Taiwan Island is at the joint of Eurasian Continent and Pacific Plate, under threatening of typhoons and northeasterly strong winds. Consequently, enormous human lives and properties are lost every year. It is necessa...Taiwan Island is at the joint of Eurasian Continent and Pacific Plate, under threatening of typhoons and northeasterly strong winds. Consequently, enormous human lives and properties are lost every year. It is necessary to develop a coastal sea-state monitoring system. This paper introduces the coastal sea-state monitoring system （CSMS） along Taiwan coast. The COMC （Coastal Ocean Monitoring Center in National Cheng Kung University） built the Taiwan coastal sea-state monitoring system, which is modern and self-sufficient, consisting of data buoy, pile station, tide station, coastal weather station, and radar monitoring station. To assure the data quality, Data Quality Check Procedure （DQCP） and Standard Operation Procedure （SOP） were developed by the COMC. In further data analysis and data implementation of the observation, this paper also introduces some new methods that make the data with much more promising uses. These methods include empirical mode decomposition （EMD） used for the analysis of storm surge water level, wavelet transform used for the analysis of wave characteristics from nearshore X-band radar images, and data assimilation technique applied in wave nowcast operation. The coastal sea-state monitoring system has a great potential in providing ocean information to serve the society.展开更多
Although the annual global sea-air CO2 flux has been estimated extensively with various wind-dependent-k parameterizations,uncertainty still exists in the estimates. The sea-state-dependent-k parameterization is expec...Although the annual global sea-air CO2 flux has been estimated extensively with various wind-dependent-k parameterizations,uncertainty still exists in the estimates. The sea-state-dependent-k parameterization is expected to improve the uncertainty existing in these estimates. In the present study,the annual global sea-air CO2 flux is estimated with the sea-state-dependent-k parameterization proposed by Woolf(2005) ,using NOAA/NCEP reanalysis wind speed and hindcast wave data from 1998 to 2006,and a new estimate,-2.18 Gt C year-1,is obtained,which is comparable with previous estimates with biochemical methods. It is interesting to note that the averaged value of previous estimates with various wind-dependent-k parameterizations is almost identical to that of previous estimates with biochemical methods by various authors,and that the new estimate is quite consistent with these averaged estimates.展开更多
Offshore support operations must balance safety and sustainability under highly variable sea conditions.Deterministic motion analyses can underestimate extreme vessel responses,leading to insufficient operational limi...Offshore support operations must balance safety and sustainability under highly variable sea conditions.Deterministic motion analyses can underestimate extreme vessel responses,leading to insufficient operational limits and increased environmental impact.We develop a fuzzy‐enhanced multi‐body dynamics framework in which key inputs significant wave height,peak period,added mass,and radiation damping are represented as fuzzy numbers.Anα-cut decomposition yields interval bounds at each confidence level,and a fourth-order Runge-Kutta scheme integrates the six-degree-of-freedom equations of motion for both lower and upper“vertex”systems.A case study off the Karnataka coast applies both full 6-DoF and single-DOF heave approximations to demonstrate methodology.The heave response envelopes under calm(nominalα=1:0.73 m;full range atα=0:0.64–1.64 m)and severe(nominal 1.58 m;range 1.32–2.36 m)sea states reveal potential underestimations of 124%and 49%,respectively,when using only nominal values.By selecting an operationalα-level(e.g.,α^(*)=0.35 to cap heave≤1.8 m),decision-makers can balance risk tolerance and conservatism.Sensitivity analysis identifies significant wave height as the dominant uncertainty driver.Computational trade-offs and adaptiveα-sampling strategies are discussed.This work provides a self-contained,uncertainty-aware tool for deriving operational envelopes that improve risk-informed planning and enable fuel-efficiency optimization.By embedding fuzzy uncertainty quantification into vessel dynamics,the methodology supports safer,more sustainable marine operations and can be extended to real-time sensor fusion,multi-vessel interactions,and frequency-dependent hydrodynamics.展开更多
基金supported by National Natural Science Foundation of China (Grant No. 51109075)Fundamental Research Funds for the Central Universities (Grant No. 2011B05814)Doctoral Fund of Ministry of Education of China (Grant No. 20100094120008)
文摘Taiwan Island is at the joint of Eurasian Continent and Pacific Plate, under threatening of typhoons and northeasterly strong winds. Consequently, enormous human lives and properties are lost every year. It is necessary to develop a coastal sea-state monitoring system. This paper introduces the coastal sea-state monitoring system （CSMS） along Taiwan coast. The COMC （Coastal Ocean Monitoring Center in National Cheng Kung University） built the Taiwan coastal sea-state monitoring system, which is modern and self-sufficient, consisting of data buoy, pile station, tide station, coastal weather station, and radar monitoring station. To assure the data quality, Data Quality Check Procedure （DQCP） and Standard Operation Procedure （SOP） were developed by the COMC. In further data analysis and data implementation of the observation, this paper also introduces some new methods that make the data with much more promising uses. These methods include empirical mode decomposition （EMD） used for the analysis of storm surge water level, wavelet transform used for the analysis of wave characteristics from nearshore X-band radar images, and data assimilation technique applied in wave nowcast operation. The coastal sea-state monitoring system has a great potential in providing ocean information to serve the society.
文摘Although the annual global sea-air CO2 flux has been estimated extensively with various wind-dependent-k parameterizations,uncertainty still exists in the estimates. The sea-state-dependent-k parameterization is expected to improve the uncertainty existing in these estimates. In the present study,the annual global sea-air CO2 flux is estimated with the sea-state-dependent-k parameterization proposed by Woolf(2005) ,using NOAA/NCEP reanalysis wind speed and hindcast wave data from 1998 to 2006,and a new estimate,-2.18 Gt C year-1,is obtained,which is comparable with previous estimates with biochemical methods. It is interesting to note that the averaged value of previous estimates with various wind-dependent-k parameterizations is almost identical to that of previous estimates with biochemical methods by various authors,and that the new estimate is quite consistent with these averaged estimates.
文摘Offshore support operations must balance safety and sustainability under highly variable sea conditions.Deterministic motion analyses can underestimate extreme vessel responses,leading to insufficient operational limits and increased environmental impact.We develop a fuzzy‐enhanced multi‐body dynamics framework in which key inputs significant wave height,peak period,added mass,and radiation damping are represented as fuzzy numbers.Anα-cut decomposition yields interval bounds at each confidence level,and a fourth-order Runge-Kutta scheme integrates the six-degree-of-freedom equations of motion for both lower and upper“vertex”systems.A case study off the Karnataka coast applies both full 6-DoF and single-DOF heave approximations to demonstrate methodology.The heave response envelopes under calm(nominalα=1:0.73 m;full range atα=0:0.64–1.64 m)and severe(nominal 1.58 m;range 1.32–2.36 m)sea states reveal potential underestimations of 124%and 49%,respectively,when using only nominal values.By selecting an operationalα-level(e.g.,α^(*)=0.35 to cap heave≤1.8 m),decision-makers can balance risk tolerance and conservatism.Sensitivity analysis identifies significant wave height as the dominant uncertainty driver.Computational trade-offs and adaptiveα-sampling strategies are discussed.This work provides a self-contained,uncertainty-aware tool for deriving operational envelopes that improve risk-informed planning and enable fuel-efficiency optimization.By embedding fuzzy uncertainty quantification into vessel dynamics,the methodology supports safer,more sustainable marine operations and can be extended to real-time sensor fusion,multi-vessel interactions,and frequency-dependent hydrodynamics.
