Kinetic Energy Variability in the North Indian Ocean Using a Numerical Model

The North Indian Ocean exhibits profound impact of variation in lower tropospheric winds. In the present study climatological monthly winds are used to force a nonlinear reduced gravity model of the North Indian Ocean to simulate climatological surface circulation and sea level anomaly for all 12 months of the year. The sea level anomalies agree reasonably well with satellite altimeter derived sea level anomalies. The model successfully simulates the varying eddy structure and current pattern of the North Indian Ocean. Finally, the kinetic energy variation in the North Indian Ocean with special reference to equatorial region and the boundaries is analyzed in detail.     

Kinetic Energy Variability in the North Indian Ocean Using a Numerical Model

The North Indian Ocean exhibits profound impact of variation in lower tropospheric winds. In the present study climatological monthly winds are used to force a nonlinear reduced gravity model of the North Indian Ocean to simulate climatological surface circulation and sea level anomaly for all 12 months of the year. The sea level anomalies agree reasonably well with satellite altimeter derived sea level anomalies. The model successfully simulates the varying eddy structure and current pattern of the North Indian Ocean. Finally, the kinetic energy variation in the North Indian Ocean with special reference to equatorial region and the boundaries is analyzed in detail.     

Inter-Comparison of Numerical Model Generated Surface Winds with QuikSCAT Winds over the Indian Ocean

The accurate surface wind in the equatorial Indian Ocean is crucial for modeling ocean circulation over this region. In this study, the surface wind analysis generated at the European Center for Medium Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP) are compared with NASA QuikSCAT satellite derived Level2B (swath level) and Level3 (gridded) surface winds for the year 2005. It is observed that the ECMWF winds exhibit speed bias of 1.5 m/s with respect to QuikSCAT Level3 in the southern equatorial Indian Ocean. The NCEP winds are found to exhibit speed bias (1.0–1.5 m/s) in the southern equatorial Indian Ocean specifically during January–February 2005. The biases are also observed in the analysis when compared with Level2B product as well; however, it is less in comparison to Level3 products. The amplitude of daily variations of both ECMWF and NCEP wind speed in Bay of Bengal and parts of the Arabian Sea is about 80% of that in QuikSCAT, while in the equatorial Indian Ocean it is about 60% of that of QuikSCAT.     

Ocean Model Simulation of Southern Indian Ocean Surface Currents

The dynamic importance of the Southern Indian Ocean (SIO) lies in the fact that it connects the three major world oceans: the Pacific, Atlantic, and Indian Oceans. Modeling study has been used to understand the circulation pattern of this very important region. Simulation of SIO (10°N-60°S and 30°E-120°E) is performed with z-coordinate Ocean General Circulation Model (OGCM) viz; MOM3.0 and the results have been compared with observed ship drift data. It is found that except near coastal boundaries and in equatorial region, the simulated current reproduce most well known current pattern such as Antarctic Circumpolar Current (ACC), South Equatorial Current (SEC) etc. and bears a resemblance to that of the observed data; however the magnitude of the surface current is weaker in model than the observed data, which may be due to deficiency in the forcing field and boundary condition and problem with observed data. The annual mean wind stress curl computed over the oceanic domain reveals about ACC and its similar importance. The way in which the ocean responds to the windstress and vertically integrated transport using model output is fascinating and rather good.     

Ocean Model Simulation of Southern Indian Ocean Surface Currents

The dynamic importance of the Southern Indian Ocean (SIO) lies in the fact that it connects the three major world oceans: the Pacific, Atlantic, and Indian Oceans. Modeling study has been used to understand the circulation pattern of this very important region. Simulation of SIO (10°N–60°S and 30°E–120°E) is performed with z-coordinate Ocean General Circulation Model (OGCM) viz; MOM3.0 and the results have been compared with observed ship drift data. It is found that except near coastal boundaries and in equatorial region, the simulated current reproduce most well known current pattern such as Antarctic Circumpolar Current (ACC), South Equatorial Current (SEC) etc. and bears a resemblance to that of the observed data; however the magnitude of the surface current is weaker in model than the observed data, which may be due to deficiency in the forcing field and boundary condition and problem with observed data. The annual mean wind stress curl computed over the oceanic domain reveals about ACC and its similar importance. The way in which the ocean responds to the windstress and vertically integrated transport using model output is fascinating and rather good.     

Simulated Heat Content Variability in the Upper Layers of the Tropical Indian Ocean

Ocean General Circulation Model (OGCM) simulations from 1970–2007 are used to study the upper ocean heat content variability in the Tropical Indian Ocean (TIO). Model computed heat contents up to 50 m (denoted by HC50 m hereafter) representing upper ocean heat content and 300 m (HC300 m) representing heat content up to thermocline depth are first compared with heat contents computed from observations of two buoys in the TIO. It is found that there is good agreement between the model and observations. Fourier analysis of heat content is carried out in different regions of TIO. The amplitudes of semi-annual variability for HC50 m and HC300 m are observed to be greater than those for the annual variability in the Bay of Bengal, while in the Arabian Sea there is a mixed result. Heat content tendency is known to be governed by net surface heat flux and horizontal as well as vertical heat transports. For understanding the relative importance of these processes, a detailed analysis of these terms in the tendency equation is carried out. Rossby wave is observed in the annual mode of heat transport while equatorial jet and Kelvin waves are observed in the semi-annual mode of heart transport. Finally, the correlation between heat content and sea surface temperature (SST) and sea level anomaly (SLA), taken one at a time, is computed. It is found that the correlation improves significantly when both these quantities are together taken into account.     

北印度洋半日潮波的数值模拟研究

基于FVCOM(Finite Volume Coast and Ocean Model)模型,建立北印度洋海域(31^°~102^°E,16^°S~31^°N)的M₂和S₂分潮潮波数值模式,研究北印度洋半日潮潮汐、潮流分布特征。对底摩擦系数进行数值试验,利用代价函数梯度下降法,得到分潮调和常数向量均方根偏差(RMSE)的变化曲线,逼近并确定最优的底摩擦系数。将采用该系数的模拟结果与TOPEX/Poseidon卫星高度计交叉点的调和常数数据、国际海道测量组织(IHO)及部分文献中的验潮站数据进行比较与验证,一致性较好。其中对比卫星数据的振幅偏差为2~4 cm、迟角偏差为7^°~8^°,与验潮站数据的振幅偏差为3~6 cm、迟角偏差为8^°~9^°。根据模拟结果,分析了北印度洋海域M₂和S₂分潮潮波传播特征和潮流椭圆的空间分布特征等。M₂分潮潮波在阿拉伯海南部有1个无潮点,在波斯湾内有2个无潮点,最大振幅超过80 cm;潮流在西北印度洋和孟加拉湾中部大多为顺时针旋转,其余海域大多为逆时针旋转;流速在阿拉伯海东北部、安达曼海、波斯湾和孟加拉湾北部较大,最大流速为160 cm/s,其他海域较小。S₂分潮的潮波传播特征、无潮点的位置和潮流椭圆的空间分布特征等都与M₂分潮类似,但潮波振幅和潮流流速等都相对M₂分潮较小。研究完善了北印度洋海域2个主要半日分潮M₂和S₂的整体特征。     

Statistical characteristics and mechanisms of mesoscale eddies in the North Indian Ocean

The statistical characteristics and mechanisms of mesoscale eddies in the North Indian Ocean are investigated by adopting multi-sensor satellite data from 1993 to 2019. In the Arabian Sea(AS), seasonal variation of eddy characteristics is remarkable, while the intraseasonal variability caused by planetary waves is crucial in the Bay of Bengal(BOB). Seasonal variation of the eddy kinetic energy(EKE) is distinct along the west boundary of AS,especially in the Somali Current region. In the BOB, lar...     

北太平洋西部和印度洋东部及其邻近海域表层水体中137Cs的分布

对北太平洋西部海域、苏禄海及印尼海、中国南海、印度洋东部海域、孟加拉湾及安达曼海等表层水体中放射性核素137Cs的活度进行了测定。结果表明,上述海域表层水体中137Cs活度显示了较大的变化范围,最低值出现在南极附近的南大洋(1.1Bqm-3),较高的活度值则出现在北太平洋西部海域及中国南海(3Bqm-3)。在所研究水域范围内,137Cs活度的纬度分布特征并没有完全有效地反映出137Cs的全球理论大气沉降趋势及其纬度效应。综合本研究及Miyake等人(1988)的测定结果,我们计算出137Cs自表层海水中的析出速率在苏禄海及印尼海约为0.016/a,在孟加拉湾及安达曼海约为0.033/a,在中国南海约为0.029/a,这一结果明显低于西北太平洋日本沿海表层水体中137Cs的析出速率。这可能是因为在这些海域,横向及纵向的水体混合过程相对都较慢,而且颗粒物对137Cs的吸附析出过程也比较弱所致。     

全球大洋潮汐模式在北印度洋潮汐预报准确性的评估

为评估DTU10、TPXO8、GOT00.2和NAO.99b 4个全球大洋潮汐模式对北印度洋潮汐的预报能力,采用英国海洋资料中心提供的海区中部和沿岸站潮汐调和常数资料,检验了这些模式4个主要分潮(M_2、S_2、K_1、O_1)的准确度。它们的各分潮调和常数资料准确度都比较高,振幅绝均差的最大值仅5.61 cm,迟角绝均差的最大值仅9.13°。这些模式的调和常数给出潮波传播特征差别不大。基于这些模式提供的调和常数,分别建立了北印度洋4、8和16分潮潮汐预报模型,将预报结果与中国海事服务网提供的沿岸24个站潮汐表资料进行对比。各模式的8分潮(M_2、S_2、N_2、K_2、K_1、O_1、P_1、Q_1)潮汐预报模型均优于4分潮(M_2、S_2、K_1、O_1)潮汐预报模型,NAO.99b模式可以提供16分潮(M_2、S_2、N_2、K_2、K_1、O_1、P_1、Q_1、MU_2、NU_2、T_2、L_2、2N_2、J_1、M1、OO_1)潮汐预报模型,但是对预报结果改善不明显;在各模式中,GOT00.2模式的8分潮潮汐预报模型对北印度洋沿岸的预报效果最好,平均绝均差为14.97 cm。     

Comparison of TOPEX/POSEIDON Altimeter Derived Wind Speed and Wave Parameters with Ocean Buoy Data in the North Indian Ocean

Results of comparison exercises carried out between the state-of-the-art TOPEX/POSEIDON altimeter-derived ocean surface wind speed and ocean wave parameters (significant wave height and wave period) and those measured by a set of ocean data buoys in the North Indian Ocean are presented in this article. Altimeter-derived significant wave height values exhibited rms deviation as small as - 0.3 m, and surface wind speed of - 1.6 m/s. These results are found consistent with those found for the Pacific Ocean. For estimation of ocean wave period, the spectral moments-based semiempirical approach, earlier applied on GEOSAT data, was extended to TOPEX/POSEIDON. For this purpose, distributions of first four years of TOPEX/POSEIDON altimeter data and climatology over the North Indian Ocean were analyzed and a new set of coefficients generated for estimation of wave period. It is shown that wave periods thus estimated from TOPEX/POSEIDON data (for the subsequent two years), when compared with independent data set of ocean data buoys deployed in the North Indian Ocean, exhibit improved accuracy (rms ~ - 1.4 nos) over those determined earlier with GEOSAT data.     

Comparison of TOPEX/POSEIDON Altimeter Derived Wind Speed and Wave Parameters with Ocean Buoy Data in the North Indian Ocean

Results of comparison exercises carried out between the state-of-the-art TOPEX/POSEIDON altimeter-derived ocean surface wind speed and ocean wave parameters (significant wave height and wave period) and those measured by a set of ocean data buoys in the North Indian Ocean are presented in this article. Altimeter-derived significant wave height values exhibited rms deviation as small as ±0.3 m, and surface wind speed of ±1.6 m/s. These results are found consistent with those found for the Pacific Ocean. For estimation of ocean wave period, the spectral moments-based semiempirical approach, earlier applied on GEOSAT data, was extended to TOPEX/POSEIDON. For this purpose, distributions of first four years of TOPEX/POSEIDON altimeter data and climatology over the North Indian Ocean were analyzed and a new set of coefficients generated for estimation of wave period. It is shown that wave periods thus estimated from TOPEX/POSEIDON data (for the subsequent two years), when compared with independent data set of ocean data buoys deployed in the North Indian Ocean, exhibit improved accuracy (rms ~ ±1.4 nos) over those determined earlier with GEOSAT data.     

近44年北印度洋海表风速变化趋势分析

利用来自ECMWF的ERA-40风场资料,就北印度洋海表风速的长期变化趋势展开分析,以期可为海洋水文保障、防灾减灾、研究全球气候变化提供参考.结果表明:(1)1958-2001年期间,北印度洋低纬度海域、索马里至斯里兰卡一带的大范围海域的海表风速表现出显著的逐年线性递增趋势,基本在0.01-0.02 m·s-1·a-1;呈显著性递减的区域主要分布于亚丁湾、红海、波斯湾、斯里兰卡北部零星海域、以及缅甸仰光西南部近海等小范围海域,约-0.01-0.005m·s-1·a-1;阿拉伯海、孟加拉湾等海域的海表风速在近44年期间则无显著性变化趋势;(2)近44年期间,北印度洋海域的海表风速整体上以0.0061m·s-1 ·a-1的速度显著性震荡递增,震荡区间在5.0-5.5 m·S-1之间;(3)不同海域海表风速的变化趋势在不同季节表现出很大差异:冬季和夏季,大部分海域海表风速的变化趋势显著,春季次之,秋季仅在赤道附近一带海域呈显著性递增;(4)近44年期间,北印度洋的海表风速存在显著的2.0年、2.6-3.7年、5.2年的变化周期,以及26年以上的长周期震荡.     

近45 年南海-北印度洋波浪能资源评估

利用 ERA-40海表10 m 风场驱动第三代海浪数值模式(WAVEWATCH-,Ⅲ简称 WW3),得到南海–北印度洋1957年9月~2002年8月的海浪资料,计算该海域的波浪能,分析波浪能流密度的四季分布特征、不同能级出现的频率及波浪能流密度的稳定性,为海浪发电、海水淡化等选址提供依据.研究发现,南海–北印度洋海域蕴藏着较为丰富的波浪能:(1)南海–北印度洋大部分海域的年平均波浪能流密度在2 kW/m 以上,大值区位于南海、孟加拉湾、索马里附近海域.(2)南海–北印度洋海域波浪能流密度大于2 kW/m 和大于4 kW/m 出现的频率都较高.(3)南海–北印度洋的波浪能流密度具有较好的稳定性,春季、秋季、冬季的稳定性好于夏季,南海的稳定性好于北印度洋