We propose a new method to estimate surface-level particulate matter(PM)concentrations by using satellite-retrieved Aerosol Optical Thickness(AOT).This method considers the distribution and variation of Planetary Boun...We propose a new method to estimate surface-level particulate matter(PM)concentrations by using satellite-retrieved Aerosol Optical Thickness(AOT).This method considers the distribution and variation of Planetary Boundary Layer(PBL)height and relative humidity(RH)at the regional scale.The method estimates surface-level particulate matter concentrations using the data simulated by an atmospheric boundary layer model RAMS and satellite-retrieved AOT.By incorporation MODIS AOT,PBL height and RH simulated by RAMS,this method is applied to estimate the surface-level PM 2.5 concentrations in North China region.The result is evaluated by using 16 ground-based observations deployed in the research region,and the result shows a good agreement between estimated PM 2.5 concentrations and observations,and the coefficient of determination R2 is 0.61 between the estimated PM 2.5 concentrations and the observations.In addition,surface-level PM 2.5 concentrations are also estimated by using MODIS AOT,ground-based LIDAR observations and RH measurements.A comparison between the two estimated PM 2.5 concentrations shows that the new method proposed in this paper is better than the traditional method.The coefficient of determination R2 is improved from 0.32 to 0.62.展开更多
We introduce the path length probability density function(PPDF) method, which is based on an equivalence theorem and parameterizes the aerosol scattering effect by adding four factors to the atmospheric transmittance ...We introduce the path length probability density function(PPDF) method, which is based on an equivalence theorem and parameterizes the aerosol scattering effect by adding four factors to the atmospheric transmittance model. Using simulated observations in the O2-A band, we examined the utility of the PPDF-based method to account for the aerosol scattering effect. First, observations were simulated using a forward model under different aerosol conditions; PPDF factors were then retrieved using an optimal estimation method; PPDF factors were used to reconstruct the observations; and finally, simulated true observations and reconstructions were compared. Analysis of the difference between the true observations and reconstructions confirmed the utility of the PPDF-based method. Additionally, the O2 band was demonstrated to be an efficient observing band for assisting the remote sensing of atmospheric trace gases in the near-infrared band.展开更多
We propose an algorithm that combines a pre-processing step applied to the a priori state vector prior to retrievals, with the modified damped Newton method (MDNM), to improve convergence. The initial constraint vec...We propose an algorithm that combines a pre-processing step applied to the a priori state vector prior to retrievals, with the modified damped Newton method (MDNM), to improve convergence. The initial constraint vector pre-processing step updates the initial state vector prior to the retrievals if the algorithm detects that the initial state vector is far from the true state vector in extreme cases where there are CO2 emissions. The MDNM uses the Levenberg-Marquardt parameter ~,, which ensures a positive Hessian matrix, and a scale factor a, which adjusts the step size to optimize the stability of the convergence. While the algorithm iteratively searches for an optimized solution using observed spectral radiances, MDNM adjusts parameters ), and a to achieve stable convergence. We present simulated retrieval samples to evaluate the performance of our algorithm and comparing it to existing methods. The standard deviation of our retrievals adding random noise was less than 3.8 ppmv. After pre-processing the initial estimate when it was far from the true value, the CO2 retrieval errors in the boundary layers were within 1.2 ppmv. We tested the MDNM algorithm's performance using GOSAT Llb data with cloud screening. Our preliminary validations comparing the results to TCCON FTS measurements showed that the average bias was less than 1.8 ppm and the correlation coefficient was approximately 0.88, which was larger than for the GOSAT L2 product.展开更多
基金supported by National Department Public Benefit Research Foundation (Ministry of Environmental Protection of the People’s Republic of China) (Grant No. 201009001)National Natural Science Foundation of China (Grant No. 41101327)
文摘We propose a new method to estimate surface-level particulate matter(PM)concentrations by using satellite-retrieved Aerosol Optical Thickness(AOT).This method considers the distribution and variation of Planetary Boundary Layer(PBL)height and relative humidity(RH)at the regional scale.The method estimates surface-level particulate matter concentrations using the data simulated by an atmospheric boundary layer model RAMS and satellite-retrieved AOT.By incorporation MODIS AOT,PBL height and RH simulated by RAMS,this method is applied to estimate the surface-level PM 2.5 concentrations in North China region.The result is evaluated by using 16 ground-based observations deployed in the research region,and the result shows a good agreement between estimated PM 2.5 concentrations and observations,and the coefficient of determination R2 is 0.61 between the estimated PM 2.5 concentrations and the observations.In addition,surface-level PM 2.5 concentrations are also estimated by using MODIS AOT,ground-based LIDAR observations and RH measurements.A comparison between the two estimated PM 2.5 concentrations shows that the new method proposed in this paper is better than the traditional method.The coefficient of determination R2 is improved from 0.32 to 0.62.
基金supported by the Key Program of the National Natural Science Foundation of China(Grant No.41130528)
文摘We introduce the path length probability density function(PPDF) method, which is based on an equivalence theorem and parameterizes the aerosol scattering effect by adding four factors to the atmospheric transmittance model. Using simulated observations in the O2-A band, we examined the utility of the PPDF-based method to account for the aerosol scattering effect. First, observations were simulated using a forward model under different aerosol conditions; PPDF factors were then retrieved using an optimal estimation method; PPDF factors were used to reconstruct the observations; and finally, simulated true observations and reconstructions were compared. Analysis of the difference between the true observations and reconstructions confirmed the utility of the PPDF-based method. Additionally, the O2 band was demonstrated to be an efficient observing band for assisting the remote sensing of atmospheric trace gases in the near-infrared band.
基金supported by the State Key Program of the National Natural Science Foundation of China (Grant No.41130528)the National Natural Science Foundation of China (Grant No.41401387)the Green Path Program of the Beijing Municipal Science and Technology Commission(Grant No.Z161100001116013)
文摘We propose an algorithm that combines a pre-processing step applied to the a priori state vector prior to retrievals, with the modified damped Newton method (MDNM), to improve convergence. The initial constraint vector pre-processing step updates the initial state vector prior to the retrievals if the algorithm detects that the initial state vector is far from the true state vector in extreme cases where there are CO2 emissions. The MDNM uses the Levenberg-Marquardt parameter ~,, which ensures a positive Hessian matrix, and a scale factor a, which adjusts the step size to optimize the stability of the convergence. While the algorithm iteratively searches for an optimized solution using observed spectral radiances, MDNM adjusts parameters ), and a to achieve stable convergence. We present simulated retrieval samples to evaluate the performance of our algorithm and comparing it to existing methods. The standard deviation of our retrievals adding random noise was less than 3.8 ppmv. After pre-processing the initial estimate when it was far from the true value, the CO2 retrieval errors in the boundary layers were within 1.2 ppmv. We tested the MDNM algorithm's performance using GOSAT Llb data with cloud screening. Our preliminary validations comparing the results to TCCON FTS measurements showed that the average bias was less than 1.8 ppm and the correlation coefficient was approximately 0.88, which was larger than for the GOSAT L2 product.