重庆强对流短临业务评分方法

结合重庆本地实际情况,以区/县为单位对强对流中出现的短历时强降水、阵性大风及雷电进行业务质量定量评估.短历时强降水、阵性大风基于加密站观测资料采用分级的方式来评定,对雷电的评定基于ADTD系统观测到地闪资料并判断所在区/县是否有地闪出现.介绍了重庆本地强对流短临业务评分方法及开发的评分软件.从2011年的评分结果看,该评分方法在重庆本地是比较合理的,在业务应用上是可行的.     

不同参数化方案对风预报效果影响个例研究

中尺度气象模式对风场的预报效果与参数化方案的适应性紧密相关.以内蒙古高原丘陵地形、江苏平缓的海陆交界地形2种典型下垫面试验风电场为模拟区域,分别用WRFV3.2 （Weather Research and Forecast Model）模式自带的6种物理过程参数化组合方案预报了2010年1月和7月两个风电场区域的风速和风向,对比分析了参数化组合方案差异对风场预报的影响.结果表明：①内蒙古试验区,边界层MRF方案描述的边界层结构较MYJ方案合理;微物理方案WSM3在夏季的风速预报能力优于WSM6,而冬季相反;复杂地形区域的风场预报需考虑陆面过程参数化方案,尤其是夏季降水发生后,陆面过程对于边界层结构的影响增大,选用Noah优于无陆面过程.②江苏试验区,边界层MRF方案描述的边界层结构较MYJ方案合理;1月陆面过程RUC方案优于陆面热量扩散和Noah;7月陆面热量扩散方案优于RUC和Noah.③风向预报6个方案的预报风向统计与实际记录风向统计有较好的一致性,风向概率分布相似,盛行风向一致且稳定.     

用于风电场功率预测的逐时风速预报

为满足风电场精细化风速预报的需要,利用MM5模式的格点输出数值预报产品以及福建沿海地区两座海上测风塔的逐时气象资料,采用逐步回归的统计方法,将MM5数值预报产品与测风塔实测气象资料要素指标值共同引入回归方程,拟合两座测风塔特定高度的逐小时风速预报方程,详细介绍了该方法的实现过程.通过一年的预报效果指标以及15日的独立样本效果检验,结果表明该方法对于逐小时风速的预报有一定的应用价值.     

基于中尺度模式与神经网络的风电功率预测

将中尺度数值天气预报模式与BP神经网络模型相结合用于风电功率预测,以WRF模式回算了2008年6月至2009年6月试验风电场的气象要素,精度检验结果显示风速预报值与对应实测值之间的相关系数达到0.72,风向、气温、湿度、气压的预报也比较准确,满足建立BP神经网络预报模型的需要.逐一建立试验风电场40台风电机组输出功率的BP神经网络预报模型,分析了数据标准化方法、隐含层神经元数对预报精度的影响.进行了26天实效为24 h的逐10 min预报试验,并以独立样本进行预报精度检验,结果显示单台风电机组输出功率相对均方根误差在24.8％～32.6％之间,预报值与实测值之间的相关系数现在0.45～0.68之间;风电场整体相对均方根误差为19.5％,预报值与实测值之间的相关系数为0.74.研究结果表明该方法可以用于实际的风电功率预测.     

Magnetosonic waveguide model of solar wind flow tubes

We consider solar wind flow tubes as a magnetosonic wave-guide. Assuming a symmetric expansion in edges of slab-modelled wave-guide, we study the propagation characteristics of magnetosonic wave in the solar wind flow tubes. We present the preliminary results and discuss their implications.     

Study on Quantitative Identification Sand and Dust Storm Using MODIS Data

In order to detect the scope and the intensity quanti cationally, the spectrum characteristic of sand and dust storm was analyzed in detail by using several MODIS data; bands that can distinguish sand and dust from cloud and surface were detected; two indices for determining the scope and intensity of sand and dust storm were found out, and were tested in several storms. Our study result shows: 1) The spectral characteristic of sand and dust in solar wavelengths is that the reflectance increases with the increasing of the wavelength. This is similar to the characteristic of the spectrum of soil. Also, the reflectance of large size dusts increases faster than small size dusts. 2) Small size dusts show typical characteristic of aerosol, being sensitive to blue band of 0.46 μm and insensitive to short wave infrared bands of 1.6 and 2.1 μm. 3) Large size dusts do not have aerosol characteristic, not sensitive to blue band but sensitive to short wave infrared bands. 4) Bands of 3.7 and 8.5 μm are sensitive to dusts. The difference of two bands can be used to identify sands and dusts and reflect the intensity to a certain extent. And 5) the two indices are very effective to monitor sands and dusts by testing a lot of sand and dust storm cases during the period of 2002-2005. Also, the method is simple and easy for operational use.     

NUMERICAL SIMULATION OF INTERANNUAL AND INTERDECADAL VARIABILITY OF SURFACE WIND OVER THE TROPICAL PACIFIC

A global atmospheric general circulation model (L9R15 AGCMs) forced by COADS SST was integrated from 1945 to 1993. Interannual and interdecadal variability of the simulated surface wind over the tropical Pacific was analyzed and shown to agree vey well with observation. Simulation of surface wind over the central-western equatorial Pacific was more successful than that over the eastern Pacific. Zonal propagating feature of interannual variability of the tropical Pacific wind anomalies and its decadal difference were also simulated successfully. The close agreement between simulation and observation on the existence of obvious interdecadal variability of tropical Pacific surface wind attested to the high simulation capability of AGCM.     

An investigation of sand–dust storm events and land surface characteristics in China using NOAA NDVI data

Observations from 560 weather stations in China show that sand–dust storms occur most frequently in April in north China. The region consists of Sub-dry Mid Temperate, Dry Mid Temperate, Sub-dry South Temperate and Dry South Temperate Zones and much of the land surface is desert or semi-desert: it is relatively dry with minimal rainfall and a high annual mean temperature. In most regions of China, the annual mean frequency of sand–dust events decreased sharply between 1980 and 1997 and then increased from 1997 to 2000. Statistical analyses demonstrate that the frequency of sand–dust storms correlates highly with wind speed, which in turn is strongly related to land surface features; on the other hand, a significant correlation between storm events and other atmospheric quantities such as precipitation and temperature was not observed. Accordingly, land surface cover characteristics (vegetation, snowfall and soil texture) may play a significant role in determining the occurrence of sand–dust storms in China. Analysis of Normalized Difference Vegetation Index derived from National Oceanic and Atmospheric Administration and Empirical Orthogonal Function show that since 1995 surface vegetation cover in large areas of Northern China has significantly deteriorated. Moreover, a high correlation is shown to exist among the annual occurrence of sand–dust storms, surface vegetation cover and snowfall. This suggests that the deterioration of surface vegetation cover may strongly influence the occurrence of sand–dust storms in China. Soils with coarse and medium textures are found to be more associated with sand–dust storms than other soils.     

Investigations on the runoff generation at the profile and plot scales,Swiss Emmental

This article describes an investigation on runoff generation at different scales in the forested catchment of the Sperbelgraben in the Emmental region (Swiss Prealps) where studies in the field of forest hydrology have a history of 100 years. It focuses on the analysis of soil profiles and the subsequent sprinkling experiments above them (1 m²), as well as on surface runoff measurements on larger plots (50 to 110 m²). In the Sperbelgraben investigation area, two very distinct runoff reactions could be observed. On the one hand, very high production of saturation overland flow was registered on wet areas of gleyic soils, with runoff coefficients between 0·39 and 0·94 for profile irrigation. On the other hand, almost no surface runoff was measured on Cambisols, with the exception at some sites of a hydrophobic reaction detected at the beginning of storms after dry periods (coefficients for profile irrigation: 0·01–0·16). This pattern was observed during 1 m² soil plot irrigation and on surface runoff plots. Apart from a less distinctive signal of the water‐repellent litter layer on the larger surface runoff plots, the dominant hydrological processes at the two scales are the same. The determined runoff reaction at the two scales corresponds well with information from a forest site type map describing soil and vegetation characteristics and used as a substitute for a soil map in this study. Theoretical considerations describing forest influence on flood discharge are discussed and evaluated to be in good agreement with observations. These findings are a sound foundation for application in hydrological catchment modelling. Copyright © 2006 John Wiley & Sons, Ltd.     

Geoeffective Analysis of CMEs Under Current Sheet Magnetic Coordinates

Using 100 CME–ICME events during 1997.01–2002.11, based on the eruptive source locations of CMEs and solar magnetic field observations at the photosphere, a current sheet magnetic coordinate (CMC) system is established in order to statistically study the characteristics of the CME–ICME events and the corresponding geomagnetic storm intensity. The transit times of CMEs from the Sun to the Earth are also investigated, by taking into account of the angle between the CME eruption normal (defined as the vector from the Sun center to the CME eruption source) and the Sun-Earth line. Our preliminary conclusions are: 1. The distribution of the CME sources in our CMC system is obviously different from that in the ordinary heliographic coordinate system. The sources of CMEs are mainly centralized near the heliospheric current sheet (HCS), and the number of events decreases with the increment of the angular distance from the CME source to the HCS on the solar surface; 2. A large portion of the total events belong to the same–side events (referring to the CME source located on the same side of the HCS as the Earth), while only a small portion belong to the opposite–side events (the CME source located on the opposite side of the HCS as the Earth). 3. The intense geomagnetic storms are usually induced by the same–side events, while the opposite side events are commonly associated with relatively weak geomagnetic storms; 4. The angle between the CME normal and the Sun–Earth line is used to estimate the transit time of the CME in order to reflect the influence of propagation characteristic of the CME along the Sun–Earth direction. With our new prediction method in context of the CMC coordinate, the averaged absolute error for these 100 events is 10.33 hours and the resulting relative error is not larger than 30% for 91% of all the events.