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采用多尺度时空投影(MSTP)预测思路建立广东月降水和季节降水预测方法。通过EOF分解、小波分析和Lanczos滤波方法进行周期分解, 采用MSTP方法进行预测。借鉴年际增量法, 对预报结果用最小二乘法进行误差订正, 得到降水预测结果。PS预测评分和均方根误差10年独立样本检验(2006—2015年)结果显示:订正后, PS预测评分起伏较小, 68.8%的月降水和季节降水PS预测评分明显提高的年份超过6年, 且有87.5%的月降水和季节降水PS预测平均分达到70以上; 在±0.5个标准差范围内, 订正后均方根误差在40%以上的概率分布明显高于订正前, 订正后的月和季节降水占81.3%, 订正前占31.3%;在±1个标准差范围内, 概率分布在70%以上的月季降水订正前后相差不多, 订正后占56.3%, 订正前占50%。 相似文献
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采用一种基于相似误差的模式后处理方法,对2011年10月18日—2012年1月5日WRF模式24 h预报的陕西延长风电场风速进行误差订正。该方法通过寻找与当前预报相似的历史预报来进行误差订正,克服了一般基于时间顺序的误差订正方法的不足,即不能处理由于天气系统的剧烈转变引起的预报误差的快速变化。相似误差订正方法减小了预报的均方根误差和中心均方根误差,相对原始预报分别减小9%和10%左右。该方法不仅可以减小系统误差,还可以减小随机误差,从而提高预报准确率。同时,订正结果相对原始预报具有更好的Taylor图模态相关。相似误差订正方法对风能预报敏感区的订正效果更为显著,均方根误差和中心均方根误差分别减小了12%和22%左右。该方法尤其适用于基于风能模式预报的风速误差订正,同时该方法对其他的预测系统和预报变量也有很好的应用潜力。 相似文献
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利用7d固定误差订正和滑动误差订正方法对2014年冬季辽宁地区中尺度业务模式2m温度预报产品插值结果进行订正,并将订正结果与中央气象台MOS预报进行对比,分析MOS、7d固定误差订正和滑动误差订正3种数值模式后处理方法对辽宁地区冬季温度预报准确率的影响。结果表明:经过两种误差订正后的预报结果准确率均比数值模式预报插值结果高,滑动误差订正效果优于7d固定误差订正;24h最高气温预报中,滑动误差订正结果的准确率最高;最低气温预报中,08时滑动误差订正结果准确率高于中央气象台MOS预报,但20时滑动误差订正结果准确率低于MOS预报。滑动误差订正需1—15d的资料积累,比MOS方法所需资料少且操作简单,适合观测资料积累少的地区开展数值模式的温度订正。 相似文献
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舟山市汛期降水量预报方法 总被引：1，自引：0，他引：1
利用基于预测误差平方和 ( PRESS)准则的逐步回归分析和基于残差平方和( RSS)准则的逐步回归分析建立了舟山市 3个县区站汛期 ( 5～ 9月 )降水量的预报模型 ,并对两种方法的预测结果进行预报集成 ,经试报和预报检验表明 ,该模型的预测效果较好 相似文献
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气候系统是一种耗散的、具有多个不稳定源的非线性、非平稳系统。该文利用支持向量机(SVM)算法在处理非线性问题中的优越性和经验模态分解(EMD)算法在处理非平稳信号中的优势,采用将EMD与SVM相结合的短期气候预测方法,并应用到广西季节降水预报中。选取广西88个气象观测站1957—2005年6—8月逐年降水量的距平百分率序列作为试验数据,通过EMD算法将标准化处理后的距平百分率序列分解成多个本征模态函数(IMF)分量和一个趋势分量,在分解中针对EMD算法存在的端点极值问题选择两种方法分别进行处理,对比得出极值延拓法效果更好。对每个分量构建不同的SVM模型进行预测,并通过重构形成最后的预测结果。试验中采用不经EMD处理的反向传播(BP)神经网络和SVM算法进行对比验证,结果表明:相对于直接预测方法,该文提出的方案均方误差最小,能够较为准确地反映出降水序列未来几年的变化趋势,具有更高的预测精度和较好的推广前景。 相似文献
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针对多普勒雷达风场反演的体积速度处理(Volume Velocity Processing,VVP)方法中系数矩阵的病态问题,从数学上进行了分析和论证,对反演的误差进行了敏感性分析,并对垂直速度的求解方程作了改进。系数矩阵的条件数将随着待反演参量的不同而差别很大,通常的处理方法是舍弃量级较小的参量,通过对误差范数的分析,证明这种处理尽管存在模型误差,但能够降低求解难度和结果误差。对系数矩阵病态原因的分析发现,系数矩阵矢量的线性相关造成了矩阵奇异,当合并或舍弃线性相关项时,待反演参量会受模型误差的影响,并且这种模型误差的大小并不仅与待反演参量的量级有关,而且随着位置的不同而改变,但是部分待参量仍然可以保持准确值。在对VVP算法误差分析的基础上,分析并验证了舍弃部分参量时的反演误差,改进的算法为准确反演降水粒子的垂直速度提供了理论基础。 相似文献
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轨道误差和长波大气延迟组成的系统误差是影响InSAR形变监测精度的重要因素之一.传统方法在空间域对干涉图的系统误差建模,容易导致长波形变和系统误差相混淆.本文在时空域利用附加系统参数对系统误差建模,同时根据观测值质量对差分相位观测值定权,采用附加系统参数的加权最小二乘法估计形变参数和系统误差,实现了长波形变和系统误差的分离.模拟实验结果表明,在形变与系统误差的空间变化特性完全一致的极端情况下,本文方法能实现两者的有效分离,估计的形变速率均方根误差比传统方法降低了98.8%.ASAR数据实验显示当形变尺度较小且分散分布时,本文方法和传统方法得到的结果相似;当形变在研究区内表现为长波变化时,本文方法比传统方法估计的形变结果更为稳健. 相似文献
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Abstract Evaluating horizontal gradients in three‐dimensional shallow water models that use bottom‐following sigma coordinates can lead to large errors near steep bathymetry. A technique that has been proposed to minimize this problem involves computing horizontal gradients in cartesian coordinates, while treating all other terms in a sigma coordinate framework. We study this technique through both truncation error analysis and numerical experimentation, and compare it to the direct application of sigma coordinates. While the Cartesian coordinate method has better convergence properties and generally smaller truncation errors when horizontal gradients are zero, the sigma coordinate method can be more accurate in other physically relevant situations. Also, the Cartesian coordinate method introduces significant numerical diffusion of variable sign near the bottom (where physical diffusion is particularly small), thus potentially leading to instabilities. Overall, we consider the sigma coordinates to be the best approach. 相似文献
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Application of the Analogue-Based Correction of Errors Method in ENSO Prediction 总被引：2，自引：0，他引：2 
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下载免费PDF全文 In this study, a method of analogue-based correction of errors（ACE） was introduced to improve El Ni？o-Southern Oscillation（ENSO） prediction produced by climate models. The ACE method is based on the hypothesis that the flow-dependent model prediction errors are to some degree similar under analogous historical climate states, and so the historical errors can be used to effectively reduce such flow-dependent errors. With this method, the unknown errors in current ENSO predictions can be empirically estimated by using the known prediction errors which are diagnosed by the same model based on historical analogue states. The authors first propose the basic idea for applying the ACE method to ENSO prediction and then establish an analogue-dynamical ENSO prediction system based on an operational climate prediction model. The authors present some experimental results which clearly show the possibility of correcting the flow-dependent errors in ENSO prediction, and thus the potential of applying the ACE method to operational ENSO prediction based on climate models. 相似文献
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L. S. Kuchment A. N. Gel’fan V. N. Demidov P. Yu. Romanov 《Russian Meteorology and Hydrology》2011,36(9):630-637
A technique is proposed of precomputing the snowmelt runoff hydrograph on the basis of physical and mathematical models of
river runoff formation, available standard data of surface hydrometeorological measurements, and satellite measurements of
Earth’s surface conditions. The computations were carried out for two regions including the basins of the Vyatka and Don rivers.
It is demonstrated that, in spite of the possible errors and gaps depending on meteorological conditions, the satellite snow
cover measurements can be an important addition to the surface measurements for simulating a spatial picture of the runoff
formation. The use of physical and mathematical models of the runoff formation enables to reduce the errors of satellite snow
cover data and to ensure the spatiotemporal continuity of its monitoring. 相似文献
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该文应用么枕生提出的中心聚类方法确定每个台站所能代表的站 ,在这些台站上对降水距平百分率进行平均 .这种平均对每个代表站逐站进行 ,由此得出的降水分布作为集成预报的对象 .应用最小预测误差平方和逐步算法逐站建立集成预报方程 .应用这一方法对在国家气候中心汛期预报中使用多年的 4个旱涝预报模型进行了集成预报试验 ,然后对每张预报图进行评分 .结果说明集成预报的评分高于 4个原始预报模型的评分 .对于 1 998年长江中下游和嫩江流域的异常洪涝 ,集成预报的评分亦高于 4个原始预报模型的评分 相似文献
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卫星资料凭着卫星遥感的全球性、连续性和高频次观测等优势,成为一种重要的非常规资料源,但卫星观测仍然存在各种各样的观测误差,其中包含由于观测偶然性所造成的统计学上的随机误差及仪器本身和辐射传输模式等造成的系统性偏差,这些误差在很大程度上影响了卫星资料的质量。文中提出了一种能有效订正卫星观测资料系统性偏差的梯度信息同化算法,该方法用一个梯度算子进行模式变量与观测变量的梯度变换,从而达到订正系统性偏差的目的。本文利用WRF（Weather Research Forecast）模式及其同化模式WRFDA（WRF Data Assimilation system）,以及AIRS（Atmospheric Infrared Sounder）资料,对台风“圆规”进行了实际的数值模拟和同化试验,数值结果表明,梯度信息同化方法能明显改善台风路径的模拟,在处理可信度较低的资料时仍然适用。另外,通过同化诊断分析,发现卫星资料的系统性偏差对于台风数值模拟有较大影响,而文中提出的梯度信息同化方法能较好的解决此类问题。 相似文献
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Using seasonal hindcasts to understand the origin of the equatorial cold tongue bias in CGCMs and its impact on ENSO 总被引：1，自引：1，他引：0
Benoît Vannière Eric Guilyardi Gurvan Madec Francisco J. Doblas-Reyes Steve Woolnough 《Climate Dynamics》2013,40(3-4):963-981
The cold equatorial SST bias in the tropical Pacific that is persistent in many coupled OAGCMs severely impacts the fidelity of the simulated climate and variability in this key region, such as the ENSO phenomenon. The classical bias analysis in these models usually concentrates on multi-decadal to centennial time series needed to obtain statistically robust features. Yet, this strategy cannot fully explain how the models errors were generated in the first place. Here, we use seasonal re-forecasts (hindcasts) to track back the origin of this cold bias. As such hindcasts are initialized close to observations, the transient drift leading to the cold bias can be analyzed to distinguish pre-existing errors from errors responding to initial ones. A time sequence of processes involved in the advent of the final mean state errors can then be proposed. We apply this strategy to the ENSEMBLES-FP6 project multi-model hindcasts of the last decades. Four of the five AOGCMs develop a persistent equatorial cold tongue bias within a few months. The associated systematic errors are first assessed separately for the warm and cold ENSO phases. We find that the models are able to reproduce either El Niño or La Niña close to observations, but not both. ENSO composites then show that the spurious equatorial cooling is maximum for El Niño years for the February and August start dates. For these events and at this time of the year, zonal wind errors in the equatorial Pacific are present from the beginning of the simulation and are hypothesized to be at the origin of the equatorial cold bias, generating too strong upwelling conditions. The systematic underestimation of the mixed layer depth in several models can also amplify the growth of the SST bias. The seminal role of these zonal wind errors is further demonstrated by carrying out ocean-only experiments forced by the AOCGCMs daily 10-meter wind. In a case study, we show that for several models, this forcing is sufficient to reproduce the main SST error patterns seen after 1 month in the AOCGCM hindcasts. 相似文献
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Benoît Vannière Eric Guilyardi Thomas Toniazzo Gurvan Madec Steve Woolnough 《Climate Dynamics》2014,43(7-8):2261-2282
Understanding the sources of systematic errors in climate models is challenging because of coupled feedbacks and errors compensation. The developing seamless approach proposes that the identification and the correction of short term climate model errors have the potential to improve the modeled climate on longer time scales. In previous studies, initialised atmospheric simulations of a few days have been used to compare fast physics processes (convection, cloud processes) among models. The present study explores how initialised seasonal to decadal hindcasts (re-forecasts) relate transient week-to-month errors of the ocean and atmospheric components to the coupled model long-term pervasive SST errors. A protocol is designed to attribute the SST biases to the source processes. It includes five steps: (1) identify and describe biases in a coupled stabilized simulation, (2) determine the time scale of the advent of the bias and its propagation, (3) find the geographical origin of the bias, (4) evaluate the degree of coupling in the development of the bias, (5) find the field responsible for the bias. This strategy has been implemented with a set of experiments based on the initial adjustment of initialised simulations and exploring various degrees of coupling. In particular, hindcasts give the time scale of biases advent, regionally restored experiments show the geographical origin and ocean-only simulations isolate the field responsible for the bias and evaluate the degree of coupling in the bias development. This strategy is applied to four prominent SST biases of the IPSLCM5A-LR coupled model in the tropical Pacific, that are largely shared by other coupled models, including the Southeast Pacific warm bias and the equatorial cold tongue bias. Using the proposed protocol, we demonstrate that the East Pacific warm bias appears in a few months and is caused by a lack of upwelling due to too weak meridional coastal winds off Peru. The cold equatorial bias, which surprisingly takes 30 years to develop, is the result of an equatorward advection of midlatitude cold SST errors. Despite large development efforts, the current generation of coupled models shows only little improvement. The strategy proposed in this study is a further step to move from the current random ad hoc approach, to a bias-targeted, priority setting, systematic model development approach. 相似文献