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21.
统计降尺度方法在北京月尺度预测中的应用 总被引:1,自引:0,他引:1
利用SDSM(statistical downscaling method)方法对北京47年(1961-2007年)的最低、最高气温和降水变化情况进行模拟评估,在此基础上对2008年北京奥运期间和2009年国庆期间天气变化进行实际预测应用。结果表明,SDSM方法具备模拟气温和降水等要素的能力。从年际变化模拟的情况上看,SDSM模型对气温模拟的效果好于降水,其中对于月平均最低(最高)气温模拟的效果好于最低(最高)气温极值的模拟。模型模拟的逐年极端最高(最低)气温结果在整体上偏低于实况气温,体现出气温极值模拟能力的不足。SDSM模型模拟的降水量整体上小于实测值,对降水极大值模拟能力更弱。对奥运会和国庆期间北京天气预测结果表明,模型对日最高、最低气温和降水的数值预测能力较差,预测值偏低于实际值,但升温和降温过程发生的时段能够准确的预测。 相似文献
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利用国家卫星气象中心处理的NOAA下午轨道卫星的OLR资料,用Xie等在1998年的文章中提出的月降水量计算模式,计算了1991-2008年地理范围在10°~60°N、75°~150°E、分辨率为0.5°×0.5°的中国大陆月降水量,得出:用OLR月距平资料可以计算出月降水量,模式估算出的降水量通过与NCEP提供的18年月降水量陆地观测数据对比,精度为:冬季相对误差49.14%、绝对误差7.97 mm;春季相对误差37.60%、绝对误差14.97 mm;夏季相对误差27.37%、绝对误差31.61mm;秋季相对误差37.99%、绝对误差16.95 mm,可见精度效果并不是太好,造成误差的主要原因是降水机制不一,层状云降水特别是逆温层状云和连续阴天不下雨,以及月平均OLR不能完整地反映月内降水云和降水量是造成用OLR月距平估算月降水量的主要误差来源.通过对FY-2C卫星云分类产品的图像分析,得出中国南方冬季主要是层状云降水,OLR月距平值较高,用全球的A、B系数估算出的降水量偏低于实况,因此对中国大陆进行分区、分季节统计A、B系数,是解决OLR月距平估算月降水量精度问题的途径. 相似文献
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选取我国长序列资料测站点中月降水与月均温资料较全的6个站点:西安、广州、汉口、沈阳、重庆、上海,以10a为一次成组实验,时域分辨率定为季,计算出各季月降水与月均温的相关系数,然后用相关分析和贝努里概型分析月均温与月降水之间的相关联系,初步得出我国长序列资料测站点春、夏、秋、冬月降水与月均温的相关稳定性联系。结果表明:①我国月降水与月均温在春、夏、秋、冬季均存在相关关系,以夏、秋季节最显著且为负相关,故我国常见干热或湿凉型夏、秋季;②我国华南地区春季月降水与月均温负相关关系显著,故常呈现干热或湿冷型春季;西北地区冬季月降水与月均温负相关关系较为明显,常呈现干热或湿冷型冬季。 相似文献
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针对动力气候模式对区域或更小空间尺度内的日降水预测技巧偏低的问题,应用最优子集回归 (OSR) 方法对国家气候中心业务化的月动力气候模式 (DERF) 输出的高度场、风场和海平面气压场进行降尺度处理用于降水预测,旨在提高预测准确率。1982—2006年交叉检验结果表明:OSR方法能显著提高降水预测技巧,其中11~40 d改善效果最为显著。在此基础上,应用一步法和两步法两种统计降尺度方法预测极端降水日数,交叉检验结果表明:两种方法均优于随机预测,冬季两步法预测技巧略高于一步法,夏季一步法略优于两步法。综合认为OSR,OSR结合随机天气发生器 (WG) 两种统计降尺度方法对月尺度降水或极端降水日数的预测均具有较高的技巧,可作为短期气候预测的重要参考信息。 相似文献
26.
攀西地区月降水时序非线性特性分析 总被引:2,自引:0,他引:2
在介绍相空间重构理论的基础上,以攀西地区4个站点47 a的月降水时间序列为例,研究了该地月降水时间序列的非线性特性。首先,运用定量的G-P关联维方法,探讨了非线性分析的主要定量指标,具体而言有,饱和关联维数D2和柯尔莫哥诺夫熵,计算表明攀西月降水时间序列具有一定的非线性混沌特性。其次,结合定性的功率谱分析方法,进一步验证了攀西月降水时序具有非线性特性。除此之外还应用Cao方法检验,从而排除了月降水时序为随机序列的可能性。本文为进一步研究月降水时序数据的复杂性及其演化规律奠定了基础。 相似文献
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Vegetation changes can significantly affect catchment water balance. It is important to evaluate the effects of vegetation cover change on streamflow as changes in streamflow relate to water security. This study focuses on the use of statistical methods to determine responses in streamflow at seven paired catchments in Australia, New Zealand, and South Africa to vegetation change. The non‐parametric Mann–Kendall test and Pettitt's test were used to identify trends and change points in the annual streamflow records. Statistically significant trends in annual streamflow were detected for most of the treated catchments. It took between 3 and 10 years for a change in vegetation cover to result in significant change in annual streamflow. Presence of the change points in streamflow was associated with changes in the mean, variance, and distribution of annual streamflow. The streamflow in the deforestation catchments increased after the change points, whereas reduction in streamflow was observed in the afforestation catchments. The streamflow response is mainly affected by the climate and underlying vegetation change. Daily flow duration curves (FDCs) for the whole period and pre‐change and post‐change point periods also were analysed to investigate the changes in flow regime. Three types of vegetation change effects on the flow regime have been identified. The relative reductions in most percentile flows are constant in the afforestation catchments. The comparison of trend, change point, and FDC in the annual streamflow from the paired experiments reflects the important role of the vegetation change. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
29.
Abstract Time series modelling approaches are useful tools for simulating and forecasting hydrological variables and their change through time. Although linear time series models are common in hydrology, the nonlinear time series model, the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model, has rarely been used in hydrology and water resources engineering. The GARCH model considers the conditional variance remaining in the residuals of the linear time series models, such as an ARMA or an ARIMA model. In the present study, the advantages of a GARCH model against a linear ARIMA model are investigated using three classes of the GARCH approach, namely Power GARCH, Threshold GARCH and Exponential GARCH models. A daily streamflow time series of the Matapedia River, Quebec, Canada, is selected for this study. It is shown that the ARIMA (13,1,4) model is adequate for modelling streamflow time series of Matapedia River, but the Engle test shows the existence of heteroscedasticity in the residuals of the ARIMA model. Therefore, an ARIMA (13,1,4)-GARCH (3,1) error model is fitted to the data. The residuals of this model are examined for the existence of heteroscedasticity. The Engle test indicates that the GARCH model has considerably reduced the heteroscedasticity of the residuals. However, the Exponential GARCH model seems to completely remove the heteroscedasticity from the residuals. The multi-criteria evaluation for model performance also proves that the Exponential GARCH model is the best model among ARIMA and GARCH models. Therefore, the application of a GARCH model is strongly suggested for hydrological time series modelling as the conditional variance of the residuals of the linear models can be removed and the efficiency of the model will be improved. Editor D. Koutsoyiannis; Associate editor C. Onof Citation Modarres, R. and Ouarda, T.B.M.J., 2013. Modelling heteroscedasticty of streamflow times series. Hydrological Sciences Journal, 58 (1), 1–11. 相似文献
30.
《水文科学杂志》2013,58(5)
Abstract A revised approach to the calculation of baseflow using the method originally proposed by the United Kingdom Institute of Hydrology is presented. The revisions resolve two aspects of the method that lead to less than optimal results; that is, the calculation of values of baseflow that exceed the corresponding values of streamflow and the dependence of the calculated values on the origin of the five-day segmentation of the input streamflow data. The approach is illustrated using streamflow monitoring information that is typical for areas of southern Ontario, Canada, where baseflow is primarily the result of groundwater discharge. 相似文献