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1.
利用2008年1月—2013年12月以及2017年1—11月全球天气预报系统(GFS)预报场资料,采用自适应线性最小二乘回归(LS)和自适应递推卡尔曼(Kalman)滤波两种动态时变参数方法,建立了河套周边地区0~168 h预报时效的总云量精细化预报,并与GFS模式直接输出的总云量、线性预报模型逐步回归预报方法得到的总云量以及非线性预报模型BP神经网络和最小二乘支持向量机回归方法(LSSVM)得到的总云量进行了对比,结果如下:(1)相比GFS模式直接输出的总云量,LS、BP神经网络、LSSVM得到的总云量与实况值的平均绝对误差均明显减小。LS方法误差最小,LS方法的年MAE均在20%~25%,且随着预报时效的延长,改进效果越大。LS方法、多元逐步回归方法、BP神经网络、LSSVM四种方法在6—8月的改进效果最大。(2)LS方法预报的总云量与实况云量的相关性最好,即使168 h预报时效的相关系数依然在0.64以上,远高于其他几种模型的预报结果。(3)LS方法能够明显地提高少云和多云天空状况下预报的击中率,且最优(少云击中率平均提高24 %,多云击中率平均提高34 %)。(4)自适应递推Kalman滤波方法存在预报滞后现象,改进效果不明显。   相似文献   

2.
基于T639数值预报产品与地面气象观测资料,以环渤海地区兴城站为例,选取与云的形成密切相关的4类预报因子——水汽类、大气不稳定度类、大气上升运动类和天气系统强度类,以总云量、低云量为预报对象,运用支持向量机,选取最佳参数,建立兴城站云量的逐月、逐时次精细化预报模型。试预报结果表明:平均预报准确率总云量为71%,低云量为69%,预报准确率较逐步回归模型有所提高;在大部分月份、时次,试预报值的变化趋势与观测值一致,可以较好地反映实际阴晴变换和云量变化;基于支持向量机的回归模型对云量有较好的预报能力。  相似文献   

3.
支持向量机在雷暴预报中的应用   总被引:2,自引:1,他引:1  
施萧  徐幼平  胡邦辉  成巍 《气象》2012,38(9):1115-1120
论文利用2002--2006年AREM模式产品和常规观测报文资料,综合运用改进的K平均聚类和主成分分析等方法,基于MOS原理逐月建立了最小二乘支持向量机和线性规划支持向量机的单站雷暴释用预报模型,并针对海口站2007年58月进行了具体的预报。结果表明:支持向量机结合AREM模式产品进行雷暴的释用预报是合适、有效的,而且主成分分析对预报结果的提高也起到了积极的作用。  相似文献   

4.
基于最小二乘支持向量机的雷暴预报初探   总被引:1,自引:0,他引:1  
利用2007年和2008年南京地区NCEP 1°×1°历史再分析资料和江苏省闪电定位资料,探讨最小二乘支持向量机(LS-SVM)方法在雷暴预报中的应用.将NCEP 1°×1°资料作为实况,选取了该资料与雷暴相关性较好的参数作为预报因子,而江苏省闪电定位资料则作为预报量,建立南京地区雷暴预报的最小二乘支持向量机模型,并用...  相似文献   

5.
以1980-2020年广西台风期间桂林、梧州、龙州、南宁、玉林等5个气象观测站的地面日极大风速为研究对象,采用多元线性回归(MR)、支持向量机(SVM)、模糊神经网络(FNN)等三种较为常用的线性和非线性方法分别进行预报建模,对2011-2020年共10a独立样本的检验.结果 表明,在全样本风速预报的平均绝对误差上,FNN模型对桂林站、梧州站、龙州站、玉林站共4个站点预报的平均绝对误差最小,总体预报精度最好,MR预报模型则对南宁站有较好的预报能力,SVM模型预报效果总体偏差.对于6级以上大风的TS评分、命中率、空报率和预报偏差等4个评估指标的统计,FNN模型的预测精度最高且相对稳定,MR方案次之,SVM在三种方案中预报效果最差.FNN方法对广西台风期间地面日极大风速的预报有较好的参考作用.  相似文献   

6.
利用2008—2010年逐年12月、次年1月的T511L61数值预报产品和单站观测资料,采用近似支持向量机方法,分别建立了南京、杭州和衢州站分类和回归结合的能见度释用预报模型(简称分类和回归结合模型)。利用2011年12月、次年1月资料作为独立样本,对模型进行试报检验,并与不分类条件下的纯回归模型进行对比。结果表明:分类和回归结合模型的预报效果好于纯回归模型,在24、36、48、60和72 h试报中,分类和回归结合模型的南京、杭州和衢州三站平均的准确率依次为75.5%、83.7%、72.1%、75.4%和78.0%,在除48 h的其余4个预报时次中,分类和回归结合模型的三站平均的准确率均高于纯回归模型。分类和回归结合模型在单站能见度预报中有较好的应用前景。   相似文献   

7.
支持向量机(SVM)的惩罚参数及核参数的选择直接影响到模型效果,通过粒子群算法(PSO)解决支持向量机的参数选择问题,实现了参数选择的自动化。将该方法应用于热带气旋强度预报,利用气候持续性因子,挑选了1990年的100个左右样本进行预报检验,预报时效为12 h、24 h、36 h、48 h的强度平均绝对误差分别为3.00、4.35、4.93和6.68 m/s。另外,还与国外预报结果及采用最小二乘回归法的预报结果进行了效果的比较,SVM方法显示了更好的预报能力。  相似文献   

8.
准确的降水天气预报是一个十分重要的研究课题。以中国气象局的T213和日本的细网格数据资料为基础,首先利用粒子群——投影寻踪对众多气象物理因子降维,其次在低维子空间利用四种线性回归方法提取降水系统的线性特征,四种神经网络模型提取降水系统的非线性特征;最后利用最小二乘支持向量机对其集成,对广西6月的逐日降水量进行试验结果表明,该模型预报稳定性好,预报准确率较高,具有较好的业务应用前景。  相似文献   

9.
天空云量预报及支持向量机和神经网络方法比较研究   总被引:9,自引:0,他引:9  
使用支持向量机和人工神经网络两种方法,分别建立了天空云量的预报模型。利用2001年5月1日~2004年12月31日的武汉市地面、高空观测值及欧洲中心的24小时预报场等资料,通过按不同比例随机抽取样本进行交叉验证的方法,分析了SVM和ANN模型的预报能力和鲁棒性;然后再用全部样本资料建立预报模型,来预报2005年1月1日~5月31日武汉市天空云量。交叉验证和实例预报的结果显示:虽然SVM和ANN模型都表现了较好的预报能力,但SVM的预报能力高于ANN方法,且在计算速度上有ANN无法比拟的优势。  相似文献   

10.
用小波分解(WT)和最小二乘支持向量机(LS-SVM)相结合的方法,建立西太平洋副热带高压面积指数的预报模型。该方法首先将西太平洋副热带面积指数(SI)分解为相对简单的带通分量信号,利用LS-SVM建立各分量信号的独立预报模型,然后对预报结果进行集成。为了评估和比较该方法的预报效果和技术优势,最后比较了在同等条件下WT~LS-SVM模型和神经网络、线性回归模型的独立检验预报效果。试验结果表明,该方法具有泛化能力强、预报精度高、训练速度快、稳定性好、便于建模等优点,具有良好的应用前景。  相似文献   

11.
Portions of the southern and southeastern United States, primarily Mississippi, Alabama, and Georgia, have experienced century-long (1895–2007) downward air temperature trends that occur in all seasons. Superimposed on them are shifts in mean temperatures on decadal scales characterized by alternating warm (1930s–1940s, 1990s) and cold (1900s; 1960s–1970s) regimes. Regional atmospheric circulation and SST teleconnection indices, station-based cloud cover and soil moisture (Palmer drought severity index) data are used in stepwise multiple linear regression models. These models identify predictors linked to observed winter, summer, and annual Southeastern air temperature variability, the observed variance (r2) they explain, and the resulting prediction and residual time series. Long-term variations and trends in tropical Pacific sea temperatures, cloud cover, soil moisture and the North Atlantic and Arctic oscillations account for much of the air temperature downtrends. Soil moisture and cloud cover are the primary predictors of 59.6 % of the observed summer temperature variance. While the teleconnections, cloud cover and moisture data account for some of the annual and summer Southeastern cooling trend, large significant downward trending residuals remain in winter and summer. Comparison is made to the northeastern United States where large twentieth century upward air temperature trends are driven by cloud cover increases and Atlantic Multidecadal Oscillation (AMO) variability. Differences between the Northeastern warming and the Southeastern cooling trends in summer are attributable in part to the differing roles of cloud cover, soil moisture, the Arctic Oscillation and the AMO on air temperatures of the 2 regions.  相似文献   

12.
利用2001年7月至2011年7月甘肃省榆中县地面测站的每日8次云量资料和同期NCEP每日4次等压面资料,由NCEP资料构造预报因子,以总云量和低云量为预报对象,分析预报因子和预报对象的相关性,采用逐步回归方法建立榆中县逐月8个时次的云量预报方程并进行回代;并利用2012年的资料检验预报方程的预报效果。结果表明:云量主要受整层湿度、垂直运动、不稳定能量、槽强度指数和700 hPa水汽通量散度影响,其中湿度状况和垂直运动是重要因素。建立的预报方程对总云量的预报效果比低云量好;总云量平均预报误差在2成左右,低云量平均预报误差在3成左右;预报值变化趋势可以部分地反映实际云量的变化趋势。  相似文献   

13.
Components of the surface radiation budget (SRB) [incoming shortwave radiation (ISR) and downwelling longwave radiation (DLR)] and cloud cover are assessed for three regional climate models (RCM) forced by analysed boundary conditions, over North America. We present a comparison of the mean seasonal and diurnal cycles of surface radiation between the three RCMs, and surface observations. This aids in identifying in what type of sky situation simulated surface radiation budget errors arise. We present results for total-sky conditions as well as overcast and clear-sky conditions separately. Through the analysis of normalised frequency distributions we show the impact of varying cloud cover on the simulated and observed surface radiation budget, from which we derive observed and model estimates of surface cloud radiative forcing. Surface observations are from the NOAA SURFRAD network. For all models DLR all-sky biases are significantly influenced by cloud-free radiation, cloud emissivity and cloud cover errors. Simulated cloud-free DLR exhibits a systematic negative bias during cold, dry conditions, probably due to a combination of omission of trace gas contributions to the DLR and a poor treatment of the water vapor continuum at low water vapor concentrations. Overall, models overestimate ISR all-sky in summer, which is primarily linked to an underestimate of cloud cover. Cloud-free ISR is relatively well simulated by all RCMs. We show that cloud cover and cloud-free ISR biases can often compensate to result in an accurate total-sky ISR, emphasizing the need to evaluate the individual components making up the total simulated SRB.  相似文献   

14.
ABSTRACT The abilities of BCC-AGCM2.1 and BCC_AGCM2.2 to simulate the annual-mean cloud vertical structure (CVS) were evaluated through comparison with GCM-Oriented CALIPSO Cloud Product (CALIPSO-GOCCP) data. BCC-AGCM2.2 has a dynamical core and physical processes that are consistent with BCC-AGCM2.1, but has a higher horizontal resolution. Results showed that both BCC-AGCM versions underestimated the global-mean total cloud cover (TCC), middle cloud cover (MCC) and low cloud cover (LCC), and that BCC_AGCM2.2 underestimated the global-mean high cloud cover (HCC). The global-mean cloud cover shows a systematic decrease from BCCA-GCM2.1 to BCC_AGCM2.2, especially for HCC. Geographically, HCC is significantly overestimated in the tropics, particularly by BCC_AGCM2,1, while LCC is generally overestimated over extra-tropical lands, but significantly underestimated over most of the oceans, especially for subtropical marine stratocumulus clouds. The leading EOF modes of CVS were extracted. The BCC_AGCMs perform well in reproducing EOF1, but with a larger variance explained. The two models also capture the basic features of EOF3, except an obvious deficiency in eigen- vector peaks. EOF2 has the largest simulation biases in both position and strength of eigenvector peaks. Furthermore, we investigated the effects of CVS on relative shortwave and longwave cloud radiative forcing (RSCRF and RLCRF). Both BCC_AGCM versions successfully reproduce the sign of regression coefficients, except for RLCRF in PC1. However, the RSCRF relative contributions from PC1 and PC2 are overestimated, while the relative contribution from PC3 is underes timated in both BCC_AGCM versions. The RLCRF relative contribution is underestimated for PC2 and overestimated for PC3.  相似文献   

15.
Summary The total cloud cover is deduced from measurements of monthly mean averages of the percent of possible sunshine duration at three locations in Egypt, Cairo, Bahtim and Sedi-Barrani stations during the period 1987–1995. This sunshine-derived total cloud cover (Cs) is compared to conventional ground-based observations of total cloud covers (Cg) made by meteorological observers. A linear relationship between the two estimates is calculated, and the difference between the two estimates as a function of Cs and Cg is fitted with a least-squares linear equation. It is found that on the average the sunshine-derived values of total cloud cover are about 7% lower than the corresponding ground-based estimated of total cloud cover. Both of these parameters are mainly used in solar radiation models and the error sources are mainly depending upon the way to describe sky cover.  相似文献   

16.
基于1961-2008年天山区域24站云量的逐日资料,使用相关和M原K检验等统计方法,分析中国天山区域云量的时空变化特征及其与降水的关系。结果表明:(1)春季、秋季和冬季,伊犁河谷以北总云量最多,夏季则在中天山和东天山的部分区域最多,低云量在夏季占总云量的比重最大;(2)区域平均总云量在春季和秋季呈减少趋势;低云量在各季节均呈增加趋势,尤其在冬季和夏季;(3)总云量的年代际变化不明显,而低云量自20世纪90年代至今,都处在高值期。(4)低云量在春季、夏季和秋季,均在20世纪90年代,而冬季在2000年左右发生了由少到多的气候突变;总云量未发生明显的气候突变。(5)总云量和低云量均和同期降水有较好的相关性。春季低云量和夏季降水,相关系数可达0.52。  相似文献   

17.
西南地区云量变化特征   总被引:1,自引:0,他引:1  
利用西南地区(云南、贵州、四川、重庆)记录较为完整的73个测站1956~2005年月平均云量资料,采用经验正交函数分析和Mann-Kendall突变检验方法,研究分析了西南地区云量的时空分布特征。结果表明:就全年而言,整个西南地区总云量的变化趋势一致,且存在着明显的年际变化特征,1990年代以后全年总云量表现出减少趋势;此外,总云量的分布在一定程度上受地形和区域气候的影响。从季节来看,夏、秋、冬季的总云量在西南地区为空间一致的变化趋势,而春季四川盆地北部总云量的变化趋势与其余地区相反;四季总云量也有明显的年际变化特征。低云量,全年和四季的时空变化特征相似,由于受地形起伏及区域气候差异的影响,川西高原东部和重庆地区的变化趋势与四川盆地的相反,且同样存在着明显的年际变化特征。另外,突变分析结果显示,西南地区的低云量近50a来呈持续减少趋势,而总云量在1990年发生突变,突变前在0线附近震荡,突变后总云量持续减少。  相似文献   

18.
Cloud cover information is used alongside weather forecasts in various fields of research; however, ground observation of cloud cover is conducted by human observers, a method that is subjective and has low temporal and spatial resolutions. To address these problems, we have developed an improved algorithm to calculate cloud cover using sky image data obtained with Skyviewer equipment. The algorithm uses a variable threshold for the Red Blue Ratio (RBR), determined from the frequency distribution of the Green Blue Ratio (GBR), to calculate cloud cover more accurately than existing algorithms. To verify the accuracy of the algorithm, we conducted daily, monthly, seasonal, and yearly statistical analyses of human observations of cloud cover, obtained every hour from 0800 to 1700 Local Standard Time (LST) for the entirety of 2012 at the Gangwon Regional Meteorological Administration (GRMA), Korea. A case study compared daily images taken at 1200 LST in each season with pixel images of cloud cover calculated by our improved algorithm. The selected cases yielded a high correlation coefficient of 0.93 with the GRMA data. A monthly case study showed low root mean square errors (RMSEs) and high correlation coefficients (Rs) for December (RMSE = 1.64 tenths and R = 0.92) and August (RMSE = 1.43 tenths and R = 0.91). In addition, seasonal cases yielded a high correlation of 0.9 and 87% consistency within ± 2 tenths for winter and a correlation of 0.83 and 82% consistency for summer, when cases of cloud-free or overcast conditions are frequent. Annual analyses showed that the bias of GRMA and Skyviewer cloud cover data for 2012 was -0.36 tenth, and the RMSE was 2.12 tenths, with the GRMA data showing more cloud cover. Considering that the GRMA and Skyviewer data were gathered at different spatial locations, GRMA and Skyviewer data were well correlated (R = 0.87) and showed a consistency of 80% in their cloud cover data (consistent within ± 2 tenths).  相似文献   

19.
全天空成像仪(total sky imager 440,TSI-440)可以实现白天全天空云量的持续自动监测,时空分辨率较高,得到的云量计算结果更精确.首先介绍了TSI-440的基本原理和资料格式,并基于太湖地区2008年5-10月的TSI-440资料及无锡站地面观测资料,采用统计方法详细地分析了不同天气情况下图像的成像特征及云量的计算误差.结果发现:图像的成像特征与能见度密切相关,红蓝比值随着能见度的减小而增大.另外,仪器在处理阴天图像及复杂天空(多云)图像时,易造成一定的云量计算误差.针对上述问题,本文通过直方图分析,重新选定了红蓝比阈值(晴空点阈值0.62,云点阈值0.66),基于新阈值计算的云量结果较仪器自带的处理结果更为准确,减小了因天气状况不同而产生的云量计算误差.  相似文献   

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