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YU Fujiang, LI Jie, BAI Shan and WANG Xinian

National Marine Environmental Forecasting Center, Beijing 100081, China


Among the coastal countries of the Northwest Pacific Ocean, the marine hazards in China is of highest frequency and most severe. In recent years, there is an ascending trend in property damage from marine disasters. The damages from marine disasters for serious disaster years (1992, 1994, 1995, 1996, 1997, 2000, 2001) was over a billion even several billion USD. It is very important and necessary to study the forecasting techniques and mechanism of marine disasters, as well as the strategy for marine disasters prevention in China. In recent years (1998 to 2002), many advances have been made in the research of marine disasters in China.



The Kalman filter data assimilation technique is incorporated into a standard two-dimensional linear storm surge model by Yu Fujiang et al. (2001). The orignal storm surge model equation and meteorological forcing are improved by adding the noise terms to the momentum equations. The deterministic model output is corrected by using the available tidal gauge station data. The stationary Kalman filter algorithm for the model domain is calculated by an iterative procedure. An application to a real storm surge event occurred in the summer, 1956 in the East China Sea is performed by means of this data assimilation technique. The result shows that Kalman filter is useful to storm surge forecast and hindcast.

A nested numerical storm surge forecast model for the East China Sea is developed by Yu Fujiang and Zhang Zhanhai (2002). They use a one-way relaxing nest method to exchange the information between coarse grid and fine grid. In the inner boundary of the fine grid model a transition area is set up to relax the forecast variables. This ensures the forecast variables of the coarse model may transit to those of fine grid gradually, which enhances the model stability. By using this model, a number of hindcast and forecast are performed for six severe storm surges caused by tropical cyclones in the East China Sea. The results show good agreement with the observations.

Du Tao and Fang Guohong (1998) developed a semi-implicit numerical model for simulating and predicting storm surge inundation in the Pear River Estuary. The application of the simplified algorithm further improves the computational efficiency of the model. It is more efficient than that of the ADI algorithm.

Jiang Yuwu, Wu Peimu and Xu Jindian (2000) developed a storm surge model which can be suitable for small harbors and the Taiwan Strait, especially which involves the flooded areas and interaction of the tide and surge. Taking Xiamen Harbor as its domain area, a model consisting of the flooded area, the interaction between tide and surge and the open boundary conditions has been developed. This model indicates a available strategy, which can makes storm surge simulation more accurately in small-scale estuary and bay.

Yu Bin, Lin Shaoyi, Wang Yongxin, Shi Jianhui and Xia Zongwan (2001) simulated some storm surge events by using their dynamical models and inquired into the relevant mechanism. The results show that the set up of water level caused by storm increases gradually from south to north along the Pear River is closely related to the strength of the tropical cyclone and to the track of storm.

Wang XiuqinQian Chengchun and Wang Wei (2001) numerically simulated the typhoon surge caused by typhoon No.7203, Rita, occurred in the Bohai Sea and the Yellow Sea by using three different calculation fields. Different results were obtained, which means that the calculation field will significantly influence the simulated results. This event shows that the storm surge is a process of forced oscillation, it will generate free oscillations in a closed or semi-closed sea, and the sea will modulate this forced oscillation. That is to say, the geometric shape of sea will seriously affect the process of the storm surge in a closed or semi-closed sea. Therefore, The satisfactory results can be obtained only when the calculation field covers the whole region.

Wang XiuqinQian Chengchun and Wang Wei (2001) pointed out that wind stress plays a major role in the formation and propagation of storm surges. In the numerical simulation of storm surges, wind stress is expressed as an empirical power law of wind speed, where the drag coefficient gives the rate of momentum transmission from air into water. Observations show that the drag coefficient increases gradually with the increase of wind speed and is a function of surface roughness and atmospheric stability. In their paper, several proposed formulae of the drag coefficient varying with the wind speed have been examined in numerical simulations of storm surges. The elevations simulated with varying drag coefficients coincide much better with the observed data than those with the constant drag coefficients. The best result is obtained when the formula proposed by Smith (1980) is adopted.

Zhou XuboSun Wenxin (2000) used a 2D numerical model to study the non-linear interaction between storm surges and astronomical tides in the sea area off the Changjiang River mouth. By using this model the storm surge set-up caused jointly by the 8114 Typhoon and the spring tides is simulated. The 8114 Typhoon is one of the greatest typhoons in the recent 20 years. The 8114 Typhoon landed by a tidal station, Wusong Station, where the complete records of water level caused by the surge are available. The simulated results agree well with the observations. This indicates that the simulation is successful. In addition, from the simulated results some useful conclusions have been drawn.

Three numerical models of typhoon surge are introduced by Wang Xinian, Yu Fujiang and Yin Qingjiang (2000), which are applied to forecasting storm surge in the China seas . The first one is called the Five-basin Model (FbM). During the five years from 1991 to 1995, some modifications of FbM , such as the product display and the MOS ability of the model, have been made, and FbM has been used for the real-time prediction of storm surges at several marine forecasting observatories, such as Qingdao, Shanghai, Guangzhou, Hainan, etc. The second one is called SLOSH (Sea, Lake, and Overland Surges from Hurricanes). Five SLOSH-type basins were developed until 1995, which cover the entire China coastlines by a cooperative project between authors and Jelesnianski et al. of U.S.A. The SLOSH model has been used for the real-time forecasting of typhoon surge at The National Marine Environmental Forecasting Center of China. The SLOSH model has been applied to the Shanghai Flood Control Information Center in 2000. The third one is a new developed model in which the inundation scheme originated by Flather and Heaps (1975) is used and astronomical tide is included. A multiple nested grid system is developed. The third model has been used to calculate the Probable Maximum Storm Surge (PMSS) of two nuclear power stations.

The analyses and investigations by Wu Shaohua, Wang Xinian et al. (2002) indicate that the frequency of storm surge of the Tianjin coastal area is the highest and its disaster is the most severe in the world. The disaster of storm surge happens in four seasons in which the disaster of extratropical storm surge occurs in spring, autumn and winter besides the disaster of typhoon surge happens in summer. The 2D model in geographical co-ordinates has been used to simulate the set-up process of the maximum extratropical storm surge events in the Bohai Sea which happened in 23 April, 1969. The verification of the calculated wind field and the time variation of storm surge in several tidal gauge stations indicates that the model can be used to do the engineering calculations of the extratropical storm surge, and the model has an ability to do the real-time prediction of storm surges.



With the sea wave spectra in a moving coordinate system as target spectra, Liang Chujin, Guan Changlong(1998) simulated the random sea waves in a moving coordinate system by using the methods presented for a static coordinate system, namely, the component method and the filter method. Through comparing the examples, it is found that in the fast-moving coordinate system the component method is superior to the filter method, while in the slow-moving one, the situation is reversed. Also, the methods of selecting the technical parameters are given.

Based on the probability statistics model of the random wave surface and using the relation of Ochi, Hou Yijun, Lu Jun, Li Mingkui, He Yijun and Yin Baoshu (2001) obtain a nonlinear statistical distribution of significant wave height as follows:

This study not only includes the two parameters logarithm-Gaussian distribution of significant wave height, but also describes the change of the statistical distribution by using the wave steepness as a nonlinear control parameter of significant wave height. Applying the result to the analysis of the TOPEX altimeter data in the South China Sea, the theoretical results are consistent with the observed data.

Based on the altimetric observations of SWH over the northern South China Sea from the GEOSAT satellite in 1988, Qi Yiquan, Shi Ping and Mao Qingwen (1998) analyzed the characteristics of SWH . The information of the sea state can be derived from the remote sensing data by a satellite altimeter. The geophysical records of the GEOSAT satellite include the data of the significant wave height (SWH) with good accuracy. The results are compared with those based on the historical data from conventional sectional observations which shows a better agreement. The altimetric observations show a distinct advantage in the study of the high sea state.

Based on the Geosat altimetric data of an ascending orbit over the western Pacific on August 11, 1987, the features of sea surface wind and wave under the influence of typhoon Betty are analyzed by Qi Yiquan, Shi Ping, Mao Qingwen and Guo Peifang (1998). It is shown that the spatial distributions of wind speed and wave height are asymmetric to the center of the typhoon. In the direction of the typhoon movement, the wind speed in the right quadrant increased more rapidly than that in the left within the inner area of the typhoon, while in the outer area the former also decreased more rapidly than the latter. However, unlike the wind speed, the spatial distribution of wave height has no obvious difference between inner and outer areas. The wave height in the left and right quadrants shows the different distributions with the distance increasing to the typhoon center. The relationships between wind speed and wave height in the right and the left quadrants are obviously different. The empirical formulae are established, which show the variations of the wind speed and wave height with the distance to the typhoon center and the relationship between wind speed and wave height.

A simple model is analytically derived by Yu Dingyong, Xu Delun and Lu Hongmin (1998) for estimating the spatial fraction of breaking sea surface at an instant of time, which is viewed as the whitecap coverage . The derivation is based on a spatial homogeneous Gaussian wave field and using the limiting surface slope tan 30.37°=0.586 (Longuet-Higgins et al.,1977) as a criterion of wave breaking. The whitecap coverage expression is found on the basis of fourth moment of spectrum, , and the critical threshold of surface slope. Expressing  in terms of the Neumann spectrum they arrived at a formula relating whitecap coverage with wind speed  

for the fully developed sea state: where  is defined by Expressing  in terms of the Krylov spectrum and employing the empirical relation used in the SMB ocean wave prediction technique, they arrived at another formula relating with both wind speed and fetch for the fetch-limited sea state :, where  represents the non-dimensional fetch: . A comparison between these results and the field data of whitecap coverage collected by Monahan et al (1980) shows a rather good agreement.

Ye Zhulin, Li Shaoying, Zhang Jinghan (1999) took into account in the course of the spectrum changes because of water depth decreasing when the deep-water wave propagates towards coastal shallow water area. Based on the observed typhoon-wave data along the coast of South China, the typhoon wave spectrum suitable for coastal sea area of South China is obtained by comparing the deep-water wind wave spectrum to the observed ocean wave spectrum, and by statistically analyzing the observed data. The obtained spectrum has also be compared with the two deep-water wind wave spectrums separately developed by Wen Shengchang and Mitsuyasu, and with the shallow water wind wave spectrum by Basinski-Massel.

Based on the numerical simulation and the observation data, Zhao Dongliang, Guan Changlong, Wu Kejian and Wen Shenchang (1999) carried out the reliability analysis of such four estimate methods of directional spectrums as the maximum-likelihood method (MLM), the extended eigenvector method(EEV), the extended maximum-entropy principle(EMEP) and the Bayesian directional method(BDM). It is shown that the spectra obtained from MLM, EEV and BLD have fairly the same directional distribution in general. However, BDM holds the best reproducibility in any cases, and is inferior to MLM and EEV in practicality. EMEP is less suitable for the observed data because of its poor stability.

Based on statistical analysis of wave observation data in Quanzhou Bay, Fujian Province, Lu Fengshan, Liao Kangming, Xiao Hui and Shen Minmin (1998) elucidated the wave distribution characteristics with seasonal variations and the mechanism of wave generation, made comprehensive analysis of annual distribution characteristics of wave types and correlative relation among wave parameters and discussed the processes of wave variations during a typhoon period. They think that waves within the Bay is much more influenced by open sea wave than by seasonal wind.



The numerical sea ice forecast for the Bohai Sea has been carried out in the National Research Center for Marine Environmental Forecasts (NRCMEF) since 1989. A three-level dynamic-thermodynamic ice model for simulating the ice growth, decay and drift in the Bohai Sea has been developed. The viscous-plastic constitutive law is applied to estimate the internal ice stress. The thermodynamic growth rates are determined by the thermodynamic forcing from atmosphere and ocean, which are parameterized according to the heat exchanges at the air/ice, air/water and ice/water interfaces. The ice model is coupled through an oceanic model and is linked to a numerical weather prediction model for forecasting ice conditions in the Bohai Sea. Statistical verification was used to make objective assessment of the model. Recently a PIC model has been used for improving the accuracy of ice edge forecasts in the Bohai Sea. It is accomplished by introducing a Lagrangian treatment of the ice volume and the area conservation equations via the ‘particle-in-cell' method.

Wang Keguang, Bai Shan, Wu Huiding (1999) analyzed the physical variables relating to the sea ice thermodynamics, such as solar short wave radiation, long wave radiation, cloud, sensible heat and latent heat in detail on the basis of the hydrological and meteorological observations in the Bohai Sea. And a parameterization scheme is presented. Two typical cases are studied by using the scheme for making a comparison between the dynamic-thermodynamic model with the sea ice thermodynamic process and the dynamic model without the thermodynamic process. The result shows this parameterization scheme is good to forecast the sea ice thermodynamic process in the Bohai Sea.

Wu Huiding, Bai Shan, Zhang Zhanhai (1998) discussed the nature of the sea ice dynamics and determined the momentum balance describing ice drift, the creation of leads and the building of ice ridge, and the sea ice rheology relating the ice stress to the ice deformation and strength. A numerical model is presented for the simulation sea ice dynamical processes. To model the ice-ice interaction, the sea ice is considered as a nonlinear viscous compressible material obeying the viscous-plastic constitutive law. This model is applied to simulate ice drift in the Bohai Sea, the Bothnia Gulf of the Baltic Sea and the Labrador Sea, respectively. The model results show that ice drift in the Bohai Sea has a strong periodical change caused by tides. The creation of lead and ridges in the Bohai Sea are simulated and a sensitivity study of the ice rheology parameters is conducted. The ice model is linked to an atmospheric model with a boundary layer model to predict sea ice of the Bohai Sea numerically.

In the light of the difference of brightness temperature and albedo between sea ice and sea water over the Bohai Sea monitored by satelllites “NOAA” and “FY-1”, Zheng Xinjiang, Qiu Kongmu, Lu Feng(1998) set up a criterion of distinguishing water from ice , and classified the sea ice according to the relation between albedo and thickness of sea ice. Based on the ice information within mixed pixel, the coverage and area of sea ice are given.

Ji Shunying, Yue Qianjin (2001), introduced the smoothed particle hydrodynamics method (SPH) to the numerical simulation of dynamical processes of sea ice. By considering the thermodynamic processes of sea ice, they applied the Hibler viscous-plastic constitutive law to carrying out the numerical simulation lasting 96 hours of the local drifting ice in the Liaodong Bay. The calculated results consist well with the real processes , which shows that the internal force has large effects on the velocity, thickness and compactness of sea ice and can't be ignored in the simulation of local drifting sea ice.



From October 10 to 17, 1997, a marine ecosystem enclosed experiment (i.e. mesocosm experiment) was carried out in the Changjiang River estuary area as a part of Sino-Japan cooperation. The experiment basin was filled with sea water of 25m3 and the initial nutrient concentrations of total dissolved nitrogen, dissolved phosphate and silicon are 24.8mmol/L, 0.65mmol/L, 40.2mmol/L, respectively. By adding dissolved phosphate concentration to 3.25mmol/L, a Harmful Algal Bloom was successfully induced. Based on the experiment data, Qiao Fangli, Yuan Yeli and Zhu Mingyuan et al. (2000) developed a marine HAB dynamical model. The model includes such six variables, as three different nutrients, nitrogen, phosphorus and silicon, two groups of photoplanktons, flagellate and diatom, and detritus. Nitrogen and phosphorus are uptake by phytoplanktons and added by phytoplankton respiration and regeneration of detritus. Silicon is absorbed by diatom and not added. Phytoplanktons increase by uptake nutrients and decrease by respiration and death. The dead phytoplanktons are changed to detritus and the later can regenerate nitrogen and phosphate through decomposition. The model results are well consistent with the available data. The present work analyses the influence of nutrient concentration and light intensity to the formation of HAB. The main results are as follows. (1) The created HAB dynamical model successfully simulates the whole process. The added dissolved phosphorus concentration is enough for strengthening the HAB process. (2) The threshold values of nitrogen and phosphorus concentration for the HAB occurrence are 4.5mmol/L and 1.0mmol/L, respectively. (3) When surface light intensity is half of the measured sea surface light intensity, the maximum chorophyll concentration is 35mg/L. When the light intensity is 35% or below, HAB will not occur.

Wan Zhenwen, Yuan Yeli and Qiao Fangli (2000) pointed out that whether or not the ecosystem parameters were evaluated well and truly was a key factor which determines the precision of an ecosystem dynamics model; in fact, an overwhelming majority of researchers specified the parameters by experience or by experiment. They tried to construct an objective function in order to assess the validity of a common ecosystem dynamics model in advance, and then specified the parameters according to a set of equations only under the control of which the objective function could get its extrema. On the different premises of in situ observations, three forms of objective functions were constructed. Each objective function was applied to optimize the parameters. Furthermore, the result of the ecosystem dynamics model and the values of parameters were compared with the data and with literatures; the model's result came closer to the data and the parameter values were under the scope of the relative values in literatures. The proposed optimization method to evaluate the ecosystem parameters was a new application of classical mathematics theory, and this method could partially replace expensive in situ observation in ecology research and relevant experiments. It is more important that the preliminary numerical experiment showed this method's validity.

In Jiao Xiaoyang's paper (2001), the research data show that the transparency has a definite relationship with the density and species of phytoplankton under general condition. The transparency is high in the low phytoplankton density, and low in the high. It is suggested that the transparency may be the parameter to forecast the red tide in test. The transparency of 1.6m should be the standard figure for the forecast of the red tide.

Qian Honglin and Liang Song (1999) pointed out that there were many species of red tide organisms in the Pearl River Estuary (up to 98 species among them which are toxic and harmful) and these species become a basis of the red tide appearance. The red tide events happened in the Pearl River Estuary and its adjacent waters, which are enumerated by them in detail. The studies show that the bigscale, long lasting and more harmful red tide caused by Gymnodinium miki motoii in the Pearl River Estuary in the spring of 1998. The density of organisms in the cage cultivation area of Guishan was 0.63× 106-7.60×106 cells/dm3, with the mean of 3.67×106 cells/dm3. This red tide led to a great loss of 3.5 billion CNY to the mariculture industry of Hong Kong and Guangdong (Hong Kong 3 billion, Guangdong 0.5 billion).

On the basis of their research into the Dalian alongshore sea field Wang Huiqing and Du Guangyu (2000) showed the relation between the red tide phytoplankton and ecological environment. The statistical analysis was done for the 13 environmental factors in the stage of the red tide occurence and multiplication. The red tide forecast model of spring and summer was attained by multiregression. This model was validated in the subsequent red tide analysis. The coincident rate was 83% in spring and 92%in summer. The technical parameters for treating the red tide by physics and chemistry measurement were put forward. At the same time the treatment prospect of biological measurement was discussed.

Liang Song, Qian Honglin, Qi Yuzao (2000) analyzed the 360 events of the red tides in the coastal China Seas (not including the events caused in the coastal Hong Kong and Taiwan sea area) from 1972 to 1998. According to the oceanographical characteristics, they classify the red tides into following types: alongshore type (estuary and bay type), oceanic type, exotic type and breed aquatics area type. On the current situation of the red tide occurrence in the coastal area of China seas in the recent more than ten years, there appear four characteristics: 1. The frequency of red tide occurrence keeps increasing. 2. The disaster-affected area gets wider, the disaster-lasting time gets longer and the disaster loss gets greater; 3.There are more new species recorded, in which the noxious red tides gets more; 4. There is a trend for “Double Type” red tides to increase and there exist more types of red tides etc.

Wei Manxin and He Benmao (1998) analyzed the distribution characteristics of nutrient salt and its relation with hydrochemical factors in the Lianzhou Bay based on the data observed in 1995. The eutrophication level of the bay is evaluated with COD, inorganic phosphorus and nutrient as the index of assessment, from which it is found that the main cause of red tide formation is the rich nutrient from land. The N/P ration shows that inorganic nitrogen is the main factor to confine the primary productivity in the bay.


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