The joint probability distribution of wind speed and significant wave height in the Bohai Bay was investigated by comparing the Gurnbel logistic model, the Gumbel-Hougaard （GH） copula function, and the Clayton copul...The joint probability distribution of wind speed and significant wave height in the Bohai Bay was investigated by comparing the Gurnbel logistic model, the Gumbel-Hougaard （GH） copula function, and the Clayton copula function. Twenty years of wind data from 1989 to 2008 were collected from the European Centre for Medium-Range Weather Forecasts （ECMWF） database and the blended wind data of the Quick Scatterometer （QSCAT） satellite data set and re-analysis data from the United States National Centers for Environmental Prediction （NCEP）. Several typhoons were taken into account and merged with the background wind fields from the ECMWF or QSCAT/NCEP database. The 20-year data of significant wave height were calculated with the unstructured-grid version of the third-generation wind wave model Simulating WAves Nearshore （SWAN） under extreme wind process conditions. The Gumbel distribution was used for univariate and marginal distributions. The distribution parameters were estimated with the method of L-moments. Based on the marginal distributions, the joint probability distributions, the associated return periods, and the conditional probability distributions were obtained. The GH copula function was found to be optimal according to the ordinary least squares （OLS） test. The results show that wind waves are the prevailing type of wave in the Bohai Bay.展开更多
Under the assumption of strictly stationary process, this paper proposes a nonparametric model to test the kurtosis and conditional kurtosis for risk time series. We apply this method to the daily returns of S＆P500 i...Under the assumption of strictly stationary process, this paper proposes a nonparametric model to test the kurtosis and conditional kurtosis for risk time series. We apply this method to the daily returns of S＆P500 index and the Shanghai Composite Index, and simulate GARCH data for verifying the efficiency of the presented model. Our results indicate that the risk series distribution is heavily tailed, but the historical information can make its future distribution light-tailed. However the far future distribution＇s tails are little affected by the historical data.展开更多
The objective of this study is to examine the use of the conditional probability function(CPF) and nonparametric regression(NPR) to identify the relationship between wind direction and concentration of PM2.5(particula...The objective of this study is to examine the use of the conditional probability function(CPF) and nonparametric regression(NPR) to identify the relationship between wind direction and concentration of PM2.5(particulate matter with aerodynamic diameter less than or equal to 2.5 μm). Twenty four-hour integrated PM2.5 mass and species concentrations were measured at the St. Louis-Midwest Supersite in East St. Louis,Illinois,USA in the periods of 22-28 June 2001,7-13 November 2001,and 19-25 March 2002. Wind directions were measured on site. The concentrations of 15 elements and ions,i.e. Al,As,Cd,Cr,Cu,Fe,Mn,Ni,Pb,Se,Zn,OC,EC,SO4,and NO3 were calculated using the CPF and NPR. The comparison between the results obtained from the CPF and NPR demonstrated that they both agreed well with the locations of the known local point sources. The CPF was simpler and easier to calculate than NPR. In contrast,NPR provided PM2.5 concentrations but with some uncertainties. This study indicates that both methods can be utilized to promote the source apportionment study of ambient PM2.5.展开更多
基金supported by the Science Fund for Creative Research Groups of the National Natural ScienceFoundation of China (Grant No. 51021004)the National High Technology Research and DevelopmentProgram of China (863 Program, Grants No. 2012AA112509 and 2012AA051702)
文摘The joint probability distribution of wind speed and significant wave height in the Bohai Bay was investigated by comparing the Gurnbel logistic model, the Gumbel-Hougaard （GH） copula function, and the Clayton copula function. Twenty years of wind data from 1989 to 2008 were collected from the European Centre for Medium-Range Weather Forecasts （ECMWF） database and the blended wind data of the Quick Scatterometer （QSCAT） satellite data set and re-analysis data from the United States National Centers for Environmental Prediction （NCEP）. Several typhoons were taken into account and merged with the background wind fields from the ECMWF or QSCAT/NCEP database. The 20-year data of significant wave height were calculated with the unstructured-grid version of the third-generation wind wave model Simulating WAves Nearshore （SWAN） under extreme wind process conditions. The Gumbel distribution was used for univariate and marginal distributions. The distribution parameters were estimated with the method of L-moments. Based on the marginal distributions, the joint probability distributions, the associated return periods, and the conditional probability distributions were obtained. The GH copula function was found to be optimal according to the ordinary least squares （OLS） test. The results show that wind waves are the prevailing type of wave in the Bohai Bay.
基金supported by the National Natural Science Foundation of China (Grant No.60773081)the Key Project of Shanghai Municipality (Grant No.S30104)
文摘Under the assumption of strictly stationary process, this paper proposes a nonparametric model to test the kurtosis and conditional kurtosis for risk time series. We apply this method to the daily returns of S＆P500 index and the Shanghai Composite Index, and simulate GARCH data for verifying the efficiency of the presented model. Our results indicate that the risk series distribution is heavily tailed, but the historical information can make its future distribution light-tailed. However the far future distribution＇s tails are little affected by the historical data.
基金supported by the National Natural Science Foundation of China under the grant number 40675060, 2006AA09Z151 program of the Ministry of Science and Technology of the People’s Republic of China, and GYHY200706031 program of China Meteorological Administration.
文摘The objective of this study is to examine the use of the conditional probability function(CPF) and nonparametric regression(NPR) to identify the relationship between wind direction and concentration of PM2.5(particulate matter with aerodynamic diameter less than or equal to 2.5 μm). Twenty four-hour integrated PM2.5 mass and species concentrations were measured at the St. Louis-Midwest Supersite in East St. Louis,Illinois,USA in the periods of 22-28 June 2001,7-13 November 2001,and 19-25 March 2002. Wind directions were measured on site. The concentrations of 15 elements and ions,i.e. Al,As,Cd,Cr,Cu,Fe,Mn,Ni,Pb,Se,Zn,OC,EC,SO4,and NO3 were calculated using the CPF and NPR. The comparison between the results obtained from the CPF and NPR demonstrated that they both agreed well with the locations of the known local point sources. The CPF was simpler and easier to calculate than NPR. In contrast,NPR provided PM2.5 concentrations but with some uncertainties. This study indicates that both methods can be utilized to promote the source apportionment study of ambient PM2.5.
