Multiscale Physical and Biological Dynamics in the Philippine Archipelago: Predictions and Processes

. The Philippine Archipelago is remarkable because of its complex geometry, with multiple islands and passages, and its multiscale dynamics, from the large-scale open-ocean and atmospheric forcing, to the strong tides and internal waves in narrow straits and at steep shelfbreaks. We employ our multiresolution modeling system to predict and study multiscale dynamics in the region, without the use of any synoptic in situ data, so as to evaluate modeling capabilities when only sparse remotely sensed sea surface height is available for assimilation. We focus on the February to March 2009 period, compare our simulation results to ocean observations, and utilize our simulations to quantify and discover oceanic features in the region. The findings include: the physical drivers for

variations, monsoon regimes, weather events, and topographic wind jets Pullen et al., 2011). Bottom forcing also occurs, for example, in deep waters that are known to be affected by hydrothermal vents (e.g., Gamo et al., 2007). Finally, and as importantly, barotropic tides, often out of phase in the different basins (Logutov, 2008), strongly affect flows, especially in shallower regions and straits. Due to the area's variable stratification, rotation, and steep topographies, they drive a wealth of internal tides, waves, and solitons, some of which are known to be among the strongest in the world (e.g., Apel et al., 1985). The purpose of the present study is to describe and reveal such regional ocean features as estimated by a multiresolution, tidally driven ocean model for the February and March 2009 period, without any in situ data assimilation.
Our ocean science focus is on biogeochemical fields and circulation features, transport balances for the Sulu Sea and flow fields in the corresponding straits, and, finally, formation mechanisms for the deep Sulu Sea water.
The goals of the Philippine Straits Dynamics Experiment (PhilEx; Gordon, 2009;Lermusiaux et al., 2009;Gordon et al., 2011) were to enhance our understanding of physical and biogeochemical processes and features arising in and around straits, and to improve our capability to predict the spatial and temporal variability of these regions. temporal and spatial scales (Broecker et al., 1986;Metzger and Hurlburt, 1996;Gordon et al., 2011) and multiple feedbacks to the lateral forcing seas. Several aBstr act. The Philippine Archipelago is remarkable because of its complex geometry, with multiple islands and passages, and its multiscale dynamics, from the large-scale open-ocean and atmospheric forcing, to the strong tides and internal waves in narrow straits and at steep shelfbreaks. We employ our multiresolution modeling system to predict and study multiscale dynamics in the region, without the use of any synoptic in situ data, so as to evaluate modeling capabilities when only sparse remotely sensed sea surface height is available for assimilation. We focus on the February to March 2009 period, compare our simulation results to ocean observations, and utilize our simulations to quantify and discover oceanic features in the region. The findings include: the physical drivers for the biogeochemical features; the diverse circulation features in each sub-sea and their variations on multiple scales; the flow fields within the major straits and their variability; the transports to and from the Sulu Sea and the corresponding balances; and finally, the multiscale mechanisms involved in the formation of the deep Sulu Sea water.
Opposite page. mit multidisciplinary simulation, estimation, and assimilation system (mseas) estimates of: (a-c) 25-m temperature at 0430Z on February 17, 2009 from three implicit two-way nested simulations at 1-km, 3-km, and 9-km resolutions, and (d) a time series of temperature profiles at the sulu sea entrance to sibutu Passage. Features are simulated at multiple scales, including the North equatorial current, mesoscale eddies, jets, filaments, and internal tides and waves.
The present work is partly inspired by our experience in coastal regions with complex geometries (Haley and Lermusiaux, 2010), especially with steep shelfbreaks and straits such as the Sicily Strait (Lermusiaux, 1999;Lermusiaux and Robinson, 2001), Massachusetts Bay and Stellwagen Bank (Besiktepe et al., 2003), Middle Atlantic Bight shelfbreak (Lermusiaux, 1999), Monterey Bay shelfbreak , and Taiwan region shelfbreak . However, in addition to being at least an order of magnitude more complex, in a large part due to the very intricate geometry and multiscale flows, a major difference between the present simulations and the earlier studies is that very little was known about the dynamics in the region prior to the three PhilEx expeditions .
For example, it is interesting to note that for the month of February, there is not one single conductivity-temperaturedepth (CTD) profile recorded for the Sulu Sea in the National Oceanographic Data Center (NODC) World Ocean Atlas 2005 (WOA05, Antonov et al., 2006;Locarnini et al., 2006), although this database goes back for more than the past 100 years.
In the following, we first outline our multiresolution simulation approach and its parameters. We then present selected  The optimization parameters were the Pierre F.J. Lermusiaux (pierrel@mit.edu Locarnini et al., 2006). WOA05 profiles for the month of we selected the COAMPS archive fluxes (27-km/9-km resolution; Hodur, 1997) for wind stress, net heat flux, and evaporation minus precipitation.
For barotropic tidal forcing, we use our multiresolution tidal elevation and velocity estimates (Logutov, 2008;Logutov and Lermusiaux, 2008), which are derived by generalized inversion from global tidal boundary conditions (Egbert et al., 1994;Egbert and Erofeeva, 2002   (2) optimizing the many interisland transports in initializations from geostrophic shear (Agarwal et al., 2010); (3) region-dependent biological initialization; (4) multiscale fully implicit two-way nesting (Haley and Lermusiaux, 2010); and (5) generalized inversion for high-resolution barotropic tidal fields (Logutov and Lermusiaux, 2008).    (Apel et al., 1985;Girton et al., 2011;Jackson et al., 2011)   which is weaker in the model during that period, even though it is simulated at most other times (Figure 3e). This issue is again due to the assimilation of SSH data, which we found erroneous during that period.

deep sulu sea Water
The Sulu Sea is a semi-enclosed basin filled and renewed by waters overflowing the above-mentioned straits and open-sea segments. Its deep water has received recent attention in part because of decadal and climate studies (e.g., Quadfasel et al., 1990;Rosenthal et al., 2003;Gamo et al., 2007;Arnold Gordon and colleagues, pers. comm., 2010). Below 1250-m depth, salinity is slightly stratified, from a minimum To confirm that these two straits are two main sources for the deep, salty Sulu Sea water, we first focus on the overflows from deep depths. Figure 9a shows   This complexity required novel modeling schemes, including our multiscale objective analyses for such regions (Agarwal and Lermusiaux, 2010), new time-dependent spatial discretizations, and fully implicit two-way nesting in telescoping domains (Haley and Lermusiaux, 2010). Without these schemes, such multiscale simulations would not have been possible. In the present study, the modeling focus was on the utilization of tuned models using no in situ synoptic data, but only infrequent and sparse remotely sensed sea surface height data.
As described in this special issue, not much was known quantitatively about the region prior to the PhilEx program and its three sea-going expeditions.