Range Doppler velocities derived from the Envisat advanced synthetic aperture radar（ASAR） wide swath images are analyzed and assessed against the numerically simulated surface current fields derived from the finite ...Range Doppler velocities derived from the Envisat advanced synthetic aperture radar（ASAR） wide swath images are analyzed and assessed against the numerically simulated surface current fields derived from the finite volume coastal ocean model（FVCOM） for the Changjiang Estuary. Comparisons with the FVCOM simulations show that the European Space Agency（ESA） Envisat ASAR based Doppler shift anomaly retrievals have the capability to capture quantitative information of the surface currents in the Changjiang Estuary. The uncertainty analysis of the ASAR range Doppler velocity estimates are discussed with regard to the azimuthal and range bias corrections, radar incidence angles, inaccuracy in the wind field corrections and the presence of rain cells.The corrected range Doppler velocities for the Changjiang Estuary area are highly valuable as they exhibit quantitative expressions related to the multiscale upper layer dynamics and surface current variability around the East China Sea, including the Changjiang Estuary.展开更多
为了更好地监测地表土壤湿度,利用多极化、多角度ASAR-APP影像数据,研究了裸露和小麦地表土壤湿度反演方法。对裸露地表,基于AIEM(advance integral equation model)模型,建立多项式半经验模型反演土壤湿度;对小麦地表,小入射角HH极化A...为了更好地监测地表土壤湿度,利用多极化、多角度ASAR-APP影像数据,研究了裸露和小麦地表土壤湿度反演方法。对裸露地表,基于AIEM(advance integral equation model)模型,建立多项式半经验模型反演土壤湿度;对小麦地表,小入射角HH极化ASAR数据与土壤湿度相关性更好,大入射角HH极化ASAR数据与小麦含水率相关性更好。基于水云模型,首先利用大入射角HH极化ASAR数据去除小麦冠层对雷达后向散射的影响,然后利用多角度ASAR数据推导建立小麦地表土壤湿度反演半经验模型;实测数据验证了裸露和小麦地表土壤湿度反演模型的适用性,利用验证数据反演裸露和小麦地表土壤湿度精度(RMSE)分别为3.55%、3.81%。结果表明,该文半经验模型具有较高的反演精度。展开更多
欧洲空间局的ENVISAT ASAR level 2算法是从合成孔径雷达(SAR)单视复图像反演涌浪方向谱的算法。该算法假设双峰海浪谱的SAR图像交叉谱是涌浪的图像交叉谱和风浪的图像交叉谱之和。实际上双峰海浪谱的SAR图像交叉谱中还有一个混合项,正...欧洲空间局的ENVISAT ASAR level 2算法是从合成孔径雷达(SAR)单视复图像反演涌浪方向谱的算法。该算法假设双峰海浪谱的SAR图像交叉谱是涌浪的图像交叉谱和风浪的图像交叉谱之和。实际上双峰海浪谱的SAR图像交叉谱中还有一个混合项,正是该混合项导致ENVI-SAT ASAR level 2算法有固有误差。利用遥感仿真的方法分析了不同海况条件下该算法的这一固有误差,结果表明,只有在有效波高较小、或风浪的成分较少、或双峰海浪的传播方向较靠近SAR距离向、或波长较长时固有误差才较小,ENVISAT ASAR level 2算法对海浪谱的反演才较为适用。展开更多
Active microwave remote sensing data were used to calculate the near-surface soil moisture in the vegetated areas.In this study,Advanced Synthetic Aperture Radar(ASAR)observations of surface soil moisture content were...Active microwave remote sensing data were used to calculate the near-surface soil moisture in the vegetated areas.In this study,Advanced Synthetic Aperture Radar(ASAR)observations of surface soil moisture content were used in a data assimilation framework to improve the estimation of the soil moisture profile at the middle reaches of the Heihe River Basin,Northwest China.A one-dimensional soil moisture assimilation system based on the ensemble Kalman filter(EnKF),the forward radiative transfer model,crop model,and the Distributed Hydrology-Soil-Vegetation Model(DHSVM)was developed.The crop model,as a semi-empirical model,was used to estimate the surface backscattering of vegetated areas.The DHSVM is a distributed hydrology-vegetation model that explicitly represents the effects of topography and vegetation on water fluxes through the landscape.Numerical experiments were conducted to assimilate the ASAR data into the DHSVM and in situ soil moisture at the middle reaches of the Heihe River Basin from June20 to July 15,2008.The results indicated that EnKF is effective for assimilating ASAR observations into the hydrological model.Compared with the simulation and in situ observations,the assimilated results were significantly improved in the surface layer and root layer,and the soil moisture varied slightly in the deep layer.Additionally,EnKF is an efficient approach to handle the strongly nonlinear problem which is practical and effective for soil moisture estimation by assimilation of remote sensing data.Moreover,to improve the assimilation results,further studies on obtaining more reliable forcing data and model parameters and increasing the efficiency and accuracy of the remote sensing observations are needed,also improving estimation accuracy of model operator is important.展开更多
The most promising approach for studying soil moisture is the assimilation of observation data and computational modeling. However, there is much uncertainty in the assimilation process, which affects the assimilation...The most promising approach for studying soil moisture is the assimilation of observation data and computational modeling. However, there is much uncertainty in the assimilation process, which affects the assimilation results. This research developed a one-dimensional soil moisture assimilation scheme based on the Ensemble Kalman Filter (EnKF) and Genetic Algorithm (GA). A two-dimensional hydrologic model-Distributed Hydrology-Soil-Vegetation Model (DHSVM) was coupled with a semi-empirical backscattering model (Oh). The Advanced Synthetic Aperture Radar (ASAR) data were assimilated with this coupled model and the field observation data were used to validate this scheme in the soil moisture assimilation experiment. In order to improve the assimilation results, a cost function was set up based on the distance between the simulated backscattering coefficient from the coupled model and the observed backscattering coefficient from ASAR. The EnKF and GA were used to re-initialize and re-parameterize the simulation process, respectively. The assimilation results were compared with the free-run simulations from hydrologic model and the field observation data. The results obtained indicate that this assimilation scheme is practical and it can improve the accuracy of soil moisture estimation significantly.展开更多
The validation and assessment of Envisat advanced synthetic aperture radar (ASAR) ocean wave spectra products are important to their application in ocean wave numerical predictions. Six-year ASAR wave spectra data are...The validation and assessment of Envisat advanced synthetic aperture radar (ASAR) ocean wave spectra products are important to their application in ocean wave numerical predictions. Six-year ASAR wave spectra data are compared with one-dimensional (1D) wave spectra of 55 co-located moored buoy observations in the northern Pacific Ocean. The ASAR wave spectra data are firstly quality control filtered and spatio-temporal matched with buoy data. The comparisons are then performed in terms of 1D wave spectra, significant wave height (SWH) and mean wave period (MWP) in different spatio-temporal offsets respectively. SWH comparison results show the evident dependence of SWH biases on wind speed and the ASAR SWH saturation effect. The ASAR wave spectra tend to underestimate SWH at high wind speeds and overestimate SWH at low wind speeds. MWP comparison results show that MWP has a systematic bias and therefore it should be bias-modified before used. The comparisons of 1D wave spectra show that both wave spectra agree better at low frequencies than at high frequencies, which indicates the ASAR data cannot resolve the high frequency waves.展开更多
基金The National Basic Research Program(973 Program)of China under contract No.2010CB951204European Space Agency-Ministry of Science and Technology of the People’s Republic of China Dragon 3 Cooperation Programme under contract No.10593+1 种基金the State Key Laboratory of Estuarine and Coastal Research,East China Normal University of China under contract No.SKLEC-2012KYYW02the 111 Project under contract No.B08022
文摘Range Doppler velocities derived from the Envisat advanced synthetic aperture radar（ASAR） wide swath images are analyzed and assessed against the numerically simulated surface current fields derived from the finite volume coastal ocean model（FVCOM） for the Changjiang Estuary. Comparisons with the FVCOM simulations show that the European Space Agency（ESA） Envisat ASAR based Doppler shift anomaly retrievals have the capability to capture quantitative information of the surface currents in the Changjiang Estuary. The uncertainty analysis of the ASAR range Doppler velocity estimates are discussed with regard to the azimuthal and range bias corrections, radar incidence angles, inaccuracy in the wind field corrections and the presence of rain cells.The corrected range Doppler velocities for the Changjiang Estuary area are highly valuable as they exhibit quantitative expressions related to the multiscale upper layer dynamics and surface current variability around the East China Sea, including the Changjiang Estuary.
文摘为了更好地监测地表土壤湿度,利用多极化、多角度ASAR-APP影像数据,研究了裸露和小麦地表土壤湿度反演方法。对裸露地表,基于AIEM(advance integral equation model)模型,建立多项式半经验模型反演土壤湿度;对小麦地表,小入射角HH极化ASAR数据与土壤湿度相关性更好,大入射角HH极化ASAR数据与小麦含水率相关性更好。基于水云模型,首先利用大入射角HH极化ASAR数据去除小麦冠层对雷达后向散射的影响,然后利用多角度ASAR数据推导建立小麦地表土壤湿度反演半经验模型;实测数据验证了裸露和小麦地表土壤湿度反演模型的适用性,利用验证数据反演裸露和小麦地表土壤湿度精度(RMSE)分别为3.55%、3.81%。结果表明,该文半经验模型具有较高的反演精度。
文摘欧洲空间局的ENVISAT ASAR level 2算法是从合成孔径雷达(SAR)单视复图像反演涌浪方向谱的算法。该算法假设双峰海浪谱的SAR图像交叉谱是涌浪的图像交叉谱和风浪的图像交叉谱之和。实际上双峰海浪谱的SAR图像交叉谱中还有一个混合项,正是该混合项导致ENVI-SAT ASAR level 2算法有固有误差。利用遥感仿真的方法分析了不同海况条件下该算法的这一固有误差,结果表明,只有在有效波高较小、或风浪的成分较少、或双峰海浪的传播方向较靠近SAR距离向、或波长较长时固有误差才较小,ENVISAT ASAR level 2算法对海浪谱的反演才较为适用。
基金Under the auspices of National Natural Science Foundation for Young Scientists of China(No.41101321)Major State Basic Research Development Program of China(No.2007CB714407)Key Projects in the National Science & Technology Pillar Program(No.2009BAG18B01,2012BAH28B03)
文摘Active microwave remote sensing data were used to calculate the near-surface soil moisture in the vegetated areas.In this study,Advanced Synthetic Aperture Radar(ASAR)observations of surface soil moisture content were used in a data assimilation framework to improve the estimation of the soil moisture profile at the middle reaches of the Heihe River Basin,Northwest China.A one-dimensional soil moisture assimilation system based on the ensemble Kalman filter(EnKF),the forward radiative transfer model,crop model,and the Distributed Hydrology-Soil-Vegetation Model(DHSVM)was developed.The crop model,as a semi-empirical model,was used to estimate the surface backscattering of vegetated areas.The DHSVM is a distributed hydrology-vegetation model that explicitly represents the effects of topography and vegetation on water fluxes through the landscape.Numerical experiments were conducted to assimilate the ASAR data into the DHSVM and in situ soil moisture at the middle reaches of the Heihe River Basin from June20 to July 15,2008.The results indicated that EnKF is effective for assimilating ASAR observations into the hydrological model.Compared with the simulation and in situ observations,the assimilated results were significantly improved in the surface layer and root layer,and the soil moisture varied slightly in the deep layer.Additionally,EnKF is an efficient approach to handle the strongly nonlinear problem which is practical and effective for soil moisture estimation by assimilation of remote sensing data.Moreover,to improve the assimilation results,further studies on obtaining more reliable forcing data and model parameters and increasing the efficiency and accuracy of the remote sensing observations are needed,also improving estimation accuracy of model operator is important.
基金Under the auspices of Major State Basic Research Development Program of China (973 Program) (No. 2007CB714400)the Program of One Hundred Talents of the Chinese Academy of Sciences (No. 99T3005WA2)
文摘The most promising approach for studying soil moisture is the assimilation of observation data and computational modeling. However, there is much uncertainty in the assimilation process, which affects the assimilation results. This research developed a one-dimensional soil moisture assimilation scheme based on the Ensemble Kalman Filter (EnKF) and Genetic Algorithm (GA). A two-dimensional hydrologic model-Distributed Hydrology-Soil-Vegetation Model (DHSVM) was coupled with a semi-empirical backscattering model (Oh). The Advanced Synthetic Aperture Radar (ASAR) data were assimilated with this coupled model and the field observation data were used to validate this scheme in the soil moisture assimilation experiment. In order to improve the assimilation results, a cost function was set up based on the distance between the simulated backscattering coefficient from the coupled model and the observed backscattering coefficient from ASAR. The EnKF and GA were used to re-initialize and re-parameterize the simulation process, respectively. The assimilation results were compared with the free-run simulations from hydrologic model and the field observation data. The results obtained indicate that this assimilation scheme is practical and it can improve the accuracy of soil moisture estimation significantly.
基金Supported by the Special Fund for Marine Commonweal Scientific Research of China (No.200705027)
文摘The validation and assessment of Envisat advanced synthetic aperture radar (ASAR) ocean wave spectra products are important to their application in ocean wave numerical predictions. Six-year ASAR wave spectra data are compared with one-dimensional (1D) wave spectra of 55 co-located moored buoy observations in the northern Pacific Ocean. The ASAR wave spectra data are firstly quality control filtered and spatio-temporal matched with buoy data. The comparisons are then performed in terms of 1D wave spectra, significant wave height (SWH) and mean wave period (MWP) in different spatio-temporal offsets respectively. SWH comparison results show the evident dependence of SWH biases on wind speed and the ASAR SWH saturation effect. The ASAR wave spectra tend to underestimate SWH at high wind speeds and overestimate SWH at low wind speeds. MWP comparison results show that MWP has a systematic bias and therefore it should be bias-modified before used. The comparisons of 1D wave spectra show that both wave spectra agree better at low frequencies than at high frequencies, which indicates the ASAR data cannot resolve the high frequency waves.
