GODAE Final Symposium

Asia and Oceania Applications

Jiang Zhu1, Toshiyuki Awaji2, Gary B. Brassington3, Norihisa Usuii4, Naoki Hirose5, Young Ho Kim6, Qinzheng Liu7, Jun She8, Yasumasa Miyazawa9, Tatsuro Watanabe10, and M.Ravichandran 11 1Institute of Atmospheric Physics, Chinese Academy of Sciences 2Kyoto University, Japan 3Centre for Australian Weather and Climate Research, Bureau of Meteorology 4Japan Meteorological Agency, Japan 5Kyushu University, Japan 6Korea Ocean Research and Development Institute, Korea 7National Marine Environmental Forecasting Center, China 8Denmark Meteorological Institute, Denmark 9JAMSTEC, Japan 10JSNFRI, Fisheries Res. Agency, Japan 11Indian National Centre for Ocean Information Services (INCOIS), India

Abstract During the GODAE period, some coastal and regional systems for short-range ocean forecasts in the Asia-Oceania have been developed. This paper first provides an overview of these operational forecast systems and some pre-operational systems developed by Australia, China, Denmark, India, Japan and Korea in the terms of model domain, resolutions, models, data inputs and data assimilation schemes. These systems cover some key ocean areas in Asia-Oceania. Then services, products, users and feedbacks provided by these systems are shown briefly. Some operational ocean analyses and forecasts support both data products and online graphical public services. Some systems such as the Bluelink ocean forecasting system of Australia have proved skilful in forecasting, coastally trapped waves, coastal upwelling, offshore ocean state and currents of the Australia’s boundary currents. As evidence of the utility of these regional systems, some highlighted examples as also given. For example, some Japanese systems successfully predicted the Korushio large meander in 2004; an operational system provided service for the 2008 Olympic sailing events; a Japan Sea/East Sea forecasting system has been used for successful reproduction and prediction of large numbers of giant jellyfishes in Japan/Sea Sea. All these systems are strongly connected with the GODAE products. The Argo and GHRSST datasets are essential inputs for initialization of these forecast systems. The Indian Ocean is relatively less covered by these regional systems. However, GOOS-CLIVAR’s effort in establishing Indian Ocean Observing system will improve the situation and some of its progresses are highlighted. Some future plans are also briefly outlined.

Key words: Ocean forecasting, Asia, Oceania, GODAE

1. Introduction Coastal ocean nowcast/forecast systems are an increased interest in a wide range of society. For instance, improved forecasts of future states in target areas are required for marine management and rescues, pollution control, and mitigation of the damage of coastal flooding and harmful algal blooms, in addition to the traditional requirement of shipping navigation and fishery managements. The 2002 GODAE Development and Implementation Plan states: “Climate and seasonal forecasting, navy applications, marine safety, fisheries, the offshore industry and management of shelf/coastal areas are among the expected beneficiaries of GODAE.” The usefulness of GODAE systems to coastal and shelf seas forecasting will therefore be one of the measures of the success of the project. During the GODAE period, various coastal and regional systems for short-range ocean forecasts in the Asia-Oceania have been developed. Operational forecast systems and some pre-operational systems developed by Australia, China, Denmark, India, Japan and Korea. These systems cover some key ocean areas in Asia-Oceania.

Bluelink is an Australian partnership between the Commonwealth Scientific and Industrial Research GODAE Final Symposium

Organisation, the Australian Bureau of Meteorology (ABoM) and the Royal Australian Navy. The primary objective of Bluelink is the development of a forecast system for the mesoscale ocean circulation in the Australian region and adjacent basins that influence this region. The Bluelink forecast system (Brassington et al. 2007) became operational at the ABoM in August 2007 providing seven day forecasts twice per week.

In Japan, several systems have been developed. Japan Meteorological Agency (JMA) started operational use of new ocean analysis / forecasting system for western North Pacific in 2008 March. This system provides the information of the ocean state in the Sea around Japan. Monitoring and forecasting of major currents around Japan such as the Kuroshio, the Oyashio, and the Tsushima current are particularly paid attention because variations of these currents strongly affect the ocean state around Japan. Outputs of this system are made use of for various purposes. The current field in this system is used for prediction of the position of drifting targets (e.g., oil spill). Also, the ocean state in this system is used for identifying causes of coastal sea level variation associated with unusual sea level. Japan Agency for Marine-Earth Science and Technology (JAMSTEC) has started an operational ocean forecast experiment for Northwestern Pacific (Japan Coastal Ocean Predictability Experiment; JCOPE) since December 2001. Fisherier Reseach Agency (FRA) has operated first version of JCOPE ocean forecast system (JCOPE1) since April 2007 for management of fishery resources off Japan through development of coupling with ecosystem models (FRA- JCOPE). JAMSTEC has further developed second version of the system (JCOPE2) with enhanced model and data assimilation schemes. Output of JCOPE2 is used for ship routing of oil tankers, fishery and drilling ships. Most recently Kyoto University has constructed a high-resolution 4-dimensional variational (4D- VAR) ocean data assimilation system with an aim to develop the integrated monitoring of synoptic to meso- scale features observed in the mixed water region for the northwestern North Pacific where is one of the most energetic regions in the world oceans. They have demonstrated that the downscaling is a powerful approach toward the better nowcast and forecast of coastal circulations in the regions such as offshore of Shimokita Peninsula where vigorous interactions with the marginal seas occur.

National Marine Environment Forecast Centre (NMEFC) of China started its operational numerical ocean forecasting since 1990s. There are several operational forecast systems covering different domains: from large scale western North Pacific to relatively small coastal regions such as Bohai Sea. Their products are delivered to users across public, government and commerce. In 2006, Chinese Academy of Sciences (CAS) started developing a preoperational ocean nowcast/forecast system around the Chinese coast lead by Institute of Atmospheric Physics (IAP). Since 2008, this system development has been enhanced further by multi- institution collaboration and establishing a long term in situ observation network of four offshore buoys that will be operated and maintained by Institute of Oceanography and Institute of South China Sea Oceanography. The aims of the system are to provide a test bed to explore the coast and shelf sea predictability and transit to operational agencies.

Beside above national efforts, international collaboration also plays an important role. Yellow Sea is a semi- enclosed sea surrounded by China and Korea. Extensive research and cooperation have been carried out in this region both in national and international level by China and Korea. However, the existing works yet to be integrated into a forecasting system. Major bottle-necks in developing the Yellow Sea monitoring- forecasting system are the lack of high quality, near real time weather forecasts, as well as coupled 3D ocean-ice models and operational infrastructure. With support from EU FP6 project YEOS (Yellow Sea Observation, forecasting and information System, 2007-2009, http://ocean.dmi.dk/yeos ) and Danish Sailors’ Union, European weather and ocean-ice forecasting system has been applied to the Yellow Sea and a pre- operational weather-ocean-ice forecasting system has been demonstrated in a period covering Beijing Olympic Game 2008. Wide range of users has enjoyed the high resolution ocean and weather services provided by the YEOS information system. YEOS also improved data exchange between China, Korean and EU partners.

2. Overview of systems The geographic coverage of each system is shown in the figure 1. Most of these systems use nesting schemes with different domain/resolution. The single domain for each system in Fig. 1 mainly represents one of its main focuses of each system. Most systems concentrated in the western North Pacific with centres GODAE Final Symposium

in the Japan Islands, Korea Peninsula and Chinese coast. The Bluelink system, surrounding the Australia, cover part of the Southern Ocean and the western Indian Ocean.

2.1 Bluelink The key elements of the Bluelink system are the Bluelink Ocean Data Assimilation System (BODAS; Oke et al. 2005) and the Ocean Forecasting Australia Model (OFAM), a global ocean general circulation model. OFAM is based on version 4.0d of the Modular Ocean Model (Griffies et al. 2004), using the hybrid mixed layer model described by Chen et al. (1994). OFAM is intended to be used for reanalyses and short- range prediction. The horizontal grid has 1191 and 968 points in the zonal and meridional directions respectively; with 1/10 o horizontal resolution around Australia (90-180E, south of 17N). Outside of this domain, the horizontal resolution decreases to 0.9o across the Pacific and Indian basins (to 10E, 60Wand 40N) and Figure 1. The geographic coverage of each system in the Aisa and Oceania. to 2o in the Atlantic Ocean. OFAM has 47 vertical levels, with 10 m resolution down to 200 m depth. The topography for OFAM is a composite of topography from a wide range of sources including dbdb2 (www7320.nrlssc.navy.mil/DBDB2 WWW/) and GEBCO (www.ngdc.noaa.gov/mgg/gebco/). Horizontal diffusion is zero. An ensemble optimal interpolation (EnOI) scheme is used for assimilating sea level anomaly from satellite altimetry, Argo profiles and satellite SST. For detailed description of the assimilation scheme see Oke et al., (2008). The operational system, OceanMAPSv1.0b (Brassington et al., 2007) produces a 9 day hind-analysis and 7 day forecast twice per week using the surface fluxes from the Bureau of Meteorology global weather forecasts and near real- time altimetry is obtained from Jason-1 and Envisat and real-time SST is obtained from AMSR-E. In situ observations are sourced from the GTS and the GDAC's for Argo and sorted fro duplicates and automatically quality controlled. An operational graphical web service (http://www.bom.gov.au/oceanography/forecasts ) and a data product service is supported at the ABoM.

2.2 MOVE/MRI.COM-WNP MOVE/MRI.COM-WNP (Multivariate Ocean Variational Estimation system / Meteorological Research Institute Community Ocean Model – western North Pacific version) uses MRI.COM as ocean model. The vertical coordinate is the -z one with which the layer thickness near the surface follows the surface topography (Hasumi 2006). For the nonlinear momentum advection, the generalized enstrophy-preserving scheme (Arakawa 1972) a12nd the scheme that contains the concept of diagonally upward/downward mass momentum fluxes along the sloping bottom are applied. A biharmonic operator is used for horizontal turbulent mixing. A biharmonic friction with a Smagorinsky-like viscosity (Griffies and Hallberg 2000) is used for momentum. The vertical viscosity and diffusivity are determined by the turbulent closure scheme of Mellor and Blumberg (2004). The model domain spans from 117E to 160W zonally and from 15N to 65N meridionally. The horizontal resolution is variable: it is 1/10o from 117E to 160E and 1/6 o from 160E to 160W, and 1/10 o from 15N to 50N and 1/6 o from 50N to 65N. There are 54 levels in the vertical direction with thickness increasing 1 m at the surface to 600 m near the bottom. Oceanic states at the side boundaries are replaced by those from a North Pacific model (MOVE-NP) with a horizontal resolution of 1/2 o (one-way nesting). A sea ice model with the thermodynamics of Mellor and Kantha (1989) and the elastic-viscous- GODAE Final Symposium

plastic rheology of Hunke and Ducowicz (1997) is also applied. More detailed about the model see Tsujino et al. (2006). The analysis scheme adopted in MOVE is a multivariate three-dimensional variational (3DVAR) analysis scheme with vertical coupled Temperature-Salinity (T-S) Empirical Orthogonal Function (EOF) modal decomposition (Fujii and Kamachi 2003). In this system, the model domain is divided into 13 subregions and vertical T-S EOF modes are calculated from the observed T-S profiles for each subregion. The 3DVAR results are inserted into the model temperature and salinity fields above 1500 m by the incremental analysis updates (Bloom et al. 1996). For more details, see Usui et al. (2006). Iin situ temperature and salinity profiles, satellite sea surface height (SSH) anomaly and sea surface temperature (SST) are assimilated. The temperature and salinity data including ARGO data are obtained from Global Temperature-Salinity Profile Program (GTSPP: http://www.nodc.noaa.gov/GTSPP/)). The SSHA data is the near-real time along-track data of Jason-1 and ENVISAT obtained from Archiving, Validation and Interpretation of Satellite Oceanographic data (AVISO: http://www.jason.oceanobs.com/). The SST data is the MGDSST produced by JMA. The assimilation run is implemented every five days, and the forecasting period of prediction is one month. The model is driven by wind stress and heat flux from the JMA's Climate Data Assimilation System (JCDAS) in assimilation run and forced by the result of the climate forecasting model in forecasting run.

2.3 JCOPE1,2 The ocean model in the JCOPE1,2 systems is based on the Princeton Ocean Model with a generalized coordinate of sigma (POMgcs) (Mellor et al., 2002). A high-resolution regional model with a spatial grid of 1/12 o and 47 vertical levels is embedded in a low-resolution model covering the North Pacific region (30S- 62N, 100E-90W) with a spatial grid of approximately 1/4o and 21 sigma levels. The inner model domain covers the western North Pacific (10.5 -62 N, 108 -180E) and its lateral boundary conditions are determined from the basin-wide model using a one-way nesting method (Guo et al., 2003). The wind stress and heat flux fields are calculated from output of 6-hourry NCEP Global Forecast System (NCEPGFS) or NCEP/NCAR reanalysis (Kalnay et al., 1996). Salinity at the ocean surface is restored to the monthly mean climatology data (Levitus et al., 1994) with a time scale of 30 days. The following observation data are assimilated into the model: the sea surface height anomaly (SSHA) obtained from the TOPEX/Poseidon and ERS-1 satellites during September 1999 to June 2002 and from the Jason-1 and the Geosat Follow-On during June 2002 to present; sea surface temperature (SST) obtained from the Advanced Very High Resolution Radiometer / Multi-Channel Sea Surface Temperature (AVHRR/MCSST) Level 2 products; and vertical profile data of temperature and salinity obtained from GTSPP. The JCOPE1 system (Miyazawa et al., 2008a) uses a combination of optimum interpolation for horizontal gridding of SSHA, SST, and subsurface temperature and salinity data and multivariate optimum interpolation for creation of three-dimentional grid data of temperature and salinity. The temperature and salinity data are introduced into the model using the Incremental Analysis Update (IAU) (Bloom et al., 1996). The JCOPE2 system (Miyazawa et al., 2008b) adopts the 3DVAR scheme with vertical coupled Temperature-Salinity Empirical Orthogonal Function modal decomposition (Fujii and Kamachi 2003).

2.4 Kyoto University System The numerical model used is the ocean general circulation model developed at Kyoto University (e.g., Toyoda et al., 2004), which employs the hybrid σ-z vertical coordinate to better simulate free surface motion of the ocean. To further enhance the representation of the upper ocean circulation, this model adopts some sophisticated parameterizations such as the Takano-Onishi scheme for the momentum equation (Ishizaki and Motoi, 1999), the turbulence closure scheme for the mixed layer parameterization (Noh et al. 2005), the 3rd order scheme (Hasumi, 2000) based on QUICKEST (Leonard, 1979) for vertical advection and UTOPIA (Leonard et al., 1993) for horizontal advection, and the isopycnal mixing scheme (Gent and McWilliams, 1990, Griffies, 1998). The model basin covers the northwestern North Pacific which includes the Sea of Japan and other marginal seas (see Fig. 1). The basic model resolution is 1/6and 1/8 in longitude and latitude, respectively, and 78 vertical levels spaced from 4 m near the sea surface to 500m at the bottom. Note that 67 vertical levels are set above 1000m depth. For the downscaling experiment focusing on the coastal circulation off Shimokita Peninsula, we employ the triple nesting approach from the above basic resolution (nest-1) to the finest resolution of 1/54gand 1/72 (nest-3) in longitude and latitude, respectively, via a medium resolution of 1/18 and 1/24 (nest-2). The nesting technique employed here is based on Oey and Chen (1992). The assimilated elements in this study are satellite-derived SST and sea surface height GODAE Final Symposium

(SSH) data, and in-situ observation data of temperature and salinity. In detail, the SST data are from the New Generation Sea Surface Temperature (NGSST) produced at Tohoku University with a horizontal resolution of 1/20 and daily coverage. The SSH data are from the SSalto/Duacs gridded absolute dynamic topography, which is the sum of the sea level anomaly derived from multi altimeter data and mean dynamic topography (Rio and Hernandez, 2004) provided by AVISO in time intervals of 3.5 days. The horizontal resolution is nearly 1/3o and the SSH data are interpolated onto the model grids for assimilation. The in-situ observation data are obtained from GTSPP. A 4D-VAR approach, optimized 4-dimensional datasets are sought by minimizing a cost function, in which the initial condition of model variables is chosen as the control variable. The cost function is composed of the background and the observational term. For more details, see Awaji et al. (2003) and Ishikawa et al. (2007).

2.5 NMEFC System for western North Pacific The NMEFC’s operational forecast system for the western North Pacific (99-150E; 2-45N) uses POM with a horizontal resolution of 1/4o by 1/4 o and 15 vertical levels. The model is driven by NMEFC’s forecasts of a mesoscale atmospheric model. The data assimilation system utilizes OI for in situ observations (ship reports and Argo profiles) and a nudging scheme for MGDSST. The system produces a daily 3-day forecast of SST of the western North Pacific.

2.6 CAS preoperational system A Chinese shelf/coastal seas model based on a three-dimensional hybrid-coordinate ocean model (HYCOM, Bleck, 2002; Chassignet et al. 2003) is used to simulate ocean circulation around China (Xiao et al, 2007). A curvilinear horizontal grid is utilized with an average horizontal resolution of 13 km. There are 22 layers in the vertical coordinate. Using the real topography, the model domain includes the whole CSCS and part of the West Pacific Ocean (see Figure1). The model was forced by ECMWF 6-hourly reanalysis dataset (Uppala and Kallberg, et al. 2005). And the lateral open boundary conditions were provided by an India- Pacific domain HYCOM simulation (1/4 degree resolution). The data assimilation system has two Table 1. A summary of ocean forecasting systems in the Asia-Oceania regions System Ocean Nesting Atmospheric forcing Ocean data input Data assimilation Agency/ Name model strategy scheme Institution Bluelink OFAM Global BoM's operational In situ T, S; SSHA; EnOI ABoM model global weather SST prediction model MOVE/MRI. MRI.CO One-way JMA's operational In situ temperature 3DVAR with JMA COM-WNP M nesting atmospheric analysis; and salinity; Along vertical coupled Results of climate track SSHA; TS-EOF modes; forecasting model. Gridded SST IAU JCOPE1,2 Modified One-way 6-hourly NCEP Along track SSHA; 3DVAR with JAMSTEC POMgcs nesting Global Forecast In-situ T,S; Along vertical coupled FRA System or track SST. TS-EOF modes; NCEP/NCAR IAU. reanalysis Kyoto U Kyoto U. One-way SST (NGSST); 4D-VAR Kyoto U OGCM nesting Gridded SSH; In- situ T, S. NMEFC POM One-way NMEFC’s mesoscale Gridded SST Nudging for SST NMEFC nesting weather forecast Argo profiles and OI for profiles CAS HYCOM One-way ECMWF reanalysis Gridded SSHA; EnOI IAP nesting mesoscale weather Gridded SST; In forecast situ T, S. YEOS BSHcomd Two-way DMI weather forecast SST Kalman Filtering DMI nesting ESROM MOM3 ECMWF reanalysis In situ temperature; 3DVAR KORDI gridded SSHA; SST alternatives: an EnOI scheme and the ensemble Kalman filter (Wan et al, 2008). The observations used for GODAE Final Symposium

assimilation include GHRSST products, Argo profiles from GTSPP and SSHA from AVISO. Xie et al (2008) compared several GHRSST products in the studied area.

2.7 YEOS The Yellow Sea 3D ocean-ice prediction system is based on DMI (Danish Meteorological Institute) BSHcmod, which is a coupled hydrostatic 3D ocean-ice model based on primitive ocean equations, and a Hibler-type sea ice model (Dick et al., 2001). The baseline set-up operates on two nested, coupled grids, making it possible to zoom in on an area of interest with high resolution. Multi-sensor SST data are assimilated into the model daily by using a simplified Kalman-Filter Scheme (Lasen et al. 2007). The model ocean is driven by atmospheric forcing, river runoff and lateral boundary conditions. Along open boundaries, sea level is specified as a combination of the tidal variation and wind/pressure driven surge. Temperature and salinity are obtained from monthly climatology. Outflowing water is stored in a buffer zone, which must be emptied before water of climatological properties are advected into the model domain. The hourly meteorological products in 7.5km horizontal resolution are derived from DMI operational NWP model HIRLAM. The 3-D ocean model domain covers the Yellow Sea and part of the East China sea, north of 33½ºN and west of 127ºE, with a horizontal resolution of 1/20º (lat.) by 1/15º (lon.) and 30 vertical levels. This is then embedded in a coarse-grid, 2-dimensional external surge model of larger extent. The undisturbed top layer thickness is 6 m in order to avoid tidal drying of the top layer, in which case the model would not be stable. The layers below are of 2 m thickness, with increasing layer thickness towards the sea bed.

2.8 ESROM ESROM(East/Japan Sea Regional Ocean Model), based on the GFDL MOM3(GFDL Modular Ocean Model version 3; Pacanowski and Griffies, 1999), has been driven by monthly mean wind stress from the ECMWF reanalysis, monthly mean heat flux calculated by bulk air-sea flux formulation using ECMWF reanalysis meteorological variables. The surface salt of the model has been restored to that of the WOA hydrographic data. For the open boundary condition, a radiation condition with a nudging term for inward boundary fluxes is applied for the tracers and barotropic currents (Marchesiello et al., 2001). The barotropic velocity through the Korea Strait is given by the volume transport monitored by the submarine cable. Using the 3-dimensional variational assimilation routine (Weaver and Courtier, 2001), the satellite-borne sea surface temperature, sea surface height (SSH) anomaly and temperature profiles have been assimilated. Kim et al. (2008) could verify the performance of the ESROM using an independent measurement dataset by the Pressure-equipped Inverted Echo Sounder in the Ulleung Basin located in the western side of the East/Japan Sea and suggested that the ESROM well reproduced the mesoscale variability as well as the general circulation.

3. Highlighted examples 3.1 Successful prediction of the Kuroshio large meander Some Japanese systems successfully predicted the Korushio large meander in 2004. Figure 2 shows the observations and forecasts of the Figure 2. The Kuroshio large meander formation in 2004. Top (bottom) panel Korushio main path in summer of shows the time sequence of the assimilated (predicted) current fields at 100 m 2004. The forecasts were made by depth. Vector and shade denote the current vector and its magnitude. The MRI system. prediction stars on 1 June) 2004 using the assimilated field as the initial GODAE Final Symposium

3.2 Operational forecast for 2008 Olympic Games An operational demonstration of weather-ocean-wave forecast has been made during August-September 2008 for Beijing Olympic Game. The weather and ocean forecast were made by DMI and wave forecast were made by the First Institute of Oceanography (FIO) by using FIO wave model WAM and forced by DMI on-line weather data. The general results are shown on YEOS website. An interesting event happened on the 49er Medal course, at kl.16 in 17 August 2008. There is an abrupt change of the states of weather and sea. The mast of Danish sailors’ sailing boat was broken due to a gust and rough sea. By borrowing a boat from Croatian team, the Danes still won the gold medal. The following figures show the forecast given by a fine resolution model (in a horizontal resolution of 2.5km resolution) downscaled from YEOS forecast.

Figure 3. High resolution Wind forecast on 17 August 2008. Left: winds time series (in Qingdao local time) at the race area of 49er Medal course of OL2008 in Qingdao; right: surface winds distribution at 2008-08-17- 08GMT in Qingdao waters.

3.3 Prediction of giant jellyfishes Recently large amount of the giant jellyfish (Nemopilema nomurai) came over from the East China Sea to the Japan Sea through the Tsushima Strait, and they migrated to the Japanese coast along the coastal and offshore branches of the Tsushima Warm Current. In 2005 season, especially, excessively large number of the jellyfish was observed for a long period (from early July until March), and serious damages to fisheries occurred. To reproduce and predict the distribution of the jellyfish in the Japan Sea a numerical simulation for the migration of the Jellyfish in 2005 was carried out by using a data assimilation model. The assimilation model was the Japan Sea Forecasting System developed by RIAM, Kyushu University (Hirose et al., 2007). Passive tracers were released from the both east and west channels of the Figure 4. Sightseeing observations of giant jellyfish (left) and tracer Tsushima Strait at the depth of 0-- forecasts (right). 22.5m as artificial jellyfishes. Based on the sightings report around the Tsushima Island, the beginning of the tracer input was set on June 23. After August 16, the calculation was carried out by using predicted current data. The reproduction of the northward migration of the jellyfish was well successful; the northward front position of the jellyfish was good agreement with sightings data within a few days. GODAE Final Symposium

3.4 Reproducing the modal transition of coastal waters off Shimokita Peninsula Coastal waters off Shimokita Peninsula (see figure 5) with a complicated geographic feature well reflects the major features of short-term (a few days) to seasonal-long circulations. A notable feature in this region is vigorous interactions with the marginal seas, particularly with the Sea of Japan through the energetic Tsugaru Warm Current (TWC). In fact, coastal currents off Shimokita Peninsula exhibits a seasonally-varying circulation characterized by a transition of the TWC between two distinct patterns: a straight path along the east coast of Honshu Island in a cold season (hereafter “straight-path mode”) and a swirl-like circulation in a warm season (hereafter “gyre-mode”). In et al. (2008) conducted a Figure 5. Time series of temperature distributions at 200m depth. (left): model and hindcast experiment for the (right) observation. (from In et al., 2008). year 2003 using a triple nesting approach. As a result, the system successfully reproduced the observed transition from the costal mode to the gyre mode and the subsequent opposite one. Figure 5 displays the time series of temperature distributions at 200 m depth, in which warm water of over 7oC that corresponds to the TWC water can be seen near Shimokita Peninsula in both the observation and the model. Interestingly, the warm water begins to extend offshore to form a gyre-like distribution.

3.5 Non-tidal coastal sea level for flood warnings and port management in Australia Accurate and timely warnings of anomalous coastal sea level is critical for the coordination of emergency response and port management. Extremes in coastal sea level frequently occur along the Australian coastline through the combined effects of high tides, storm surge and many other local and non local coastal Figure 6: Sea level anomaly in the Great Australian Bight off processes across a range of time and space South Australia at 21:00, 29th Oct 2007 from the BLUElink scales. During the Austral winter-spring period, OceanMAPSv1.0b operational system. cold fronts from the Southern Ocean propagate GODAE Final Symposium

over the Great Australian Bight (GAB) and other southern regions of Australia producing large coastal surges which can be of O(1)m. The resulting surge can propagate along the southern coastline as a free or forced coastally trapped wave. An example in October 2007 is shown in Fig.6 where the surge formed in GAB has propagated eastward to record a 0.7m non- tidal sea level in the Gulf of St Vincent. The coastal trapped wave represented in BLUElink in this example has a wavelength of approximately 500km and a period of approximately two days. The non-tidal sea level in coastal and shelf regions are frequented by a wide range of processes that are modelled in the BLUElink Figure 7. The root mean square error of 24 hr averaged non-tital system including storm-surge, coastally trapped sea level from BLUElink OceanMAPSv1.0b compared waves, boundary currents and eddies. Australian coastal tide gauges for a 6 day forecast period. BLUElink does not currently resolve tides, wind-waves or swell or river discharge. Evaluations from both the the BLUElink reanalysis (Oke et al.,2008; Schiller et al., 2008) and the operational BLUElink OceanMAPSv1.0b (Brassington et al., 2007) indicate the non tidal sea level of these systems has low RMS errors and good correlations with coastal tide gauge (CTG) time series around the Australian coastline. Fig.7 shows the RMSE scores for the forecast system over the 6 day forecast period compared with Australian tide gauges. During the period where the atmospheric forecasts have skill O(48) hrs the non-tidal sea level forecasts have a RMSE range from 4 to 9 cm. At longer lead times the RMSE grows indicating that the error has not reached saturation. Longer periods of skill can be obtained from the coastal ocean processes. For example, coastally trapped waves generated in the GAB continue to propagate along the east coast of Australia reaching northern Queensland approximately 5 days after the initial disturbance. Coastal boundary currents and coastal eddies also contribute to anomalous coastal sea level over longer periods, particularly where the continental shelf is narrow. BLUElink has demonstrated useful forecast skill at combining the leading processes influencing non tidal coastal sea level.

4. Summary and outlook During the GODAE period, several regional operational and preoperational systems have been developed in the Asia-Oceania. These systems have demonstrated their usefulness via providing routine service for public, government and commerce or by successful forecasting/hindcasting high impact (socially, economically and scientifically) events.

All these regional systems have strong connections with the GODAE products. The Argo and GHRSST datasets are essential inputs for initialization of these forecast systems. The large scale GODAE products are also used to provide side boundary conditions (e.g., MOVE-NP). A 15 year ocean reanalysis from BLUElink has proved useful for engineering design for example the modelling of internal waves through downscaling and assisted the planning of the successful search for HMAS Sydney which was sunk during World War II. The BLUElink operational forecasts have also demonstrated skill at forecasting a wide range of phenomena including: extreem coastal sea level, anomalous currents impacting offshore oil and gas operations, anomalous heat content over the North West Shelf influencing continental rainfall and many other processes. Most of these systems have been developed in GODAE related projects. For example, the 3D ocean forecasting system DMI BSHcmod has been continuously developed in projects MERSEA and ECOOP. The MERSEA Baltic Sea forecasting system is based on the same model.

It is still a challenging task to further develop the existing systems from science perspective (De Mey et al., 2007). Establishing more observation networks, increasing model resolution, adding sea ice model, using more advanced data assimilation and coupling with atmospheric models are among the near future activities. For example, in the near future, JMA will introduce an assimilation scheme of sea ice concentration to GODAE Final Symposium

MOVE/MRI.COM-WNP, which would yield some improvements not only sea ice extent but also ocean state in the subarctic region, especially in the Okhotsk Sea. JMA is also planning to develop a coastal ocean modeling/assimilation system using a high-resolution model with a horizontal resolution of a few kilometers that is intended for a possible operational use in JMA’s forecasting and warning systems for the coastal region of Japan. BLUElink through a follow-on research project will also introduce an upgraded reanalysis and operational prediction global prediction system (mid-2010) and introduce a new coupled regional ocean- atmosphere system for tropical cyclone predcition. The global prediction system will enhance the eddy- resolving region to include the Indian Ocean and South Pacific and will also include advances in data assimilation, initialisation scheme and atmospheric fluxes.

Another challenge of how to further apply the achievements in Asia-Oceania operational activities comes from high-level decision-makers. The Indian Ocean is relatively less covered by these regional systems. GOOS-CLIVAR’s effort in establishing Indian Ocean Observing system (IndOOS) will improve the situation. Research Moored Array for African-Asian-Australian Monsoon Analysis and Prediction, a new observational Multi-national network designed for Indian Ocean, a subset of IndOOS, similar to TAO (pacific) and PIRATA (Atlantic), to address outstanding scientific questions related to Indian Ocean variability and the monsoons. 22 out of 46 moored buoys are already occupied (McPhaden et al, 2008). On the other hand, Southeast Asian countries also urgently requires such a service for storm-surge forecast, coastal engineering and disaster prevention etc, and some existing systems such as YEOS system are ready to be extended to cover entire NW Pacific coastal/shelf seas. There are encouraging signs of more Asia- Oceania countries plan to develop operational systems. A study on pre-operational oceanographic system will be funded from Ministry of Land Transport and Ocean Affairs of Korea from next year. They will start to produce data product of coastal environment forecast for the coastal waters around Korea.

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