The ESMD method can be seen as a new alternate of the well-known Hilbert-Huang transform (HHT) for non-steady data processing. It is good at finding the optimal adaptive global mean fitting curve, which is superior to...The ESMD method can be seen as a new alternate of the well-known Hilbert-Huang transform (HHT) for non-steady data processing. It is good at finding the optimal adaptive global mean fitting curve, which is superior to the common least-square method and running-mean approach. Take the air-sea momentum flux investigation as an example, only when the non-turbulent wind components is well extracted, can the remainder signal be seen as actual oscillations caused by turbulence. With the aid of —5/3 power law for the turbulence, a mode-filtering approach based on ESMD decomposition is developed here. The test on observational data indicates that this approach is very feasible and it may greatly reduce the error caused by the non-turbulent components.展开更多
Due to the poor understanding of the small-scale processes at the air-water interface, some lab experiments are done in a water tank by infrared techniques. With the help of ESMD method, the stochastic temperature seq...Due to the poor understanding of the small-scale processes at the air-water interface, some lab experiments are done in a water tank by infrared techniques. With the help of ESMD method, the stochastic temperature sequences extracted from the infrared photographs are decomposed into several empirical modes of general periodic forms. The corresponding analyses on the modes reveal that, within certain limits, both spatial and temporal frequencies increase along the wind speed. As for the amplitudes, the existence of wind may result in fold increasing of their values. In addition, when the wind speed is added from 4 m/s to 5 m/s, both frequency and amplitude of the surface temperature decrease and it implies an enhanced mixing and a weakened temperature gradient under the force of wind blowing.展开更多
文摘The ESMD method can be seen as a new alternate of the well-known Hilbert-Huang transform (HHT) for non-steady data processing. It is good at finding the optimal adaptive global mean fitting curve, which is superior to the common least-square method and running-mean approach. Take the air-sea momentum flux investigation as an example, only when the non-turbulent wind components is well extracted, can the remainder signal be seen as actual oscillations caused by turbulence. With the aid of —5/3 power law for the turbulence, a mode-filtering approach based on ESMD decomposition is developed here. The test on observational data indicates that this approach is very feasible and it may greatly reduce the error caused by the non-turbulent components.
文摘Due to the poor understanding of the small-scale processes at the air-water interface, some lab experiments are done in a water tank by infrared techniques. With the help of ESMD method, the stochastic temperature sequences extracted from the infrared photographs are decomposed into several empirical modes of general periodic forms. The corresponding analyses on the modes reveal that, within certain limits, both spatial and temporal frequencies increase along the wind speed. As for the amplitudes, the existence of wind may result in fold increasing of their values. In addition, when the wind speed is added from 4 m/s to 5 m/s, both frequency and amplitude of the surface temperature decrease and it implies an enhanced mixing and a weakened temperature gradient under the force of wind blowing.
