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 method to estimate NSSR (net surface shortwave radiation) from LST (land surface temperature) in regional scale is discussed. First, an elliptical model between the time series of normalized LST and NSSR was d...The method to estimate NSSR (net surface shortwave radiation) from LST (land surface temperature) in regional scale is discussed. First, an elliptical model between the time series of normalized LST and NSSR was developed using the daily evolution of LST and NSSR. Second, time series of LST and NSSR were simulated by common land model (CoLM) and were proved to be of high accuracy. On the basis of these, a non-linear least square ellipse fitting using the genetic algorithm method was used to fit the normalized LST and NSSR. Finally, LST was inverted using MODIS (moderate resolution imaging spectroradiometer) data with the split-window algorithm, and the regional NSSR was then estimated with LST and an elliptical model. The validation result shows that the derived average NSSR of 50×50 pixels of MODIS data was quite close to the observed data, and the distribution was reasonable, which indicates that the proposed method was capable of estimating NSSR on a regional scale.展开更多
To harness the rich solar energy resources in Xinjiang Region of Northwest China,this study tries to address the issue of lack of downward surface shortwave radiation(DSSR)observations and the need to improve the accu...To harness the rich solar energy resources in Xinjiang Region of Northwest China,this study tries to address the issue of lack of downward surface shortwave radiation(DSSR)observations and the need to improve the accuracy of satellite retrieval and numerical simulation of DSSR under varied sky and meteorological conditions.(1)A two-layer aerosol model specific to Xinjiang was developed to capture the vertical distributions of aerosols based on multiple data sources including lidar,GPS sounding,ground meteorological observations,and profiles from the ECMWF reanalysis version 5(ERA5)data.The results show that the ERA5/PBLH(planetary boundary layer height)and ERA5/ALH(aerosol layer height)could be used to establish the two-layer aerosol model and characterize the vertical distribution of aerosols in Xinjiang Region.(2)Using the Santa Barbara Discrete Atmospheric Radiative Transfer(SBDART)model,a localized inverse model of clear-sky DSSR was established.After parameter adjustment and using the optimal combination of input parameters for DSSR simulation together with the two-layer aerosol model,the model-simulated DSSR(DSSRSBD)under clear-sky conditions improved significantly compared to the initial results,with all fitting indices greatly improved.(3)In addition,the study demonstrated that the impact of the two-layer aerosol model on DSSR was more pronounced under dust conditions than clear-sky conditions.(4)Using the localized clear-sky DSSR inversion model and its required parameters,simulations were also conducted to capture the spatiotemporal distribution of DSSR under clear-sky conditions in Xinjiang from 2017 to 2019.The annual average DSSR_(SBD)under clear-sky conditions in Xinjiang during 2017–2019 was 606.78 W m^(-2),while DSSR from CERES(DSSR_(CER))under the same conditions was generally higher(703.95 W m^(-2)).(5)It is found that satellite remote sensing products experienced data loss in high-altitude snow areas,where numerical simulation technology could serve as a valuable complement.展开更多
In the context of 1985—1988 ERBE and 1984—1988 ISCCP planetary scale albedoes and total cloudiness in combination with Qinghai-Xizang actinometric measurements,investigation was performed of the climatic retrieval o...In the context of 1985—1988 ERBE and 1984—1988 ISCCP planetary scale albedoes and total cloudiness in combination with Qinghai-Xizang actinometric measurements,investigation was performed of the climatic retrieval of surface absorbed shortwave radiation(SASWR)in the research highland.Evidence suggests that the method has given higher fitting accuracy with mean error of 9.8 W m^(-2),whereupon was calculated the monthly mean SASWR flux density at the gridpoints of 2.5°×2.5°resolution over 25—40°N,75—95°E and 63 stations alongside a set of the distribution maps prepared for its basic features.展开更多
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Supported by the Knowledge Innovation Programs of Chinese Academy of Sciences (XMXX280722)China International Science and Technology Cooperation Project (0819)+1 种基金National Program on Key Basic Research Project (2010CB428800)Wong K C Education Foundation, Hong Kong
文摘The method to estimate NSSR (net surface shortwave radiation) from LST (land surface temperature) in regional scale is discussed. First, an elliptical model between the time series of normalized LST and NSSR was developed using the daily evolution of LST and NSSR. Second, time series of LST and NSSR were simulated by common land model (CoLM) and were proved to be of high accuracy. On the basis of these, a non-linear least square ellipse fitting using the genetic algorithm method was used to fit the normalized LST and NSSR. Finally, LST was inverted using MODIS (moderate resolution imaging spectroradiometer) data with the split-window algorithm, and the regional NSSR was then estimated with LST and an elliptical model. The validation result shows that the derived average NSSR of 50×50 pixels of MODIS data was quite close to the observed data, and the distribution was reasonable, which indicates that the proposed method was capable of estimating NSSR on a regional scale.
基金Science and Technology Planning Program of Xinjiang(2022E01047)National Natural Science Foundation of China(42030612 and 41905131)+2 种基金Scientific Research Program Funded by Education Department of Shaanxi Provincial Government(23JK0625)Natural Science Basic Research Program of Shaanxi Province(2021JQ-768)Social Science Planning Fund Program of Xi’an City(23JX150)。
文摘To harness the rich solar energy resources in Xinjiang Region of Northwest China,this study tries to address the issue of lack of downward surface shortwave radiation(DSSR)observations and the need to improve the accuracy of satellite retrieval and numerical simulation of DSSR under varied sky and meteorological conditions.(1)A two-layer aerosol model specific to Xinjiang was developed to capture the vertical distributions of aerosols based on multiple data sources including lidar,GPS sounding,ground meteorological observations,and profiles from the ECMWF reanalysis version 5(ERA5)data.The results show that the ERA5/PBLH(planetary boundary layer height)and ERA5/ALH(aerosol layer height)could be used to establish the two-layer aerosol model and characterize the vertical distribution of aerosols in Xinjiang Region.(2)Using the Santa Barbara Discrete Atmospheric Radiative Transfer(SBDART)model,a localized inverse model of clear-sky DSSR was established.After parameter adjustment and using the optimal combination of input parameters for DSSR simulation together with the two-layer aerosol model,the model-simulated DSSR(DSSRSBD)under clear-sky conditions improved significantly compared to the initial results,with all fitting indices greatly improved.(3)In addition,the study demonstrated that the impact of the two-layer aerosol model on DSSR was more pronounced under dust conditions than clear-sky conditions.(4)Using the localized clear-sky DSSR inversion model and its required parameters,simulations were also conducted to capture the spatiotemporal distribution of DSSR under clear-sky conditions in Xinjiang from 2017 to 2019.The annual average DSSR_(SBD)under clear-sky conditions in Xinjiang during 2017–2019 was 606.78 W m^(-2),while DSSR from CERES(DSSR_(CER))under the same conditions was generally higher(703.95 W m^(-2)).(5)It is found that satellite remote sensing products experienced data loss in high-altitude snow areas,where numerical simulation technology could serve as a valuable complement.
文摘In the context of 1985—1988 ERBE and 1984—1988 ISCCP planetary scale albedoes and total cloudiness in combination with Qinghai-Xizang actinometric measurements,investigation was performed of the climatic retrieval of surface absorbed shortwave radiation(SASWR)in the research highland.Evidence suggests that the method has given higher fitting accuracy with mean error of 9.8 W m^(-2),whereupon was calculated the monthly mean SASWR flux density at the gridpoints of 2.5°×2.5°resolution over 25—40°N,75—95°E and 63 stations alongside a set of the distribution maps prepared for its basic features.