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为检验臭氧卫星资料同化对臭氧分析场和预报场的影响,基于集合平方根滤波(ENSRF)理论,结合通用地球系统模式(CESM),构建了CESM-ENSRF同化预报系统。系统构建过程考虑了卡尔曼滤波同化中的关键问题:利用全场随机扰动对初始场加扰,结合一般协方差膨胀和松弛协方差膨胀方法实现协方差膨胀,使用五阶距离相关函数进行协方差局地化。将构建的系统用于微波临边探测器(MLS)臭氧廓线数据的同化,分析臭氧卫星资料同化对模式预报的影响。结果表明:构建的CESM-ENSRF同化系统有效实现了臭氧资料同化,臭氧卫星资料同化对臭氧分析场和预报场精度有较大改进。 相似文献
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GRAPES集合卡尔曼滤波资料同化系统Ⅰ:系统设计及初步试验 总被引：5，自引：0，他引：5
集合卡尔曼滤波资料同化方法,可以用集合样本统计出随天气形势变化的误差协方差,是当前资料同化领域的研究热点。主要介绍了GRAPES集合卡尔曼滤波资料同化系统的设计以及初步的试验结果。针对集合卡尔曼滤波同化实际观测资料难以实施的问题,采用成批观测同化的顺序同化方法进行多变量的集合卡尔曼滤波同化;为了滤除有限集合数造成的误差相关噪音和缓解求逆矩阵不满秩的问题,在水平和垂直方向都采用了Schur滤波;建立了与GRAPES预报模式的垂直坐标和预报变量一致的模式面集合卡尔曼滤波系统;集合样本的生成考虑了模式变量的空间相关和模式变量之间的相关,通过利用三维变分分析中的控制变量变换得到模式变量扰动场。通过比较GRAPES集合卡尔曼滤波资料同化系统和GRAPES区域三维变分资料同化系统的单点观测资料同化分析结果,对比背景误差相关系数的分布,验证了GRAPES集合卡尔曼滤波系统的正确性。此外,同化区域探空观测资料试验结果表明,GRAPES集合卡尔曼滤波资料同化系统能够得到合理的分析,并且具有实际运行能力。对分析结果进行12h预报表明,GRAPES集合卡尔曼滤波资料同化系统的分析协调性不如三维变分资料同化系统。 相似文献
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为评价静止卫星大气温度廓线产品资料同化对飓风预报的影响,以2018年飓风“迈克尔”为例,选用GOES-16温度廓线产品,开展静止卫星资料同化及其对飓风预报影响的研究。首先,通过评估温度廓线产品精度,选取质量较好的高度层并以统计的各层均方根误差作为观测误差用于同化试验;然后,利用WRF-3DVar系统进行不同稀疏化及不同同化频次的循环同化敏感性试验;最后,利用WRF模式开展24 h数值预报。试验结果表明,在飓风“迈克尔”期间温度廓线在200~1 000 hPa之间的误差在2 K以内,将水平分辨率稀疏化为模式分辨率的6倍且循环同化频次为6 h时同化该资料对模式的初始场有最为合理的改进,从大尺度环境场上看使模式具备更合理的环流形势,能够有效提高对飓风的路径及强度的预报效果,更准确地模拟降水落区及美国佛罗里达州等降水关键区域的雨强。 相似文献
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针对未来1~10 a气候状态的近期气候预测(年代际预测)是当前国际气候领域的研究热点。本文综述了中国科学院大气物理研究所发展的基于耦合气候系统模式的年代际气候预测系统IAP-DecPreS相关的研究进展。IAP-DecPreS系统的核心部分是耦合模式海洋分量初始化方案,“集合最优插值-分析增量更新”(EnOI-IAU)方案,该方案将集合最优插值(EnOI)和增量分析更新(IAU)结合起来,能够同化原始的海洋次表层温度廓线观测资料,对耦合模式进行初始化。系统的年代际回报试验表明,IAP-DecPreS对太平洋年代际振荡和大西洋多年代际变率的预测技巧与耦合模式比较计划第五阶段(CMIP5)技巧较高的模式相当。IAP-DecPreS系统被广泛应用于气候预测相关研究,包括火山气溶胶对年代际预测技巧的影响,全场同化和异常场同化两种不同的初始化方法对ENSO、印度洋偶极子模态和印度洋洋盆模态等的预测技巧的影响。最后,结合国际发展态势,对未来IAP-DecPreS的发展进行了讨论。 相似文献
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印度洋偶极子（IOD）是热带印度洋年际变率主导模态之一,对于区域乃至全球气候有重要影响。准确预报IOD对于短期气候预测具有重要意义。中国科学院大气物理研究所最近建立了近期气候预测系统IAP-DecPreS,其初始化方案采用“集合最优插值—分析增量更新”（EnOI-IAU）方案,能够同化观测的海洋次表层温度廓线资料。本文分析了IAP-DecPreS季节回报试验对IOD的回报技巧,重点比较了全场同化和异常场同化两种初始化策略下预测系统对IOD的回报技巧。分析表明,8月起报秋季IOD,无论从确定性预报还是概率性预报的角度,基于全场同化的回报试验技巧均高于异常场同化的回报试验。对于5月起报的秋季IOD,基于两种初始化策略的回报试验技巧相当。研究发现,全场同化策略相对于异常场的优势主要源于它提高了对伴随ENSO发生的IOD的预报技巧。ENSO遥强迫触发的热带东印度洋“风—蒸发—SST”正反馈过程是IOD发展和维持的关键。采用全场同化策略的回报结果能够更好地模拟出IOD发展过程中ENSO遥强迫产生的异常降水场和异常风场的空间分布特征;而采用异常场同化策略,模拟的异常降水场和风场偏差较大。导致两种初始化策略预测结果技巧差异的主要原因是,全场同化能够减小模式对热带印度洋气候平均态降水固有的模拟偏差,从而提升了热带印度洋对ENSO遥强迫响应的模拟能力。而异常场同化由于在同化过程中保持了模式固有的气候平均态,因此模拟的热带印度洋对ENSO遥强迫的响应存在与模式自由积分类似的模拟偏差。 相似文献
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利用美国普林斯顿大学海洋模式 (POM )对 1995年 5月南海AXBT海洋观测资料和MISST卫星观测的海面温度进行模式四维同化分析研究。POM模式同化处理使用最优插值分析与逼近方法 ,从模式积分到第 4年开始 ,使用COADS气候平均风应力场、净热通量场强迫海洋 ,从第 5年 5月开始加入 1995年 5月的MISST和AXBT资料同化积分 30d ,然后对同化结果进行分析。结果表明 ,资料同化可以改进模式对温度场的预报 ,也可改进模式对海流的模拟。分析结果还显示 ,1995年 5月南海浅层有暖涡和冷涡形成 相似文献
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基于WRF预报模式、WRFDA Hybrid集合变分同化系统和ETKF方法,构建了面向城市气象观测网数据的快速更新混合同化系统。针对北京地区地基微波辐射计和风廓线雷达组网观测资料数据同化,开展了静态背景误差调整因子(特征长度尺度因子和方差因子)、局地化距离和集合权重系数4个重要参数敏感性试验研究。试验结果表明：当温度、相对湿度、u风和v风的特征长度尺度因子和方差因子分别调整为0.7/1.0、1.0/1.0、0.7/1.0和0.7/1.0,局地化距离和集合权重系数分别调整为11.2 km和0.5时,快速更新混合同化系统的分析场均方根误差最小。为对比三种常用同化方案,开展了默认参数混合同化、最优参数混合同化、三维变分同化对比试验,试验结果表明：在针对北京地区地基微波辐射计和风廓线雷达组网观测资料的快速更新同化预报试验中,混合同化方案表现优于三维变分,同时相对于默认参数混合同化方案,最优参数混合同化方案的风场、温度及湿度的分析场和预报场得到了进一步改善：风温湿的分析场均方根误差分别最大降低了13%、19%和5%,12～24 h预报场的均方根误差分别最大降低了2%、12%和5%。 相似文献
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基于WRF模式构建了Hybrid En SRF-En3DVar同化系统,该系统使用En SRF方案直接更新集合扰动。利用构建的同化系统针对台风"桑美"分别进行集合协方差权重敏感性试验和同化雷达不同观测资料的敏感性试验。集合协方差权重敏感性试验发现:当集合协方差权重分别为0.25、0.5和0.75时,同化效果优于3DVar试验,其中0.75的集合协方差权重试验得到了分析场的最优估计;当集合协方差权重为1.0时,分析场最差。同化雷达不同观测资料的敏感性试验表明,联合同化雷达径向风及反射率能有效改善大气湿度场和风场,但对风场的改善效果不如仅同化雷达径向风好。将En SRF集合扰动更新方案与扰动观测方案综合分析发现,扰动观测方案集合离散度较小,计算代价大,En SRF方案优于扰动观测方案。 相似文献
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针对GRAPES(Global/Regional Assimilation and Prediction System)模式三维变分系统高层背景场温湿廓线外推方案的局限性,提出以气候垂直廓线重新构造高层温湿垂直结构,以减小外推方案的偏差。首先采用一维变分同化系统,展开模拟实验:分析目前模式中使用的外推方案误差及其对反演结果的影响,利用高层大气气候廓线构造垂直结构并分析同化偏差。最后,运用GRAPES全球分析预报系统进行同化实验并分析改进程度。结果显示:模拟研究表明采用高层背景场温湿廓线外推方案与实际观测相比最大偏差在1 h Pa附近可达数十度以上,不仅影响平流层,而且对对流层也有影响;用气候温度数据修正GRAPES高层温度数据,可以减少50%以上的偏差,证明了用气候值高层数据优化现行GRAPES模式中同化系统高层插值方案的可行性。全球GRAPES三维变分同化试验结果显示,改进方案不仅显著的改善平流层分析质量,对对流层中高层也有改进。 相似文献
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Preliminary evaluations of FGOALS-g2 for decadal predictions 总被引：3，自引：0，他引：3
王斌 刘咪咪 俞永强 李立娟 林鹏飞 董理 刘利 刘骥平 黄文誉 徐世明 申思 普业 薛巍 夏坤 王勇 孙文奇 胡宁 黄小猛 刘海龙 郑伟鹏 吴波 周天军 杨广文 《大气科学进展》2013,30(3):674-683
The Flexible Global Ocean-Atmosphere-Land System model, Grid-point Version 2 (FGOALS-g2) for decadal predictions, is evaluated preliminarily, based on sets of ensemble 10-year hindcasts that it has produced. The results show that the hindcasts were more accurate in decadal variability of SST and surface air temperature (SAT), particularly in that of Nin o3.4 SST and China regional SAT, than the second sample of the historical runs for 20th-century climate (the control) by the same model. Both the control and the hindcasts represented the global warming well using the same external forcings, but the control overestimated the warming. The hindcasts produced the warming closer to the observations. Performance of FGOALS-g2 in hindcasts benefits from more realistic initial conditions provided by the initialization run and a smaller model bias resulting from the use of a dynamic bias correction scheme newly developed in this study. The initialization consists of a 61-year nudging-based assimilation cycle, which follows on the control run on 01 January 1945 with the incorporation of observation data of upper-ocean temperature and salinity at each integration step in the ocean component model, the LASG IAP Climate System Ocean Model, Version 2 (LICOM2). The dynamic bias correction is implemented at each step of LICOM2 during the hindcasts to reduce the systematic biases existing in upper-ocean temperature and salinity by incorporating multi-year monthly mean increments produced in the assimilation cycle. The effectiveness of the assimilation cycle and the role of the correction scheme were assessed prior to the hindcasts. 相似文献
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Argo大洋观测资料的同化及其在短期气候预测和海洋分析中的应用 总被引：3，自引：0，他引：3
国际Argo(Array for Real-time Geostrophic Oceanography)计划的实施,提供了前所未有的全球深海大洋0～2000 m水深范围内的海水温度和盐度观测资料,在大气和海洋科研业务中应用这一全新的资料,是深入认识大气和海洋变异、提高我国气候预测、海洋监测分析和预报能力的一个关键所在.通过开发非线性温—盐协调同化方案和利用同化高度计资料来调整模式的温度和盐度场,建立了可同化包括Argo等多种海洋观测资料的全球海洋资料变分同化系统,提高了对全球海洋的监测分析能力.实现了海洋资料同化系统与全球海气耦合模式的耦合,显著提高了短期气候预测水平.利用Argo资料改进了海洋动力模式中的物理过程参数化方案,有效提高了海洋模式对真实大洋的模拟能力和对厄尔尼诺/拉尼娜的预测能力.开发了利用Argo浮标漂流轨迹推算全球海洋表层和中层流的方法,提高了推算的全球表层流、中层流资料质量,有效弥补了洋流观测的匮乏. 相似文献
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A New Global Four-Dimensional Variational Ocean Data
Assimilation System and Its Application 总被引：1，自引：0，他引：1
A four-dimensional variational data assimilation （4DVar） system of the LASG/IAP Climate Ocean Model, version 1.0 （LICOM1.0）, named LICOM-3DVM, has been developed using the three-dimensional variational data assimilation of mapped observation （3DVM）, a 4DVar method newly proposed in the past two years. Two experiments with 12-year model integrations were designed to validate it. One is the assimilation run, called ASSM, which incorporated the analyzed weekly sea surface temperature （SST） fields from Reynolds and Smith （OISST） between 1990 and 2001 once a week by the LICOM-3DVM. The other is the control run without any assimilation, named CTL. ASSM shows that the simulated temperatures of the upper ocean （above 50 meters）, especially the SST of equatorial Pacific, coincide with the Tropic Atmosphere Ocean （TAO） mooring data, the World Ocean Atlas 2001 （WOA01） data and the Met Office Hadley Centre＇s sea ice and sea surface temperature （HadISST） data. It decreased the cold bias existing in CTL in the eastern Pacific and produced a Nifio index that agrees with observation well. The validation results suggest that the LICOM-3DVM is able to effectively adjust the model results of the ocean temperature, although it＇s hard to correct the subsurface results and it even makes them worse in some areas due to the incorporation of only surface data. Future development of the LICOM-3DVM is to include subsurface in situ observations and satellite observations to further improve model simulations. 相似文献
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经过近60年的发展,我国短期气候预测技术和方法也有了长足进步。近年来,一些新的预报技术和机理认识不断应用于短期气候预测业务。ARGO海洋观测资料的使用大大提高了业务模式的预测技巧,新一代气候预测模式系统已经投入准业务化运行,研发了多种模式降尺度释用技术,多模式气候预测产品解释应用集成系统(MODES)和动力-统计结合的季节预测系统(FODAS)逐渐应用于业务中,大气季节内振荡(MJO)逐步在延伸期预报中得到应用。近年来,对全球海洋、北极海冰、欧亚积雪、南半球环流系统对东亚季风影响的新认识也不断引入到短期气候预测业务中。这些新技术和新认识的应用极大提高了我国短期气候预测的业务能力。 相似文献
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The development and application of a regional ocean data assimilation system are among the aims of the Global Ocean Data Assimilation Experiment. The ocean data assimilation system in the regions including the Indian and West Pacific oceans is an endeavor motivated by this goal. In this study, we describe the system in detail. Moreover, the reanalysis in the joint area of Asia, the Indian Ocean, and the western Pacific Ocean(hereafter AIPOcean) constructed using multi-year model integration with data assimilation is used to test the performance of this system. The ocean model is an eddy-resolving,hybrid coordinate ocean model. Various types of observations including in-situ temperature and salinity profiles(mechanical bathythermograph, expendable bathythermograph, Array for Real-time Geostrophic Oceanography, Tropical Atmosphere Ocean Array, conductivity–temperature–depth, station data), remotely-sensed sea surface temperature, and altimetry sea level anomalies, are assimilated into the reanalysis via the ensemble optimal interpolation method. An ensemble of model states sampled from a long-term integration is allowed to change with season, rather than remaining stationary. The estimated background error covariance matrix may reasonably reflect the seasonality and anisotropy. We evaluate the performance of AIPOcean during the period 1993–2006 by comparisons with independent observations, and some reanalysis products. We show that AIPOcean reduces the errors of subsurface temperature and salinity, and reproduces mesoscale eddies. In contrast to ECCO and SODA products, AIPOcean captures the interannual variability and linear trend of sea level anomalies very well. AIPOcean also shows a good consistency with tide gauges. 相似文献
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The Argo(Array for Real-time Geostrophic Oceanography) data from 1998 to 2003 were used in the Beijing Climate Center-Global Ocean Data Assimilation System(BCC-GODAS). The results show that the utilization of Argo global ocean data in BCC-GODAS brings about remarkable improvements in assimilation effects. The assimilated sea surface temperature(SST) of BCC-GODAS can well represent the climatological states of observational data. Comparison experiments based on a global coupled atmosphere-ocean general circulation model(AOCGM) were conducted for exploring the roles of ocean data assimilation system with or without Argo data in improving the climate predictability of rainfall in boreal summer. Firstly, the global ocean data assimilation system BCC-GODAS was used to obtain ocean assimilation data under the conditions with or without Argo data. Then, the global coupled atmosphere-ocean general circulation model(AOCGM) was utilized to do hindcast experiments with the two sets of the assimilation data as initial oceanic fields. The simulated results demonstrate that the seasonal predictability of rainfall in boreal summer, particularly in China, increases greatly when initial oceanic conditions with Argo data are utilized. The distribution of summer rainfall in China hindcast by the AOGCM under the condition when Argo data are used is more in accordance with observation than that when no Agro data are used. The area of positive correlation between hindcast and observation enlarges and the hindcast skill of rainfall over China in summer improves significantly when Argo data are used. 相似文献
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HAN Guijun LI Wei ZHANG Xuefeng LI Dong HE Zhongjie WANG Xidong WU Xinrong YU Ting MA Jirui 《大气科学进展》2011,28(3):682-690
A regional ocean reanalysis system for the coastal waters of China and adjacent seas has been developed by the National Marine Data and Information Service(NMDIS).It produces a dataset package called CORA (China ocean reanalysis).The regional ocean model used is based on the Princeton Ocean Model with a generalized coordinate system(POMgcs).The model is parallelized by NMDIS with the addition of the wave breaking and tidal mixing processes into model parameterizations.Data assimilation is a sequential three-dimensional variational(3D-Var) scheme implemented within a multigrid framework.Observations include satellite remote sensing sea surface temperature(SST),altimetry sea level anomaly(SLA),and temperature/salinity profiles.The reanalysis fields of sea surface height,temperature,salinity,and currents begin with January 1986 and are currently updated every year. Error statistics and error distributions of temperature,salinity and currents are presented as a primary evaluation of the reanalysis fields using sea level data from tidal gauges,temperature profiles,as well as the trajectories of Argo floats.Some case studies offer the opportunity to verify the evolution of certain local circulations.These evaluations show that the reanalysis data produced provide a good representation of the ocean processes and phenomena in the coastal waters of China and adjacent seas. 相似文献
18.
You-Soon Chang Shaoqing Zhang Anthony Rosati Thomas L. Delworth William F. Stern 《Climate Dynamics》2013,40(3-4):775-803
The Geophysical Fluid Dynamics Laboratory has developed an ensemble coupled data assimilation (ECDA) system based on the fully coupled climate model, CM2.1, in order to provide reanalyzed coupled initial conditions that are balanced with the climate prediction model. Here, we conduct a comprehensive assessment for the oceanic variability from the latest version of the ECDA analyzed for 51 years, 1960–2010. Meridional oceanic heat transport, net ocean surface heat flux, wind stress, sea surface height, top 300 m heat content, tropical temperature, salinity and currents are compared with various in situ observations and reanalyses by employing similar configurations with the assessment of the NCEP’s climate forecast system reanalysis (Xue et al. in Clim Dyn 37(11):2511–2539, 2011). Results show that the ECDA agrees well with observations in both climatology and variability for 51 years. For the simulation of the Tropical Atlantic Ocean and global salinity variability, the ECDA shows a good performance compared to existing reanalyses. The ECDA also shows no significant drift in the deep ocean temperature and salinity. While systematic model biases are mostly corrected with the coupled data assimilation, some biases (e.g., strong trade winds, weak westerly winds and warm SST in the southern oceans, subsurface temperature and salinity biases along the equatorial western Pacific boundary, overestimating the mixed layer depth around the subpolar Atlantic and high-latitude southern oceans in the winter seasons) are not completely eliminated. Mean biases such as strong South Equatorial Current, weak Equatorial Under Current, and weak Atlantic overturning transport are generated during the assimilation procedure, but their variabilities are well simulated. In terms of climate variability, the ECDA provides good simulations of the dominant oceanic signals associated with El Nino and Southern Oscillation, Indian Ocean Dipole, Pacific Decadal Oscillation, and Atlantic Meridional Overturning Circulation during the whole analyzed period, 1960–2010. 相似文献
19.
Towards quantifying uncertainty in transient climate change 总被引：2，自引：3，他引：2
Matthew Collins Ben B. B. Booth Glen R. Harris James M. Murphy David M. H. Sexton Mark J. Webb 《Climate Dynamics》2006,27(2-3):127-147
Ensembles of coupled atmosphere–ocean global circulation model simulations are required to make probabilistic predictions of future climate change. “Perturbed physics” ensembles provide a new approach in which modelling uncertainties are sampled systematically by perturbing uncertain parameters. The aim is to provide a basis for probabilistic predictions in which the impact of prior assumptions and observational constraints can be clearly distinguished. Here we report on the first perturbed physics coupled atmosphere–ocean model ensemble in which poorly constrained atmosphere, land and sea-ice component parameters are varied in the third version of the Hadley Centre model (the variation of ocean parameters will be the subject of future study). Flux adjustments are employed, both to reduce regional sea surface temperature (SST) and salinity biases and also to admit the use of combinations of model parameter values which give non-zero values for the global radiation balance. This improves the extent to which the ensemble provides a credible basis for the quantification of uncertainties in climate change, especially at a regional level. However, this particular implementation of flux-adjustments leads to a weakening of the Atlantic overturning circulation, resulting in the development of biases in SST and sea ice in the North Atlantic and Arctic Oceans. Nevertheless, model versions are produced which are of similar quality to the unperturbed and un-flux-adjusted version. The ensemble is used to simulate pre-industrial conditions and a simple scenario of a 1% per year compounded increase in CO2. The range of transient climate response (the 20 year averaged global warming at the time of CO2 doubling) is 1.5–2.6°C, similar to that found in multi-model studies. Measures of global and large scale climate change from the coupled models show simple relationships with associated measures computed from atmosphere-mixed-layer-ocean climate change experiments, suggesting that recent advances in computing the probability density function of climate change under equilibrium conditions using the perturbed physics approach may be extended to the transient case. 相似文献
20.
海洋环流对全球增暖趋势的调制：基于FGOALS-s2的数值模拟研究 总被引：1，自引：0，他引：1
在工业革命以来全球长期增暖趋势背景下,全球平均表面气温还同时表现出年代际变化特征,二者叠加在一起使得全球平均气温在某些年份增暖相对停滞(如1999～2008年)或者增暖相对较快(如1980～1998年).利用中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室(LASG)发展的耦合气候模式FGOALS-s2历史气候和典型路径浓度(RCPs)模拟试验结果研究了可能造成全球增暖的年代际停滞及加速现象的原因,特别是海洋环流对全球变暖趋势的调制作用.该模式模拟的全球平均气温与观测类似,即在长期增暖趋势之上,还叠加了显著的年代际变化.对全球平均能量收支分析表明,模拟的气温年代际变化与大气顶净辐射通量无关,意味着年代际表面气温变化可能与能量在气候系统内部的重新分配有关.通过对全球增暖加速和停滞时期大气和海洋环流变化的合成分析及回归分析,发现全球表面气温与大部分海区海表温度(SST)均表现出几乎一致的变化特征.在增暖停滞时期,SST降低,更多热量进入海洋次表层和深层,使其温度增加;而在增暖加速时期,更多热量停留在表层,使得大部分海区SST显著增加,次表层海水和深海相对冷却.进一步分析表明,热带太平洋表层和次表层海温年代际变化主要是由于副热带—热带经圈环流(STC)的年代际变化所致,然后热带太平洋海温异常可以通过风应力和热通量强迫作用引起印度洋、大西洋海温的年代际变化.在此过程中,海洋环流变化起到了重要作用,例如印度尼西亚贯穿流(ITF)年代际异常对南印度洋次表层海温变化起到关键作用,而大西洋经圈翻转环流(AMOC)则能直接影响到北大西洋深层海温变化. 相似文献