共查询到18条相似文献，搜索用时 46 毫秒
1.
本文根据CMAP(The Climate Prediction Center Merged Analysis of Precipitation)观测资料,使用相关系数和均方根误差,对CHFP2(Coupled Historical Forecast Project, phase 2 )的2个模式对东亚夏季降雨的季节预报技巧作出评价。在完美模式的理论框架下,分别使用基于信噪比的潜在相关系数和基于信息熵的潜在可预报性指标,对该区域主要针对夏季降雨的可预报性作出评价。通过最可预报分量分析(PrCA),得到季节降雨的最可预报型。将最可预报型投影到海温场,得到了降水最可预报型对应的海温分布。研究发现:相关系数所反映的预报和观测的线性相关程度总体上是低纬度海洋区域比高纬度陆地区域高,而均方根误差反映的则是在海洋区域降雨预报偏离实际值的程度较陆地区域大,预报水平与目前降雨的季节预报水平相符。潜在可预报性估计表明,潜在可预报率存在空间上的变化,从低纬度向高纬度、从海洋到内陆,呈衰减趋势。同时,信号和噪音的分析表明,信号成分占主导作用,形成了潜在可预报率的空间分布格局,暗示了海洋外强迫的重要作用;中国大陆缺少像海洋区域那样明显的外强迫,因此降水季节预报技巧相比热带海洋区域非常有限。海温投影的分析表明海洋的外强迫是东亚降雨季节预报的重要来源。尽管厄尔尼诺本身的复杂性,它对东亚夏季风的重要影响及其与东亚降雨预报之间的遥相关揭示了它们内在的联系。 相似文献
2.
印度洋偶极子预报技巧在多模式中的对比研究 总被引：1，自引：0，他引：1
本文采用北美多模式集合产品数据，分析了印度洋偶极子指数在不同模式中实际预报技巧和潜在可预报性的差异，并进一步探究其可能的原因。结果表明，印度洋偶极子的有效预报时效在不同模式中差别较大，从2个月到4个月不等。其中东极子海温异常在不同模式中预报技巧的差别较西极子海表面温度异常更明显，表明模式误差和初始误差对东极子海表面温度异常演变的影响更为显著。另外，印度洋偶极子的实际预报技巧和潜在预报技巧存在明显的线性关系，潜在预报技巧高的模式，其实际预报技巧也高。最后，本文诊断、分析了厄尔尼诺对印度洋偶极子预报技巧的影响，发现在厄尔尼诺和印度洋偶极子相关性较高的气候模式中，印度洋偶极子实际预报技巧也较高。 相似文献
3.
POAMA海气耦合模式对2003和2004年南海夏季风预报能力的评估 总被引：5，自引：0，他引：5
运用澳大利亚大气海洋耦合预报模式（Predictive Ocean Atmosphere Model for Australia,POAMA）的输出结果,采用泰勒图与分类统计分析方法,评估了该模式对2003和2004年南海夏季风的爆发和演变进行实时预报的能力。通过对泰勒图的分析发现,随着预报初始时间越来越接近实际的季风爆发时间,模式预报南海夏季风爆发和演变的能力越来越强。当提前1-30d预报南海夏季风时,模式能够很好地预报风场、射出长波辐射OLR（Outgoing Longwave Radiation）和降水场的空间分布,其中对风场的预报最好。通过对季风爆发指数和分类统计的分析,定量分析了模式预报南海夏季风爆发的能力,结果表明该模式对南海夏季风爆发时间有一定的预报能力,其最大预报时限可以提前10-15d左右,这与目前中期预报的上限（2周）是一致的。 相似文献
4.
使用球坐标下1.5 层约化重力浅水模式模拟海洋风生双环流, 结果显示双环流射流存在拉伸模态和收缩模态间的年际变化。以双环流从拉伸模态向收缩模态的转变过程为背景场, 利用条件非线性最优扰动(CNOP)方法, 考察初始误差对双环流变异可预报性的影响, 得到两类初始误差: 全局CNOP型和局部CNOP(LCNOP)型, 两类初始误差对双环流变异的影响几乎相反。通过考察误差发展, 发现在射流从拉伸模态向收缩模态转变过程中, CNOP 型初始误差使射流弯曲程度变大, 并在预报时刻导致涡脱落; 而LCNOP 型初始误差则使射流弯曲程度变小。相比LCNOP, CNOP 型初始误差引起更大预报误差, 导致双环流变异的预报技巧下降更多。两类误差得到较大发展的区域可能存在正压不稳定, 使误差能够不断从背景场吸收能量进而得到快速发展。给出了两类使双环流变异预报技巧下降最大的初始误差, 在实际的数值预报中减少这两种类型的误差, 将有助于提高双环流变异的预报技巧。 相似文献
5.
本文提出一种基于支持向量回归的统计预报方法,通过经验正交分解对原始数据矩阵进行时空分解,提取出空间模态和时间系数。由于海面高度变化具有非线性、大惯性的特点,对时间系数进行小波分析,能有效滤除其中的高频信号,得到表征海面高度变化的低频信号。利用支持向量回归方法对小波分解后的低频信号构建预报模型。最后,进行小波重构,还原时间序列长度,实现未来7天的海面高度预报。通过黑潮附近海域的海面高度预报结果验证,该预报方法的预报效果优于整合滑动平均自回归预报方法。本文通过机器学习的算法实现了海面高度的预报,为海洋预报方法提供了新的思路。 相似文献
6.
大气模式中季节内振荡特征对不同海温强迫场的响应 总被引：2，自引：0，他引：2
利用美国国家大气研究中心 (NCAR)的全球大气模式 (CCM3) ,分别以月平均和周平均海表温度 (SST)为强迫场进行 2个积分试验 (称为 CCMM和 CCMW试验 )。积分结果与观测资料的对比分析发现 ,CCM3模拟大气季节内振荡 (MJO)信号的强度均较观测资料偏弱 ,而其中以CCMW模拟的强度略大而较接近真实。表明 SST强迫场包含更真实的季节内变化信息对提高模拟 MJO强度有作用。 CCMM与 CCMW模拟 MJO活动的时间位相均与观测差别较大 ,直接原因在于 CCM3中降水季节内振荡与 SST变化的相关关系不正确 ,而更根本的问题在于大气模式无法反映资料分析发现的季节内时间尺度的 SST与大气的相互作用。 相似文献
7.
与反任意分布的观测值通过空间和时间插值分析到网格点的方法相比较，利用动力关系分析问题，其优势性十分明显，在一个能提供时间连续和动力耦合的模式预报方程中，有机地结合现在和过去的资料，即众所周知的四维资料同化。从目前经常应用的四维资料同化方法出发，详细分析了它们的特点和今后四维资料同化方法在预报模式中的应用前景。 相似文献
8.
利用全球中期预报模式T63L9,选取2004年6月4日至13日10d作为试验个例进行了集合预报试验,分析了不同集合成员个数对于预报结果的影响。结果表明,集合预报的技巧都明显高于单个控制预报。在集合成员较少时,随集合成员教的增加,集合预报的技巧提高明显,当集合成员数多于11个时,集合预报的效果提高缓慢。在中期预报时段内。集合成员数11为集合预报效果随集合成员教趋于饱和的临界值,如果继续增加成员数.预报效果提高较少,但计算量却大大的增加。本文只是单个试验个例的分析结果。为验证结论的普适性,还需要进行更多的试验。 相似文献
9.
三维斜压台风模式 Ⅱ.预报试验 总被引：1，自引：0，他引：1
一种斜压多重移动套网格台网模式在国家海洋环境预报中心已被应用于海洋环境预报。本文第一部分已描述了模式方程组和数值方法。本文继续概述模式网格、变分调整初始化和预报试验结果。最外粗网格域固定,内部细网格域随台风中心轨迹移动。模式中,粗细网格变量采用双向耦合。平衡方程和方程,理想台风场和变分调整方案被用于台风模式初始化。一种简单而有效的资料同化方法,即用第6h台风报和弱约束变分原理调整初始场,被应用于提高预报结果。最后本文给出预报试验结果。预报误差统计显示本模式对台风路径预报具有相当能力,而且可以提供海面风和气压场较好的预报。本模式已经与海浪模式联结,得到满意的波高预报结果。 相似文献
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11.
Yanjie Cheng Youmin Tang Tongwen Wu Xiaoge Xin Xiangwen Liu Jianglong Li Xiaoyun Liang Qiaoping Li Junchen Yao Jinghui Yan 《海洋学报(英文版)》2022,41(5):99-109
The El Ni?o-Southern Oscillation(ENSO) ensemble prediction skills of the Beijing Climate Center(BCC) climate prediction system version 2(BCC-CPS2) are examined for the period from 1991 to 2018. The upper-limit ENSO predictability of this system is quantified by measuring its “potential” predictability using information-based metrics, whereas the actual prediction skill is evaluated using deterministic and probabilistic skill measures.Results show that:(1) In general, the current operational BCC ... 相似文献
12.
With the observational wind data and the Zebiak-Cane model, the impact of Madden-Julian Oscillation (MJO) as external forcing on El Ni(n)o–Southern Oscillation (ENSO) predictability is studied. The obs... 相似文献
13.
A group of 30 surface drifters, launched over a 4 day period as part of a US Navy exercise in early October 2007, are used to assess the predictability of trajectories in a confined geographic region at the northwestern edge of the Kuroshio north of Taiwan. Model trajectories were computed from archives of hourly hindcast velocities from the US Navy East Asian Seas (EAS16) model with 1/16° horizontal resolution. Three metrics are defined for comparing observed and modeled trajectories. All three metrics indicated that model trajectories separated from observations by roughly 15 km after the first 24 h on average. Because of the unique launch strategy for these drifters, with six repetitions of launches from four locations, the dependence of predictability on both launch time and launch location could be assessed separately. Predictive skill displayed only modest dependence on launch time, likely influenced by the passage of a typhoon near the experiment area a few days prior to the first drifter launch. Launch location was a much more reliable indicator of predictive skill, with trajectories for launches closest to the edge of the Kuroshio typically hardest to predict, and those for launches on the shelf, where currents tended to be weaker, predicted more accurately. Comparisons of skill metric statistics for modeled trajectories from hindcasts with and without tides suggested that tidal currents have only a small impact on predictive skill. The influence of archive time and space resolution was also studied using sets of model trajectories computed from hindcast archives that were systematically subsampled separately in space and time. Coarsening by up to a factor of eight in either space or time had little impact on predictive skill. Further coarsening degraded trajectory predictions, particularly when coarsening in time leads to an archive time step too large to adequately resolve the tides. While accurate trajectory predictions remain challenging for ocean models, skill assessments like the one presented here are important for developing error estimates for users of trajectory forecasts and for gaining new insight into potential sources of model errors. 相似文献
14.
利用1993~2017年海表面高度异常数据集,分析研究了西北太平洋季节内变化(20~120d)的整体分布特征,结果表明空间上季节内信号在20°N附近海域(16°~24°N)最强,时间上在6~8月达到一年中的最大值。在吕宋海峡东侧(123.875°E,20.125°N)季节内信号周期(70d)和传播速度(10.7~12.7cm/s)均大于吕宋海峡西侧(119.625°E, 20.125°N)(60 d, 6.5~7.8cm/s)。在大洋内部(123°~140°E, 18°~24°N)存在准90d的周期信号,传播速度约10.3cm/s。传播路径受黑潮的影响发生改变,由沿纬度西传转向向西北方向传播。第一斜压Rossby波理论对海表面高度季节内变化的周期和传播速度具有很好的解释性。 相似文献
15.
Using observations and numerical simulations, this study examines the intraseasonal variability of the surface zonal current(u ISV) over the equatorial Indian Ocean, highlighting the seasonal and spatial differences, and the causes of the differences. Large-amplitude u ISV occurs in the eastern basin at around 80°–90°E and near the western boundary at 45°–55°E. In the eastern basin, the u ISV is mainly caused by the atmospheric intraseasonal oscillations(ISOs), which explains 91% of the standard... 相似文献
16.
The rapid decrease in Arctic sea ice cover and thickness not only has a linkage with extreme weather in the midlatitudes but also brings more opportunities for Arctic shipping routes and polar resource exploration, both of which motivate us to further understand causes of sea-ice variations and to obtain more accurate estimates of seaice cover in the future. Here, a novel data-driven method, the causal effect networks algorithm, is applied to identify the direct precursors of September sea-ice extent covering the Northern Sea Route and Transpolar Sea Route at different lead times so that statistical models can be constructed for sea-ice prediction. The whole study area was also divided into two parts: the northern region covered by multiyear ice and the southern region covered by seasonal ice. The forecast models of September sea-ice extent in the whole study area(TSIE) and southern region(SSIE) at lead times of 1–4 months can explain over 65% and 79% of the variances, respectively,but the forecast skill of sea-ice extent in the northern region(NSIE) is limited at a lead time of 1 month. At lead times of 1–4 months, local sea-ice concentration and sea-ice thickness have a larger influence on September TSIE and SSIE than other teleconnection factors. When the lead time is more than 4 months, the surface meridional wind anomaly from northern Europe in the preceding autumn or early winter is dominant for September TSIE variations but is comparable to thermodynamic factors for NSIE and SSIE. We suggest that this study provides a complementary approach for predicting regional sea ice and is helpful in evaluating and improving climate models. 相似文献
17.
Using a mesoscale ensemble to predict forecast error and perform targeted observation 总被引：2，自引：0，他引：2
Using NCEP short range ensemble forecast（SREF） system,demonstrated two fundamental on-going evolutions in numerical weather prediction（NWP） are through ensemble methodology.One evolution is the shift from traditional single-value deterministic forecast to flow-dependent（not statistical） probabilistic forecast to address forecast uncertainty.Another is from a one-way observation-prediction system shifting to an interactive two-way observation-prediction system to increase predictability of a weather system.In the first part,how ensemble spread from NCEP SREF predicting ensemble-mean forecast error was evaluated over a period of about a month.The result shows that the current capability of predicting forecast error by the 21-member NCEP SREF has reached to a similar or even higher level than that of current state-of-the-art NWP models in predicting precipitation,e.g.,the spatial correlation between ensemble spread and absolute forecast error has reached 0.5 or higher at 87 h（3.5 d） lead time on average for some meteorological variables.This demonstrates that the current operational ensemble system has already had preliminary capability of predicting the forecast error with usable skill,which is a remarkable achievement as of today.Given the good spread-skill relation,the probability derived from the ensemble was also statistically reliable,which is the most important feature a useful probabilistic forecast should have.The second part of this research tested an ensemble-based interactive targeting（E-BIT） method.Unlike other mathematically-calculated objective approaches,this method is subjective or human interactive based on information from an ensemble of forecasts.A numerical simulation study was performed to eight real atmospheric cases with a 10-member,bred vector-based mesoscale ensemble using the NCEP regional spectral model（RSM,a sub-component of NCEP SREF） to prove the concept of this E-BIT method.The method seems to work most effective for basic atmospheric state variables,moderately effective for convective instabilities and least effective for precipitations.Precipitation is a complex result of many factors and,therefore,a more challenging field to be improved by targeted observation. 相似文献
18.
Long-range empirical forecasts of North Atlantic anomalous conditions are issued, using sea ice concentration anomalies in the same region as predictors. Conditions in the North Atlantic are characterized by anomalies of sea surface temperature, of 850 hPa air temperature and of sea level pressure. Using the Singular Value Decomposition of the cross-covariance matrix between the sea ice field (the predictor) and each of the predictand variables, empirical models are built, and forecasts at lead times from 3 to 18 months are presented. The forecasts of the air temperature anomalies score the highest levels of the skill, while forecasts of the sea level pressure anomalies are the less sucessful ones.
To investigate the sources of the forecast skill, we analyze their spatial patterns. In addition, we investigate the influence of major climatic signals on the forecast skill. In the case of the air temperature anomalies, the spatial pattern of the skill may be connected to El Niño Southern Oscillation (ENSO) influences. The ENSO signature is present in the predictor field, as shown in the composite analysis. The composite pattern indicates a higher (lower) sea ice concentration in the Labrador Sea and the opposite situation in the Greenland–Barents Seas during the warm (cold) phase of ENSO. The forecasts issued under the El Niño conditions show improved skill in the Labrador region, the Iberian Peninsula and south of Greenland for the lead times considered in this paper. For the Great Lakes region the skill increases when the predictor is under the influence of a cold phase. Some features in the spatial structure of the skill of the forecasts issued in the period of the Great Salinity Anomaly present similarities with those found for forecasts made during the cold phase of ENSO. The strength of the dependence on the Great Salinity Anomaly makes it very difficult to determine the influence of the North Atlantic Oscillation. 相似文献
To investigate the sources of the forecast skill, we analyze their spatial patterns. In addition, we investigate the influence of major climatic signals on the forecast skill. In the case of the air temperature anomalies, the spatial pattern of the skill may be connected to El Niño Southern Oscillation (ENSO) influences. The ENSO signature is present in the predictor field, as shown in the composite analysis. The composite pattern indicates a higher (lower) sea ice concentration in the Labrador Sea and the opposite situation in the Greenland–Barents Seas during the warm (cold) phase of ENSO. The forecasts issued under the El Niño conditions show improved skill in the Labrador region, the Iberian Peninsula and south of Greenland for the lead times considered in this paper. For the Great Lakes region the skill increases when the predictor is under the influence of a cold phase. Some features in the spatial structure of the skill of the forecasts issued in the period of the Great Salinity Anomaly present similarities with those found for forecasts made during the cold phase of ENSO. The strength of the dependence on the Great Salinity Anomaly makes it very difficult to determine the influence of the North Atlantic Oscillation. 相似文献