Based on the scattering properties of nonspherical dust aerosol, a new method is developed for retrieving dust aerosol optical depths of dusty clouds. The dusty clouds are defined as the hybrid system of dust plume an...Based on the scattering properties of nonspherical dust aerosol, a new method is developed for retrieving dust aerosol optical depths of dusty clouds. The dusty clouds are defined as the hybrid system of dust plume and cloud. The new method is based on transmittance measurements from surface-based instruments multi-filter rotating shadowband radiometer （MFRSR） and cloud parameters from lidar measurements. It uses the difference of absorption between dust aerosols and water droplets for distinguishing and estimating the optical properties of dusts and clouds, respectively. This new retrieval method is not sensitive to the retrieval error of cloud properties and the maximum absolute deviations of dust aerosol and total optical depths for thin dusty cloud retrieval algorithm are only 0.056 and 0.1, respectively, for given possible uncertainties. The retrieval error for thick dusty cloud mainly depends on lidar-based total dusty cloud properties.展开更多
The continuous, over two-decade data record from the Multi-Filter Rotating Shadowband Radiometer （MFRSR） is ideal for climate research which requires timely and accurate information of important atmospheric componen...The continuous, over two-decade data record from the Multi-Filter Rotating Shadowband Radiometer （MFRSR） is ideal for climate research which requires timely and accurate information of important atmospheric components such as gases, aerosols, and clouds. Except for parameters derived from MFRSR measurement ratios, which are not impacted by calibration error, most applications require accurate calibration factor（s）, angular correction, and spectral response function（s） from calibration. Although a laboratory lamp （or reference） calibration can provide all the information needed to convert the instrument readings to actual radiation, in situ calibration methods are implemented routinely （daily） to fill the gaps between lamp calibrations. In this paper, the basic structure and the data collection and pretreatment of the MFRSR are described. The laboratory lamp calibration and its limita- tions are summarized. The cloud screening algorithms for MFRSR data are presented. The in situ calibration methods, the standard Langley method and its variants, the ratio-Langley method, the general method, Alexandrov＇s comprehensive method, and Chen＇s multi-channel method, are outlined. The reason that all these methods do not fit for all situations is that they assume some properties, such as aerosol optical depth （AOD）, total optical depth （TOD）, precipitable water vapor （PWV）, effective size of aerosol particles, or angstrom coefficient, are invariant over time. These properties are not universal and some of them rarely happen. In practice, daily calibration factors derived from these methods should be smoothed to restrain elTor.展开更多
A Bayesian optimal estimation （OE） retrieval technique was used to retreive aerosol optical depth （AOD）, aerosol single scattering albedo （SSA）, and an asymmetry factor （g） at seven ultraviolet wavelengths, al...A Bayesian optimal estimation （OE） retrieval technique was used to retreive aerosol optical depth （AOD）, aerosol single scattering albedo （SSA）, and an asymmetry factor （g） at seven ultraviolet wavelengths, along with total column ozone （TOC）, from the measurements of the UltraViolet Multifilter Rotating Shadowband Radiometer （UV-MFRSR） deployed at the Southern Great Plains （SGP） site during March through November in 2009. The OE technique specifies appropriate error covariance matrices and optimizes a forward model （Tropospheric ultraviolet radiative transfer model, TUV）, and thus provides a supplemental method for use across the network of the Department of Agriculture UV-B Monitoring and Research Program （USDA UVMRP） for the retrieval of aerosol properties and TOC with reasonable accuracy in the UV spectral range under various atmo- spheric conditions. In order to assess the accuracy of the OE technique, we compared the AOD retreivals from this method with those from Beer＇s Law and the AErosol RObotic Network （AERONET） AOD product. We also examine the OE retrieved TOC in comparison with the TOC from the U.S. Department of Agriculture UV-B Monitoring and Research Program （USDA UVMRP） and the Ozone Monitoring Instrument （OMI） satellite data. The scatterplots of the estimated AOD from the OE method agree well with those derived from Beer＇s law and the collocated AERONET AOD product, showing high values of correlation coefficients, generally 0.98 and 0.99, and large slopes, ranging from 0.95 to 1.0, as well as small offsets, less than 0.02 especially at 368 nm. The comparison of TOC retrievals also indicates the promising accuracy of the OE method in that the standard deviations of the difference between the OE derived TOC and other TOC products are about 5 to 6 Dobson Units （DU）. Validation of the OE retrievals on these selected dates suggested that the OE technique has its merits and can serve as a supplemental tool in further analyzing UVMRP data.展开更多
基金supported by the Knowledge Innovation Program of the Chinese Academy of Sciences (No.IAP09311)the National Natural Science Foundation of China (Nos.40725015 and 40633017)
文摘Based on the scattering properties of nonspherical dust aerosol, a new method is developed for retrieving dust aerosol optical depths of dusty clouds. The dusty clouds are defined as the hybrid system of dust plume and cloud. The new method is based on transmittance measurements from surface-based instruments multi-filter rotating shadowband radiometer （MFRSR） and cloud parameters from lidar measurements. It uses the difference of absorption between dust aerosols and water droplets for distinguishing and estimating the optical properties of dusts and clouds, respectively. This new retrieval method is not sensitive to the retrieval error of cloud properties and the maximum absolute deviations of dust aerosol and total optical depths for thin dusty cloud retrieval algorithm are only 0.056 and 0.1, respectively, for given possible uncertainties. The retrieval error for thick dusty cloud mainly depends on lidar-based total dusty cloud properties.
文摘The continuous, over two-decade data record from the Multi-Filter Rotating Shadowband Radiometer （MFRSR） is ideal for climate research which requires timely and accurate information of important atmospheric components such as gases, aerosols, and clouds. Except for parameters derived from MFRSR measurement ratios, which are not impacted by calibration error, most applications require accurate calibration factor（s）, angular correction, and spectral response function（s） from calibration. Although a laboratory lamp （or reference） calibration can provide all the information needed to convert the instrument readings to actual radiation, in situ calibration methods are implemented routinely （daily） to fill the gaps between lamp calibrations. In this paper, the basic structure and the data collection and pretreatment of the MFRSR are described. The laboratory lamp calibration and its limita- tions are summarized. The cloud screening algorithms for MFRSR data are presented. The in situ calibration methods, the standard Langley method and its variants, the ratio-Langley method, the general method, Alexandrov＇s comprehensive method, and Chen＇s multi-channel method, are outlined. The reason that all these methods do not fit for all situations is that they assume some properties, such as aerosol optical depth （AOD）, total optical depth （TOD）, precipitable water vapor （PWV）, effective size of aerosol particles, or angstrom coefficient, are invariant over time. These properties are not universal and some of them rarely happen. In practice, daily calibration factors derived from these methods should be smoothed to restrain elTor.
基金Acknowledgements This work was supported by the National Natural Science Foundation of China （Grant No. 41101037）, the National Basic Research Program of China （No. 2010CB951603）, USDA NIFA project （2011-34263-30654）, the Research Fund for the Doctoral Program of Higher Education （20100076120024）, and the Fundamental Research Funds for the Central Universities （East China Normal University）. We would also like to thank the PI investigators and their staff for establishing and maintaining the AERONET site used in this investigation.
文摘A Bayesian optimal estimation （OE） retrieval technique was used to retreive aerosol optical depth （AOD）, aerosol single scattering albedo （SSA）, and an asymmetry factor （g） at seven ultraviolet wavelengths, along with total column ozone （TOC）, from the measurements of the UltraViolet Multifilter Rotating Shadowband Radiometer （UV-MFRSR） deployed at the Southern Great Plains （SGP） site during March through November in 2009. The OE technique specifies appropriate error covariance matrices and optimizes a forward model （Tropospheric ultraviolet radiative transfer model, TUV）, and thus provides a supplemental method for use across the network of the Department of Agriculture UV-B Monitoring and Research Program （USDA UVMRP） for the retrieval of aerosol properties and TOC with reasonable accuracy in the UV spectral range under various atmo- spheric conditions. In order to assess the accuracy of the OE technique, we compared the AOD retreivals from this method with those from Beer＇s Law and the AErosol RObotic Network （AERONET） AOD product. We also examine the OE retrieved TOC in comparison with the TOC from the U.S. Department of Agriculture UV-B Monitoring and Research Program （USDA UVMRP） and the Ozone Monitoring Instrument （OMI） satellite data. The scatterplots of the estimated AOD from the OE method agree well with those derived from Beer＇s law and the collocated AERONET AOD product, showing high values of correlation coefficients, generally 0.98 and 0.99, and large slopes, ranging from 0.95 to 1.0, as well as small offsets, less than 0.02 especially at 368 nm. The comparison of TOC retrievals also indicates the promising accuracy of the OE method in that the standard deviations of the difference between the OE derived TOC and other TOC products are about 5 to 6 Dobson Units （DU）. Validation of the OE retrievals on these selected dates suggested that the OE technique has its merits and can serve as a supplemental tool in further analyzing UVMRP data.
