A novel wind speed forecasting model for wind farms of Northwest China

Wind resources are becoming increasingly significant due to their clean and renewable characteristics, and the integration of wind power into existing electricity systems is imminent. To maintain a stable power supply system that takes into account the stochastic nature of wind speed, accurate wind speed forecasting is pivotal. However, no single model can be applied to all cases. Recent studies show that wind speed forecasting errors are approximately 25% to 40% in Chinese wind farms. Presently, hybrid wind speed forecasting models are widely used and have been verified to perform better than conventional single forecasting models, not only in short-term wind speed forecasting but also in long-term forecasting. In this paper, a hybrid forecasting model is developed, the Similar Coefficient Sum (SCS) and Hermite Interpolation are exploited to process the original wind speed data, and the SVM model whose parameters are tuned by an artificial intelligence model is built to make forecast. The results of case studies show that the MAPE value of the hybrid model varies from 22.96% to 28.87 %, and the MAE value varies from 0.47 m/s to 1.30 m/s. Generally, Sign test, Wilcoxon’s Signed-Rank test, and Morgan--Granger--Newbold test tell us that the proposed model is different from the compared models.     

A COMPARISON OF METHODS FOR CALCULATION OF RADAR-RAINFALL HOURLY ACCUMULATIONS1

ABSTRACT: We compared two interpolation schemes for calculation of hourly accumulation of radar-rainfall. The schemes are: (1) the Advection Method, and (2) the Space-Time Kriging Method. The performance of the methods is investigated using numerical simulation experiments. Space-time evolution of rainfall fields is generated from a stochastic model. The generated fields are sampled following typical radar scanning strategies, and the investigated schemes are applied to obtain accumulated rainfall patterns. The statistical results and a visual analysis of the graphical images suggest that it is advisable to use an interpolation scheme for radar observations even when storm velocity is not high. The Space-Time Kriging Method provides the best results for low wind velocity. The Advection Method has the smallest standard deviation and mean absolute error, and preserves well the true rainfall pattern for high wind velocity.     

边界条件和偏移距的变化对分形插值精度的影响

地震数据空间道插值是地震资料预处理的重要内容之一。本文以分形理论为基础,借助压缩映射原理和不动点理论及实变函数理论,给出了分形插值函数的显式表达式及垂直比例因子的局部显式表达式。正演模拟中采用了吸收边界条件,边界条件的应用使得靠近边界的地震道分形插值重建的误差要高于远离边界的地震道,即随着检波器逐渐靠近边界,分形插值重建的误差逐渐增大。偏移距的变化也会对分形插值重建的精度产生影响,随着偏移距的增大,分形插值重建的误差有增大的趋势,但不明显。总体上来说,分形插值重建的地震道是原始地震道的良好近似,相位和振幅都得到了很好的恢复。     

基于灰色拓扑的公共聚集场所火灾预测模型

根据1991—2006年间中国公共聚集场所火灾统计资料,针对公共聚集场所火灾影响因子的不确定性和数据的波动性,运用灰色拓扑预测方法探讨公共聚集场所火灾发生的规律,并建立灰色拓扑预测模型,预测未来5年内火灾发生情况。结果表明,所建立的灰色拓扑预测模型的检验精度都达到"好"的标准。因此,采用该模型对公共聚集场所火灾发生情况进行预测,其结果比较可靠,可供消防部门参考。     

改进的有限单元法在河流水质数值模拟中的应用

利用有限单元法进行二维水质模拟不用考虑河流速度和流量分布等资料,可以直接根据河床地形特点求出水质分布.但传统方法需要利用作图法求出累积流量曲线,是整个模拟过程中最耗人力物力的过程.为解决这一问题,探讨了拉格朗日插值法在复杂河段二维水质模型数值计算中的应用,运用该方法对三峡长寿段的排污口对干流影响进行了数值计算,并将计算结果与作图法的结果进行了比较,比较结果验证了该方法具有省时、高效的优点,具有更加广阔的应用前景.     

downscaling procedures as a tool for integration of multiple air issues

In assessing the risks associated with climate change,downscaling has proven useful in linking surfacechanges, at scales relevant to decision making, tolarge-scale atmospheric circulation derived from GCMoutput. Stochastic downscaling is related to synopticclimatology, weather-typing approaches (classifyingcirculation patterns) such as the Lamb Weather Typesdeveloped for the United Kingdom (UK), the EuropeanGrosswetterlagen (Bardossy and Plate, 1992) and thePerfect Prognosis (Perfect Prog) method from numericalweather prediction. The large-scale atmosphericcirculation is linked with site-specific observationsof atmospheric variables, such as precipitation, windspeed or temperature, within a specified region. Classifying each day by circulation patterns isachieved by clustering algorithms, fuzzy rule bases,neural nets or decision trees. The linkages areextended to GCM output to account for climate change. Stochastic models are developed from the probabilitydistributions for extreme events. Objective analysiscan be used to interpolate values of these models toother locations. The concepts and some applicationsare reviewed to provide a basis for extending thedownscaling approach to assessing the integrated riskof the six air issues: climate change, UV-B radiation,acid rain, transport of hazardous air pollutants, smogand suspended particulates.     

基于格点数据的中国1961—2016年≥5 ℃、≥10 ℃有效积温时空演变

为了解气候变暖对农作物种植区域的影响,基于5日滑动平均、累积距平、MK检验、多元回归插值方法,选用格点数据对中国农业热量资源进行分析。结果表明：（1）≥5 ℃、≥10 ℃有效积温整体呈上升趋势,且≥5 ℃整体升幅更为显著,两者升幅均表现为南方地区最大,北方次之,青藏高原最小,秦巴山区积温呈现下降现象。（2）在空间分布上,≥5 ℃、≥10 ℃有效积温整体表现出自南向北随纬度更替变化的地带性分布和自东向西随海拔变化的阶梯状分布,东、中部地区受纬度影响明显,西部地区受海拔影响强于纬度。适宜喜凉作物种植的区域远大于喜温作物的适宜种植面积。（3）≥5 ℃、≥10 ℃有效积温均在1997年发生突变,突变后≥5 ℃、≥10 ℃各积温带界线呈现向北、向高海拔移动的趋势,积温整体升高。南方地区≥5 ℃、≥10 ℃积温增幅整体大于北方,青藏高原及高山山区增幅最小,秦岭地区积温增幅为负。（4）≥5 ℃、≥10 ℃有效积温初始日（结束日）整体呈提前（推迟）现象,且多数格点提前（推迟）日数在0~10 d以内,持续时间在突变后整体延长。青藏高原≥5 ℃、≥10 ℃积温初始日（结束日）提前（推迟）天数最大。     

资料同化方法在空气污染数值预报中的应用研究

基于第5代中尺度非静力气象模式MM5以及区域气溶胶和沉积模式REMSAD耦合的空气污染数值预报模型系统,分别采用最优插值法和集合卡尔曼滤波法对南京2002-08～2002-09 NOx和SO2模型预报结果进行了资料同化试验,结果表明,NOx和SO2经最优插值法同化后偏差平均值的改进率分别为34.20%、47.53%,均方根误差的改进率分别为31.95%、42.04%;NOx和SO2经集合个数为30的集合卡尔曼滤波法同化后偏差平均值的改进率分别为26.73%、60.75%,均方根误差的改进率分别为25.20%、55.16%;说明最优插值法和集合卡尔曼滤波法都具有改善空气污染数值预报中污染物浓度初始场的作用.进行了集合卡尔曼滤波法中集合个数为61时2种同化方法同化效果比较的试验,结果表明,随着集合卡尔曼滤波法集合个数的增加,NOx和SO2的同化效果都较集合个数为30时有所改善,并且,集合卡尔曼滤波法对NOx和SO2模式预报结果的改善效果将好于最优插值法.     

江苏省人口数据空间离散化研究及其精度分析

针对传统人口数据表达方法在表达人口空间分布上的不足,设计了人口数据离散化模型,通过分析人口数据与土地覆被信息之间的关系,将分县统计的人口数据分配到空间1 km×1 km栅格单元上。在江苏省的研究表明,利用该方法能获得比较高的精度。基于离散化后的人口数据,发现江苏省人口空间分布有两大特点：(1)人口分布自城市中心向城市外围由密集渐变为分散;(2)苏南的城市人口规模显著大于苏中和苏北,苏南、苏中、苏北三大区域的人口城镇化水平呈现由高到低排列。江苏省人口空间分布的上述特点与江苏省三大区域的经济发展状况及各个区域的城镇化水平相一致。离散化后生成的1 km×1 km栅格人口数据,能够精确表达人口分布的区域差异,可以作为制订资源开发、环境规划、区域发展战略等重要参考依据。     

高维空间插值在海洋环境数据预处理中的应用

基于国家海洋局东海分局环境监测中心1999到2006年在上海海域的原始监测数据,提出了一种新的数据预处理方法.该方法在高维空间中使用最邻近插值算法,消除了周期性变化以及边界截断误差的影响,实现了对研究区域任意时间,任意地点的插值,在海洋环境领域有着一定的应用前景.