Search

Atmospheric aerosol optical depth (AOD) plays an important role in radiation modeling and partly determines the accuracy of estimated downward surface shortwave radiation (DSSR). In this study, Iqbal’s model C was used to estimate DSSR under cloud-free conditions over the Koohin and Chitgar sites in Tehran, Iran; the estimated DSSR was based on (1) our proposed hybrid modeling scheme where the AOD is retrieved using the Simplified Aerosol Retrieval Algorithm (SARA), ground-based measurements at the AERONET site in Zanjan and (2) the AOD from the Terra MODerate-resolution Imaging Spectroradiometer (MODIS) sensor. Several other Terra MODIS land and atmospheric products were also used as input data, including geolocation properties, water vapor, total ozone, surface reflectance, and top-of-atmosphere (TOA) radiance. SARA-based DSSR and MODIS-based DSSR were evaluated with ground-based DSSR measurements at the Koohin and Chitgar sites in 2011 and 2013, respectively; the averaged statistics for SARA-based DSSR [R2 ≈ 0.95, RMSE ≈ 22 W/m2 (2.5% mean value), and bias ≈ 3 W/m2] were stronger than those for MODIS-based DSSR [R2 ≈ 0.79, RMSE ≈ 51 W/m2 (5.8% mean value), and bias ≈ 34 W/m2]. These results show that the proposed hybrid scheme can be used at regional to global scales under the assumption of future access to spatially distributed AERONET sites. Additionally, the robustness of this modeling scheme was exemplified by estimating the aerosol radiative forcing (ARF) during a dust storm in Southwest Asia. The results were comparable to those of previous studies and showed the strength of our modeling scheme.

Atmospheric aerosol optical depth (AOD) plays a determinant role in estimations of surface shortwave (SW) radiative fluxes. Therefore, this study aims to develop a hybrid scheme to produce surface SW fluxes, based on AOD at 1-km spatial resolution retrieved from the Simplified Aerosol Retrieval Algorithm (SARA) and several Terra MODIS land and atmospheric products (i.e., geolocation properties, water vapor amount, total ozone column, surface reflectance, and top-of-atmosphere (TOA) radiance). Estimations based on SARA were made over the Southern Great Plains (SGP) under cloud-free conditions in 2014 and compared with estimations based on the latest Terra MODIS AOD product at 3-km resolution. Validation against ground-based measurements showed that SARA-based fluxes obtain lower RMSE and bias values compared with MODIS-based estimations. MODIS-based downward and net fluxes are satisfactory, while the direct and diffuse components are less reliable. The results demonstrate that the SARA-based scheme produces better surface SW radiative fluxes than the MODIS-based estimates provided in this and other similar studies and that these fluxes are comparable to existing CERES data products which have been tested over the SGP.

Atmospheric aerosol optical depth (AOD) plays an important role in radiation modeling and partly determines the accuracy of estimated downward surface shortwave radiation (DSSR). In this study, Iqbal’s model C was used to estimate DSSR under cloud-free conditions over the Koohin and Chitgar sites in Tehran, Iran; the estimated DSSR was based on (1) our proposed hybrid modeling scheme where the AOD is retrieved using the Simplified Aerosol Retrieval Algorithm (SARA), ground-based measurements at the AERONET site in Zanjan and (2) the AOD from the Terra MODerate-resolution Imaging Spectroradiometer (MODIS) sensor. Several other Terra MODIS land and atmospheric products were also used as input data, including geolocation properties, water vapor, total ozone, surface reflectance, and top-of-atmosphere (TOA) radiance. SARA-based DSSR and MODIS-based DSSR were evaluated with ground-based DSSR measurements at the Koohin and Chitgar sites in 2011 and 2013, respectively; the averaged statistics for SARA-based DSSR [R2 ≈ 0.95, RMSE ≈ 22 W/m2 (2.5% mean value), and bias ≈ 3 W/m2] were stronger than those for MODIS-based DSSR [R2 ≈ 0.79, RMSE ≈ 51 W/m2 (5.8% mean value), and bias ≈ 34 W/m2]. These results show that the proposed hybrid scheme can be used at regional to global scales under the assumption of future access to spatially distributed AERONET sites. Additionally, the robustness of this modeling scheme was exemplified by estimating the aerosol radiative forcing (ARF) during a dust storm in Southwest Asia. The results were comparable to those of previous studies and showed the strength of our modeling scheme.

Atmospheric aerosol optical depth (AOD) plays a determinant role in estimations of surface shortwave (SW) radiative fluxes. Therefore, this study aims to develop a hybrid scheme to produce surface SW fluxes, based on AOD at 1-km spatial resolution retrieved from the Simplified Aerosol Retrieval Algorithm (SARA) and several Terra MODIS land and atmospheric products (i.e., geolocation properties, water vapor amount, total ozone column, surface reflectance, and top-of-atmosphere (TOA) radiance). Estimations based on SARA were made over the Southern Great Plains (SGP) under cloud-free conditions in 2014 and compared with estimations based on the latest Terra MODIS AOD product at 3-km resolution. Validation against ground-based measurements showed that SARA-based fluxes obtain lower RMSE and bias values compared with MODIS-based estimations. MODIS-based downward and net fluxes are satisfactory, while the direct and diffuse components are less reliable. The results demonstrate that the SARA-based scheme produces better surface SW radiative fluxes than the MODIS-based estimates provided in this and other similar studies and that these fluxes are comparable to existing CERES data products which have been tested over the SGP.