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 estimation of downward surface shortwave radiation(DSSR)is important for the Earth’s energy budget and climate change studies.This review was organised from the perspectives of satellite sensors,algorithms and fu...The estimation of downward surface shortwave radiation(DSSR)is important for the Earth’s energy budget and climate change studies.This review was organised from the perspectives of satellite sensors,algorithms and future trends,retrospects and summaries of the satellite-based retrieval methods of DSSR that have been developed over the past 10 years.The shortwave radiation reaching the Earth’s surface is affected by both atmospheric and land surface parameters.In recent years,studies have given detailed considerations to the factors which affect DSSR.It is important to improve the retrieval accuracy of cloud microphysical parameters and aerosols and to reduce the uncertainties caused by complex topographies and high-albedo surfaces(such as snow-covered areas)on DSSR estimation.This review classified DSSR retrieval methods into four categories:empirical,parameterisation,look-up table and machine-learning methods,and evaluated their advantages,disadvantages and accuracy.Further efforts are needed to improve the calculation accuracy of atmospheric parameters such as cloud,haze,water vapor and other land surface parameters such as albedo of complex terrain and bright surface,organically combine machine learning and other methods,use the new-generation geostationary satellite and polar orbit satellite data to produce highresolution DSSR products,and promote the application of radiation products in hydrological and climate models.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.
基金supported by the Second Tibetan Plateau Scientific Expedition and Research Program(STEP)(Grant No.2019QZKK0206)the National Natural Science Foundation of China(Grant No.41771395)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA20100300)。
文摘The estimation of downward surface shortwave radiation(DSSR)is important for the Earth’s energy budget and climate change studies.This review was organised from the perspectives of satellite sensors,algorithms and future trends,retrospects and summaries of the satellite-based retrieval methods of DSSR that have been developed over the past 10 years.The shortwave radiation reaching the Earth’s surface is affected by both atmospheric and land surface parameters.In recent years,studies have given detailed considerations to the factors which affect DSSR.It is important to improve the retrieval accuracy of cloud microphysical parameters and aerosols and to reduce the uncertainties caused by complex topographies and high-albedo surfaces(such as snow-covered areas)on DSSR estimation.This review classified DSSR retrieval methods into four categories:empirical,parameterisation,look-up table and machine-learning methods,and evaluated their advantages,disadvantages and accuracy.Further efforts are needed to improve the calculation accuracy of atmospheric parameters such as cloud,haze,water vapor and other land surface parameters such as albedo of complex terrain and bright surface,organically combine machine learning and other methods,use the new-generation geostationary satellite and polar orbit satellite data to produce highresolution DSSR products,and promote the application of radiation products in hydrological and climate models.
