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
The moving-mean method is one of the conventional approaches for trend-extraction from a data set. It is usually applied in an empirical way. The smoothing degree of the trend depends on the selections of window lengt...The moving-mean method is one of the conventional approaches for trend-extraction from a data set. It is usually applied in an empirical way. The smoothing degree of the trend depends on the selections of window length and weighted coefficients, which are associated with the change pattern of the data. Are there any uniform criteria for determining them? The present article is a reaction to this fundamental problem. By investigating many kinds of data, the results show that: 1) Within a certain range, the more points which participate in moving-mean, the better the trend function. However, in case the window length is too long, the trend function may tend to the ordinary global mean. 2) For a given window length, what matters is the choice of weighted coefficients. As the five-point case concerned, the local-midpoint, local-mean and global-mean criteria hold. Among these three criteria, the local-mean one has the strongest adaptability, which is suggested for your usage.展开更多
Drought is one of the severe natural disasters to impact human society and occurs widely and frequently in China,causing considerable damage to the living environment of humans.The Yellow River basin(YRB)of China show...Drought is one of the severe natural disasters to impact human society and occurs widely and frequently in China,causing considerable damage to the living environment of humans.The Yellow River basin(YRB)of China shows great vulnerability to drought in the major basins;thus,drought monitoring in the YRB is particularly important.Based on monthly data of 124 meteorological stations from 1961 to 2015,the Standardized Precipitation Evapotranspiration Index(SPEI)was used to explore the temporal and spatial patterns of drought in the YRB.The periods and trends of drought were identified by Extreme-point Symmetric Mode Decomposition(ESMD),and the research stages were determined by Bernaola-Galvan Segmentation Algorithm(BGSA).The annual and seasonal variation,frequency and intensity of drought were studied in the YRB.The results indicated that(1)for the past 55 years,the drought in the YRB has increased significantly with a tendency rate of-0.148(10 a)^(-1),in which the area Lanzhou to Hekou was the most vulnerable affected(-0.214(10 a)^(-1));(2)the drought periods(2.9,5,10.2 and 18.3 years)and stages(1961–1996,1997–2002 and 2003–2015)were characterized and detected by ESMD and BGSA;(3)the sequence of drought frequency was summer,spring,autumn and winter with mean values of 71.0%,47.2%,10.2%and 6.9%,respectively;and(4)the sequence of drought intensity was summer,spring,winter and autumn with mean values of 0.93,0.40,0.05 and 0.04,respectively.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.
文摘The moving-mean method is one of the conventional approaches for trend-extraction from a data set. It is usually applied in an empirical way. The smoothing degree of the trend depends on the selections of window length and weighted coefficients, which are associated with the change pattern of the data. Are there any uniform criteria for determining them? The present article is a reaction to this fundamental problem. By investigating many kinds of data, the results show that: 1) Within a certain range, the more points which participate in moving-mean, the better the trend function. However, in case the window length is too long, the trend function may tend to the ordinary global mean. 2) For a given window length, what matters is the choice of weighted coefficients. As the five-point case concerned, the local-midpoint, local-mean and global-mean criteria hold. Among these three criteria, the local-mean one has the strongest adaptability, which is suggested for your usage.
基金supported by the Henan Province Scientific and Technological Project (Grant Nos. 162102410066 & 172102410075)the National Key Research and Development Plan (Grant No. 2016YFC0401407)the open research fund of the State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin at the China Institute of Water Resources and Hydropower Research (Grant No. IWHR-SKL-201701)
文摘Drought is one of the severe natural disasters to impact human society and occurs widely and frequently in China,causing considerable damage to the living environment of humans.The Yellow River basin(YRB)of China shows great vulnerability to drought in the major basins;thus,drought monitoring in the YRB is particularly important.Based on monthly data of 124 meteorological stations from 1961 to 2015,the Standardized Precipitation Evapotranspiration Index(SPEI)was used to explore the temporal and spatial patterns of drought in the YRB.The periods and trends of drought were identified by Extreme-point Symmetric Mode Decomposition(ESMD),and the research stages were determined by Bernaola-Galvan Segmentation Algorithm(BGSA).The annual and seasonal variation,frequency and intensity of drought were studied in the YRB.The results indicated that(1)for the past 55 years,the drought in the YRB has increased significantly with a tendency rate of-0.148(10 a)^(-1),in which the area Lanzhou to Hekou was the most vulnerable affected(-0.214(10 a)^(-1));(2)the drought periods(2.9,5,10.2 and 18.3 years)and stages(1961–1996,1997–2002 and 2003–2015)were characterized and detected by ESMD and BGSA;(3)the sequence of drought frequency was summer,spring,autumn and winter with mean values of 71.0%,47.2%,10.2%and 6.9%,respectively;and(4)the sequence of drought intensity was summer,spring,winter and autumn with mean values of 0.93,0.40,0.05 and 0.04,respectively.
