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1.
本研究发展了一个全球海洋资料同化系统ZFL_GODAS。该系统是一个短期气候数值预测业务系统的子系统,为短期气候预测海气耦合模式提供全球海洋初始场。系统能够同化的观测资料包括卫星高度计资料、卫星海表温度(SST)资料,以及Argo、XBT、TAO等各种不同来源的现场温盐廓线资料。系统使用的海洋模式为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开发的气候系统海洋模式LICOM1.0,同化方案为集合最优插值(EnOI)方案。系统使用一个由海洋模式自由积分得到的静态样本来估计背景场误差协方差。这样的基于集合样本的背景场误差协方差具有多变量协变、各向异性的特征,且能反映海洋物理过程固有的空间尺度特征。针对EnOI同化程序的特点,开发了一套特色鲜明、负载均衡、高效的并行化同化程序。本文通过与不同类型观测资料的比较,对同化系统的性能进行了评估。通过比较海表温度和海面高度的年际变率,海表温度异常随时间的变化,SST、海面高度异常(SLA)以及次表层温盐预报产品的均方根误差,5年平均温度偏差廓线、平均盐度廓线、平均纬向流速廓线等发现:系统工作正常、同化效果较好;经过同化以后,各变量都更加接近观测,误差更小,与观测场的相关性更好,可以为短期气候预测系统提供较好的海洋初始场,也可以为物理海洋学的研究提供有效的再分析资料。 相似文献
2.
介绍了从全球电信系统(GTS)上获得的海洋温度、盐度观测资料在中国国家气候中心(BCC)新一代海洋同化系统中的应用情况。通过资料的质量控制判断温、盐观测的重复记录、观测深度、地形、极端值、气候变率、层结、空间差异,有效地过滤了错误的或不可靠的观测信息。质量控制后,将温、盐观测资料加入同化系统,有效地改进了模块化全球海洋环流模式MOM4中的全球热带、副热带海洋,尤其是太平洋地区的多年平均海表温度、盐度场分布特征;此外,同化温、盐资料对南北半球中纬度地区的海表温度分布特征也有明显的改进。对比同化前后的均方根误差(RMSE)发现,同化后大部分海区,尤其是热带海洋的海表温度/盐度的均方根误差明显降低,降幅通常在0.1—1.0℃/psu,模拟与观测的海表温、盐分布特征也更为接近。进一步分析指出,同化明显地改善了模式对Nino3、Nino4区海温时间演变特征的模拟,同化后的Nino3海温与最优插值海表温度的差异减小,但其通常在上半年改进较多(差值绝对值多在0.5℃左右),而在下半年则改进较少(差值绝对值常达1℃左右);Nino4区的海温特征则改进明显,其与最优插值海表温度的差值绝对值通常都控制在0.5℃以下。 相似文献
3.
通过同化系统将观测资料与海洋数值模式融合得到的海洋再分析产品为海洋科学研究提供了重要的资料基础.本文采用WOA,SODA,AVISO和GLORS四种数据资料与我国自主研发的中国全球海洋预报系统(CGOFS)的气候态结果进行了对比,结果表明:CGOFS和SODA的全球海表面温度与WOA的均方根误差分别为0.51和0.43℃.CGOFS和SODA的海表面盐度与WOA的均方根误差分别为0.48和0.40 PSU;海流方面,CGOFS能较好的刻画主要大洋环流分布及赤道潜流的垂向结构;CGOFS的全球海表面高度异常与AVISO的均方根误差为0.018m;多年月平均海冰外缘线覆盖面积介于SODA和GLORS之间,海冰体积的生消规律与SODA和GLORS一致.总体来看,CGOFS全球高分辨率海洋再分析产品的气候态结果与国际同类产品基本一致,可为提升我国海洋综合科技实力提供可靠的资料保障. 相似文献
4.
参照Griffies et al.(2009)提出的海洋—海冰耦合模式参考试验(Coordinated Ocean-ice Reference Experiments,COREs),设计了一个800年积分的数值试验,对一个质量严格守恒的压力坐标海洋环流模式(Pressure Coordinate Ocean Model,PCOM1.0)的基本模拟性能进行了评估,并与观测资料和再分析资料进行了对比。结果表明,PCOM1.0模拟的温盐场和基本流场与COREs模式的模拟水平基本接近。其中,模拟的大西洋经向翻转流在45°N附近达到18 Sv(1 Sv=106 m3 s-1),与观测估计值接近;对海表面温度的模拟误差主要集中在北太平洋黑潮区和北大西洋湾流区等中高纬度急流区;模拟的热带太平洋温跃层过于深厚;模拟的经德雷克海峡的体积输送达130 Sv,比大部分COREs模式及再分析资料都更接近于观测估计值。 相似文献
5.
GRAPES全球三维变分同化中卫星微波温度计亮温的背景误差及在质量控制中的应用 总被引：2，自引：0，他引：2
模式变量背景误差在观测空间的投影,也即观测变量的背景误差包含了变分同化系统的重要信息,其在诊断和分析变分同化系统中资料的影响等方面具有重要作用,特别是在背景场检查质量控制中。在GRAPES全球三维变分同化(3DVar)系统中仅给定了控制变量的背景误差,并未直接给定观测变量的背景误差。为了能够对GRAPES全球3DVar进行全面的诊断和分析,改进卫星微波温度计资料的质量控制,推导出GRAPES全球3DVar同化系统控制变量随机扰动方法估计观测变量的背景误差的公式,为分析和改进GRAPES全球3DVar提供了一个有力工具,并进而估计了AMSU-A亮温的背景误差,分析了AMSU-A不同通道亮温的背景误差特征,将其应用于GRAPES全球3DVar的AMSU-A亮温的背景场检查质量控制中。结果表明,控制变量随机扰动方法估计的GRAPES全球3DVar同化系统AMSU-A亮温的背景误差正确合理。同化循环预报试验结果表明,亮温的背景误差在背景场检查中的应用显著提高了GRAPES全球3DVar同化的亮温资料的数量,显著提高了GRAPES南半球对流层中高层位势高度场的预报技巧。在GRAPES全球3DVar同化系统中推导和实现的控制变量扰动方法为诊断和分析GRAPES全球3DVar观测资料同化效果提供了有力工具。 相似文献
6.
为了更加有效地同化地面自动气象站观测资料,针对模式地形与观测站地形存在的高度差异对同化效果的影响,提出了相应的解决方案。在同化系统的位温和露点观测误差中分别引入位温和露点地形代表性误差,在WRF模式中应用集合均方根滤波方法（EnSRF）同化地面自动气象站观测资料,并对2016年一次京津冀暴雨个例进行数值试验。研究结果表明,同化地面资料后,同化阶段的均方根误差、预报阶段的降水TS评分和前13个时次各要素预报均有整体改进。在观测误差中引入地形代表性误差与引入前相比,风场均方根误差得到整体改进;位温和露点的均方根误差在前期表现并不稳定,在后期有所改进;预报阶段前24 h累计降水与后24 h累计降水TS评分在整体上均有所提高。新方案能够减少高度差异对同化效果的影响。 相似文献
7.
云分辨尺度下一种综合调整水物质含量的闪电资料同化方法 总被引：3，自引：0，他引：3
在直接调整水汽含量（称为F12）和直接调整冰相粒子浓度（称为Q14）两种闪电资料同化方法的基础上,提出了一种综合调整冰相粒子浓度和水汽含量（称为C17）的闪电资料同化方法,选取一次具有完整闪电观测资料（云闪加地闪）的飑线过程,利用WRF在云分辨尺度进行数值模拟,详细比较了3种闪电资料同化方法的模拟结果。与不进行闪电资料同化的控制试验相比,闪电资料同化试验明显改进了模式对流活动的模拟能力,但是不同同化方法有所差异。在同化时段内,F12方法中回波强度较小,形成大范围层云区,回波中心比实测偏向下游;Q14方法回波强度和落区同实测最为接近,但是对层云区的模拟无明显改进;C17方法综合了F12和Q14方法的优势,与F12方法相比,回波强度增大,落区更加接近实测,层云区面积扩大。同化结束后,F12方法冷池有所增强,雨区向东北方向延伸,但是强度较弱,形成大范围的弱降水区,同化正面效果保持最久;Q14方法低层大气偏干,地表冷池偏强,对流系统迅速移动并衰减,降水区域比实测偏南,同化正面效果消失较快;C17方法冷池范围和强度与实际观测最为接近,降水较F12方法增强,模拟出的飑线形态得到调整,模拟出了实测中的另一降水中心,同化正面效果保持时间延长。 相似文献
8.
基于集合平方根滤波方法(En SRF)同化方法和NOAH陆面模式的WRF-En SRF陆面同化系统,同化了江苏省70个自动站资料进行试验,研究加入不同的同化资料(地表温度、10 cm土壤温度、20 cm土壤温度)及初始扰动强度的大小对陆面数据同化系统性能的影响,以及对不同区域(降水大值区和降水小值区)的分析场进行效果对比,并且检验了同化系统在一次典型的梅雨锋暴雨的同化效果,证明了这个系统的有效性和可行性。对于资料选取试验,比较全场平均的同化时刻分析场模拟观测相对真实观测的均方根误差可以得到:同化地表温度资料并且初始扰动强度1 K的时候同化效果最理想。对于选定的降水大值区和降水小值区来讲,降水大值区的土壤温度和土壤湿度分析场更加接近于真实场。运用于一次梅雨锋暴雨的同化实验,对于最后一个同化时次的分析场作为背景场做集合预报,最终证明预报结果是有效的。土壤温度、土壤湿度、地表温度和近地面风场的预报结果都较用NCEP再分析资料直接做预报作为控制试验的结果有不同程度的改进。这说明该系统应用于实际同化中的性能较为良好,可以应用于实际土壤湿度与温度的预报。 相似文献
9.
上海组网风廓线雷达数据质量评估 总被引：4，自引：3，他引：1
利用2014年6月美国国家环境预报中心(NCEP)的全球模式分析资料,对上海及周边地区组网的七部边界层风廓线雷达的水平测风数据进行了初步分析和比较。由于NCEP全球模式分析资料并未使用上海13:15加密观测探空秒间隔数据,首先用该数据对NCEP分析资料的准确性和代表性进行了检验。结果表明,两者平均偏差与均方根误差均较小,故认为NCEP分析资料可用于客观检验上海及周边地区组网的七部边界层风廓线雷达的水平测风数据。对比分析风廓线雷达与NCEP分析资料表明总体上,风廓线雷达与NCEP分析资料的平均风场风速偏差为-0.14 m·s~(-1),均方根误差为2.72 m·s~(-1),风向偏差为-4.28°。上海组网风廓线雷达测风资料质量与探空观测水平接近,有较高的可用性。 相似文献
10.
基于一维变分算法的地基微波辐射计遥感大气温湿廓线研究 总被引：3，自引：1，他引：2
为研究地基微波辐射计遥感温、湿度廓线的一维变分算法的反演能力,用北京地区2010—2011年00和12时(世界时)的多通道地基微波辐射计亮温资料进行试验。首先,利用同时次的地面观测资料、红外亮温(由地基微波辐射计自带红外传感器测得)及探空观测数据,给出提取无云样本的方案,得到432个无云样本;再以辐射传输模式计算得到的模拟亮温为参考,对无云条件下的观测亮温进行质量控制;然后利用探空数据进行模拟试验,结果发现,一维变分算法对3 km以下的温度廓线有较大调整。使反演结果更加接近探空,而对湿度廓线在0—10 km都有不同程度的优化;最后利用一维变分算法对地基微波辐射计观测亮温进行大气温湿廓线反演,将结果与探空对比可以看出,温度廓线的均方根误差小于2.9 K,绝对湿度的均方根误差小于0.47 g/m~3;进一步与地基微波辐射计自带神经网络的反演结果比较表明,一维变分的反演结果更接近实际大气。 相似文献
11.
在51年(1958-2008)西北太平洋区域海洋再分析CORA1.0产品的基础上,改进了模式配置和同化方法,研制了2009-18年的CORA产品并对其进行以下检验:(1)温盐和海表高度异常均方根误差分布检验;(2)35°N处温度断面分布检验;(3)再分析流场和表漂浮标轨迹对比检验.结果显示,2009-18年的CORA产品可以再现海洋要素长时间序列,时空多尺度的变化特征,为研究特征海洋现象和过程提供背景信息. 相似文献
12.
Wei Zhou Mengyan Chen Wei Zhuang Fanghua Xu Fei Zheng Tongwen Wu Xin Wang 《大气科学进展》2016,33(2):208-220
The second-generation Global Ocean Data Assimilation System of the Beijing Climate Center(BCC_GODAS2.0) has been run daily in a pre-operational mode.It spans the period 1990 to the present day.The goal of this paper is to introduce the main components and to evaluate BCC_GODAS2.0 for the user community.BCC_GODAS2.0 consists of an observational data preprocess,ocean data quality control system,a three-dimensional variational(3DVAR) data assimilation,and global ocean circulation model[Modular Ocean Model 4(MOM4)].MOM4 is driven by six-hourly fluxes from the National Centers for Environmental Prediction.Satellite altimetry data,SST,and in-situ temperature and salinity data are assimilated in real time.The monthly results from the BCC_GODAS2.0 reanalysis are compared and assessed with observations for 1990-2011.The climatology of the mixed layer depth of BCC-GODAS2.0 is generally in agreement with that of World Ocean Atlas 2001.The modeled sea level variations in the tropical Pacific are consistent with observations from satellite altimetry on interannual to decadal time scales.Performances in predicting variations in the SST using BCC_GODAS2.0 are evaluated.The standard deviation of the SST in BCC-GODAS2.0 agrees well with observations in the tropical Pacific.BCC-GODAS2.0 is able to capture the main features of E1 Nino Modoki I and Modoki Ⅱ,which have different impacts on rainfall in southern China.In addition,the relationships between the Indian Ocean and the two types of E1 Nino Modoki are also reproduced. 相似文献
13.
New diagnostics of the Madden–Julian oscillation (MJO) cycle in ocean temperature and, for the first time, salinity are presented. The MJO composites are based on 4 years of gridded Argo float data from 2003 to 2006, and extend from the surface to 1,400 m depth in the tropical Indian and Pacific Oceans. The MJO surface salinity anomalies are consistent with precipitation minus evaporation fluxes in the Indian Ocean, and with anomalous zonal advection in the Pacific. The Argo sea surface temperature and thermocline depth anomalies are consistent with previous studies using other data sets. The near-surface density changes due to salinity are comparable to, and partially offset, those due to temperature, emphasising the importance of including salinity as well as temperature changes in mixed-layer modelling of tropical intraseasonal processes. The MJO-forced equatorial Kelvin wave that propagates along the thermocline in the Pacific extends down into the deep ocean, to at least 1,400 m. Coherent, statistically significant, MJO temperature and salinity anomalies are also present in the deep Indian Ocean. 相似文献
14.
China Ocean ReAnalysis (CORA) version 1.0 products and validation for 2009–18: 2009–18年西北太平洋区域海洋再分析CORA1.0产品研制及检验 
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下载免费PDF全文 《大气和海洋科学快报》2021,14(5):100023
China Ocean ReAnalysis (CORA) version 1.0 products for the period 2009–18 have been developed and validated. The model configuration and assimilation algorithm have both been updated compared to those of the 51-year (1958–2008) products. The assimilated observations include temperature and salinity field data, satellite remote sensing sea surface temperature, and merged sea surface height (SSH) anomaly data. The validation includes the following three aspects: (1) Temperature, salinity, and SSH anomaly root-mean-square errors (RMSEs) are computed as a primary evaluation of the reanalysis quality. The 0–2000 m domain-averaged RMSEs of temperature and salinity are 0.61°C and 0.08 psu, respectively. The SSH anomaly RMSE is less than 0.2 m in most regions. (2) The 35°N temperature section is used to evaluate the ability to reproduce the thermocline, mixing layer, and Yellow Sea cold water mass. In summer, the thermocline is reinforced, with the gradient changing from 3°C in May to 10°C in August. The mixing-layer depth reproduced by CORA is consistent with that computed from the observed climatology. The Yellow Sea cold water mass forms at a depth of 50 m. (3) The reanalysis current is examined against the tracks of some drifting buoys. The results show that the reanalysis current can capture the mesoscale eddies near the Kuroshio, which are similar to those described by the drifting buoys. Overall, the 2009–18 CORA reanalysis products are capable of reproducing major oceanic phenomena and processes in the coastal waters of China and adjacent seas.摘要在51年 (1958–2008) 西北太平洋区域海洋再分析CORA1.0产品的基础上, 改进了模式配置和同化方法, 研制了2009-18年的CORA产品并对其进行以下检验: (1) 温盐和海表高度异常均方根误差分布检验; (2) 35°N处温度断面分布检验; (3) 再分析流场和表漂浮标轨迹对比检验.结果显示, 2009–18年的CORA产品可以再现海洋要素长时间序列,时空多尺度的变化特征, 为研究特征海洋现象和过程提供背景信息. 相似文献
15.
A comparison study is performed to contrast the improvements in the tropical Pacific oceanic state of a low-resolution model respectively via data assimilation and by an increase in horizontal resolution.A low resolution model (LR) (1°lat by 2°lon) and a high-resolution model (HR) (0.5°lat by 0.5°lon) are employed for the comparison. The authors perform 20-yr numerical experiments and analyze the annual mean fields of temperature and salinity. The results indicate that the low-resolution model with data assimilation behaves better than the high-resolution model in the estimation of ocean large-scale features.From 1990 to 2000, the average of HR's RMSE (root-mean-square error) relative to independent Tropical Atmosphere Ocean project (TAO) mooring data at randomly selected points is 0.97℃ compared to a RMSE of 0.56℃ for LR with temperature assimilation. Moreover, the LR with data assimilation is more frugal in computation. Although there is room to improve the high-resolution model, the low-resolution model with data assimilation may be an advisable choice in achieving a more realistic large-scale state of the ocean at the limited level of information provided by the current observational system. 相似文献
16.
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
17.
We use a heat- and salt-conserving ocean state estimation product to study the seasonal cycles of the mixed layer (ML) temperature (MLT) and salinity (MLS) balances over the southwestern tropical Indian Ocean (SWTIO) thermocline ridge (STR; 50°–75°E, 12°–5°S). For seasonal MLT, surface heat flux and ocean processes are both important. They tend to re-enforce each other during peak cooling (May–June) and warming (November) periods, but not during transition periods. The dominant ocean process is wind-driven vertical mixing. It is modulated by the variable strength of the monsoon winds (which affect the vertical diffusivity), and to a lesser extent by variability of thermocline depth (which influences the vertical stratification across the ML base). For example, thermocline shoaling in April–July alters the vertical stratification near the ML base; thus, when the monsoon winds heighten (June–September) and the vertical diffusivity increases (deepening the ML base), relatively cool subsurface water is near the ML base and easily incorporated into the ML by vertical mixing. However, vertical advection as a direct response to thermocline shoaling has little affect on MLT. This explains why MLT and thermocline depth are not positively correlated here on the seasonal timescale (as they are on the interannual timescale). Meridional advection associated with Ekman transport driven by the monsoon winds plays a secondary role. Seasonal MLS, however, is dominated by meridional advection. Vertical process effects on MLS are small, due to a weak salinity gradient near the ML base throughout the year. 相似文献
18.
Hydrographic and direct current measurements were made in the Eastern Equatorial Indian Ocean in May 2010 and April 2011 as part of the Eastern Indian Ocean Cruises(EIOC) organized by the South China Sea Institute of Oceanology(SCSIO).Analyses of the shipdrift Acoustic Doppler Current Profiler(ADCP) data indicate that the equatorial currents observed in May 2010 are characterized by a strongly eastward surface current(Wyrtki Jets,WJs) with a maximum velocity of 0.9 m s 1,while that observed in April 2011 is weak and without a consistent direction.The strongly eastward WJ transports the surface water eastward,resulting in a deeper upper mixed layer,as shown in the temperature and salinity profiles.However,it was found that the Equatorial Undercurrent(EUC) in the Eastern Indian Ocean is strong in April 2011 and weak in May 2010.The EUC was located approximately at the position of the thermocline,and it had higher salinity(up to approximately 35.5 psu) than the upper and lower waters. 相似文献
19.
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