气候模式和再分析数据中北冰洋中层水再现能力的评估

The simulations of the Arctic Intermediate Water in four datasets of climate models and reanalyses, CCSM3, CCSM4, SODA and GLORYS, are analyzed and evaluated. The climatological core temperatures and depths in both CCSM models exhibit deviations over 0.5°C and 200 m from the PHC. SODA reanalysis reproduces relatively reasonable spatial patterns of core temperature and depth, while GLORYS, another reanalysis, shows a remarkable cooling and deepening drift compared with the result at the beginning of the dataset especially in the Eurasian Basin(about 2°C). The heat contents at the depth of intermediate water in the CCSM models are overestimated with large positive errors nearly twice of that in the PHC. To the contrary, the GLORYS in 2009 show a negative error with a similar magnitude, which means the characteristic of the water mass is totally lost. The circulations in the two reanalyses at the depth of intermediate water are more energetic and realistic than those in the CCSMs, which is attributed to the horizontal eddy-permitting resolution. The velocity fields and the transports in the Fram Strait are also investigated. The necessity of finer horizontal resolution is concluded again. The northward volume transports are much larger in the two reanalyses, although they are still weak comparing with mooring observations. Finally, an investigation of the impact of assimilation is done with an evidence of the heat input from assimilation. It is thought to be a reason for the good performance in the SODA, while the GLORYS drifts dramatically without assimilation data in the Arctic Ocean.     

Argo时代东南印度洋上层盐度变化对海平面年代际演变的影响

In the past nearly two decades, the Argo Program has created an unprecedented global observing array with continuous in situ salinity observations, providing opportunities to extend our knowledge on the variability and effects of ocean salinity. In this study, we utilize the Argo data during 2004–2017, together with the satellite observations and a newly released version of ECCO ocean reanalysis, to explore the decadal salinity variability in the Southeast Indian Ocean(SEIO) and its impacts on the regional sea level changes. Both the observations and ECCO reanalysis show that during the Argo era, sea level in the SEIO and the tropical western Pacific experienced a rapid rise in 2005–2013 and a subsequent decline in 2013–2017. Such a decadal phase reversal in sea level could be explained, to a large extent, by the steric sea level variability in the upper 300 m. Argo data further show that, in the SEIO, both the temperature and salinity changes have significant positive contributions to the decadal sea level variations. This is different from much of the Indo-Pacific region, where the halosteric component often has minor or negative contributions to the regional sea level pattern on decadal timescale. The salinity budget analyses based on the ECCO reanalysis indicate that the decadal salinity change in the upper 300 m of SEIO is mainly caused by the horizontal ocean advection. More detailed decomposition reveals that in the SEIO, there exists a strong meridional salinity front between the tropical low-salinity and subtropical high salinity waters. The meridional component of decadal circulation changes will induce strong cross-front salinity exchange and thus the significant regional salinity variations.     

集合同化方法在黄海海域海表面温度同化中的应用

The effects of sea surface temperature(SST) data assimilation in two regional ocean modeling systems were examined for the Yellow Sea(YS). The SST data from the Operational Sea Surface Temperature and Sea Ice Analysis(OSTIA) were assimilated. The National Marine Environmental Forecasting Center(NMEFC) modeling system uses the ensemble optimal interpolation method for ocean data assimilation and the Kunsan National University(KNU) modeling system uses the ensemble Kalman filter. Without data assimilation, the NMEFC modeling system was better in simulating the subsurface temperature while the KNU modeling system was better in simulating SST. The disparity between both modeling systems might be related to differences in calculating the surface heat flux, horizontal grid spacing, and atmospheric forcing data. The data assimilation reduced the root mean square error(RMSE) of the SST from 1.78°C(1.46°C) to 1.30°C(1.21°C) for the NMEFC(KNU) modeling system when the simulated temperature was compared to Optimum Interpolation Sea Surface Temperature(OISST) SST dataset. A comparison with the buoy SST data indicated a 41%(31%) decrease in the SST error for the NMEFC(KNU) modeling system by the data assimilation. In both data assimilative systems, the RMSE of the temperature was less than 1.5°C in the upper 20 m and approximately 3.1°C in the lower layer in October. In contrast, it was less than 1.0°C throughout the water column in February. This study suggests that assimilations of the observed temperature profiles are necessary in order to correct the lower layer temperature during the stratified season and an ocean modeling system with small grid spacing and optimal data assimilation method is preferable to ensure accurate predictions of the coastal ocean in the YS.     

基于ROMS模式利用集合最优插值同化沿轨海表面高度异常数据的研究

The ensemble optimal interpolation （EnOI） is applied to the regional ocean modeling system （ROMS） with the ability to assimilate the along-track sea level anomaly （TSLA）. This system is tested with an eddy-resolving system of the South China Sea （SCS）. Background errors are derived from a running seasonal ensemble to account for the seasonal variability within the SCS. A fifth-order localization function with a 250 km localization radius is chosen to reduce the negative effects of sampling errors. The data assimilation system is tested from January 2004 to December 2006. The results show that the root mean square deviation （RMSD） of the sea level anomaly decreased from 10.57 to 6.70 cm, which represents a 36.6% reduction of error. The data assimilation reduces error for temperature within the upper 800 m and for salinity within the upper 200 m, although error degrades slightly at deeper depths. Surface currents are in better agreement with trajectories of surface drifters after data assimilation. The variance of sea level improves significantly in terms of both the amplitude and position of the strong and weak variance regions after assimilating TSLA. Results with AGE error （AGE） perform better than no AGE error （NoAGE） when considering the improvements of the temperature and the salinity. Furthermore, reasons for the extremely strong variability in the northern SCS in high resolution models are investigated. The results demonstrate that the strong variability of sea level in the high resolution model is caused by an extremely strong Kuroshio intrusion. Therefore, it is demonstrated that it is necessary to assimilate the TSLA in order to better simulate the SCS with high resolution models.     

基于高光谱遥感的渤海海冰厚度半经验模型

Sea ice thickness is one of the most important input parameters for the prevention and mitigation of sea ice disasters and the prediction of local sea environments and climates. Estimating the sea ice thickness is currently the most important issue in the study of sea ice remote sensing. With the Bohai Sea as the study area, a semiempirical model of the sea ice thickness(SEMSIT) that can be used to estimate the thickness of first-year ice based on existing water depth estimation models and hyperspectral remote sensing data according to an optical radiative transfer process in sea ice is proposed. In the model, the absorption and scattering properties of sea ice in different bands(spectral dimension information) are utilized. An integrated attenuation coefficient at the pixel level is estimated using the height of the reflectance peak at 1 088 nm. In addition, the surface reflectance of sea ice at the pixel level is estimated using the 1 550–1 750 nm band reflectance. The model is used to estimate the sea ice thickness with Hyperion images. The first validation results suggest that the proposed model and parameterization scheme can effectively reduce the estimation error associated with the sea ice thickness that is caused by temporal and spatial heterogeneities in the integrated attenuation coefficient and sea ice surface. A practical semi-empirical model and parameterization scheme that may be feasible for the sea ice thickness estimation using hyperspectral remote sensing data are potentially provided.     

SMAP卫星海表盐度产品的检验与校正

In this study, sea surface salinity(SSS) Level 3(L3) daily product derived from soil moisture active passive(SMAP)during the year 2016, was validated and compared with SSS daily products derived from soil Moisture and ocean salinity(SMOS) and in-situ measurements. Generally, the root mean square error(RMSE) of the daily SSS products is larger along the coastal areas and at high latitudes and is smaller in the tropical regions and open oceans. Comparisons between the two types of daily satellite SSS product revealed that the RMSE was higher in the daily SMOS product than in the SMAP, whereas the bias of the daily SMOS was observed to be less than that of the SMAP when compared with Argo floats data. In addition, the latitude-dependent bias and RMSE of the SMAP SSS were found to be primarily influenced by the precipitation and the sea surface temperature(SST). Then, a regression analysis method which has adopted the precipitation and SST data was used to correct the larger bias of the daily SMAP product. It was confirmed that the corrected daily SMAP product could be used for assimilation in high-resolution forecast models, due to the fact that it was demonstrated to be unbiased and much closer to the in-situ measurements than the original uncorrected SMAP product.     

Three-dimensional structure of an observed cyclonic mesoscale eddy in the Northwest Pacific and its assimilation experiment

Mesoscale eddies play an important role in modulating the ocean circulation. Many previous studies on the threedimensional structure of mesoscale eddies were mainly based on composite analysis, and there are few targeted observations for individual eddies. A cyclonic eddy surveyed during an oceanographic cruise in the Northwest Pacific Ocean is investigated in this study. The three-dimensional structure of this cyclonic eddy is revealed by observations and simulated by the four-dimensional variational data assimilation(4 DVAR) system combined with the Regional Ocean Modeling System. The observation and assimilation results together present the characteristics of the cyclonic eddy. The cold eddy has an obvious dual-core structure of temperature anomaly.One core is at 50–150 m and another is at 300–550 m, which both have the average temperature anomaly of approximately-3.5°C. The salinity anomaly core is between 250 m and 500 m, which is approximately-0.3. The horizontal velocity structure is axis-asymmetric and it is enhanced on the eastern side of the cold eddy. In the assimilation experiment, sea level anomaly, sea surface temperature, and in situ measurements are assimilated into the system, and the results of assimilation are close to the observations. Based on the high-resolution assimilation output results, the study also diagnoses the vertical velocity in the mesoscale eddy, which reaches the maximum of approximately 10 m/d. The larger vertical velocity is found to be distributed in the range of 0.5 to 1 time of the normalized radius of the eddy. The validation of the simulation result shows that the 4 DVAR method is effective to reconstruct the three-dimensional structure of mesoscale eddy and the research is an application to study the mesoscale eddy in the Northwest Pacific by combining observation and assimilation methods.     

基于ROMS和4DVAR的沿轨与网格化SSH数据同化效果评价

Remote sensing products are significant in the data assimilation of an ocean model. Considering the resolution and space coverage of different remote sensing data, two types of sea surface height(SSH) product are employed in the assimilation, including the gridded products from AVISO and the original along-track observations used in the generation. To explore their impact on the assimilation results, an experiment focus on the South China Sea(SCS) is conducted based on the Regional Ocean Modeling System(ROMS) and the four-dimensional variational data assimilation(4 DVAR) technology. The comparison with EN4 data set and Argo profile indicates that, the along-track SSH assimilation result presents to be more accurate than the gridded SSH assimilation, because some noises may have been introduced in the merging process. Moreover, the mesoscale eddy detection capability of the assimilation results is analyzed by a vector geometry–based algorithm. It is verified that, the assimilation of the gridded SSH shows superiority in describing the eddy's characteristics, since the complete structure of the ocean surface has been reconstructed by the original data merging.     

Summer Monsoon and Annual Variability of Sea Surface Slope and Their Effects on Alongshore Current near Qingdao

Based on the monthly mean sea level data obtained from 3 years‘ (1999--2001) tide-gauge measurements, the annual variability of the sea level near Qingdao and Jiaozhou Bay is studied and discussed in this paper. Results show that the sea surface height at all the tide gauges becomes higher in summer than that in winter,with an obvious seasonal variability. Furthermore the sea surface height measured at a short distance outside the bay is lower than that in the bay, showing a sea surface slope downward from north to south. The reasons for the formation of the slope are explained as well. The dynamic action of the summer monsoon and the sea surface slope, and their effects on the monthly mean current are studied by means of dynamics principles. The importance of the summer monsoon and the pressure gradient generated by the sea surface slope, with their effects on the alongshore current, is pointed out and emphasized in this paper.     

南海混合层近惯性能通量的时空变化

On the basis of the QSCAT/NCEP blended wind data and simple ocean data assimilation(SODA), the wind-induced near-inertial energy flux(NIEF) in the mixed layer of the South China Sea(SCS) is estimated by a slab model, and the model results are verified by observational data near the Xisha Islands in the SCS. Then, the spatial and temporal variations of the NIEF in the SCS are analyzed. It is found that, the monthly mean NIEF exhibits obvious spatial and temporal variabilities, i.e., it is large west of Luzon Island all the year, east of the Indo-China Peninsula all the year except in spring, and in the northern SCS from May to September. The large monthly mean NIEF in the first two zones may be affected by the large local wind stress curl whilst that in the last zone is probably due to the shallow mixed layer depth. Moreover, the monthly mean NIEF is relatively large in summer and autumn due to the passage of typhoons. The spatial mean NIEF in the mixed layer of the SCS is estimated to be about 1.25 m W/m2 and the total wind energy input from wind is approximately 4.4 GW. Furthermore, the interannual variability of the spatial monthly mean NIEF and the Ni?o3.4 index are negatively correlated.     

基于CORA资料的中国海海表面温度季节和年际变化特征分析

基于1986-2008年的中国近海及邻近海域再分析产品(CORA),采用经验正交函数分解方法(EOF)分析了海表面温度(SST)的季节及年际变化特征,并用相应的SODA、AVHRR以及Levitus资料对CORA做了对比评估。相比于AVHRR而言,CORA资料SST的偏差和均方根误差均小于SODA,相比Levitus资料而言CORA资料温度盐度的均方根误差随深度的变化皆小于SODA。 CORA与SODA资料相比,两者前3个模态的时空分布大体一致,区别在于CORA资料能更好地反映参量的一些细微特征。结果表明,CORA资料能很好的刻画中国近海SST的季节、年际变化特征,尤其是黑潮流经区域SST的局地变化特征。季节EOF第二模态显示的是SST对由风引起的潜热释放的响应特征。第三模态刻画了冬夏转换季的分布特征,主要揭示了东北-西南走向的锋面特征。SST年际变化与ENSO密切相关,区域平均的南海SSTA与Nino指数的吻合程度CORA优于SODA。     

基于神经网络的全球三维温盐场重构技术研究

文章利用果蝇优化广义回归神经网络算法FOAGRNN (fruit fly optimization algorithm, FOA; generalized regression neural network, GRNN)对SODA (simple ocean data assimilation)再分析数据进行训练, 构建海表温度、盐度、海面高度与次表层温盐场之间的投影关系模型, 并在全球范围使用SODA和卫星遥感数据评估了模型的应用性能。首先, 利用独立的2016年SODA海表数据作为模型输入进行理想重构试验, 结果显示全球重构温、盐平均均方根误差(MRMSE)分别为0.36℃和0.08‰, 与世界海洋图集WOA13资料相比减小约50%和60%。然后, 利用卫星观测的海表信息作为模型输入进行实际应用试验, 并与Argo观测剖面进行比较评估。试验结果表明, 重构模型能有效表征海水温、盐特征, 其中重构温、盐MRMSE分别为0.79℃和0.16‰, 相比WOA气候态减小27%和11%。误差的垂向分布显示, 重构温度RMSE从海表向下迅速增大, 至100m达到峰值1.35℃, 而后又迅速回落,至250m处为0.81℃, 跃层往下不断减小; 重构盐度RMSE基本随深度增大而减小, 误差峰值位于25m附近, 约为0.25‰。此外, Argo浮标跟踪分析和区域水团统计结果也表明模型能够较好地刻画海洋三维温盐场的内部结构特征。     

大气模式中季节内振荡特征对不同海温强迫场的响应

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。     

西太平洋暖池热状况变化特征及其东传过程

应用JEDAC海温和SODA再分析资料,分析研究了西太平洋暖池(WPWP)的热状况变化特征,探讨了WPWP的热含量变化与不同深度海温变化,特别是与表层和次表层海温场之间的内在联系,分析研究了WPWP异常海温东传过程中与温跃层变化之间的关系,最后讨论了赤道潜流在异常海温东传过程的作用。结果表明,WPWP区域的热含量变化与次表层的海温变化具有相同变化趋势。WPWP区域的热含量变化与次表层海温达到(超过)99.9%信度检验的相关出现在次表层海温变化超前热含量变化的12个月至次表层海温变化滞后热含量变化12个月,最佳相关出现在同期,相关系数r=0.92(样本n=552)。WPWP区域的热含量变化与SST达到99.9%信度检验的相关只出现在热含量滞后SST5个月至同期。这一结果表明,WPWP区域的热含量变化主要体现了次表层海温场的变化特征。由此认为,WPWP区域热含量变化(次表层海温场)对气候变化的贡献主要体现在东向传播对ENSO的贡献上。由WPWP异常海温沿赤道东传过程和温跃层变化之间的关系可知,温跃层变化滞后于WPWP区域东传的异常海温,在WPWP区域异常海温东传过程中,赤道潜流起了重要作用。     

4DVAR Data Assimilation with the Regional Ocean Modeling System (ROMS): Impact on the Water Mass Distributions in the Yellow Sea

In this study, we evaluate the performance of the recently developed incremental strong constraint 4-dimensional variational (4DVAR) data assimilation applied to the Yellow Sea (YS) using the Regional Ocean Modeling System (ROMS). Two assimilation experiments are compared: assimilating remote-sensed sea surface temperature (SST) and both the SST and in-situ profiles measured by shipboard CTD casts into a regional ocean modeling from January to December of 2011. By comparing the two assimilation experiments against a free-run without data assimilation, we investigate how the assimilation affects the hydrographic structures in the YS. Results indicate that the SST assimilation notably improves the model behavior at the surface when compared to the non-assimilative free-run. The SST assimilation also has an impact on the subsurface water structure in the eastern YS; however, the improvement is seasonally dependent, that is, the correction becomes more effective in winter than in summer. This is due to a strong stratification in summer that prevents the assimilation of SST from affecting the subsurface temperature. A significant improvement to the subsurface temperature is made when the in-situ profiles of temperature and salinity are assimilated, forming a tongue-shaped YS bottom cold water from the YS toward the southwestern seas of Jeju Island.     

Comparison of EnOI and EnKF regional ocean reanalysis systems

This study compares two regional eddy resolving ocean reanalysis systems, based on the ensemble Kalman filter (EnKF) and ensemble optimal interpolation (EnOI), focusing on data assimilation aspects. Both systems are configured for the Tasman Sea using the same ocean model with 0.1° resolution and commonly available observations of satellite altimetry, sea surface temperature and subsurface temperature and salinity. The primary goals are to quantify the difference in performance of the EnKF and EnOI and investigate how important this difference might be from an oceanographic perspective. We find that both systems generally constrain mesoscale circulation in the region, with some exceptions for the East Australian Current separation region, the most energetic and chaotic part of the domain. Overall, the EnKF is found to consistently outperform the EnOI, producing on average 9–21% smaller innovations. The EnKF also has better forecast skill relative to the persisted analysis than the EnOI. For SST the EnKF forecast outperforms persisted analysis by about 17%, which indicates that the surface circulation is mainly constrained. The EnKF and EnOI are shown to produce qualitatively different increments of unobserved or sparsely observed variables; however, we find only moderate improvements of the EnKF over EnOI in subsurface temperature fields when compared against withheld XBT observations. We attribute this lack of a major improvement in subsurface reconstruction to the inability of the EnKF to linearly constrain the system due to initialisation shock, model error caused by open boundaries, and possibly insufficient observations.     

El Ni(n)o phenomenon in simple ocean data assimilation data

To study how the air and sea interact with each other during El Nino/La Nina onsets, extended associate pattern analysis (EAPA) is adopted with the simple ocean data assimilation (SODA) data. The results show that as El Nino/La Nina' s parents their behaviors are quite different, there does not exist a relatively independent tropical atmosphere but does exist a relatively independent tropical Pacific Ocean because the air is heated from the bottom surface instead of the top surface and of much stronger baroclinic instability than the sea and has a very large inter-tropical convergence zone covering the most tropical Pacific Ocean. The idea that it is the wester burst and wind convergence, coming from middle latitudes directly that produce the seawater eastward movement and meridional convergence in the upper levels and result in the typical El Nino sea surface temperature warm signal is confirmed again.     

北太平洋副热带海洋环流强度异常对长江中下游夏季降水的影响

利用SODA资料和ECCO资料计算得到的北太平洋副热带海洋环流强度,和国家气候中心整编的中国160站逐月降水资料,结合NCEP/NCAR再分析资料和Hadley中心海表面温度资料,分析了1970－2007年海洋环流强度异常同期的大尺度大气环流异常特征及对中国东部夏季降水的影响。结果表明:海洋环流强度变化与长江中下游地区降水存在密切的反相关。环流强度异常可以通过影响西太平洋副热带高压的南北位置异常进而影响长江中下游降水。海洋环流偏弱时,副高位置偏南,长江中下游地区受气旋性环流异常影响,来自副高西北侧的强西南水汽输送至此,在该地区形成强水汽辐合中心,同时伴随上升运动加强和对流的加强,进一步导致该地区降水偏多;当海洋环流偏强时,西太平洋副高位置偏北,长江中下游地区受反气旋性环流异常影响,伴随辐散下沉及水汽辐散,导致该地区降水偏少;海洋环流强度异常导致的中纬度海区海表面温度异常,可能是导致副高南北位置异常的主要原因。     

E1 Nio phenomenon in simple ocean data assimilation data

1 IntroductionIt is well known that interaction between the trop-ical ocean and atmosphere produces the largest inter-annual climate signal, El Nino-Southern Oscillation(ENSO). In past decades many efforts have been madein understanding and predicting ENSO: such as the hy-pothesis of Bjerknes (1969) that ENSO arises as aself-sustained cycle in which SSTA in the Pacific O-cean causes the trade winds to strengthen or slackenand that this in turn drives the ocean circulation changesthat …