This paper demonstrates that the spatial distribution of the ionospheric TEC over the Indian region can be reconstructed with appreciable accuracy using minimal numbers of empirical orthogonal functions as a basis.The...This paper demonstrates that the spatial distribution of the ionospheric TEC over the Indian region can be reconstructed with appreciable accuracy using minimal numbers of empirical orthogonal functions as a basis.These basis functions were derived using the Singular Value Decomposition of a matrix composed of pragmatic vertical Total Electron Content(VTEC)values collected across varied ionospheric conditions and measured over the region of interest.The reconstruction was achieved by linearly combining the appropriately chosen significant bases with corresponding weight factors.The reconstruction accuracy of the algorithm was found to be better than 4 TECU(TECU=1016electrons/m2)for more than 99.9%of the time when tested over the complete year of 2016 with only eight basis vectors.The containment factor,defined here,indicates the goodness of the chosen bases in representing the arbitrary VTEC distributions and is found to remain typically high,aiding in improved algorithm performance.The performance,however,was found to be sensitive to the seasons and geomagnetic conditions.Deteriorated performance was observed when tested for the St.Patrick's Day storm data.The deterioration was attributed to the structural alteration of the ionospheric plasma density and the presence of atypical modes during the storm.The results ascertain the prospect of a faithful representation of the spatial distribution of the ionospheric VTEC using limited parametric variables,which may find utility in navigation,radar,and various other applications.展开更多
This study presents an analysis of the spectral characteristics of remote sensing reflectance(Rrs)in northwestern South China Sea based on the in situ optical and water quality data for August 2018.Rrswas initially di...This study presents an analysis of the spectral characteristics of remote sensing reflectance(Rrs)in northwestern South China Sea based on the in situ optical and water quality data for August 2018.Rrswas initially divided into four classes,classes A to D,using the max-classification algorithm,and the spectral properties of whole Rrs were characterized using the empirical orthogonal function(EOF)analysis.Subsequently,the dominant factors in each EOF mode were determined.The results indicated that more than 95%of the variances of Rrs are partly driven by the back-scattering characteristics of the suspended matter.The initial two EOF modes were well correlated with the total suspended matter and back-scattering coefficient.Furthermore,the first EOF modes of the four classes of Rrs(A-D Rrs-EOF1)significantly contributed to the total variances of each Rrs class.In addition,the correlation coefficients between the amplitude factors of class A-D Rrs-EOF1 and the variances of the relevant water quality and optical parameters were better than those of the unclassified ones.The spectral shape of class ARrs-EOF1 was governed by the absorption characteristic of chlorophyll a and colored dissolved organic matter(CDOM).The spectral shape of class B Rrs-EOF1 was governed by the absorption characteristic of CDOM since it exhibited a high correlation with the absorption coefficient of CDOM(ag(λ)),whereas the spectral shape of class C Rrs-EOF1 was governed by the back-scattering characteristics but not affected by the suspended matter.The spectral shape of class D Rrs-EOF1 exhibited a relatively good correlation with all the water quality parameters,which played a significant role in deciding its spectral shape.展开更多
A one-step band-limited extrapolation procedure is systematically developed under an a priori assumption of bandwidth. The rationale of the proposed scheme is to expand the known signal segment based on a band-limited...A one-step band-limited extrapolation procedure is systematically developed under an a priori assumption of bandwidth. The rationale of the proposed scheme is to expand the known signal segment based on a band-limited basis function set and then to generate a set of Empirical Orthogonal Functions (EOF’s) adaptively from the sample values of the band-limited function set. Simulation results indicate that, in addi- tion to the attractive adaptive feature, this scheme also appears to guarantee a smooth result for inexact data, thus suggesting the robustness of the proposed procedure.展开更多
The initial ensemble perturbations for an ensemble data assimilation system are expected to reasonably sample model uncertainty at the time of analysis to further reduce analysis uncertainty. Therefore, the careful ch...The initial ensemble perturbations for an ensemble data assimilation system are expected to reasonably sample model uncertainty at the time of analysis to further reduce analysis uncertainty. Therefore, the careful choice of an initial ensemble perturbation method that dynamically cycles ensemble perturbations is required for the optimal performance of the system. Based on the multivariate empirical orthogonal function (MEOF) method, a new ensemble initialization scheme is developed to generate balanced initial perturbations for the ensemble Kalman filter (EnKF) data assimilation, with a reasonable consideration of the physical relationships between different model variables. The scheme is applied in assimilation experiments with a global spectral atmospheric model and with real observations. The proposed perturbation method is compared to the commonly used method of spatially-correlated random perturbations. The comparisons show that the model uncertainties prior to the first analysis time, which are forecasted from the balanced ensemble initial fields, maintain a much more reasonable spread and a more accurate forecast error covariance than those from the randomly perturbed initial fields. The analysis results are further improved by the balanced ensemble initialization scheme due to more accurate background information. Also, a 20-day continuous assimilation experiment shows that the ensemble spreads for each model variable are still retained in reasonable ranges without considering additional perturbations or inflations during the assimilation cycles, while the ensemble spreads from the randomly perturbed initialization scheme decrease and collapse rapidly.展开更多
Aiming at the difficulty of accurately constructing the dynamic model of subtropical high, based on the potential height field time series over 500 hPa layer of T106 numerical forecast products, by using EOF（empirica...Aiming at the difficulty of accurately constructing the dynamic model of subtropical high, based on the potential height field time series over 500 hPa layer of T106 numerical forecast products, by using EOF（empirical orthogonal function） temporal-spatial separation technique, the disassembled EOF time coefficients series were regarded as dynamical model variables, and dynamic system retrieval idea as well as genetic algorithm were introduced to make dynamical model parameters optimization search, then, a reasonable non-linear dynamic model of EOF time-coefficients was established. By dynamic model integral and EOF temporal-spatial components assembly, a mid-/long-term forecast of subtropical high was carried out. The experimental results show that the forecast results of dynamic model are superior to that of general numerical model forecast results. A new modeling idea and forecast technique is presented for diagnosing and forecasting such complicated weathers as subtropical high.展开更多
In this paper,some short time series of pnserved data pm sectopm 18°20′N in the tropical western Pacificwere reorganized to give mixed depth-time series,and processed by means of means of empirical orthogonal fo...In this paper,some short time series of pnserved data pm sectopm 18°20′N in the tropical western Pacificwere reorganized to give mixed depth-time series,and processed by means of means of empirical orthogonal fonction analysis. It is indicated that the original form of element distribution could be obtained by linear combination of several main canonical distribution functions, and the intrinsic structure of element distribution on a certain section and its variation propertiescould be reveled by canonical distribution function and profiles in corresponding periods.展开更多
文摘This paper demonstrates that the spatial distribution of the ionospheric TEC over the Indian region can be reconstructed with appreciable accuracy using minimal numbers of empirical orthogonal functions as a basis.These basis functions were derived using the Singular Value Decomposition of a matrix composed of pragmatic vertical Total Electron Content(VTEC)values collected across varied ionospheric conditions and measured over the region of interest.The reconstruction was achieved by linearly combining the appropriately chosen significant bases with corresponding weight factors.The reconstruction accuracy of the algorithm was found to be better than 4 TECU(TECU=1016electrons/m2)for more than 99.9%of the time when tested over the complete year of 2016 with only eight basis vectors.The containment factor,defined here,indicates the goodness of the chosen bases in representing the arbitrary VTEC distributions and is found to remain typically high,aiding in improved algorithm performance.The performance,however,was found to be sensitive to the seasons and geomagnetic conditions.Deteriorated performance was observed when tested for the St.Patrick's Day storm data.The deterioration was attributed to the structural alteration of the ionospheric plasma density and the presence of atypical modes during the storm.The results ascertain the prospect of a faithful representation of the spatial distribution of the ionospheric VTEC using limited parametric variables,which may find utility in navigation,radar,and various other applications.
基金The Key Projects of the Guangdong Education Department under contract No.2019KZDXM019the Fund of Southern Marine Science and Engineering Guangdong Laboratory(Zhanjiang)under contract No.ZJW-2019-08+2 种基金High-Level Marine Discipline Team Project of Guangdong Ocean University under contract No.002026002009the Guangdong Graduate Academic Forum Project under contract No.230420003the"First Class"discipline construction platform project in 2019 of Guangdong Ocean University under contract No.231419026。
文摘This study presents an analysis of the spectral characteristics of remote sensing reflectance(Rrs)in northwestern South China Sea based on the in situ optical and water quality data for August 2018.Rrswas initially divided into four classes,classes A to D,using the max-classification algorithm,and the spectral properties of whole Rrs were characterized using the empirical orthogonal function(EOF)analysis.Subsequently,the dominant factors in each EOF mode were determined.The results indicated that more than 95%of the variances of Rrs are partly driven by the back-scattering characteristics of the suspended matter.The initial two EOF modes were well correlated with the total suspended matter and back-scattering coefficient.Furthermore,the first EOF modes of the four classes of Rrs(A-D Rrs-EOF1)significantly contributed to the total variances of each Rrs class.In addition,the correlation coefficients between the amplitude factors of class A-D Rrs-EOF1 and the variances of the relevant water quality and optical parameters were better than those of the unclassified ones.The spectral shape of class ARrs-EOF1 was governed by the absorption characteristic of chlorophyll a and colored dissolved organic matter(CDOM).The spectral shape of class B Rrs-EOF1 was governed by the absorption characteristic of CDOM since it exhibited a high correlation with the absorption coefficient of CDOM(ag(λ)),whereas the spectral shape of class C Rrs-EOF1 was governed by the back-scattering characteristics but not affected by the suspended matter.The spectral shape of class D Rrs-EOF1 exhibited a relatively good correlation with all the water quality parameters,which played a significant role in deciding its spectral shape.
文摘A one-step band-limited extrapolation procedure is systematically developed under an a priori assumption of bandwidth. The rationale of the proposed scheme is to expand the known signal segment based on a band-limited basis function set and then to generate a set of Empirical Orthogonal Functions (EOF’s) adaptively from the sample values of the band-limited function set. Simulation results indicate that, in addi- tion to the attractive adaptive feature, this scheme also appears to guarantee a smooth result for inexact data, thus suggesting the robustness of the proposed procedure.
基金supported by the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant No. KZCX1-YW-12-03)the National Basic Research Program of China (Grant No. 2010CB951901)the National Natural Science Foundation of China (Grant No. 40805033)
文摘The initial ensemble perturbations for an ensemble data assimilation system are expected to reasonably sample model uncertainty at the time of analysis to further reduce analysis uncertainty. Therefore, the careful choice of an initial ensemble perturbation method that dynamically cycles ensemble perturbations is required for the optimal performance of the system. Based on the multivariate empirical orthogonal function (MEOF) method, a new ensemble initialization scheme is developed to generate balanced initial perturbations for the ensemble Kalman filter (EnKF) data assimilation, with a reasonable consideration of the physical relationships between different model variables. The scheme is applied in assimilation experiments with a global spectral atmospheric model and with real observations. The proposed perturbation method is compared to the commonly used method of spatially-correlated random perturbations. The comparisons show that the model uncertainties prior to the first analysis time, which are forecasted from the balanced ensemble initial fields, maintain a much more reasonable spread and a more accurate forecast error covariance than those from the randomly perturbed initial fields. The analysis results are further improved by the balanced ensemble initialization scheme due to more accurate background information. Also, a 20-day continuous assimilation experiment shows that the ensemble spreads for each model variable are still retained in reasonable ranges without considering additional perturbations or inflations during the assimilation cycles, while the ensemble spreads from the randomly perturbed initialization scheme decrease and collapse rapidly.
基金Project supported by the National Natural Science Foundation of China (No.40375019) the Tropical Marine and Meteorology Science Foundation (No.200609) the Jiangsu Key Laboratory of Meteorological Disaster Foundation (No.KLME0507)
文摘Aiming at the difficulty of accurately constructing the dynamic model of subtropical high, based on the potential height field time series over 500 hPa layer of T106 numerical forecast products, by using EOF（empirical orthogonal function） temporal-spatial separation technique, the disassembled EOF time coefficients series were regarded as dynamical model variables, and dynamic system retrieval idea as well as genetic algorithm were introduced to make dynamical model parameters optimization search, then, a reasonable non-linear dynamic model of EOF time-coefficients was established. By dynamic model integral and EOF temporal-spatial components assembly, a mid-/long-term forecast of subtropical high was carried out. The experimental results show that the forecast results of dynamic model are superior to that of general numerical model forecast results. A new modeling idea and forecast technique is presented for diagnosing and forecasting such complicated weathers as subtropical high.
文摘In this paper,some short time series of pnserved data pm sectopm 18°20′N in the tropical western Pacificwere reorganized to give mixed depth-time series,and processed by means of means of empirical orthogonal fonction analysis. It is indicated that the original form of element distribution could be obtained by linear combination of several main canonical distribution functions, and the intrinsic structure of element distribution on a certain section and its variation propertiescould be reveled by canonical distribution function and profiles in corresponding periods.
