热带地区低层风场几种周期振荡的分析

本文对1983年5—7月(90°E—90°W,50°N—40°S)广阔区域中850hPa纬向风(u)的周期振荡做了功率谱及交叉谱分析。对同年5—9月资料做了EOF分析。着重讨论了中期以上几种周期振荡(40天、26天、13天)的分布特征及位相传播。并且分析了40天周期振荡与大气环流和海况季节转变之间的联系。     

“20030816”云南暴雨过程的中尺度分析

 应用天气图、卫星云图TBB资料和多普勒雷达回波资料,分析了云南2003年8月16日的暴雨天气过程.结果表明:这次暴雨过程时空分布具有明显的中尺度特征,大尺度天气形势为中尺度系统的形成和发展提供了有利的环流背景、不稳定条件、能量条件和动力条件;在卫星云图上切变线云系在西南移过程中发展形成飑线,其上诱发产生的3个中-α尺度云团和1个中-β尺度的云团直接造成了强降水;在多普勒雷达上偏东风和偏西风之间的中-β尺度的切变线和逆风区对中-α尺度飑线的形成和发展起着重要作用,还诱发产生出了超级单体和中气旋,中-α尺度飑线导致了这次暴雨天气过程.     

一种新的多因子约束下的NWP反演ZTD残差改正模型

对流层延迟是GNSS定位的主要误差源之一,利用NWP模型的气象数据积分反演ZTD是当前研究热点.然而,采用两大气象预报中心(ECMWF和NCEP)的再分析资料反演ZTD的残差一般在±60 mm之间浮动,预报资料反演的ZTD的精度更差,都不能直接用于精密定位.一般是先将此反演的ZTD作为初值,设定先验方差,将残差作为未知参数求解.NWP反演的ZTD的精度,将直接影响对流层和模糊度参数在滤波过程中收敛速度.前人的研究表明,NWP反演ZTD的残差大小与测站所在纬度相关,利用纬度与残差的相关函数可提高NWP反演ZTD的精度,但效果并不明显.针对以上问题,比较ECMWF和NCEP再分析资料反演ZTD的精度,然后分析精度较高的ECMWF资料反演的ZTD的残差随温度、湿度、纬度、季节等因子变化的规律,并结合基于最小绝对残差法的多项式拟合方法拟合残差,提出一种新的多因子约束下的NWP反演ZTD的残差改正模型,从而提高NWP反演ZTD的精度.为验证模型的性能,以133个IGS站高精度ZTD为参考,拟合2015年ECMWF反演ZTD的残差,构建残差改正模型,并利用此模型改正2016年ECMWF反演的ZTD.实验结果表明：在纬度高于15°的地区,NWP反演的ZTD的平均残差和均方根误差比使用模型前分别减小了86.9%和36.3%.另外,对于较低纬度地区,此残差改正模型的效果不明显.     

基于风云3C卫星双氧通道的云检测算法

风云3C卫星微波湿度计(MWHS)增加一组频点为118.75 GHz的氧气吸收通道,该组探测通道与微波湿度计(MWTS)中的50~60 GHz的氧气吸收通道综合发展一种云检测方法。应用高频和低频通道对云的散射作用不同的原理,利用在根据双氧通道之间在晴空条件下的关系,进而发展出的一种综合的云检测方法。     

保护水土资源和气候资源防止生态恶化

当代人类的各种活动,无不受到生态环境的深刻影响和制约,目前我国生态恶化严重,本文从如何合理利用水土资源,以及气候资源对生态环境改善的两个方面来阐述如何防止生态恶化。     

基于气象威胁场的无人机三维航迹规划

针对无人机航迹规划中气象威胁要素模糊性强、不确定性高等特点,提出了改进的BP神经网络的气象威胁度评估方法,对区域内气象威胁要素进行评估以建立表征气象威胁的气象威胁场。在所建立的气象威胁场上采用改进稀疏A*算法进行三维航迹规划,改进稀疏A*算法通过引入自适应操作提高了收敛速度以及效率。仿真结果表明,这种威胁评估方法可较为准确地评估区域内的气象威胁,改进稀疏A*算法能够准确、快速地在三维气象威胁场上寻找到最优航迹,具有一定的应用价值。     

城市化对2008年8月25日上海一次特大暴雨的影响

本文利用新一代中尺度数值天气模式Weather Research and Forecasting Model(v3.1.1,WRFV3)、日本气象厅20 km分析资料及自动站观测数据等模拟了2008年8月25日上海一次特大暴雨过程,并研究了城市化对这次暴雨过程的影响.研究结果表明:WRFV3模式能够较好地模拟出上海0825暴雨的主要分布特征,强降水中心以及暴雨随时间变化趋势;上海城市化使得这次暴雨过程在城市中心区域和迎风区降雨增强,城市背风区降雨减少;而城市化引起的陆面粗糙度等变化的动力作用对城市地区低层风场产生阻挡,使得城市迎风区垂直上升运动增强、水汽增多,是造成城市迎风区降雨增强的主要原因.     

云南省路南县农业气候资源特点及评价初探

本文通过光、热、水资源、农业气象灾害及气候生产潜力的分析，提出了路南县发展农业生产的有利因素及限制因素，进而提出增加粮食产量的有效途径。     

How to make value-driven climate science for policy more ethical

In previous works, I examine inferential methods employed in Probabilistic Weather Event Attribution studies (PEAs), and explored various ways they can be used to aid in climate policy decisions and decision-making about climate justice issues. This paper evaluates limitations of PEAs and considers how PEA researchers’ attributions of “liability” to specific countries for specific extreme weather events could be made more ethical. In sum, I show that it is routinely presupposed that PEA methods are not prone to inductive risks and presuppose that PEA researchers thus have no epistemic consequences or responsibilities for their attributions of liability. I argue that although PEAs are nevertheless crucially useful for practical decision-making, the attributions of liability made by PEA researchers are in fact prone to indicative risks and are influenced by non-epistemic values that PEA researchers should make transparent to make such studies more ethical. Finally, I outline possible normative approaches for making sciences, including PEAs, more ethical; and discuss implications of my arguments for the ongoing debate about how PEAs should guide climate policy and relevant legal decisions.     

A comparative evaluation of objective and subjective weather forecasts in the united states

This paper is concerned primarily with the evaluation and comparison of objective and subjective weather forecasts. Operational forecasts of three weather elements are considered: (1) probability forecasts of precipitation occurrence, (2) categorical (i.e. non-probabilistic) forecasts of maximum and minimum temperatures and (3) categorical forecasts of cloud amount. The objective forecasts are prepared by numerical-statistical procedures, whereas the subjective forecasts are based on the judgements of individual forecasters. In formulating the latter, the forecasters consult information from a variety of sources, including the objective forecasts themselves. The precipitation probability forecasts are found to be both reliable and skilful, and evaluation of the temperature/cloud amount forecasts reveals that they are quite accurate/skilful. Comparison of the objective and subjective forecasts of precipitation occurrence indicates that the latter are generally more skilful than the former for shorter lead times (e.g. 12–24 hours), whereas the two types of forecasts are of approximately equal skill for longer lead times (e.g. 36–48 hours). Similar results are obtained for the maximum and minimum temperature forecasts. Objective cloud amount forecasts are more skilful than subjective cloud amount forecasts for all lead times. Examination of trends in performance over the last decade reveals that both types of forecasts for all three elements increased in skill (or accuracy) over the period, with improvements in objective forecasts equalling or exceeding improvements in subjective forecasts. The role and impact of the objective forecasts in the subjective weather forecasting process are discussed in some detail. The need to conduct controlled experiments and other studies of this process, with particular reference to the assimilation of information from different sources, is emphasized. Important characteristics of the forecasting system in meteorology are identified, and they are used to describe similarities and differences between weather forecasting and forecasting in other fields. Acquisition of some of these characteristics may be beneficial to other forecasting systems.