Based on the effect of sample size on the near- infrared （NIR） spectrum, the absorbance （log（R）） in any wavelength is divided into two parts, and one of them is defined as non-particle-size-related spectrometry ...Based on the effect of sample size on the near- infrared （NIR） spectrum, the absorbance （log（R）） in any wavelength is divided into two parts, and one of them is defined as non-particle-size-related spectrometry （nPRS） because it is not influenced by particle size. To study the relationship between the absorbance and l^article size, the experiment material including nine samples with different particle size was used. According to the regression analysis, the relationship was studied as the reciprocal regression model, y = a ~ bx ＋ c/x. Meanwhile, the model divides absorbance into two parts, one of them forms nPRS. According to the nPRS, a new correction method, particle size regression correction （PRC） was introduced. In discriminate analysis, the spectra from three different samples （rice, glutinous rice and sago）, pretreated by PRC, could be directly and accurately distinguished by principal component analysis （PCA）, while by the traditional correction method, such as multiplicative signal correction （MSC） and standard normal variate （SNV）, could not do that.展开更多
A regressive correction method is presented with the primary goal of improving ENSO simulation in regional coupled GCM.It focuses on the correction of ocean-atmosphere exchanged fluxes.On the basis of numerical experi...A regressive correction method is presented with the primary goal of improving ENSO simulation in regional coupled GCM.It focuses on the correction of ocean-atmosphere exchanged fluxes.On the basis of numerical experiments and analysis,the method can be described as follows:first,driving the ocean model with heat and momentum flux computed from a long-term observation data set;the pro-duced SST is then applied to force the AGCM as its boundary condition;after that the AGCM’s simula-tion and the corresponding observation can be correlated by a linear regressive formula.Thus the re-gressive correction coefficients for the simulation with spatial and temporal variation could be obtained by linear fitting.Finally the coefficients are applied to redressing the variables used for the calculation of the exchanged air-sea flux in the coupled model when it starts integration.This method together with the anomaly coupling method is tested in a regional coupled model,which is composed of a global grid-point atmospheric general circulation model and a high-resolution tropical Pacific Ocean model.The comparison of the results shows that it is superior to the anomaly coupling both in reducing the coupled model‘climate drift’and in improving the ENSO simulation in the tropical Pacific Ocean.展开更多
基金The work was made possible with support from two research projects by the National Natural Science Foundation of China （Grant Nos. 61144012 and 31101289）.
文摘Based on the effect of sample size on the near- infrared （NIR） spectrum, the absorbance （log（R）） in any wavelength is divided into two parts, and one of them is defined as non-particle-size-related spectrometry （nPRS） because it is not influenced by particle size. To study the relationship between the absorbance and l^article size, the experiment material including nine samples with different particle size was used. According to the regression analysis, the relationship was studied as the reciprocal regression model, y = a ~ bx ＋ c/x. Meanwhile, the model divides absorbance into two parts, one of them forms nPRS. According to the nPRS, a new correction method, particle size regression correction （PRC） was introduced. In discriminate analysis, the spectra from three different samples （rice, glutinous rice and sago）, pretreated by PRC, could be directly and accurately distinguished by principal component analysis （PCA）, while by the traditional correction method, such as multiplicative signal correction （MSC） and standard normal variate （SNV）, could not do that.
基金the National Natural Science Foundation of China(Grant Nos.40523001,40631005,and 40620130113)
文摘A regressive correction method is presented with the primary goal of improving ENSO simulation in regional coupled GCM.It focuses on the correction of ocean-atmosphere exchanged fluxes.On the basis of numerical experiments and analysis,the method can be described as follows:first,driving the ocean model with heat and momentum flux computed from a long-term observation data set;the pro-duced SST is then applied to force the AGCM as its boundary condition;after that the AGCM’s simula-tion and the corresponding observation can be correlated by a linear regressive formula.Thus the re-gressive correction coefficients for the simulation with spatial and temporal variation could be obtained by linear fitting.Finally the coefficients are applied to redressing the variables used for the calculation of the exchanged air-sea flux in the coupled model when it starts integration.This method together with the anomaly coupling method is tested in a regional coupled model,which is composed of a global grid-point atmospheric general circulation model and a high-resolution tropical Pacific Ocean model.The comparison of the results shows that it is superior to the anomaly coupling both in reducing the coupled model‘climate drift’and in improving the ENSO simulation in the tropical Pacific Ocean.
