福建省热带气旋暴雨落区完全预报方法

通过分析近几年影响和登陆福建省的热带气旋区域暴雨过程的T106部分物理量场的分布特征,发现其中的k指数、比湿q、涡度ζ和垂直速度ω场对预报福建省热带气旋区域暴雨有较好的指示意义,它们分别反映了产生暴雨所必须的水汽、不稳定能量和辐合上升运动等基本条件。为了提高暴雨落区预报的效果,提出以动态方式确定物理量临界值的方法作热带气旋暴雨落区预报。通过对1995~2001年7~10月的144个个例T106物理量场的普查和统计分析,得到福建省热带气旋区域暴雨预报的着眼点和物理量诊断模型,建立了应用T213数值预报模式输出的物理量预报场,以动态方式确定物理量临界值,作为福建省热带气旋区域暴雨落区预报的完全预报(PP)方法。     

煤矿瓦斯浓度与气象因子相关分析及预报模型

对山西省大同市地方煤矿1979~1997年发生的90起重大典型事故案例进行分析,发现瓦斯事故是发生次数最多,占事故总数的33%,而其造成的灾害也最重。瓦斯浓度的高低与气象因子具有一定的相关性,通过统计计算,得出了旬瓦斯浓度与旬气温、旬气压的相关关系,建立了旬瓦斯浓度预报模型和逐日瓦斯浓度等级预报模型,预报拟合率和试报效果较好。利用该研究成果,结合中短期天气预报,可以提前预报瓦斯浓度的变化趋势,对于搞好煤矿安全生产的管理,及时加大通风,减少事故发生具有重要意义。     

南海热带气旋路径集合预报试验

利用3种不同模式的初始资料，通过它们生成得到16个不同的初始场，分别对2004年南海及其周边地区9个热带气旋个例进行集合预报试验，最后筛选得到了7个南海热带气旋初值集合成员，由此初步探讨了南海热带气旋初值集合成员的生成方法。结果表明，采用不同模式的初始资料生成得到初值集合成员的方法用于集合预报，对南海热带气旋路径预报有一些明显的改进。     

气候变化与北疆北部2000年特大雪灾的必然性及预测

利用1960～2003年新疆阿勒泰地区7测站及塔城地区北部5测站当年11月至次年1月,44a气温、降水资料,研究了北疆北部冬季气候变化特征,解释了2000年该地区冬季特大雪灾极端气候事件出现的必然性,最后探讨了该地区冬季降水的预测问题;并得出一点很有意义的结论:在气候增暖、增湿背景下,特大雪灾也是可以预报的。     

和田地区春季一次强天气过程分析

2005年4月6～10日,和田地区出现了大降水、强降温、沙尘天气过程。利用常规天气资料、ECMWF和T213数值预报产品,对此次天气过程的影响系统、有关物理量场等方面进行分析,发现:这次天气过程是冷空气从南疆西北翻山入侵南疆盆地,天气系统相互叠加而造成的,ECMWF和T213数值预报产品对和田地区这次强天气有很好的预报能力和指示意义。     

使用SVM进行短期气候预测的应用试验

从气象角度介绍了利用SVM方法的预报原理,对西安短期气候预测做了实验,并分析预报结果,得出SVM方法在天气预报领域有一定的使用空间的结论。     

Multi-Year Simulations and Experimental Seasonal Predictions for Rainy Seasons in China by Using a Nested Regional Climate Model （RegCM_NCC） Part Ⅱ： The Experimental Seasonal Prediction

A nested regional climate model has been experimentally used in the seasonal prediction at the China National Climate Center (NCC) since 2001. The NCC/IAP (Institute of Atmospheric Physics) T63 coupled GCM (CGCM) provides the boundary and initial conditions for driving the regional climate model (RegCM NCC). The latter has a 60-km horizontal resolution and improved physical parameterization schemes including the mass flux cumulus parameterization scheme, the turbulent kinetic energy closure scheme (TKE) and an improved land process model (LPM). The large-scale terrain features such as the Tibetan Plateau are included in the larger domain to produce the topographic forcing on the rain-producing systems. A sensitivity study of the East Asian climate with regard to the above physical processes has been presented in the first part of the present paper. This is the second part, as a continuation of Part I. In order to verify the performance of the nested regional climate model, a ten-year simulation driven by NCEP reanalysis datasets has been made to explore the performance of the East Asian climate simulation and to identify the model’s systematic errors. At the same time, comparative simulation experiments for 5 years between the RegCM2 and RegCM NCC have been done to further understand their differences in simulation performance. Also, a ten-year hindcast (1991–2000) for summer (June–August), the rainy season in China, has been undertaken. The preliminary results have shown that the RegCM NCC is capable of predicting the major seasonal rain belts. The best predicted regions with high anomaly correlation coefficient (ACC) are located in the eastern part of West China, in Northeast China and in North China, where the CGCM has maximum prediction skill as well. This fact may reflect the importance of the largescale forcing. One significant improvement of the prediction derived from RegCM NCC is the increase of ACC in the Yangtze River valley where the CGCM has a very low, even a negative, ACC. The reason behind this improvement is likely to be related to the more realistic representation of the large-scale terrain features of the Tibetan Plateau. Presumably, many rain-producing systems may be generated over or near the Tibetan Plateau and may then move eastward along the Yangtze River basin steered by upper-level westerly airflow, thus leading to enhancement of rainfalls in the mid and lower basins of the Yangtze River. The real-time experimental predictions for summer in 2001, 2002, 2003 and 2004 by using this nested RegCM NCC were made. The results are basically reasonable compared with the observations.     

Remotely sensed estimation of forest canopy density: A comparison of the performance of four methods

In recent years, a number of alternative methods have been proposed to predict forest canopy density from remotely sensed data. To date, however, it remains difficult to decide which method to use, since their relative performance has never been evaluated. In this study the performance of: (1) an artificial neural network, (2) a multiple linear regression, (3) the forest canopy density mapper and (4) a maximum likelihood classification method was compared for prediction of forest canopy density using a Landsat ETM+ image. Comparison of confusion matrices revealed that the regression model performed significantly worse than the three other methods. These results were based on a z-test for comparison of weighted kappa statistics, which is an appropriate statistic for analysis of ranked categories. About 89% of the variance of the observed canopy density was explained by the artificial neural networks, which outperformed the other three methods in this respect. Moreover, the artificial neural networks gave an unbiased prediction, while other methods systematically under or over predicted forest canopy density. The choice of biased method could have a high impact on canopy density inventories.     

龙泉山断裂带地震活动性浅析

通过对龙泉山断裂带东坡断裂和西坡断裂的地震活动性研究,表明该带是一条活断层。历史地震记载和现今地震活动均呈现沿断裂带分布,地震活动呈现周期性和南北跳迁的特点,近10年来地震监测资料表明该带地震活动在增强。     

四川水氡测值突跳异常与地震

在四川开展水氡前兆观测的初期,部分水氡点的水氡测值突跳异常很好地对应了其可预测范围内的中强以上地震。水氡测值突跳异常曾作为松潘—平武和盐源—宁蒗等地震预报的重要依据。但在水氡观测至今的完整时间段内,水氡突跳异常总体表现出对应率低,漏报率高的现象。多次预报攻关研究结果显示,水氡观测的异常表现是多种多样的,水氡测值突跳异常只是其中的表现之一。在今后四川及邻区的中强以上地震预报实践中,水氡测值突跳异常仍可作为地震短临预报的重要参考。