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
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
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
充分掌握大尺度流域降雨侵蚀力的时空变化特征对流域水土保持、防洪减灾和生态环境保护至关重要。基于长江中下游的119个气象站点57a逐日降雨资料,通过Xie模型计算各站降雨侵蚀力,使用旋转经验正交函数(REOF)法对降雨侵蚀力进行区域划分...充分掌握大尺度流域降雨侵蚀力的时空变化特征对流域水土保持、防洪减灾和生态环境保护至关重要。基于长江中下游的119个气象站点57a逐日降雨资料,通过Xie模型计算各站降雨侵蚀力,使用旋转经验正交函数(REOF)法对降雨侵蚀力进行区域划分;结合Mann-Kendal检验、重标极差(R/S)法和相关性分析方法分析长江中下游降雨侵蚀力的时空变化特征,并揭示其与植被覆盖度之间的关系。结果表明:(1)长江中下游降雨侵蚀力整体呈上升趋势,年均降雨侵蚀力为5643MJ mm hm^(-2)h^(-1)。(2)不同季节降雨侵蚀力空间分布存在差异。冷季降雨侵蚀力空间分布不均,高值区主要集中在流域的西部和东北部,而暖季降雨侵蚀力则表现为以江西省为中心沿西北方向递减的空间分布格局,最大值和最小值出现在鄱阳湖环湖区(III区)和长江干流武汉以下段及太湖水系(IV区)。(3)长江中下游相邻地理分区间降雨侵蚀力变化速率差异较大,降雨侵蚀力区域性差异显著。其中III区、湘江及赣江流域(I区)和IV区年均降雨侵蚀力呈显著增长趋势(P<0.05)且未来将保持该趋势,为水土保持重点关注区域。(4)研究所发现的长江中下游水土保持重点关注区域的降雨侵蚀力与植被覆盖度存在负相关。但值得注意的是I区在冷季呈现正相关,而且其中的湘江上游流域出现显著正相关。研究表明降雨侵蚀力是影响地表侵蚀过程的关键因素,侵蚀性降水会影响植被覆盖情况,进而影响地表的侵蚀过程。因此在重点关注高降雨侵蚀力地区的同时还需加强植被保护工作。研究结果可为长江中下游区域水土保持及生态环境保护工作提供科学依据。展开更多
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.
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.
文摘充分掌握大尺度流域降雨侵蚀力的时空变化特征对流域水土保持、防洪减灾和生态环境保护至关重要。基于长江中下游的119个气象站点57a逐日降雨资料,通过Xie模型计算各站降雨侵蚀力,使用旋转经验正交函数(REOF)法对降雨侵蚀力进行区域划分;结合Mann-Kendal检验、重标极差(R/S)法和相关性分析方法分析长江中下游降雨侵蚀力的时空变化特征,并揭示其与植被覆盖度之间的关系。结果表明:(1)长江中下游降雨侵蚀力整体呈上升趋势,年均降雨侵蚀力为5643MJ mm hm^(-2)h^(-1)。(2)不同季节降雨侵蚀力空间分布存在差异。冷季降雨侵蚀力空间分布不均,高值区主要集中在流域的西部和东北部,而暖季降雨侵蚀力则表现为以江西省为中心沿西北方向递减的空间分布格局,最大值和最小值出现在鄱阳湖环湖区(III区)和长江干流武汉以下段及太湖水系(IV区)。(3)长江中下游相邻地理分区间降雨侵蚀力变化速率差异较大,降雨侵蚀力区域性差异显著。其中III区、湘江及赣江流域(I区)和IV区年均降雨侵蚀力呈显著增长趋势(P<0.05)且未来将保持该趋势,为水土保持重点关注区域。(4)研究所发现的长江中下游水土保持重点关注区域的降雨侵蚀力与植被覆盖度存在负相关。但值得注意的是I区在冷季呈现正相关,而且其中的湘江上游流域出现显著正相关。研究表明降雨侵蚀力是影响地表侵蚀过程的关键因素,侵蚀性降水会影响植被覆盖情况,进而影响地表的侵蚀过程。因此在重点关注高降雨侵蚀力地区的同时还需加强植被保护工作。研究结果可为长江中下游区域水土保持及生态环境保护工作提供科学依据。
