Short-Range Prediction Experiments with Operational Data Assimilation System for the Kuroshio South of Japan

The short-range (one month) variability of the Kuroshio path was predicted in 84 experiments (90-day predictions) using a model in an operational data assimilation system based on data from 1993 to 1999. The predictions started from an initial condition or members of a set of initial conditions, obtained in a reanalysis experiment. The predictions represent the transition from straight to meander of the Kuroshio path, and the results have been analyzed according to previously proposed mechanisms of the transition with eddy propagation and interaction acting as a trigger of the meander and self-sustained oscillation. The reanalysis shows that the meander evolves due to eddy activity. Simulation (no assimilation) shows no meander state, even with the same atmospheric forcing as the prediction. It is suggested therefore that the initial condition contains information on the meander and the system can represent the evolution. Mean (standard deviation) values of the axis error for all 84 cases are 13, 17, and 20 (10, 10, and 12) km, in 138.5°E, in the 30-, 60-, and 90-day predictions respectively. The observed mean deviation from seasonal variation is 30 km. The predictive limit of the system is thus about 80 days. The time scale of the limit depends on which stage in the transition is adopted as the initial condition. The gradual decrease of the amplitude in a stage from meander to straight paths is also predicted. The predictive limit is about 20 days, which is shorter than the prediction of the opposite transition. This revised version was published online in July 2006 with corrections to the Cover Date.     

Sequential forecasting of the surface and subsurface conditions in the Japan Sea

This study estimates a realistic change of the Japan Sea by assimilating satellite measurements into an eddy-resolving circulation model. Suboptimal but feasible assimilation schemes of approximate filtering and nudging play essential roles in the system. The sequential update of error covariance significantly outperforms the asymptotic covariance in the sequential assimilation due to the irregular sampling patterns from multiple altimeter satellites. The best estimates show an average rms difference of only 1.2°C from the radiometer data, and also explain about half of the sea level variance measured by the altimeter observation. The subsurface conditions associated with the mesoscale variabilities are also improved, especially in the Tsushima Warm Current region. It is demonstrated that the forecast limit strongly depends on variable, depth, and location.     

Mass, Heat and Salt Balances in the Eastern Barents Sea Obtained by Inversion of Hydrographic Section Data

Standard hydrological section data, collected in the eastern Barents Sea in September 1997, have been analyzed using a variational data assimilation technique. This method allows us to obtain temperature, salinity and velocity fields that are consistent with observations and dynamically balanced within the framework of a steady-state model describing large-scale nearly geostrophic circulation. Error bars of the optimized fields are computed by explicit inversion of the Hessian matrix. The optimized velocity field is in agreement with independent velocity observations derived from surface drifter trajectories in the southwestern part of the Barents Sea. Optimized fields provide the following estimates of integral characteristics of the circulation in the region: i) the North Cape current transport is 2.12 ± 0.25 Sv; ii) the Karskie Vorota Strait throughflow is 0.7 ± 0.06 Sv; iii) heat flux with Atlantic water is 4.7 ± 0.16⋅10¹¹ W; iv) salt import from the Atlantic Ocean is 7.41 ± 0.46⋅10³ kg/s. The imbalance of the heat budget in the eastern part of the Barents Sea indicates the presence of statistically insignificant surface heat fluxes which are less than 1 W/m². This revised version was published online in July 2006 with corrections to the Cover Date.     

Evaluation of the U.S. Navy’s Modular Ocean Data Assimilation System (MODAS) Using South China Sea Monsoon Experiment (SCSMEX) Data

The Navy’s Modular Ocean Data Assimilation System (MODAS) is an oceanographic tool to create high-resolution temperature and salinity on three-dimensional grids, by assimilating a wide range of ocean observations into a starting field. The MODAS products are used to generate the sound speed for ocean acoustic modeling applications. Hydrographic data acquired from the South China Sea Monsoon Experiment (SCSMEX) from April through June 1998 are used to verify the MODAS model. MODAS has the capability to provide reasonably good temperature and salinity nowcast fields. The errors have a Gaussian-type distribution with mean temperature nearly zero and mean salinity of −0.2 ppt. The standard deviations of temperature and salinity errors are 0.98°C and 0.22 ppt, respectively. The skill score of the temperature nowcast is positive, except at depth between 1750 and 2250 m. The skill score of the salinity nowcast is less than that of the temperature nowcast, especially at depth between 300 and 400, where the skill score is negative. Thermocline and halocline identified from the MODAS temperature and salinity fields are weaker than those based on SCSMEX data. The maximum discrepancy between the two is in the thermocline and halocline. The thermocline depth estimated from the MODAS temperature field is 10–40 m shallower than that from the SCSMEX data. The vertical temperature gradient across the thermocline computed from the MODAS field is around 0.14°C/m, weaker than that calculated from the SCSMEX data (0.19°–0.27 °C/m). The thermocline thickness computed from the MODAS field has less temporal variation than that calculated from the SCSMEX data (40–100 m). The halocline depth estimated from the MODAS salinity field is always deeper than that from the SCSMEX data. Its thickness computed from the MODAS field varies slowly around 30 m, which is generally thinner than that calculated from the SCSMEX data (28–46 m).     

Balance of Volume Transports between Horizontal Circulation and Meridional Overturn in the North Pacific Subarctic Region

Horizontal and meridional volume transports on timescales from intra-seasonal to interannual in the North Pacific subarctic region were investigated using a reanalysis dataset for 1993–2001 that was constructed from an assimilation of the TOPEX altimeter and in situ data into an eddy-permitting North Pacific ocean general circulation model. The barotropic flow is excited along east of the Emperor Seamounts by the western intensification dynamics. The volume transport of this flow compensates for that across the interior region east of the Seamounts below the summit depth of the Seamounts. The Oyashio, which is also considered as a compensation flow for the transport in the whole interior region, includes baroclinic as well as barotropic components. Baroclinic transports in the whole interior region exceed those in the western boundary region in the upper (200–1000 m) and lower (2000–5000 m) layers, and the total transport is northward (southward) in the upper (lower) layer. These excesses of the baroclinic transport are balanced by a vertical transport of the meridional overturn. The meridional overturn has a complementary relation to the basin-scale baroclinic circulation in the North Pacific subactic region. This revised version was published online in July 2006 with corrections to the Cover Date.     

Ocean Data Assimilation in the Tropical Pacific: A Short Survey

This short survey presents several research and operational developments of ocean data assimilation in the tropical Pacific, primarily for climate-scale phenomena. Aspects of theoretical error estimations, diagnostics and practical reduced space techniques are also briefly reported. This revised version was published online in August 2006 with corrections to the Cover Date.     

Impact on the tropical cyclone “Vongfong” forecast using the Quik SCAT wind data

Since QuikSCAT is available in cloudy and rainy condition, its wind data are valuable in monitoring and real timeorecasting the wind field, especially in sparse genesis regions of tropical cyclones. In order to understand and investigate the impact of QuikSCAT wind data, the three-dimensional variational data assimilation (3D-VAR) of scatterometric wind data has been employed for the tropical cyclone “Vongfong” in the year 2002. The result shows that the QuikSCAT wind data have positive impact on the analysis and forecasting. But the positive impact is slight. The present results suggest that how to assimilate QuikSCAT wind data effectively is important and will be a challenge to meteorologists.     

FY-3C积雪产品在同化中对微波资料质量控制的影响分析

T639-GSI全球系统同化AMSU-A资料的过程中,目前使用的月平均积雪产品并不能反映中高纬度大陆上快速地降雪/融雪过程,而FY-3C日积雪产品在时间精度上要高于GSI月平均积雪覆盖数据。由于同化系统对AMSU-A较低通道辐射率资料的质量控制需要依据更准确的地表积雪信息,所以本文结合冬春季节的FY-3C日积雪产品和NCEP再分析资料,研究了北半球中高纬度地区不同积雪覆盖率初值对分析场不同高度层温度场的影响,以及在同化过程中对预报结果的影响。结果表明,在对AMSU-A辐射率资料的质量控制中,月平均积雪数据和日积雪产品对温度场影响较大的区域与两者积雪覆盖差异区域有明显的对应;冬春季节,使用FY-3C日积雪产品代替GSI月平均积雪数据作为背景场中积雪下垫面数据,对进入同化系统的AMSU-A辐射率资料质量控制时,120 h之内1000—600 h Pa的中低层温度场的预报效果得到改善。