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Significant systematic errors in the tropical Atlantic Ocean are common in state-of-the-art coupled ocean–atmosphere general circulation models. In this study, a set of ensemble hindcasts from the NCEP coupled forecast system (CFS) is used to examine the initial growth of the coupled model bias. These CFS hindcasts are 9-month integrations starting from perturbed real-time oceanic and atmospheric analyses for 1981–2003. The large number of integrations from a variety of initial states covering all months provides a good opportunity to examine how the model systematic errors grow. The monthly climatologies of ensemble hindcasts from various initial months are compared with both observed and analyzed oceanic and atmospheric datasets. Our analyses show that two error patterns are dominant in the hindcasts. One is the warming of the sea surface temperature (SST) in the southeastern tropical Atlantic Ocean. This error grows faster in boreal summer and fall and peaks in November–December at round 2°C in the open ocean. It is caused by an excessive model surface shortwave radiative flux in this region, especially from boreal summer to fall. The excessive radiative forcing is in turn caused by the CFS inability to reproduce the observed amount of low cloud cover in the southeastern ocean and its seasonal increase. According to a comparison between the seasonal climatologies from the CFS hindcasts and a long-term simulation of the atmospheric model forced with observed SST, the CFS low cloud and radiation errors are inherent to its atmospheric component. On the other hand, the SST error in CFS is a major cause of the model’s southward bias of the intertropical convergence zone (ITCZ) in boreal winter and spring. An analysis of the SST errors of the 6-month ensemble hindcasts by seven coupled models in the Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction project shows that this SST error pattern is common in coupled climate hindcasts. The second error pattern is an excessive deepening of the model thermocline depth to the north of the equator from the western coast toward the central ocean. This error grows fastest in boreal summer. It is forced by an overly strong local anticyclonic surface wind stress curl and is in turn related to the weakened northeast trade winds in summer and fall. The thermocline error in the northwest delays the annual shoaling of the equatorial thermocline in the Gulf of Guinea remotely through the equatorial waveguide. 相似文献
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A high-resolution tropical Pacific general circulation model (GCM) coupled to a global atmospheric GCM is described in this paper. The atmosphere component is the 5°×4°global general circulation model of the Institute of Atmospheric Physics (IAP) with 9 levels in the vertical direction. The ocean component with a horizontal resolution of 0.5°, is based on a low-resolution model (2°×1°in longitude-latitude).Simulations of the ocean component are first compared with its previous version. Results show that the enhanced ocean horizontal resolution allows an improved ocean state to be simulated; this involves (1) an apparent decrease in errors in the tropical Pacific cold tongue region, which exists in many ocean models,(2) more realistic large-scale flows, and (3) an improved ability to simulate the interannual variability and a reduced root mean square error (RMSE) in a long time integration. In coupling these component models, a monthly "linear-regression" method is employed to correct the model's exchanged flux between the sea and the atmosphere. A 100-year integration conducted with the coupled GCM (CGCM) shows the effectiveness of such a method in reducing climate drift. Results from years 70 to 100 are described.The model produces a reasonably realistic annual cycle of equatorial SST. The large SSTA is confined to the eastern equatorial Pacific with little propagation. Irregular warm and cold events alternate with a broad spectrum of periods between 24 and 50 months, which is very realistic. But the simulated variability is weaker than the observed and is also asymmetric in the sense of the amplitude of the warm and cold events. 相似文献
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通过讨论省 (甚至地、市) 气象部门要不要开展数值天气预报工作的问题, 认为不是所有的地方都要开展, 只是那些希望搞科研型业务、迫切要求提高当地高影响天气的预报准确率的地方要开展。对于如何开展的问题, 提出不是去重复类似于主流途径的做法, 而是开辟另类途径, 并阐述了另类途径的内容、方法和意义。强调开展另类途径无需构建模式 (这是非常困难的工作), 只需运转现成的模式, 借助所关心的现象的历史数据来改造现成模式, 使之本地化, 是完全可行的。 相似文献
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舍入误差对大气环流模式模拟结果的影响 总被引：8，自引：2，他引：6
此文旨在研究气候数值模式的长期计算时受舍入误差的影响。通过对大气环流谱模式SAMIL采用不同CPU数计算时获得的长时间积分结果进行分析,发现使用不同CPU数进行单精度计算时,其十年平均月平均500 hPa高度场随机误差在正负6～8 gpm范围内,而使用双精度计算时相应的误差为正负3～4 gpm。对于气候平均场而言,作者的试验表明SAMIL在并行计算时由于计算顺序改变而引起的误差在可接受范围之内。然而,虽然舍入误差的全球平均值不大,但其误差分布的差别范围并不小。数值试验得到的不同模拟结果之间误差大小与模拟结果的自身年际变化大小在同样的量级,因此对于“年际变化”这样的问题来说,其影响是不可忽略的,必须要使用集合预报的办法来减小误差的影响。文中列出了3种研究复杂数值模式舍入误差的实验方法,指出其一定条件下的等效性和不同适用范围,对于其他模式的舍入误差影响研究有一定的参考价值。在舍入误差分析的基础上,介绍了一种新型的专门针对舍入误差的集合预报方法（舍入误差平均集合,RME）,指出了其在气候模拟研究中的应用价值。 相似文献
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数值模式的热带气旋强度预报订正及其集成应用 总被引：2，自引：0，他引：2
提供热带气旋强度预报产品的业务数值天气预报模式有很多,并已表现出一定的预报技巧,为提高对模式热带气旋强度预报产品的定量应用能力,分析2010—2012年7个业务数值模式的西北太平洋热带气旋强度预报,发现预报误差不仅受到模式热带气旋初始强度误差的显著影响,还与热带气旋及其所处环境的初始状况有密切关系,包括热带气旋初始强度、尺度、移速、环境气压、环境风切变、热带气旋发展潜势等。根据这些因子与各模式热带气旋强度预报误差之间的相关性,采用逐步回归方法建立热带气旋强度预报误差的统计预估模型,并通过逐个热带气旋滚动式建模来进行独立样本检验。检验结果表明,基于误差预估的模式订正预报比模式直接输出的热带气旋强度预报有显著改进,在此基础上建立的热带气旋强度多模式集成预报方案相对气候持续性预报方法在12 h有28%的正技巧,在24—72 h则稳定在15%—20%,具有业务参考价值。 相似文献
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C. Covey A. Abe-Ouchi G. J. Boer B. A. Boville U. Cubasch L. Fairhead G. M. Flato H. Gordon E. Guilyardi X. Jiang T. C. Johns H. Le Treut G. Madec G. A. Meehl R. Miller A. Noda S. B. Power E. Roeckner G. Russell E. K. Schneider R. J. Stouffer L. Terray J.-S. von Storch 《Climate Dynamics》2000,16(10-11):775-787
We examine the seasonal cycle of near-surface air temperature simulated by 17 coupled ocean-atmosphere general circulation models participating in the Coupled Model Intercomparison Project (CMIP). Nine of the models use ad hoc “flux adjustment” at the ocean surface to bring model simulations close to observations of the present-day climate. We group flux-adjusted and non-flux-adjusted models separately and examine the behavior of each class. When averaged over all of the flux-adjusted model simulations, near-surface air temperature falls within 2?K of observed values over the oceans. The corresponding average over non-flux-adjusted models shows errors up to ～6?K in extensive ocean areas. Flux adjustments are not directly applied over land, and near-surface land temperature errors are substantial in the average over flux-adjusted models, which systematically underestimates (by ～5?K) temperature in areas of elevated terrain. The corresponding average over non-flux-adjusted models forms a similar error pattern (with somewhat increased amplitude) over land. We use the temperature difference between July and January to measure seasonal cycle amplitude. Zonal means of this quantity from the individual flux-adjusted models form a fairly tight cluster (all within ～30% of the mean) centered on the observed values. The non-flux-adjusted models perform nearly as well at most latitudes. In Southern Ocean mid-latitudes, however, the non-flux-adjusted models overestimate the magnitude of January-minus-July temperature differences by ～5?K due to an overestimate of summer (January) near-surface temperature. This error is common to five of the eight non-flux-adjusted models. Also, over Northern Hemisphere mid-latitude land areas, zonal mean differences between July and January temperatures simulated by the non-flux-adjusted models show a greater spread (positive and negative) about observed values than results from the flux-adjusted models. Elsewhere, differences between the two classes of models are less obvious. At no latitude is the zonal mean difference between averages over the two classes of models greater than the standard deviation over models. The ability of coupled GCMs to simulate a reasonable seasonal cycle is a necessary condition for confidence in their prediction of long-term climatic changes (such as global warming), but it is not a sufficient condition unless the seasonal cycle and long-term changes involve similar climatic processes. To test this possible connection, we compare seasonal cycle amplitude with equilibrium warming under doubled atmospheric carbon dioxide for the models in our data base. A small but positive correlation exists between these two quantities. This result is predicted by a simple conceptual model of the climate system, and it is consistent with other modeling experience, which indicates that the seasonal cycle depends only weakly on climate sensitivity. 相似文献
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Model errors offset by constant and time-variant optimal forcing vector approaches(termed COF and OFV, respectively)are analyzed within the framework of El Nio simulations. Applying the COF and OFV approaches to the well-known Zebiak–Cane model, we re-simulate the 1997 and 2004 El Nio events, both of which were poorly degraded by a certain amount of model error when the initial anomalies were generated by coupling the observed wind forcing to an ocean component. It is found that the Zebiak–Cane model with the COF approach roughly reproduced the 1997 El Nio, but the 2004 El Nio simulated by this approach defied an ENSO classification, i.e., it was hardly distinguishable as CP-El Nio or EP-El Nio. In both El Nio simulations, substituting the COF with the OFV improved the fit between the simulations and observations because the OFV better manages the time-variant errors in the model. Furthermore, the OFV approach effectively corrected the modeled El Nio events even when the observational data(and hence the computational time) were reduced.Such a cost-effective offset of model errors suggests a role for the OFV approach in complicated CGCMs. 相似文献
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数值模式误差对降水四维变分资料同化及预报的影响 总被引：3，自引：1，他引：2
利用一个无量纲的水汽发展方程,针对同化时间窗口内出现和不出现降水两种情况,分析了不同模式误差和初始误差对降水四维变分资料同化预报效果的影响。结果表明,应用四维变分资料同化方法进行降水预报前,应该充分考虑数值模式中的误差,才能得到比较满意的同化及预报结果。假定同化窗口内获得的比湿观测场是准确的,当不存在模式误差时,四维变分资料同化方法可以有效地消除初始场误差,找到比湿真实初始场;而存在模式误差时,四维变分资料同化后的模式初始场会偏离真实的比湿初始场,并且模式误差越大,偏离程度越严重。在一些模式误差情况下,由于模式误差在同化窗口及延伸预报时段的作用不同,进行四维变分资料同化处理后,尽管累积降水量的预报结果在同化时间窗口内优于同化前的预报,而在最终预报时刻反而差于同化前。 相似文献
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在复杂地形条件下嵌套细网格模式的基础上，建立了与球圈模式相嵌套的区域模式系统，对几种不同条件下的嵌套误差进行了比较分析，研究了区域模式嵌套误差的特征分布及时空演变特征。初步分析表明:区域模式嵌套造成的误差在不同区域的分布不同，且不同的物理量在时空的分布也不同；动能场的误差主要在边界区上层的流入区，感热场的误差在边界区上层，水汽的误差在边界区上层的流入区；侧边界输入时间间隔对模式嵌套误差有一定的影响。有限区细网格模式在上层长波误差大于粗网格环圈模式上层误差，在下层短波模拟的误差比粗网格环圈模式的下层误差要小。相速误差对侧边界嵌套误差的影响在下层很严重，嵌套误差的大小与大小模式的网格距之比有关；在大小模式物理参数化过程一致的条件下，无日变化的区域模式其嵌套误差远大于有日变化的区域模式嵌套误差。 相似文献
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Progress in the Development and Application of Climate Ocean
Models and Ocean-Atmosphere Coupled Models in China 总被引：5，自引：3，他引：2
ZHOU Tianjun YU Yongqiang LIU Hailong LI Wei YOU Xiaobao ZHOU Guangqing 《大气科学进展》2007,24(6):1109-1120
A review is presented about the development and application of climate ocean models and oceanatmosphere coupled models developed in China as well as a review of climate variability and climate change studies performed with these models. While the history of model development is briefly reviewed, emphasis has been put on the achievements made in the last five years. Advances in model development are described along with a summary on scientific issues addressed by using these models. The focus of the review is the climate ocean models and the associated coupled models, including both global and regional models, developed at the Institute of Atmospheric Physics, Chinese Academy of Sciences. The progress of either coupled model development made by other institutions or climate modeling using internationally developed models also is reviewed. 相似文献
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误差非线性的增长理论及可预报性研究 总被引：11，自引：9，他引：2
对非线性系统的误差发展方程不作线性化近似,直接用原始的误差发展方程来研究初始误差的发展,提出了误差非线性的增长理论。首先,在相空间中定义一个非线性误差传播算子,初始误差在这个算子的作用下,可以非线性发展成任意时刻的误差;然后,在此基础上,引入了非线性局部Lyapunov指数的概念。由平均非线性局部Lyapunov指数可以得到误差平均相对增长随时间的演变情况;对于一个混沌系统,误差平均相对增长被证明将趋于一个饱和值,利用这个饱和值,混沌系统的可预报期限可以被定量地确定。误差非线性的增长理论可以应用于有限尺度大小初始扰动的可预报性研究,较误差的线性增长理论有明显的优越性。 相似文献
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为讨论不同时间序列模型对电离层垂直总电子含量（VTEC）的预报效果,在平静电离层条件下,采用载波相位平滑伪距法解算单站上空的电离层VTEC值,分别利用自回归积分滑动平均模型（ARIMA）与Holt-Winters指数平滑模型进行逐站建模,通过时长为9 d的样本序列实现3 d预报,并对预报值进行系统评估.结果表明,时间序列模型能够较好地反映预报期内的电离层VTEC变化情况,均方根误差均值不超5 TECU.此外,Holt-Winters乘法模型的预报值偏差最大,加法模型次之,ARIMA模型在11个测站的相对精度都高于Holt-Winters指数平滑模型,且其均方根误差峰值最小,具有最高的预报精度. 相似文献
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This paper investigates the possible sources of errors associated with tropical cyclone (TC) tracks forecasted using the Global/Regional Assimilation and Prediction System (GRAPES). In Part I, it is shown that the model error of GRAPES may be the main cause of poor forecasts of landfalling TCs. Thus, a further examination of the model error is the focus of Part II. Considering model error as a type of forcing, the model error can be represented by the combination of good forecasts and bad forecasts. Results show that there are systematic model errors. The model error of the geopotential height component has periodic features, with a period of 24 h and a global pattern of wavenumber 2 from west to east located between 60°S and 60°N. This periodic model error presents similar features as the atmospheric semidiurnal tide, which reflect signals from tropical diabatic heating, indicating that the parameter errors related to the tropical diabatic heating may be the source of the periodic model error. The above model errors are subtracted from the forecast equation and a series of new forecasts are made. The average forecasting capability using the rectified model is improved compared to simply improving the initial conditions of the original GRAPES model. This confirms the strong impact of the periodic model error on landfalling TC track forecasts. Besides, if the model error used to rectify the model is obtained from an examination of additional TCs, the forecasting capabilities of the corresponding rectified model will be improved. 相似文献
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The Atmospheric Boundary Layer Over Baltic Sea Ice 总被引：4，自引：0，他引：4
A new parametrization for the surface energy balance of urban areas is presented. It is shown that this new method can represent some of the important urban phenomena, such as an urban heat island and the occurrence of a near-neutral nocturnal boundary layer with associated positive turbulent heat fluxes, unlike the traditional method for representing urban areas within operational numerical weather prediction (NWP) models. The basis of the new parametrization is simple and can be applied easily within an operational NWP model. Also, it has no additional computational expense compared to the traditional scheme and is hence applicable for operational forecasting requirements. The results show that the errors for London within the Met Office operational mesoscale model have been significantly reduced since the new scheme was introduced. The bias and root-mean-square (rms) errors have been approximately halved, with the rms error now similar to the model as a whole. The results also show that a seasonal cycle still exists in the model errors, but it is suggested that this may be caused by anthropogenic heat sources that are neglected in the urban scheme.The British Crowns right to retain a non-exclusive royalty-free license in and to any copyright is acknowledged. 相似文献
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The initial value error and the imperfect numerical model are usually considered as error sources of numerical weather prediction (NWP). By using past multi-time observations and model output, this study proposes a method to estimate imperfect numerical model error. This method can be inversely estimated through expressing the model error as a Lagrange interpolation polynomial, while the coefficients of polynomial are determined by past model performance. However, for practical application in the full NWP model, it is necessary to determine the following criteria: (1) the length of past data sufficient for estimation of the model errors, (2) a proper method of estimating the term "model integration with the exact solution" when solving the inverse problem, and (3) the extent to which this scheme is sensitive to the observational errors. In this study, such issues are resolved using a simple linear model, and an advection-diffusion model is applied to discuss the sensitivity of the method to an artificial error source. The results indicate that the forecast errors can be largely reduced using the proposed method if the proper length of past data is chosen. To address the three problems, it is determined that (1) a few data limited by the order of the corrector can be used, (2) trapezoidal approximation can be employed to estimate the "term" in this study; however, a more accurate method should be explored for an operational NWP model, and (3) the correction is sensitive to observational error. 相似文献
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Satellite data obtained over synoptic data-sparse regions such as an ocean contribute toward improving the quality of the initial state of limited-area models. Background error covariances are crucial to the proper distribution of satellite-observed information in variational data assimilation. In the NMC (National Meteorological Center) method, background error covariances are underestimated over data-sparse regions such as an ocean because of small differences between different forecast times. Thus, it is necessary to reconstruct and tune the background error covariances so as to maximize the usefulness of the satellite data for the initial state of limited-area models, especially over an ocean where there is a lack of conventional data. In this study, we attempted to estimate background error covariances so as to provide adequate error statistics for data-sparse regions by using ensemble forecasts of optimal perturbations using bred vectors. The background error covariances estimated by the ensemble method reduced the overestimation of error amplitude obtained by the NMC method. By employing an appropriate horizontal length scale to exclude spurious correlations, the ensemble method produced better results than the NMC method in the assimilation of retrieved satellite data. Because the ensemble method distributes observed information over a limited local area, it would be more useful in the analysis of high-resolution satellite data. Accordingly, the performance of forecast models can be improved over the area where the satellite data are assimilated. 相似文献
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一个ENSO动力-相似误差订正模式及其后报初检验 总被引：5，自引：1，他引：4
为有效利用历史资料中的相似信息,减小模式误差对ENSO这类跨季节-年际尺度预测问题的影响提高动力模式的预测水平.作者利用一种基于统计相似的模式误差订正方法,以国家气候中心简化海气耦合模式为平台建立了相应的动力-相似误差订正(DAEC)模式,并着重探讨了系统相似程度(全相似或部分相似)、误差重估周期以及相似样本个数等因素对预报效果的影响.结果表明,利用该方法可以有效地改善原有模式的预报性能,其中 "全相似" 比 "部分相似" 更能反映海气耦合系统的相似程度,从而对模式误差做出更为准确的估计,使预报误差明显减小.海洋和大气的误差重估周期对结果也有较大影响,在不同相似程度下分别存在着某种最优配置使得预报效果达到最佳.另外,在对相似样本存在状况及影响的研究中则发现在当前资料长度内整体上只存在着有限个相似样本,在此范围内随着样本取样数目的增加DAEC模式的预报性能逐渐提高. 相似文献