Simulating a typhoon storm surge in the East Sea of China using a coupled model

A coupled numerical model with a 2' x 2' resolution grid has been developed and used to simulate five typical typhoon storm surges (5612, 7413, 7910, 8114, and 9711) in the East Sea of China. Three main driving forces have been considered in this coupled model: wave radiation stress, combined wave-current bottom shear stress and wave-state-dependent surface wind stress. This model has then been compared with in situ measurements of the storm set-up. The effect of different driving force components on the total storm surge has also been investigated. This study has found that the coupled model with high resolution is capable of simulating the five typical typhoons better than the uncoupled models, and that the wave-dependent surface wind stress plays an important role in typhoon storm surge-wave coupling in this area and can increase the storm set-up by 1 m. The study of the five typhoon cases has shown that the general coupling effects could increase storm set-up by 20-32%. Thus, it is suggested that to predict typhoon storm surges in the East Sea of China, a storm surge-wave coupled model be adopted. (C) 2008 National Natural Science Foundation of China and Chinese Academy of Sciences. Published by Elsevier Limited and Science in China Press. All rights reserved.

Dynamics of nonlinear error growth and season-dependent predictability of El Nino events in the Zebiak-Cane model

With the intermediate-complexity Zebiak-Cane model, we investigate the 'spring predictability barrier' (SPB) problem for El Nino events by tracing the evolution of conditional nonlinear optimal perturbation (CNOP), where CNOP is superimposed on the El Nino events and acts as the initial error with the biggest negative effect on the El Nino prediction. We show that the evolution of CNOP-type errors has obvious seasonal dependence and yields a significant SPB, with the most severe occurring in predictions made before the boreal spring in the growth phase of El Nino. The CNOP-type errors can be classified into two types: one possessing a sea-surface-temperature anomaly pattern with negative anomalies in the equatorial central-western Pacific, positive anomalies in the equatorial eastern Pacific, and a thermocline depth anomaly pattern with positive anomalies along the Equator, and another with patterns almost opposite to those of the former type. In predictions through the spring in the growth phase of El Nino, the initial error with the worst effect on the prediction tends to be the latter type of CNOP error, whereas in predictions through the spring in the decaying phase, the initial error with the biggest negative effect on the prediction is inclined to be the former type of CNOP error. Although the linear singular vector (LSV)-type errors also have patterns similar to the CNOP-type errors, they cover a more localized area than the CNOP-type errors and cause a much smaller prediction error, yielding a less significant SPB. Random errors in the initial conditions are also superimposed on El Nino events to investigate the SPB. We find that, whenever the predictions start, the random errors neither exhibit an obvious season-dependent evolution nor yield a large prediction error, and thus may not be responsible for the SPB phenomenon for El Nino events. These results suggest that the occurrence of the SPB is closely related to particular initial error patterns. The two kinds of CNOP-type error are most likely to cause a significant SPB. They have opposite signs and, consequently, opposite growth behaviours, a result which may demonstrate two dynamical mechanisms of error growth related to SPB: in one case, the errors grow in a manner similar to El Nino; in the other, the errors develop with a tendency opposite to El Nino. The two types of CNOP error may be most likely to provide the information regarding the 'sensitive area' of El Nino-Southern Oscillation (ENSO) predictions. If these types of initial error exist in realistic ENSO predictions and if a target method or a data assimilation approach can filter them, the ENSO forecast skill may be improved. Copyright (C) 2009 Royal Meteorological Society

Shallow water tidal constituents in the Bohai Sea and the Yellow Sea from a numerical adjoint model with TOPEX/POSEIDON altimeter data

A numerical adjoint model with TOPEX/POSEIDON (T/P) altimeter data was set up to investigate the shallow water tidal constituents in the Bohai Sea and the Yellow Sea. Shallow water tidal constituents W-4, MS4 and M-6) in the Bohai Sea and the Yellow Sea were first extracted from nearly 10 years of T/P data and then assimilated into a nonlinear barotropic tidal model by using adjoint method in order to fully describe the tides in this area. The general patterns of M-4 and MS4 solutions were in good agreement with those of Kang et al. (Cont. Shelf. Res. IS (1998) 739.) and Lefevre et al., (J. Geophys. Res. 105 (2000) 8707.). The RMS values for the principal constituents and coastal constituents were obviously less than those calculated by Kang et al. (1998) and Lefevre et al. (2000). It was shown that the calculated tidal constituents charts obtained in the present study were more accurate than those in other models. In the future the model will be applied to other coastal areas and some semi-enclosed seas. (C) 2004 Elsevier Ltd. All rights reserved.

Annual cycle of carbon, nitrogen and phosphorus in the Bohai Sea: A model study

The annual cycle of nutrient-phytoplankton dynamics in Bohai Sea (BS) is simulated using a coupled physical-biological model in this study. By comparison, the modeled seasonal variations of nutrients and primary productivity agree with observations rather well. Although the annual cycles of chlorophyll a and primary production are both characterized by a double-peak configuration, a structural difference is still apparent: the phytoplankton biomass reaches the highest value in spring while summer is characterized by the most productivity in the BS, which can be ascribed to the combined impact of seawater temperature and zooplankton-grazing pressure on the growth of algae. Based on the validated simulations, the annual budgets of carbon, nitrogen and phosphorus are estimated, and are about 0.82 mt C surplus, 39 kt N deficit and 12kt P surplus, respectively, implying that the BS ecosystem is somewhat nitrogen limited. The contribution of two external nutrient sources, namely river discharges and resuspended sediments, to the growth of algae is also examined numerically, and it is found that the influence of river-borne nutrients mainly concentrates in estuaries, whereas the reduction of sediment-borne nutrients may significantly inhibit the onset of algae bloom in the whole BS. (c) 2007 Elsevier Ltd. All rights reserved.

Annual cycle of stratification and tidal fronts in the Bohai Sea: A model study

In general, competition between buoyancy mechanisms and mixing dynamics largely determines the water column structure in a shelf sea. A three dimensional baroclinic ocean model forced by surface heat fluxes and the 2.5 order Mellor-Yamada turbulence scheme is used to simulate the annual cycle of the temperature in the Bohai Sea. The difference between the sea surface temperature (SST) and sea bottom temperature (SBT) is used to examine the evolution of its vertical stratification. It is found that the water column is well-mixed from October to March and that the seasonal thermocline appears in April, peaks in July and then weakens afterwards, closely following the heat budget. In addition, the Loder parameter based on the topography and tidal current amplitude is also computed in order to examine tidal fronts in the BS, which are evident in summer months when the wind stirring mechanism is weak.

Seasonal and interannual variability of primary and export production in the South China Sea: a three-dimensional physical-biogeochemical model study

To investigate the seasonal and interannual variations in biological productivity in the South China Sea (SCS), a Pacific basin-wide physical - biogeochemical model has been developed and used to estimate the biological productivity and export flux in the SCS. The Pacific circulation model, based on the Regional Ocean Model Systems (ROMS), is forced with daily air-sea fluxes derived from the NCEP (National Centers for Environmental Prediction) reanalysis between 1990 and 2004. The biogeochemical processes are simulated with a carbon, Si(OH)(4), and nitrogen ecosystem (CoSiNE) model consisting of silicate, nitrate, ammonium, two phytoplankton groups (small phytoplankton and large phytoplankton), two zooplankton grazers (small micrograzers and large mesozooplankton), and two detritus pools. The ROMS-CoSiNE model favourably reproduces many of the observed features, such as ChI a, nutrients, and primary production (PP) in the SCS. The modelled depth-integrated PP over the euphotic zone (0-125 m) varies seasonally, with the highest value of 386 mg C m (-2) d (-1) during winter and the lowest value of 156 mg C m (-2) d (-1) during early summer. The annual mean value is 196 mg C m (-2) d (-1). The model-integrated annual mean new production (uptake of nitrate), in carbon units, is 64.4 mg C m (-2) d (-1) which yields an f-ratio of 0.33 for the entire SCS. The modelled export ratio (e-ratio: the ratio of export to PP) is 0.24 for the basin-wide SCS. The year-to-year variation of biological productivity in the SCS is weaker than the seasonal variation. The large phytoplankton group tends to dominate over the smaller phytoplankton group, and likely plays an important role in determining the interannual variability of primary and new production.