Cloud top pressure(CTP)is one of the critical cloud properties that significantly affects the radiative effect of clouds.Multi-angle polarized sensors can employ polarized bands(490 nm)or O_(2)A-bands(763 and 765 nm)t...Cloud top pressure(CTP)is one of the critical cloud properties that significantly affects the radiative effect of clouds.Multi-angle polarized sensors can employ polarized bands(490 nm)or O_(2)A-bands(763 and 765 nm)to retrieve the CTP.However,the CTP retrieved by the two methods shows inconsistent results in certain cases,and large uncertainties in low and thin cloud retrievals,which may lead to challenges in subsequent applications.This study proposes a synergistic algorithm that considers both O_(2)A-bands and polarized bands using a random forest(RF)model.LiDAR CTP data are used as the true values and the polarized and non-polarized measurements are concatenated to train the RF model to determine CTP.Additionally,through analysis,we proposed that the polarized signal becomes saturated as the cloud optical thickness(COT)increases,necessitating a particular treatment for cases where COT<10 to improve the algorithm's stability.The synergistic method was then applied to the directional polarized camera(DPC)and Polarized and Directionality of the Earth’s Reflectance(POLDER)measurements for evaluation,and the resulting retrieval accuracy of the POLDER-based measurements(RMSEPOLDER=205.176 hPa,RMSEDPC=171.141 hPa,R^(2)POLDER=0.636,R^(2)DPC=0.663,respectively)were higher than that of the MODIS and POLDER Rayleigh pressure measurements.The synergistic algorithm also showed good performance with the application of DPC data.This algorithm is expected to provide data support for atmosphere-related fields as an atmospheric remote sensing algorithm within the Cloud Application for Remote Sensing,Atmospheric Radiation,and Updating Energy(CARE)platform.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
The Chinese High-resolution Earth Observation System(CHEOS)program has successfully launched 7 civilian satellites since 2010.These satellites are named by Gaofen(meaning high resolution in Chinese,hereafter noted as ...The Chinese High-resolution Earth Observation System(CHEOS)program has successfully launched 7 civilian satellites since 2010.These satellites are named by Gaofen(meaning high resolution in Chinese,hereafter noted as GF).To combine the advantages of high temporal and comparably high spatial resolution,diverse sensors are deployed to each satellite.GF-1 and GF-6 carry both high-resolution cameras(2m resolution panchromatic and 8m resolution multispectral camera),providing high spatial imaging for land use monitoring;GF-3 is equipped with a C-band multipolarization synthetic aperture radar with a spatial resolution of up to 1 meter,mostly monitoring marine targets;GF-5 carried 6 sensors including hyperspectral camera and directional polarization camera,dedicated to environmental remote sensing and climate research,such as aerosol,clouds,and greenhouse gas monitoring;and GF-7 laser altimeter system payload enables a three-dimensional surveying and mapping of natural resource and land surveying,facilitating the accumulation of basic geographic information.This study provides an overview of GF civilian series satellites,especially their missions,sensors,and applications.展开更多
基金the National Natural Science Foundation of China(Grant Nos.42025504,No.41905023)National Natural Science Youth Science Foundation(Grant No.41701406)Youth Innovation Promotion Association of Chinese Academy of Sciences(Grant No.:2021122).
文摘Cloud top pressure(CTP)is one of the critical cloud properties that significantly affects the radiative effect of clouds.Multi-angle polarized sensors can employ polarized bands(490 nm)or O_(2)A-bands(763 and 765 nm)to retrieve the CTP.However,the CTP retrieved by the two methods shows inconsistent results in certain cases,and large uncertainties in low and thin cloud retrievals,which may lead to challenges in subsequent applications.This study proposes a synergistic algorithm that considers both O_(2)A-bands and polarized bands using a random forest(RF)model.LiDAR CTP data are used as the true values and the polarized and non-polarized measurements are concatenated to train the RF model to determine CTP.Additionally,through analysis,we proposed that the polarized signal becomes saturated as the cloud optical thickness(COT)increases,necessitating a particular treatment for cases where COT<10 to improve the algorithm's stability.The synergistic method was then applied to the directional polarized camera(DPC)and Polarized and Directionality of the Earth’s Reflectance(POLDER)measurements for evaluation,and the resulting retrieval accuracy of the POLDER-based measurements(RMSEPOLDER=205.176 hPa,RMSEDPC=171.141 hPa,R^(2)POLDER=0.636,R^(2)DPC=0.663,respectively)were higher than that of the MODIS and POLDER Rayleigh pressure measurements.The synergistic algorithm also showed good performance with the application of DPC data.This algorithm is expected to provide data support for atmosphere-related fields as an atmospheric remote sensing algorithm within the Cloud Application for Remote Sensing,Atmospheric Radiation,and Updating Energy(CARE)platform.
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.
基金This study was supported by the National Natural Science Foundation of China(Grant Nos.41830109,42025504,42175152,41871254,and 41701406).
文摘The Chinese High-resolution Earth Observation System(CHEOS)program has successfully launched 7 civilian satellites since 2010.These satellites are named by Gaofen(meaning high resolution in Chinese,hereafter noted as GF).To combine the advantages of high temporal and comparably high spatial resolution,diverse sensors are deployed to each satellite.GF-1 and GF-6 carry both high-resolution cameras(2m resolution panchromatic and 8m resolution multispectral camera),providing high spatial imaging for land use monitoring;GF-3 is equipped with a C-band multipolarization synthetic aperture radar with a spatial resolution of up to 1 meter,mostly monitoring marine targets;GF-5 carried 6 sensors including hyperspectral camera and directional polarization camera,dedicated to environmental remote sensing and climate research,such as aerosol,clouds,and greenhouse gas monitoring;and GF-7 laser altimeter system payload enables a three-dimensional surveying and mapping of natural resource and land surveying,facilitating the accumulation of basic geographic information.This study provides an overview of GF civilian series satellites,especially their missions,sensors,and applications.