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
A 4th-order low-pass filter （LPF） based on active-Gm-RC structure for multi-standard system application is presented in this paper. The performances of LPF are controlled by a 1-bit control- voltage, and the cut-off...A 4th-order low-pass filter （LPF） based on active-Gm-RC structure for multi-standard system application is presented in this paper. The performances of LPF are controlled by a 1-bit control- voltage, and the cut-off frequency, channel selectivity, and linearity of the proposed filter can be reconfigured accordingly. In order to improve the accuracy of the cut-off frequency, a binary-weigh- ted switched-capacitor array is employed as the auto-tuning circuits to calibrate the RC-time con- stant. Fabricated in TSMC 0. 18μm RF CMOS process, the proposed LPF achieves a measured cutoff frequency of 1.95 and 12.3MHz for WCDMA and GPS/Galileo application with a bandwidth de viation less than 4%. The measured l dB compression points are -3.0dBm and -5.1 dBm respectively for different modes. The core circuit of LPF consumes l mW and 1.6mW for WCDMA and GPS/Galileo respectively. And the proposed LPF occupies an area of 0.78ram2.展开更多
Optimizing the parameters of a land surface process model(LSPM) through data assimilation(DA) can not only improve and perfect the parameterization schemes in the LSPM through the physical mechanism, but also increase...Optimizing the parameters of a land surface process model(LSPM) through data assimilation(DA) can not only improve and perfect the parameterization schemes in the LSPM through the physical mechanism, but also increase its regional adaptability and simulation capability. This has practical importance for improving simulation results and the climate-prediction capability of general circulation models(GCMs) and regional climate models(RCMs). This paper presents a DA-based method for optimizing the parameterization schemes in LSPMs. We optimize the unsaturated-soil water flow(Un SWF) model as an example by developing a soil-moisture assimilation scheme based on the Un SWF model and the extended Kalman filter(EKF) algorithm, and then combining them with the Variable Infiltration Capacity(VIC) model. Using a month as the assimilation window, we used the Shuffled Complex Evolution–University of Arizona(SCE-UA) algorithm to minimize the objective function through simulated and assimilated soil moisture, achieved the best fit with the given objective function measurement, and optimized the parameters of the Un SWF model, including the saturated-soil hydraulic conductivity, moisture content, matrix potential, and the Clapp and Hornberger constant. The optimal values of the model parameters were obtained during the DA period(the year 1986), and then the optimized parameters were used to improve the Un SWF model. Finally, numerical simulation experiments were carried out from 1986 to 1993 to evaluate the simulation capability of the improved model and to explore and realize the DA-based method for optimizing the soil water parameterization scheme in LSPMs. The experimental results indicated that the optimized model parameters improved and perfected the model based on the physical mechanism, and increased its simulation capability; the optimized model parameters had good temporal portability and their adaptability was stronger, achieving the aim of improving the model. Therefore, this method is reasonable and feasible. This paper provides a good reference for DA-based optimization of the parameterization schemes in LSPMs.展开更多
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Supported by the National Basic Research Program of China(No.2010CB327404)the Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘A 4th-order low-pass filter （LPF） based on active-Gm-RC structure for multi-standard system application is presented in this paper. The performances of LPF are controlled by a 1-bit control- voltage, and the cut-off frequency, channel selectivity, and linearity of the proposed filter can be reconfigured accordingly. In order to improve the accuracy of the cut-off frequency, a binary-weigh- ted switched-capacitor array is employed as the auto-tuning circuits to calibrate the RC-time con- stant. Fabricated in TSMC 0. 18μm RF CMOS process, the proposed LPF achieves a measured cutoff frequency of 1.95 and 12.3MHz for WCDMA and GPS/Galileo application with a bandwidth de viation less than 4%. The measured l dB compression points are -3.0dBm and -5.1 dBm respectively for different modes. The core circuit of LPF consumes l mW and 1.6mW for WCDMA and GPS/Galileo respectively. And the proposed LPF occupies an area of 0.78ram2.
基金supported by the National Natural Science Foundation of China(Grant Nos.4157136840971229&41130528)+1 种基金the Important National Project of High-resolution Earth Observation System(Grant No.05-Y30B02-9001-13/15-8)the Special Foundation for Free Exploration of the State Key Laboratory of Remote Sensing Science(Grant No.14ZY-01)
文摘Optimizing the parameters of a land surface process model(LSPM) through data assimilation(DA) can not only improve and perfect the parameterization schemes in the LSPM through the physical mechanism, but also increase its regional adaptability and simulation capability. This has practical importance for improving simulation results and the climate-prediction capability of general circulation models(GCMs) and regional climate models(RCMs). This paper presents a DA-based method for optimizing the parameterization schemes in LSPMs. We optimize the unsaturated-soil water flow(Un SWF) model as an example by developing a soil-moisture assimilation scheme based on the Un SWF model and the extended Kalman filter(EKF) algorithm, and then combining them with the Variable Infiltration Capacity(VIC) model. Using a month as the assimilation window, we used the Shuffled Complex Evolution–University of Arizona(SCE-UA) algorithm to minimize the objective function through simulated and assimilated soil moisture, achieved the best fit with the given objective function measurement, and optimized the parameters of the Un SWF model, including the saturated-soil hydraulic conductivity, moisture content, matrix potential, and the Clapp and Hornberger constant. The optimal values of the model parameters were obtained during the DA period(the year 1986), and then the optimized parameters were used to improve the Un SWF model. Finally, numerical simulation experiments were carried out from 1986 to 1993 to evaluate the simulation capability of the improved model and to explore and realize the DA-based method for optimizing the soil water parameterization scheme in LSPMs. The experimental results indicated that the optimized model parameters improved and perfected the model based on the physical mechanism, and increased its simulation capability; the optimized model parameters had good temporal portability and their adaptability was stronger, achieving the aim of improving the model. Therefore, this method is reasonable and feasible. This paper provides a good reference for DA-based optimization of the parameterization schemes in LSPMs.
