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Taiwan is often threaten by typhoon during summer and autumn. The surges brought by theses typhoons not only cause human lives in danger, but also cause severe floods in coastal area. Storm surge prediction remains still a complex coastal engineering problem to solve since lots of parameters may affect the predictions. The purpose of this study is to predict storm surges using an Artificial Neural Network (ANN). A non-linear hidden-layer forward feeding neural network using back-propagation learning algorithms was developed. The study included a detailed analysis the factors may affect the predictions. The factors were obtained from the formulation of storm surge discrepancies after Horikawa (1987). Storm surge behaviors may vary from different geographical locations and weather conditions. A correlation analysis of the parameters was carried out first to pick up those factors shown high correlations as input parameters for establishing the typhoon surge predictions. The applications started with collecting tide and meteorological data (wind speed, wind direction and pressure) of Dapeng Bay and Kaohsiung harbor. A harmonic analysis was utilized to identify surge deviations. The surge deviation recorded at Dapeng Bay was found higher then Kaohsiung harbor for the same typhoon events. Correlation analysis has shown positive correlations between wind field, both wind speed and direction, and the associated storm surge deviations at Dapeng Bay. Correlation coefficients (CC) 0.6702 and 0.58 were found respectively. The variation of atmospheric pressure during typhoons is found with positive correlation too (i.e. CC=0.3626). Whereas the analysis has shown that the surges at Kaohsiung harbor were only sensitive to wind speed (CC=0.3723), while the correlation coefficients of the wind direction (CC=-0.1559) and atmospheric pressure (CC= -0.0337) are low. The wind direction, wind speed and atmospheric pressure variation were then used as input parameters for the training and predictions. An optimum network structure was defined using the Dapeng Bay data. The best results were obtained by using wind speed, wind direction and pressure variation as input parameters. The ANN model can predict the surge deviation better if the empirical mode decomposition (EMD) method was used for training.

In order to better understand the flow dynamics in the Taiwan Strait (TS) and the adjacent seas, a series of field experiments were conducted to monitor the currents by deploying 30 SVP drifters, using shipboard ADCP measurements and analyzing historical drifter data in the TS. Examinations of historical drifter data reveal that the surface waters in the TS originate from the shelf of the South China Sea (SCS) in the summer. In wintertime, the mean surface current flows toward the south in the northern TS with a mean speed of approximately 0.3~0.4 m/s. The surface current in the eastern TS mainly flows northward, and it flows southward in the western TS in the fall. The surface waters of the Kuroshio do not intrude into the SCS in summer. Instead, a northeastward current of 0.5~0.7 m/s west of Luzon Island impinges on the Kuroshio across the Luzon Strait. Drifter tracks in the TS are classified according to the wind condition. The first type of drifter tracks is that the drifters move northward in the TS with an intensified flows in the Peng-hu Channel when the southwest monsoon prevails. The second and third types of drifter tracks are under the influence of strong northeast monsoon. The drifters are carried onto the shelf of East China Sea from the Kuroshio or the East China Sea, and then move southward along the TS. Some drifters are grounded at the west coast of Taiwan, and the others drift through the TS. The third type of drifter tracks show that drifters start from the Luzon Strait and move northward into the TS. However, they can only reach the neighboring area of Peng-Hu archipelagoes, then they change the direction of drifting to the south or southwest and toward the SCS. The fourth type is that drifters are carried northward from the SCS into the northern TS under the weak northeast wind, and then veer to the south when the northeast monsoon intensifies. The fifth type of drifter tracks demonstrates the flow pattern of the northern TS when the northeast monsoon diminishes. This flow pattern belongs to the Taiwan Warm Current (TWC) in wintertime. The surface speed of TWC is about 0.2~0.4 m/s northward. The second, fourth and fifth flow patterns in the TS have not been quite discovered in previous studies. In-situ marine observations right beneath typhoons are very scanty and valuable. In this study we have found several events with some drifters happened to get caught by typhoons. The maximum speed of drifters near the typhoon center is found to be about 2 m/s. The SST, which is observed by the drifter, reduces 2~4¢J after the typhoon passes. Our results indicate that for the case of the Typhoon Haitang the Matsu weather station measured a sudden increase of wind speed of about 3 m/s every hour, and the corresponding drifter speed increases 0.52 m/s. There were two events in summer of 2006 when the Typhoon Billis and Saomai passed the northern region of Taiwan, and some drifters located at the Kuroshio to the north of typhoon were carried rapidly onto the ECS shelf with a maximum speed of about 1.1 m/s. This result indicates that the Kuroshio waters can penetrate into the ECS shelf by means of the passage of typhoon in this region during summertime. Three cruises with the shipboard ADCP were performed by three research vessels concurrently along two transects during 2002-2004. Various phase averaging methods were employed to eliminate tidal effects. The calculated volume transport of the TS for the period of August 2002, September 2003 and March 2004 is 3.4, 3.6 and 2.8 Sv, respectively. These transport values are compatible with the output of EASCNFS model. The estimated uncertainty of the residual flow through the Peng-hu Channel derived from the 5-phase-averaging, 4-phase-averaging, 3-phase-averaging and 2-phase-averaging methods is 0.3, 0.3, 1.3 and 4.6 cm/s, respectively. Procedures for choosing a best phase average method to remove tidal currents in any particular region are also suggested.

This thesis seeks to identify locations in which errors in numerical model initial conditions may compromise skill in tropical cyclone (TC) track forecasts. Two major TCs that made landfall in 2008 are analyzed: Hurricane Ike and Typhoon Sinlaku. In order to examine the sensitivity of the TC to selected synoptic features, a vorticity perturbation technique is developed. Within a chosen radius and atmospheric depth, the vorticity is amplified or decreased, followed by a re-balancing of the fields. The following questions are proposed: (1) How does the TC track vary with respect to initial perturbations of differing amplitude, spatial scale and distance to the storm? (2) How does the evolving perturbation act to modify the synoptic environment surrounding the TC, and thereby the track? (3) Is it best to follow an objective technique to determine the sensitive areas, or is it better to use a subjective method based on fundamental synoptic reasoning? Utilizing the Weather Research and Forecasting (WRF) model, the ?control? simulation for each TC is found to replicate forecast errors evident in the operational global models. For Sinlaku, this includes a premature recurvature in the forecast. For Ike, this comprises a landfall too far south along the Texas coast due to no recurvature being forecast. The size, magnitude and location of vorticity perturbations to the control analysis are chosen subjectively. For Sinlaku, these locations include a large mid-latitude shortwave trough around 3000 km to the north-northwest, a smaller upper-level shortwave immediately to the north, a low-level monsoon trough to the west-southwest, a weak tropical storm to the northeast, and a local perturbation in the immediate environment. It is found that WRF forecasts of Sinlaku exhibit high sensitivity, with large modifications to its track arising from the perturbation of each selected targets in the synoptic environment. The greatest improvement in the track forecast occurs by weakening the vorticity associated with each of two shortwaves to the north of Sinlaku, suggesting that either or both of the shortwaves may have been initialized too strongly in the model analysis, thereby contributing to an erroneous recurvature. For Ike, the perturbation locations include a large mid-latitude shortwave trough 2500 km to its north, an upper-level cutoff low to the east-northeast, a low-level shortwave trough to the northwest, a tropical storm in the East Pacific, and a local perturbation in the immediate environment. In contrast to Sinlaku, the perturbation of synoptic targets around Ike produces less sensitivity, likely due to the fact that Ike is not in a position of imminent recurvature. The only perturbation that leads to an accurate 4-day forecast of recurvature and landfall in North Texas is the strengthening of the large mid-latitude shortwave trough, suggesting that the shortwave may have been initialized too weakly in the operational models. Finally, a comparison of targets selected objectively by the Ensemble Transform Kalman Filter (ETKF) versus the above subjectively-chosen targets suggests that while the ETKF effectively indicates similar target regions to those selected subjectively, it may be less effective in ranking the relative sensitivities of those targets. Overall, it is found that the TC track is more sensitive to perturbations of larger amplitude and spatial scale, and less so to the distance between the perturbation and the TC, and sensitivity is confined to specific regions of the flow. The perturbation methodology employed here may be used to offer suggestions of locations in which extra high-density satellite data may be assimilated.

Terpios hoshinota is a blackish-gray cyanobacteriosponge encrusting on stony corals with fast expansion rates in shallow waters. The sponge population exploded at Green Island and Orchid Island during 2006 to 2008. Here, we surveyed at Green Island and Orchid Island in 2009 and 2010, compared the sponge densities, individual lengths, sponge coverage and scleractinian coral coverage between 2008 and 2010. We also tested the hypothesis that typhoon may play a role inhibiting the sponges by monitoring individual sponges before and after. In these three years, the sponge coverages remained the same; sponge length and densities had no significant difference at 2~3 m depth at Green Island, but densities decreased and length increase at 5 m depth at Green Island and 2~3 m depth at Orchid Island, but the rate increased was significant slower than average growth speed . Although sponge coverages were not significant different between these years, the scleractinian corals coverages decreased at Green Island among these years. The main wind direction was southwest during the Typhoon Marakot at Green Island, and only the sponges at southwest coast of Green Island decreased in size significantly among the three coasts monitored. The population of Sponge T. hoshinota exploded in 2006, the strength of typhoons were smaller than other years during 2005 to 2009. The typhoon may be the main factor that inhibiting the sponge T. hoshinota at these two islands.

This study collected zooplankton and hydrographic data in the Taiwan Strait (TS) using the cruises of ¡§Fishery Research I¡¨ from January 2005 to October 2006, to investigate the seasonal and spatial distribution of planktonic pteropods associated with hydrographic conditions. In total, 29 species of pteropods belonging to 10 genera and 5 families were identified, with mean abundance of 97.14 ¡Ó 66.16 ind./100 m3. The abundances and species number of pteropods exhibited apparent seasonal changes, abundance was higher in summer and lower during winter, while species numbers was higher in fall and lower in winter. Pteropods showed higher diversity in oceanic waters than in shallower shelf waters, but the abundance showed no significant difference. The night-time abundance and species number were significantly higher than the day-time. The effect of typhoon on the abundance and species numbers of pteropods was not significant. The four predominant species found in this study area were Creseis clava, Creseis acicula, Limacina inflate and Limacina trochiformis, together they accounted for 95% of the total pteropod catch, among these, C. clava constitued 48% of the total catch. The pteropod communition was similar among seasons, but ranked differently. Different dominant species showed different seasonal distribution patterns. The distribution of pteropods showed no clear spatial difference in the TS, but higher species richness was usually observed in the southern TS. The pteropods found in this study mostly belonged to the widespread oceanic species, and the dominant species were similar to the previous studies in the South China Sea. The total abundance, species number, and species diversity index of pteropods showed significantly positive correlation with the seawater temperature, and the species number was negative correlated with salinity. Among the four predominant species, the abundance of C. clava, C. acicula, and L. trochiformis were positively correlation with seawater temperature, meanwhile, C. acicula and L. trochiformis showed significantly negative correlations with salinity. This study proposed that the abundance, species number, and species diversity of Pteropods were not obviously influenced by typhoon, instead seasonal succession of water masses and day/night change might be the important factor affecting the distribution patterns of pteropods.

Temporal variations of macroalgal cover and biomass (wet weight and dry weight) abundance and assemblage structure, and also the relationships between abiotic factors and assemblage structure, were studied in northeastern Taiwan (GPS: 25o06¡¦80¡¨N; 121o54¡¦60¡¨E¡^during 2001-2003. This study also investigated the causes affecting Gelidium natural resource and its management. Twenty-seven families with 67 species (5 families with 13 species for Chlorophyta, 3 families with 8 species for Phaeophyta, 19 families with 46 species for Rhodophyta) were recorded. The dominant species such as Pterocladiella capillacea and Polyopes polyideoides belong to temperate species. Macroalgal coverage, areal biomass, diversity, eveness and assemblage structure during 2001-2003 showed significant temporal changes with year and seasonal variations; however, the seasonal rhythm is changing between years. The seasonal pattern is different between 2001 and 2002/2003, biomass peaked in spring of 2002 and 2003. Pterocladiella capillacea, Polyopes polyideoides, Marginisporum crassissimum, Jania ungulate and Chondrus ocellatus contribute to temporal variations in assemblage structure. The results of multi-variate and uni-variate analysis suggest significant temporal variations in macroalgal assemblage structure in northeastern Taiwan, and the data from ANOSIM and SIMPER analysis demonstrated that the seasonal pattern was variable between years, in which it is coincident with seasonal variations in macroalgal abundance. Water temperature, summer high temperature, winter low temperature, nutrient and typhoon are attributable to temporal variations in macroalgal assemblage structure. Low temperature in winter, nutrient availability, and also typhoon restrict the natural resource of Gelidium in northeastern Taiwan; it is hypothesized that low P condition together with enhanced collection deep the decline of Gelidium resource, finally limiting the recovery of Gelidium population in next year. We found that the agar contents of Pterocladiella capillacea showed year and season variations with a negative relationship to biomass. Temporal fluctuations in agar contents was enhanced by low temperatures and high P but decreased by high N. Based on the observations, we conclude that over-collection in winter results in a decline of Gelidium resource in the coming years, thus it could be suggested that winter collection has to be controlled to maintain the sustainable utilization of Gelidium in northeastern Taiwan.

There are many approach for The study of marine resources and now in Taiwan is a lot of express , but the damage to net-cage by typhoon is cost much money . The most important study in Taiwan is to use new teconology to update the traditional business and get advanture in international.

Thesis (M. Arch.)--University of Hong Kong, 2002. / Special report entitled: Lighting and water. Includes bibliographical references.

Thesis (M.Arch.)--University of Hong Kong, 2002. / Special report entitled : Lighting and water. Includes bibliographical references. Also available in print.