The Development Of A Wave-tide-circulation Coupled Model And Its Upwelling Simulation Application In The Indonesian Seas

As a large biodiversity region and with high potential fish resources, Indonesia isknown as a productive marine area with4.8million tons/year pelagic fish production.Upwelling, as an area of rising water and the vertical upward movements that reach thesurface, is known regionally to identify fish abundance. An accurate upwelling predictionwould help the well-documented relationship with fisheries production and provide scientificsupport for fishery management to assist the local government in developing the economicresources in their region. To develop some simple series that can represent variations ofupwelling is also an urgent demand for information on the locations and times of strongupwelling eventsThe three-dimensional wave-tide-circulation coupled model developed by theLaboratory of Marine Sciences and Numerical Modeling （MASNUM）, State OceanicAdministration of China has been set up for the China seas, and it has dramatically improvedthe performance of the numerical circulation model. The model also shows a reasonably goodperformance in Malaysian water simulation. The wave-tide-circulation coupled model now isset up to simulate the upwelling in Indonesian seas and implemented on the southern coast ofJava. This region is known as a strong upwelling region, and some previous studies havebeen conducted to adopt upwelling mechanisms.The stability of vertical velocity is used as the basis for the calculation of anupwelling index, instead of calculating the frequency of upwelling based on the changes ofsea surface temperature and Ekman transport which have often been used as an upwellingindex. The index is used to represent the upwelling variations and also compared with thechlorophyll-a variations and fisheries production. The reason for using the numerical modelto define the upwelling index is that the model with realistic forcing is an inexpensive andflexible tool that can calculate variables and relationships with high resolution in both spaceand time. The simulations used in this study employed the parallelization computing methodto deal with the computational problem. To check its accuracy, the model results have been validated and examined againstsatellite data and field observation data. Significant Wave Height （SWH） from the wavemodel was compared with SWH from altimeter data which obtained from Jason-1satellitedata. The lateral boundary can produce significant errors to the wave model and errors duringwinter time are larger than that in summer. Some errors are also found in the coupled modelwhen we validate the coupled model with observed data. The insufficient grid resolutioncannot cover the local influences at measurement position. The other possible cause is thatthe sigma coordinate conversion may not represent the subsurface layer optimally. Theinsufficient temporal resolution also may cause some error. Another factor of the error may beattributed to the inaccuracy of meterological forcings.In general, the model can produce the upwelling index and show positiverelationships with chlorophyll-a and fish catch data. The model shows that the verticalvelocity in east Java is stronger compared with other regions. In vertical, the strongestvertical velocity is at approximately80m depth, and with the annual averaged values of2.3x10^-6m/s,2x10^-6m/s and1.06x10^-5m/s for three regions: south of west Java, south ofcentral Java and south of east Java, respectively. From the vertical velocity profile, the modelresults also show that upwelling in west Java and central Java shows seasonal variabilitywhile it is quite steady and strong for east Java. Numerical experiments show that the wind isnot responsible for the steady upwelling in south of east Java. It is expected that the SouthEquatorial Current （SEC） and Indonesian Throughflow （ITF） may be responsible for theamount of upwelling. ITF plays an important role in the upwelling system and can control thesystem55–65%.The strongest vertical velocity is used as a reference to define the upwelling index andwas implemented in the three regions. Upwelling intensity from the upwelling index seemsto be modulated by the Indian Ocean Dipole. The positive relationships between fish catchdata and the index of upwelling is analyzed.