Conditional nonlinear optimal perturbation(CNOP) is an extension of the linear singular vector technique in the nonlinear regime.It represents the initial perturbation that is subjected to a given physical constraint,...Conditional nonlinear optimal perturbation(CNOP) is an extension of the linear singular vector technique in the nonlinear regime.It represents the initial perturbation that is subjected to a given physical constraint,and results in the largest nonlinear evolution at the prediction time.CNOP-type errors play an important role in the predictability of weather and climate.Generally,when calculating CNOP in a complicated numerical model,we need the gradient of the objective function with respect to the initial perturbations to provide the descent direction for searching the phase space.The adjoint technique is widely used to calculate the gradient of the objective function.However,it is difficult and cumbersome to construct the adjoint model of a complicated numerical model,which imposes a limitation on the application of CNOP.Based on previous research,this study proposes a new ensemble projection algorithm based on singular vector decomposition(SVD).The new algorithm avoids the localization procedure of previous ensemble projection algorithms,and overcomes the uncertainty caused by choosing the localization radius empirically.The new algorithm is applied to calculate the CNOP in an intermediate forecasting model.The results show that the CNOP obtained by the new ensemble-based algorithm can effectively approximate that calculated by the adjoint algorithm,and retains the general spatial characteristics of the latter.Hence,the new SVD-based ensemble projection algorithm proposed in this study is an effective method of approximating the CNOP.展开更多
We studied the structure of the Indian Ocean(IO)Meridional Overturning Circulation(MOC)by applying a nonlinear inertia theory and analyzed the coupled relationship between zonal wind stress and MOC anomalies.Our resul...We studied the structure of the Indian Ocean(IO)Meridional Overturning Circulation(MOC)by applying a nonlinear inertia theory and analyzed the coupled relationship between zonal wind stress and MOC anomalies.Our results show that the inertia theory can represent the main characteristics of the IO MOC:the subtropical cell(STC)and cross-equator cell(CEC).The stream function in equatorial and northern IO changes a sign from winter to summer.The anomalies of the zonal wind stress and stream function can be decomposed into summer monsoon mode,winter monsoon mode,and abnormal mode by using the singular vector decomposition(SVD)analysis.The first two modes correlate with the transport through 20°S and equator simultaneously whereas the relationship obscures between the third mode and transports across 20°S and equator,showing the complex air-sea interaction process.The transport experiences multi-time scale variability according to the continuous power spectrum analysis,with major periods in inter-annual and decadal scale.展开更多
Tower-based solar-induced chlorophyll fluorescence(SIF)measurements have yielded crucial datasets for investigating the diurnal patterns of SIF and its relationship with vegetation photosynthesis.This study assessed t...Tower-based solar-induced chlorophyll fluorescence(SIF)measurements have yielded crucial datasets for investigating the diurnal patterns of SIF and its relationship with vegetation photosynthesis.This study assessed the performance of 3 distinct SIF retrieval algorithms,including band shape fitting(BSF),3-band Fraunhofer line discrimination(3FLD),and a data-driven approach based on singular vector decomposition(SVD),for retrieving far-red SIF diurnal patterns from tower-based observations at the 2 flux sites in China.This study analyzed diurnal patterns of SIF and SIF yield,as well as correlations between SIF,near-infrared radiance reflected by vegetation(NIRvR),and gross primary productivity(GPP)at diurnal and seasonal scales.More pronounced inconsistencies in retrieved SIF by different algorithms at noon compared with the morning and afternoon were observed.Similarly,correlations between the SIF and NIRvR or GPP are weaker during midday.This study underscores the need to consider the reliability of SIF data when investigating diurnal patterns,and the necessity for developments in tower-based SIF retrieval algorithms.展开更多
基金jointly sponsored by the National Natural Science Foundation of China(Grant Nos.41176013,41230420 and 41006007)
文摘Conditional nonlinear optimal perturbation(CNOP) is an extension of the linear singular vector technique in the nonlinear regime.It represents the initial perturbation that is subjected to a given physical constraint,and results in the largest nonlinear evolution at the prediction time.CNOP-type errors play an important role in the predictability of weather and climate.Generally,when calculating CNOP in a complicated numerical model,we need the gradient of the objective function with respect to the initial perturbations to provide the descent direction for searching the phase space.The adjoint technique is widely used to calculate the gradient of the objective function.However,it is difficult and cumbersome to construct the adjoint model of a complicated numerical model,which imposes a limitation on the application of CNOP.Based on previous research,this study proposes a new ensemble projection algorithm based on singular vector decomposition(SVD).The new algorithm avoids the localization procedure of previous ensemble projection algorithms,and overcomes the uncertainty caused by choosing the localization radius empirically.The new algorithm is applied to calculate the CNOP in an intermediate forecasting model.The results show that the CNOP obtained by the new ensemble-based algorithm can effectively approximate that calculated by the adjoint algorithm,and retains the general spatial characteristics of the latter.Hence,the new SVD-based ensemble projection algorithm proposed in this study is an effective method of approximating the CNOP.
基金supported by the National Basic Research Program of China(Grant No.2010CB950300)
文摘We studied the structure of the Indian Ocean(IO)Meridional Overturning Circulation(MOC)by applying a nonlinear inertia theory and analyzed the coupled relationship between zonal wind stress and MOC anomalies.Our results show that the inertia theory can represent the main characteristics of the IO MOC:the subtropical cell(STC)and cross-equator cell(CEC).The stream function in equatorial and northern IO changes a sign from winter to summer.The anomalies of the zonal wind stress and stream function can be decomposed into summer monsoon mode,winter monsoon mode,and abnormal mode by using the singular vector decomposition(SVD)analysis.The first two modes correlate with the transport through 20°S and equator simultaneously whereas the relationship obscures between the third mode and transports across 20°S and equator,showing the complex air-sea interaction process.The transport experiences multi-time scale variability according to the continuous power spectrum analysis,with major periods in inter-annual and decadal scale.
基金funded by the National Key Research and Development Program of China(2022YFF1301900)the National Natural Science Foundation of China(42071310 and 42425001).
文摘Tower-based solar-induced chlorophyll fluorescence(SIF)measurements have yielded crucial datasets for investigating the diurnal patterns of SIF and its relationship with vegetation photosynthesis.This study assessed the performance of 3 distinct SIF retrieval algorithms,including band shape fitting(BSF),3-band Fraunhofer line discrimination(3FLD),and a data-driven approach based on singular vector decomposition(SVD),for retrieving far-red SIF diurnal patterns from tower-based observations at the 2 flux sites in China.This study analyzed diurnal patterns of SIF and SIF yield,as well as correlations between SIF,near-infrared radiance reflected by vegetation(NIRvR),and gross primary productivity(GPP)at diurnal and seasonal scales.More pronounced inconsistencies in retrieved SIF by different algorithms at noon compared with the morning and afternoon were observed.Similarly,correlations between the SIF and NIRvR or GPP are weaker during midday.This study underscores the need to consider the reliability of SIF data when investigating diurnal patterns,and the necessity for developments in tower-based SIF retrieval algorithms.
