共查询到10条相似文献，搜索用时 125 毫秒
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集合方法在月动力预报信息提取中的应用 总被引：1，自引：0，他引：1
本工作将集合方法应用于提取月动力预报有用信息。利用中国气象局国家气候中心Ｔ６３Ｌ１６全球谱模式的５００百帕高度场月集合预报产品（集合成员数为８个，初始场的选取采用滞后方法（ＬＡＦ），即相邻两天的００００，０６００，１２００和１８００ＧＭＴ的初始化资料），就１９９７年１月至５月共１５次预报，分析了集合预报成员间的离散度与预报评分（距平相关系数和均方根误差）的关系，研究了用集合各成员预报离散度作为各个成员逐日预报的权重对月预报效果的影响。结果表明集合预报成员的离散度与预报评分有显著的相关，是有效预报长度Ｎ的一个很好估计；用离散度作为权重平均的月预报高度距平相关系数明显高于算术平均和线性权重，此外个例分析表明月平均环流及其异常的预报得到明显的提高。 相似文献
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The approach of getting useful information of monthly dynamical prediction from ensemble forecasts is studied. The extended
range ensemble forecasts (8 members, the initial perturbations of the lagged average forecast (LAF)(0000, 0600, 1200 and 1800
GMT in two consecutive days) of the 500 hPa height field with the global spectral model (T63L16) from January to May 1997
are provided by the National Climate Center of China. The relationship between the spread of ensemble measured by root–mean–square
deviation of ensemble member from ensemble mean and forecast skill (the anomaly correlation or the root–mean–square distance
between the ensemble mean forecast and the observation) is significant. The spread of ensemble can evaluate the useful forecast
days N for the best estimate of 30 days mean. Thus, a weighted mean approach based on ensemble spread is put forward for monthly
dynamical prediction. The anomaly correlation of the weighted monthly mean by the ensemble spread is higher than that of both
the arithmetic mean and the linear weighted mean. Better results of the monthly mean circulation and anomaly are obtained
from the ensemble spread weighted mean.
Supported by the Excellent National State Key Laboratory Project (49823002), the National Key Project ‘Study on Chinese Short-Term
Climate Forecast System’ (96-908-02) and IAP Innovation Foundation (8-1308).
The data were provided through the National Climate Center of China. The authors wish to thank Ms. Chen Lijuan for her assistance. 相似文献
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扩展经验正交函数(EEOF)及其在月、季降水预测中的应用 总被引：4，自引：0，他引：4
本文提出一种降水长期预测的新方案，用扩展经验正交函数(EEOF)展开连续月组成的月（季）降水分布场，求取各月的特征向量场和对应的时间权重系数，分析各场的天气学意义及前后承替的相互关系，用前期出现的特征向量场的特征来预测后期的降水场分布趋势，同时利用特征向量场所对应的时间系数作二维点聚图，估算预报月（季）份的降水总趋势。 相似文献
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使用集合天气预报系统的多个成员的风场预报来驱动海浪模式WAVEWATCH Ⅲ, 计算出含多个成员的海浪预报场,并相应开发出各海浪要素的集合预报产品,如集合平均、离散度、集合概率等,建立了一个集合海浪数值预报系统。使用该系统进行了2007年9—10月为期两个月的预报试验,利用太平洋和大西洋海域范围的浮标观测资料对系统的预报水平的初步检验分析显示,该集合海浪预报方法能够有效地将传统的确定性预报扩展到概率预报领域,且集合平均的预报水平要优于单一的确定性预报,采用集合预报方法可以提供单纯确定性预报所不能够提供的额外信息,具有较好的应用潜力。 相似文献
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H. Jean Thiébaux 《大气与海洋》2013,51(4):291-305
Abstract Data assimilation in numerical weather forecasting corrects current forecast values by subtracting a portion of interpolated forecast‐minus‐observation differences at the points of a three‐dimensional grid. Deviations used in updating a forecast data field are forecast errors obtained or derived from observations available at update time. When observations are missing at mandatory levels, construction of full vertical soundings by interpolation introduces extraneous errors. The present paper is concerned with determination of the error in vertical extrapolations of surface winds, and of aircraft and satellite cloud‐tracked winds. In addition it examines the effect on accuracy of using location‐specific statistics compared to averaged statistics as the basis for the interpolation weighting scheme and compares errors of one‐ and two‐variable interpolations. Interpolation accuracy tests demonstrate the influence of the interpolation scheme on the quality of interpolated information used in forecast updating. The results show that the level of accuracy exceeds the benchmark provided by monthly mean forecast error values only with bivariate interpolation of wind components from off‐level data sources. 相似文献
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It has been demonstrated that ensemble mean forecasts, in the context of the sample mean, have higher forecasting skill than deterministic(or single) forecasts. However, few studies have focused on quantifying the relationship between their forecast errors, especially in individual prediction cases. Clarification of the characteristics of deterministic and ensemble mean forecasts from the perspective of attractors of dynamical systems has also rarely been involved. In this paper, two attractor statistics—namely, the global and local attractor radii(GAR and LAR, respectively)—are applied to reveal the relationship between deterministic and ensemble mean forecast errors. The practical forecast experiments are implemented in a perfect model scenario with the Lorenz96 model as the numerical results for verification. The sample mean errors of deterministic and ensemble mean forecasts can be expressed by GAR and LAR, respectively, and their ratio is found to approach2~(1/2) with lead time. Meanwhile, the LAR can provide the expected ratio of the ensemble mean and deterministic forecast errors in individual cases. 相似文献
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充分利用T213和ECMWF数值预报产品的优势，对相关预报场进行定量集成。根据历史统计和产生暴雨的几个必要条件，选取相关因子进行判别，并按权重进行叠加，得出未来24h暴雨落区概率预报图，在业务应用取得了满意的效果。 相似文献