A comparison of shelf observation platforms for assimilation in an eddy-resolving ocean model

An assessment of the likely benefits of assimilating in situ temperature (T) and salinity (S) observations from repeat glider transects and surface velocity observations from high-frequency radar arrays into an eddy-resolving ocean model is presented. The deployment of new shelf observation platforms around Australia is being undertaken through the Australian Integrated Marine Observing System program. In this study, various options for an observing system along the coast of New South Wales, Australia, are assessed for their benefits to an ocean forecast and reanalysis system. The forecast system considered here uses ensemble optimal interpolation (EnOI) for data assimilation. Using error estimates from the EnOI scheme, estimates of the theoretical analysis errors are calculated for different observing systems that include a range of remotely sensed and in situ observations. The results demonstrate that if HF radar observations are assimilated along with the standard components of the global ocean observing system, the analysis errors are likely to reduce by as much as 80% for velocity and 60% for T, S and sea-level in the vicinity of the observations. Owing to the relatively short along-shore decorrelation length-scales for T and S near the shelf, the glider observations are likely to provide the forecast system with a more modest gain.     

A comparison of shelf observation platforms for assimilation in an eddy-resolving ocean model

An assessment of the likely benefits of assimilating in situ temperature (T) and salinity (S) observations from repeat glider transects and surface velocity observations from high-frequency radar arrays into an eddy-resolving ocean model is presented. The deployment of new shelf observation platforms around Australia is being undertaken through the Australian Integrated Marine Observing System program. In this study, various options for an observing system along the coast of New South Wales, Australia, are assessed for their benefits to an ocean forecast and reanalysis system. The forecast system considered here uses ensemble optimal interpolation (EnOI) for data assimilation. Using error estimates from the EnOI scheme, estimates of the theoretical analysis errors are calculated for different observing systems that include a range of remotely sensed and in situ observations. The results demonstrate that if HF radar observations are assimilated along with the standard components of the global ocean observing system, the analysis errors are likely to reduce by as much as 80% for velocity and 60% for T, S and sea-level in the vicinity of the observations. Owing to the relatively short along-shore decorrelation length-scales for T and S near the shelf, the glider observations are likely to provide the forecast system with a more modest gain.     

A comprehensive model inter-comparison study investigating the water budget during the BALTEX-PIDCAP period

Summary A comparison of 8 regional atmospheric model systems was carried out for a three-month late summer/early autumn period in 1995 over the Baltic Sea and its catchment area. All models were configured on a common grid using similar surface and lateral boundary conditions, and ran in either data assimilation mode (short term forecasts plus data assimilation), forecast mode (short term forecasts initialised daily with analyses) or climate mode (no re-initialisation of model interior during entire simulation period). Model results presented in this paper were generally post processed as daily averaged quantities, separate for land and sea areas when relevant. Post processed output was compared against available analyses or observations of cloud cover, precipitation, vertically integrated atmospheric specific humidity, runoff, surface radiation and near surface synoptic observations. The definition of a common grid and lateral forcing resulted in a high degree of agreement among the participating model results for most cases. Models operated in climate mode generally displayed slightly larger deviations from the observations than the data assimilation or forecast mode integration, but in all cases synoptic events were well captured. Correspondence to near surface synoptic quantities was good. Significant disagreement between model results was shown in particular for cloud cover and the radiative properties, average precipitation and runoff. Problems with choosing appropriate initial soil moisture conditions from a common initial soil moisture field resulted in a wide range of evaporation and sensible heat flux values during the first few weeks of the simulations, but better agreement was shown at later times. Received September 8, 2000 Revised April 3, 2001     

Assimilating surface observations in a four-dimensional variational Doppler radar data assimilation system to improve the analysis and forecast of a squall line case

This paper examines how assimilating surface observations can improve the analysis and forecast ability of a fourdimensional Variational Doppler Radar Analysis System(VDRAS).Observed surface temperature and winds are assimilated together with radar radial velocity and reflectivity into a convection-permitting model using the VDRAS four-dimensional variational(4DVAR) data assimilation system.A squall-line case observed during a field campaign is selected to investigate the performance of the technique.A single observation experiment shows that assimilating surface observations can influence the analyzed fields in both the horizontal and vertical directions.The surface-based cold pool,divergence and gust front of the squall line are all strengthened through the assimilation of the single surface observation.Three experiments—assimilating radar data only,assimilating radar data with surface data blended in a mesoscale background,and assimilating both radar and surface observations with a 4DVAR cost function—are conducted to examine the impact of the surface data assimilation.Independent surface and wind profiler observations are used for verification.The result shows that the analysis and forecast are improved when surface observations are assimilated in addition to radar observations.It is also shown that the additional surface data can help improve the analysis and forecast at low levels.Surface and low-level features of the squall line—including the surface warm inflow,cold pool,gust front,and low-level wind—are much closer to the observations after assimilating the surface data in VDRAS.     

Impacts of XBT, TAO, Altimetry and ARGO Observations on the Tropical Pacific Ocean Data Assimilation

This study aims at assessing the relative impacts of four major components of the tropical Pacific Ocean observing system on assimilation of temperature and salinity fields. Observations were collected over a period between January 2001 through June 2003 including temperature data from the expendable bathythermographs (XBT), thermistor data from the Tropical Ocean Global Atmosphere Tropical Atmosphere-Ocean (TOGA-TAO) mooring array, sea level anomalies from the Topex/Poseidon and Jason-1 altimetry (T/P-J),and temperature and salinity profiles from the Array for Real-time Geostrophic Oceanography (ARGO) floats.An efficient three-dimensional variational analysis-based method was introduced to assimilate the above data into the tropical-Pacific circulation model. To evaluate the impact of the individual component of the observing system, four observation system experiments were carried out. The experiment that assimilated all four components of the observing system was taken as the reference. The other three experiments were implemented by withholding one of the four components. Results show that the spatial distribution of the data influences its relative contribution. XBT observations produce the most distinguished effects on temperature analyses in the off-equatorial region due to the large amount of measurements and high quality.Similarly, the impact of TAO is dominant in the equatorial region due to the focus of the spatial distribution.The Topex/Poseidon-Jason-1 can be highly complementary where the XBT and TAO observations are sparse.The contribution of XBT or TAO on the assimilated salinity is made by the model dynamics because no salinity observations from them are assimilated. Therefore, T/P-J, as a main source for providing salinity data, has been shown to have greater impacts than either XBT or TAO on the salinity analysis. Although ARGO includes the subsurface observations, the relatively smaller number of observation makes it have the smallest contribution to the assimilation system.     

Impacts of XBT, TAO, Altimetry and ARGO Observations on the Tropical Pacific Ocean Data Assimilation

This study aims at assessing the relative impacts of four major components of the tropical Pacific Ocean observing system on assimilation of temperature and salinity fields. Observations were collected over a period between January 2001 through June 2003 including temperature data from the expendable bathythermographs （XBT）, thermistor data from the Tropical Ocean Global Atmosphere Tropical Atmosphere-Ocean （TOGA-TAO） mooring array, sea level anomalies from the Topex/Poseidon and Jason-1 altimetry （T/P-J）, and temperature and salinity profiles from the Array for Real-time Geostrophic Oceanography （ARGO） floats. An efficient three-dimensional variational analysis-based method was introduced to assimilate the above data into the tropical-Pacific circulation model. To evaluate the impact of the individual component of the observing system, four observation system experiments were carried out. The experiment that assimilated all four components of the observing system was taken as the reference. The other three experiments were implemented by withholding one of the four components. Results show that the spatial distribution of the data influences its relative contribution. XBT observations produce the most distinguished effects on temperature analyses in the off-equatorial region due to the large amount of measurements and high quality. Similarly, the impact of TAO is dominant in the equatorial region due to the focus of the spatial distribution. The Topex/Poseidon-Jason-1 can be highly complementary where the XBT and TAO observations are sparse. The contribution of XBT or TAO on the assimilated salinity is made by the model dynamics because no salinity observations from them are assimilated. Therefore, T/P-J, as a main source for providing salinity data, has been shown to have greater impacts than either XBT or TAO on the salinity analysis. Although ARGO includes the subsurface observations, the relatively smaller number of observation makes it have the smallest contribution to the assimilation syst     

GTS的温盐资料在BCC_GODAS中的同化结果分析

分析了从GTS(全球无线通讯系统)获得的2002-2007年海洋温盐观测资料在国家气候中心第2代全球海洋资料同化系统(BCC_GODAS 2.0)中的同化结果。与SODA(简易海洋同化数据)资料的比较表明:GTS中的海洋温盐资料同化对模式温盐场的改进之处主要表现在混合层暖区的范围和中心强度、温跃层中温度槽脊的深度、温跃层附近的温度梯度以及盐度高、低值区的范围和中心强度等方面,同化后全球温盐场的均方根误差得到一定程度的降低。挑选位于不同海区的单点温盐廓线与ARGO(地转海洋学实时观测阵)观测作了进一步比较,结果表明:大多数情况下,同化后温盐廓线的均方根误差得到明显降低,模拟的温盐垂向分布特征也更为准确。与TAO(热带大气海洋观测网)资料的比较也同样表明:同化后的温盐场特征会得到一定程度改善。     

Assimilation of Hourly Surface Observations with the Canadian High-Resolution Ensemble Kalman Filter

An hourly-cycling ensemble Kalman filter (EnKF) working at 2.5?km horizontal grid spacing is implemented over southern Ontario (Canada) to assimilate Meteorological Terminal Aviation Routine Weather Reports (METARs) in addition to the observations assimilated operationally at the Canadian Meteorological Centre. This high-resolution EnKF (HREnKF) system employs ensemble land analyses and perturbed roughness length to prevent an ensemble spread that is too small near the surface. The HREnKF then performs continuously for a four-day period, from which twelve-hour ensemble forecasts are launched every six hours. The impact on analyses and short-term forecasts of assimilating METAR data is given special attention.

It is shown that using ensemble land surface analyses increases near-surface ensemble spreads for temperature and specific humidity. Perturbing roughness length enlarges the spread for surface wind. Given sufficient ensemble spread, the four-day case study shows that the near-surface model state is brought closer to surface observations during the cycling process. The impact of assimilating surface data can also be seen at higher levels by using aircraft reports for verification. The ensemble forecast verification suggests that METAR data assimilation improves ensemble forecasts of air temperature and dewpoint near the surface up to a lead time of six hours or even longer. However, only minor improvement is found in surface wind forecasts.     

Impact of Assimilation of Radiosonde and UAV Observations from the Southern Ocean in the Polar WRF Model

Weather forecasting in the Southern Ocean and Antarctica is a challenge above all due to the rarity of observations to be assimilated in numerical weather prediction(NWP) models. As observations are expensive and logistically challenging,it is important to evaluate the benefit that additional observations could bring to NWP. Atmospheric soundings applying unmanned aerial vehicles(UAVs) have a large potential to supplement conventional radiosonde sounding observations.Here, we applied UAV and rad...     

Improved tropical cyclone forecasts over north Indian Ocean with direct assimilation of AMSU-A radiances

The Weather Research and Forecasting (WRF-ARW) model and its three-dimensional variational data assimilation (3D-Var) system are used to investigate the impact of the Advanced Microwave Sounding Unit-A (AMSU-A) radiances on the prediction of Indian Ocean tropical cyclones. Three tropical cyclones are selected for this study: cyclone Mala (April 2006; Bay of Bengal), cyclone Gonu (June 2007; Arabian Sea), and cyclone Sidr (November 2007; Bay of Bengal). For each case, observing system experiments are designed, by producing two sets of analyses from which forecasts are initialized. Both sets of analyses contain all conventional and satellite observations operationally used, including, but not limited to, Quick Scatterometer (QuikSCAT) surface winds, Special Sensor Microwave/Imager (SSM/I) surface winds, Meteosat-derived atmospheric motion vectors (AMVs), and differ only in the exclusion (CNT) or inclusion (EXP) of AMSU-A radiances. Results show that the assimilation of AMSU-A radiances changes the large-scale thermodynamic structure of the atmosphere, and also produce a stronger warm core. These changes cause large forecast track improvements. In particular, without AMSU-A assimilation, most forecasts do not produce landfall. On the contrary, the forecasts initialized from improved EXP analyses in which AMSU-A data are included produce realistic landfall. In addition, intensity forecast is also improved. Even if the analyzed cyclone intensity is not affected by the assimilation of AMSU-A radiances, the predicted intensity improves substantially because of the development of warm cores which, through creation of stronger gradients, helps the model in producing intense low centre pressure.     

A global ocean temperature and altimeter data assimilation system for studies of climate variability

 An ocean data assimilation (ODA) system which can assimilate both temperature and altimeter observations has been applied to the global ocean and tested between January 1993–October 1996. A statistical method has been used to convert sea surface height (SSH) anomalies observations from TOPEX/POSEIDON into synthetic temperature profiles. The innovative aspect of this method is the introduction of time dependency in the correlations used to transform the altimeter observations into temperature corrections. The assimilation system is based on a univariate variational optimal interpolation scheme applied to assimilate both in situ and synthetic temperature profiles. In addition, a longer global analysis for the upper-ocean temperature starting from January 1979 and ending November 1997, has been produced to examine the skill of sea temperature assimilation with a rather simple and practical method. The temperature analysis shows encouraging improvement over a corresponding ocean simulation when compared to independent (not assimilated) temperature data both at seasonal and interannual time scales. However, the univariate data assimilation of hydrographic data does not result in an improvement of the velocity field. In fact the assimilation of sparse in situ data can introduce unrealistic spatial variability in the temperature field which affects the velocity field in a negative way. This deficiency is partially overcome when we also assimilate altimeter observations since the coverage is complete and uniform for this data. In particular, our study shows that temperature corrections due to the altimeter signal have a positive impact on the current system in the tropical Pacific. Received: 28 May 2000 / Accepted: 6 November 2000     

全球海洋资料同化系统ZFL_GODAS的研制和初步评估试验

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。     

Influence of Surface Temperature and Emissivity on AMSU-A Assimilation over Land

AMSU-A (Advanced Microwave Sounding Unit-A) measurements for channels that are sensitive to the surface over land have not been widely assimilated into numerical weather prediction (NWP) models due to complicated land surface features. In this paper, the impact of AMSU-A assimilation over land in Southwest Asia is investigated with the Weather Research and Forecasting (WRF) model. Four radiance assimilation experiments with different land-surface schemes are designed, then compared and verified against radiosonde observations and global analyses. Besides the surface emissivity calculated from the emissivity model and surface temperature from the background field in current WRF variational data assimilation (WRF-VAR) system, the surface parameters from the operational Microwave Surface and Precipitation Products System (MSPPS) are introduced to understand the influence of surface parameters on AMSU-A assimilation over land. The sensitivity of simulated brightness temperatures to different surface configurations shows that using MSPPS surface alternatives significantly improves the simulation with reduced root mean square error (RMSE) and allows more observations to be assimilated. Verifications of 24-h temperature forecasts from experiments against radiosonde observations and National Centers for Environmental Prediction (NCEP) global analyses show that the experiments using MSPPS surface alternatives generate positive impact on forecast temperatures at lower atmospheric layers, especially at 850 hPa. The spatial distribution of RMSE for forecast temperature validation indicates that the experiments using MSPPS surface temperature obviously improve forecast temperatures in the mountain areas. The preliminary study indicates that using proper surface temperature is important when assimilating lower sounding channels of AMSU-A over land.     

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

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.     

南海温盐流数值产品构建及评估

基于区域海洋模式ROMS构造了一套覆盖中国南海的40年（1980—2019年）温盐流数值产品OCEAN＿SCS。OCEAN＿SCS的变量包含了温度、盐度、流速、流向以及海表高度。OCEAN＿SCS的水平空间分辨率为0.1°×0.1°,垂向分层40层（0～5 000 m）,时间分辨率为1小时,包含潮汐信息。利用独立的观测资料对OCEAN＿SCS进行了初步评估,评估对象包括温度、盐度、海表高度、海流、潮位和增水。在不包含资料同化的前提下,OCEAN＿SCS的模拟精度达到了较高的水准。OCENA＿SCS的构建将为南海海洋环境的研究提供数据支撑,并服务于南海海洋环境保障。     

Water mass properties and transports in the Arabian Sea from Argo observations

The information acquired from Argo floats such as temperature and salinity profiles is used to study water mass properties in the Arabian Sea from 2002 to 2004. An examination of water mass structure at different locations reveals the presence of high salinity water of marginal seas in the Arabian Sea. During the southwest monsoon season, the impact of the early onset of southwesterlies is noticed in the upper ocean temperature and salinity structure over the Western Arabian Sea (WAS) during 2002. Surface density variations are found to be more during the southwest monsoon season due to strong wind forcing. Argo temperature and salinity profiles showed that the winter cooling and the formation of Arabian Sea High Salinity Water (ASHSW) over the Northern Arabian Sea (NAS) began during the second half of November within the upper 100 m depth. In the NAS, the Persian Gulf Water (PGW) salinity is above 36, as PGW moves towards the south along isopycnal layer of 26.6σ_θ (σ_θ is potential density) salinity decreases. It is observed that the PGW high salinity water is not continuously prominent over the WAS in 2002 and in 2003. In the WAS the 27.2σ_θ isopycnal layer depth, corresponding to Red Sea Water (RSW), did not exactly follow the pattern of isotherms as is seen in the northern and eastern Arabian Sea. The variability related to RSW salinity is due to the underwater currents. The present study also confirms that RSW is prominent in the southeast Arabian Sea at the potential density of 27.2 with a maximum in summer monsoon compared to other seasons. The observed peak in the salinity at 27.2 density level during the spring intermonsoon is due to the influence of winter time spreading of RSW to the south of Socotra in 2002. Westward movement of Argo floats in the region east of Socotra during the winter is evident in both the observations and model studies. Water mass properties change when they move away from their source region due to the consistent horizontal advection. The changes in the water mass properties along the Argo float trajectory are confirmed by comparing with the climatological mean monthly values from the World Ocean Atlas 2001 data set.     

集合卡尔曼滤波同化多普勒雷达资料的数值试验

利用集合卡尔曼滤波(EnKF)在云数值模式中同化模拟多普勒雷达资料,并考察了不同条件下EnKF同化方法的性能.结果显示,经过几个同化周期后,EnKF分析结果非常接近真值.单多普勒雷达资料EnKF同化对雷达位置不太敏感,双雷达资料同化结果在同化的初期阶段比单雷达资料同化结果准确.同化由反射率导出的雨水比直接同化反射率资料更有效,联合同化径向速度和雨水有利于提高同化分析效果.协方差对EnKF同化效果起着非常重要的作用,考虑模式全部预报变量与径向速度协方差的同化效果比仅考虑速度场与径向速度协方差的同化效果好.雷达资料缺值降低了同化效果,此时增加地面常规观测资料的同化可以明显提高同化分析效果.EnKF同化技术对雷达观测资料误差不太敏感.初始集合对同化分析有较大影响.EnKF同化受集合大小和观测资料影响半径.同化对模式误差较敏感.利用EnKF同化双多普勒雷达资料,分析了一次梅雨锋暴雨过程的中尺度结构.结果表明,EnKF同化技术能够从双多普勒雷达资料反演暴雨中尺度系统的动力场、热力场和微物理场,反演的风场是较准确的,反演的热力场和微物理场分布也是基本合理的.中低层切变线是此次暴雨的主要动力特征,对流云表现为低层辐合、高层辐散并有垂直上升运动伴随,其热力特征表现为低层是低压区,高层为高压区,中部为暖区而上、下部为冷区,水汽、云水和雨水分别集中在对流云体内、上升气流区和强回波区.     

Assimilating QuikSCAT Ocean Surface Winds with the Weather Research and Forecasting Model for Surface Wind-Field Simulation over the Chukchi/Beaufort Seas

To achieve a high-quality simulation of the surface wind field in the Chukchi/Beaufort Sea region, quick scatterometer (QuikSCAT) ocean surface winds were assimilated into the mesoscale Weather Research and Forecasting model by using its three-dimensional variational data assimilation system. The SeaWinds instrument on board the polar-orbiting QuikSCAT satellite is a specialized radar that measures ice-free ocean surface wind speed and direction at a horizontal resolution of 12.5 km. A total of eight assimilation case studies over two five-day periods, 1–5 October 2002 and 20–24 September 2004, were performed. The simulation results with and without the assimilation of QuikSCAT winds were then compared with QuikSCAT data available during the subsequent free-forecast period, coastal station observations, and North American Regional Reanalysis data. It was found that QuikSCAT winds are a potentially valuable resource for improving the simulation of ocean near-surface winds in the Chukchi/Beaufort Seas region. Specifically, the assimilation of QuikSCAT winds improved, (1) offshore surface winds as compared to unassimilated QuikSCAT winds, (2) sea-level pressure, planetary boundary-layer height, as well as surface heat fluxes, and (3) low-level wind fields and geopotential height. Verification against QuikSCAT data also demonstrated the temporal consistency and good quality of QuikSCAT observations.     

The retrospective prediction of El Niño-southern oscillation from 1881 to 2000 by a hybrid coupled model: (I) Sea surface temperature assimilation with ensemble Kalman filter

In this study, we assimilated sea surface temperature (SST) data of the past 120 years into an oceanic general circulation model (OGCM) for El Niño-southern oscillation (ENSO) retrospective predictions using ensemble Kalman filter (EnKF). It was found that the ensemble covariance matrix in EnKF can act as a time-variant transfer operator to project the SST corrections onto the subsurface temperatures effectively when initial perturbations of ensemble were constructed using vertically coherent random fields. As such the increments of subsurface temperatures can be obtained via the transfer operator during assimilation cycles. The results show that the SST assimilation improves the model simulation skills significantly, not only for the SST anomalies over the whole assimilated domain, but also for the subsurface temperature anomalies of the upper 100 m over the tropical Pacific off the equator. Along the equator, the improvement of the assimilation is confined within the mixing layer because strong upwelling motions there prevent the downward transfer of SST information. The retrospective prediction skills of ENSO over the past 120 years from 1881 to 2000 were significantly improved by the SST assimilation at all leads of 1–12 months, especially for the 3–6 months leads, compared with those initialized by the control run without assimilation. The skilful predictions by the assimilation allow us to further study ENSO predictability using this coupled model.     

2009-18年西北太平洋区域海洋再分析CORA1.0产品研制及检验

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.