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A timescale decomposed threshold regression(TSDTR) downscaling approach to forecasting South China early summer rainfall(SCESR) is described by using long-term observed station rainfall data and NOAA ERSST data. It makes use of two distinct regression downscaling models corresponding to the interannual and interdecadal rainfall variability of SCESR.The two models are developed based on the partial least squares(PLS) regression technique, linking SCESR to SST modes in preceding months on both interannual and interdecadal timescales. Specifically, using the datasets in the calibration period 1915–84, the variability of SCESR and SST are decomposed into interannual and interdecadal components. On the interannual timescale, a threshold PLS regression model is fitted to interannual components of SCESR and March SST patterns by taking account of the modulation of negative and positive phases of the Pacific Decadal Oscillation(PDO). On the interdecadal timescale, a standard PLS regression model is fitted to the relationship between SCESR and preceding November SST patterns. The total rainfall prediction is obtained by the sum of the outputs from both the interannual and interdecadal models. Results show that the TSDTR downscaling approach achieves reasonable skill in predicting the observed rainfall in the validation period 1985–2006, compared to other simpler approaches. This study suggests that the TSDTR approach,considering different interannual SCESR-SST relationships under the modulation of PDO phases, as well as the interdecadal variability of SCESR associated with SST patterns, may provide a new perspective to improve climate predictions. 相似文献
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利用GFDL CM2p1模式, 本文探讨了初始海温误差对印度洋偶极子(IOD)事件可预报性的影响. 当热带印度洋存在初始海温误差时, IOD预报发生了冬季预报障碍(WPB)现象和夏季预报障碍(SPB)现象. WPB发生与否与正IOD事件发展位相冬季的厄尔尼诺-南方涛动(ENSO)有关. 即当冬季存在ENSO时, IOD预测不发生WPB现象, 反之亦然. 相比之下, SPB发生与否和ENSO没有必然联系. 此外, 进一步探讨了最容易导致SPB现象的初始海温误差的主要模态, 指出该模态在热带印度洋上表现为东-西偶极子型, 这和前人研究中最容易导致WPB现象的初始海温误差模态相似. 当在热带印度洋上叠加这些初始海温误差后, 热带太平洋上出现了海表温度异常和风场异常, 进而通过大气桥和印尼贯穿流的作用影响热带印度洋, 使之在夏季出现了东-西偶极子型的海表温度异常, 该异常在Bjerknes作用下快速发展, 加强, 最终导致SPB现象的发生. 相似文献
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Since the last International Union of Geodesy and Geophysics General Assembly(2003),predictability studies in China have made significant progress.For dynamic forecasts,two novel approaches of conditional nonlinear optimal perturbation and nonlinear local Lyapunov exponents were proposed to cope with the predictability problems of weather and climate,which are superior to the corresponding linear theory.A possible mechanism for the"spring predictability barrier"phenomenon for the El Ni(?)o-Southern Oscillation (ENSO)was provided based on a theoretical model.To improve the forecast skill of an intermediate coupled ENSO model,a new initialization scheme was developed,and its applicability was illustrated by hindcast experiments.Using the reconstruction phase space theory and the spatio-temporal series predictive method, Chinese scientists also proposed a new approach to improve dynamical extended range(monthly)prediction and successfully applied it to the monthly-scale predictability of short-term climate variations.In statistical forecasts,it was found that the effects of sea surface temperature on precipitation in China have obvious spatial and temporal distribution features,and that summer precipitation patterns over east China are closely related to the northern atmospheric circulation.For ensemble forecasts,a new initial perturbation method was used to forecast heavy rain in Guangdong and Fujian Provinces on 8 June 1998.Additionally, the ensemble forecast approach was also used for the prediction of a tropical typhoons.A new downscaling model consisting of dynamical and statistical methods was provided to improve the prediction of the monthly mean precipitation.This new downsealing model showed a relatively higher score than the issued operational forecast. 相似文献
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The role of the Indonesian Throughflow(ITF) in the influence of the Indian Ocean Dipole(IOD) on ENSO is investigated using version 2 of the Parallel Ocean Program(POP2) ocean general circulation model. We demonstrate the results through sensitivity experiments on both positive and negative IOD events from observations and coupled general circulation model simulations. By shutting down the atmospheric bridge while maintaining the tropical oceanic channel, the IOD forcing is shown to influence the ENSO event in the following year, and the role of the ITF is emphasized. During positive IOD events,negative sea surface height anomalies(SSHAs) occur in the eastern Indian Ocean, indicating the existence of upwelling.These upwelling anomalies pass through the Indonesian seas and enter the western tropical Pacific, resulting in cold anomalies there. These cold temperature anomalies further propagate to the eastern equatorial Pacific, and ultimately induce a La Nia-like mode in the following year. In contrast, during negative IOD events, positive SSHAs are established in the eastern Indian Ocean, leading to downwelling anomalies that can also propagate into the subsurface of the western Pacific Ocean and travel further eastward. These downwelling anomalies induce negative ITF transport anomalies, and an El Nio-like mode in the tropical eastern Pacific Ocean that persists into the following year. The effects of negative and positive IOD events on ENSO via the ITF are symmetric. Finally, we also estimate the contribution of IOD forcing in explaining the Pacific variability associated with ENSO via ITF. 相似文献
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亚洲区域海—陆—气相互作用对全球和亚洲气候变化的作用研究进展 总被引：13，自引：4，他引：9
围绕全球变化研究国家重大研究计划项目“亚洲区域海—陆—气相互作用机理及其在全球变化中的作用”预定的总体研究内容和科学目标,项目执行两年多以来,取得了一系列阶段性科研成果.关于气候动力学方面,项目揭示了热带印度洋—西太平洋暖池的海温变化是全球热带气候年代际变化的重要驱动力,是全球尺度副热带干旱的重要调控器;发现热带东太平洋海温存在冷舌模态,它是一个海气耦合模态,阐明在全球变暖背景下其对ENSO型态变异的作用及影响东亚气候的机理;揭示了青藏高原热力强迫的异常特征及其气候效应;提出了水平非均匀基流中行星波传播的理论,研究了其在不同东亚夏季风背景下的传播特征.关于气候预测方法方面,提出了若干有物理基础的气候预测方法,如尺度分离的降尺度预测新方法、基于北大西洋涛动(NAO)-ENSO的东亚夏季风预测模型、基于南半球环状模的东亚气候预测模型等,为业务部门提供了重要参考.关于观测方面,项目在亚洲区域海气补充观测和海洋资料同化方面也取得突出进展,成功进行了南海18°N断面海洋综合观测,为形成我国第一条南海断面长期海气观测打下了基础.在国际合作方面,项目还继续推动和领导了“亚洲季风年”(AMY2007-2012)与“东亚气候模拟”国际计划,提升了我国在该领域的国际地位. 相似文献
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本文总结了近年来条件非线性最优扰动方法的应用研究的主要进展.主要包括四个方面:(1)将条件非线性最优扰动(CNOP)方法拓展到既考虑初始扰动又考虑模式参数扰动,形成了拓展的CNOP方法.拓展的CNOP方法不仅能够应用于研究分别由初始误差和模式参数误差导致的可预报性问题,而且能够用于探讨初始误差和模式参数误差同时存在的情形;(2)将拓展的CNOP方法分别应用于ENSO和黑潮可预报性研究,考察了初始误差和模式参数误差对其可预报性的影响,揭示了初始误差在导致ENSO和黑潮大弯曲路径预报不确定性中的重要作用;(3)考察了阻塞事件发生的最优前期征兆(OPR)以及导致其预报不确定性的最优增长初始误差(OGR),揭示了OPR和OGR空间模态及其演变机制的相似性及其局地性特征;(4)研究了台风预报的目标观测问题,用CNOP方法确定了台风预报的目标观测敏感区,通过观测系统模拟试验(OSSEs)和/或观测系统试验(OSEs),表明了CNOP敏感区在改进台风预报中的有效性.具体地,台风OGR的主要误差分布在某一特定区域,空间分布具有明显的局地性特征,在台风OGR的局地性区域增加观测,有效改进了台风的预报技巧,该区域代表了台风预报的初值敏感区.事实上,上述El Ni(n)o事件、黑潮路径变异以及阻塞事件的OGR的空间分布也具有明显的局地性特征,这些事件的OGR刻画的局地性区域可能也代表了初值敏感区. 相似文献
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A New Strategy for Solving a Class of Constrained Nonlinear Optimization Problems Related to Weather and Climate Predictability 总被引：2，自引：0，他引：2
There are three common types of predictability problems
in weather and climate, which each involve different constrained nonlinear
optimization problems: the lower bound of maximum predictable time, the
upper bound of maximum prediction error, and the lower bound of maximum
allowable initial error and parameter error. Highly efficient algorithms
have been developed to solve the second optimization problem. And this
optimization problem can be used in realistic models for weather and climate
to study the upper bound of the maximum prediction error. Although a
filtering strategy has been adopted to solve the other two problems, direct
solutions are very time-consuming even for a very simple model, which
therefore limits the applicability of these two predictability problems in
realistic models. In this paper, a new strategy is designed to solve these
problems, involving the use of the existing highly efficient algorithms for
the second predictability problem in particular. Furthermore, a series of
comparisons between the older filtering strategy and the new method are
performed. It is demonstrated that the new strategy not only outputs the
same results as the old one, but is also more computationally efficient.
This would suggest that it is possible to study the predictability problems
associated with these two nonlinear optimization problems in realistic
forecast models of weather or climate. 相似文献
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XU Huiand DUAN Wansuo State Laboratory of Numerical Modeling for Atmospheric Sciences Geophysical Fluid Dynamics 《大气科学进展》2008,(4)
With the Zebiak-Cane(ZC)model,the initial error that has the largest effect on ENSO prediction is explored by conditional nonlinear optimal perturbation(CNOP).The results demonstrate that CNOP-type errors cause the largest prediction error of ENSO in the ZC model.By analyzing the behavior of CNOP- type errors,we find that for the normal states and the relatively weak El Nino events in the ZC model,the predictions tend to yield false alarms due to the uncertainties caused by CNOP.For the relatively strong El Nino events,the ZC model largely underestimates their intensities.Also,our results suggest that the error growth of El Nino in the ZC model depends on the phases of both the annual cycle and ENSO.The condition during northern spring and summer is most favorable for the error growth.The ENSO prediction bestriding these two seasons may be the most diffcult.A linear singular vector(LSV)approach is also used to estimate the error growth of ENSO,but it underestimates the prediction uncertainties of ENSO in the ZC model.This result indicates that the different initial errors cause different amplitudes of prediction errors though they have same magnitudes.CNOP yields the severest prediction uncertainty.That is to say,the prediction skill of ENSO is closely related to the types of initial error.This finding illustrates a theoretical basis of data assimilation.It is expected that a data assimilation method can filter the initial errors related to CNOP and improve the ENSO forecast skill. 相似文献