected to be progressively greater from south to north or from southwest to northeast across eastern Canada. The relative decrease in magnitude of future daily freezing rain events in the warmest months is projected to be much less than the relative increase in magnitude in the coldest months.     

通量和平流形式预报方程的数值预报试验

本文利用1982年5月8日和1979年6月28日两个实例,进行了四种方案的48小时数值预报试验,比较了它们的预报质量及彼此间的差异。四种方案是:经典通量、通量修正、经典平流和平流修正。试验表明,在有地形的数值预报模式中,采用平流形式的预报方程组比采用通量形式的为好,既可有较高的计算精度,又可节省计算时间。     

PRELIMINARY STUDY OF BAROTROPIC STOCHASTIC DIFFERENCE MODEL APPLIED TO WEATHER PREDICTION

In order to consider both the deterministic and the stochastic property of atmospheric motion simul-taneously,in this paper,the weather prediction is proposed as the problem of the evolution of meteorologicalfield.The historical viewpoint of atmospheric motion is emphasized here.Based on time series analysis te-chnique,a stochastic-dynamical model with multiple initial fields is derived.Thus,weather forecasting is sum-meal up as a problem of solving a set of stochastic difference equations.For the barotropic atmosphere,thenumerical solutions of the equations are obtained by using the method of empirical orthogonal functions(EOF),and examples of medium-range weather prediction are given here.Meanwhile,selecting the order oftime series,i.e.,determining the number of initial fields properly,is also discussed.     

梧州市森林火险气象预报

使用１９８０－１９９１年森林火灾及相应的气象资料，分析了森林火灾与有关气象要素的相关性。在此基础上，计算了森林火险天气预报指标，建立了预报模式，开展了森林火险天气等级预报。经试用效果较好。     

沙漠地区春季近地层气象要素分布规律的观测研究

利用2005年1月至2006年4月朱日和地区20 m气象塔的风向、风速、气温、相对湿度的观测资料,分析沙漠地区春季近地层气象要素的分布规律。结果表明: 春季温度回升,风速最大,相对湿度最小,利于起沙,故沙尘天气频繁。风速满足幂指数率分布规律,并且幂指数m能够很好的反映出风速梯度的变化情况;在沙尘暴、扬沙、背景、浮尘的天气条件下,春季近地面层风速梯度依次增大,湍流动量、热量交换系数依次减小;风向以西南为主。浮尘、扬沙天气各气层平均增温率分别大于或小于同时段的背景大气;沙尘暴期间温度下降,平均降温率为0.61 ℃\5h-1。春季相对湿度的平均递减率(递增率)与平均增温率(降温率)的大小正相关。浮尘天气相对湿度的平均递减率大于同时段的背景大气;扬沙天气相对湿度的平均递减率小于同时段的背景大气;沙尘暴天气相对湿度增大,平均增大率为2.80%\5h-1。     

2004年春季中国沙尘天气特征分析

利用全国681个站的沙尘天气观测资料分析得出,2004年春季中国北方的沙尘天气明显偏少、偏弱,主要表现在：（1）2004年春季681个站累计的沙尘天气日数2 080 d,相当于历史平均值的46.9%,是近四十余年中第三个偏少年份。沙尘暴的总面积约190万km2,仅为历史平均值的37.3%。（2）危害性较大的沙尘暴和强沙尘暴过程6次,不足2001年的一半。（3）4月和5月沙尘天气明显偏少导致整个春季显著偏少。沙尘天气出现时,PM10浓度相对增加,空气质量恶化,但与历史上较典型的强沙尘暴个例相比,PM10浓度增加的幅度不大。进一步分析表明,2004年春季沙尘天气偏少、偏弱的主要原因是大气动力条件不足,是比较特殊的一个年份。     

自动站与人工观测降水量差值的成因分析

通过自动站与人工站在降水量观测差值的对比,对差值原因进行了分析。     

多普勒雷达数据处理显示系统

多普勒天气雷达目前已经成为对短时强烈天气进行监测的主要手段之一。为了方便资料的处理和分析 ,将科研成果向业务应用转化 ,提高观测资料软件和资料处理能力 ,为预报员和科研人员提供方便 ,我们开发了多普勒雷达资料分析显示系统。该软件是兼原始数据处理、反演、显示功能于一体的雷达数据处理系统 ,有很好的兼容性和可移植性 ,其交互式、多线程、多窗口、多任务的汉化操作界面 ,灵活、简便 ,容易使用。根据用户需要 ,水平风场可用风矢量、风羽、流线或等值线等不同方式表达 ,多种水平变量也可以任意叠加     

基于MICAPS系统的数字化天气图及常规气象资料检索分析系统

介绍了基于“9210工程”和MICAPS系统的资料自动存储、整理、检索和历史天气图分析业务系统——基于MICAPS系统的数字化天气图及常规气象资料检索分析系统，较全面地介绍了该系统高度自动化、设计友好的功能和在业务中的应用。