Surface incident shortwave radiation (ISR) is a crucial parameter in the land surface radiation budget. Many reanalysis, observation-based, and satellite-derived global radiation products have been developed but often have insufficient accuracy and spatial resolution for many applications. In this dissertation, I propose an optimization-based method (OB-Algorithm) based on a radiative transfer model for estimating surface ISR from Moderate Resolution Imaging Spectroradiometer (MODIS) Top of Atmosphere (TOA) observations by optimizing the surface and atmospheric variables with a cost function. This approach consisted of two steps: retrieving surface bidirectional reflectance distribution function parameters, aerosol optical depth (AOD), and cloud optical depth (COD); and subsequently calculating surface ISR. I also adapted the algorithm to VIIRS data and performed global

validation with 34 Baseline Surface Radiation Network (BSRN) sites for both instantaneous and daily mean ISR. Researches on estimating daily and diurnal ISR was also made on Advanced Himawari Imager (AHI) and Advanced Baseline Imager (ABI). Geostationary satellites capture diurnal ISR variation better than polar-orbiting ones, especially in cloudy cases.

Validation against measurements at seven Surface Radiation Budget Network (SURFRAD) sites resulted in an R2 of 0.91, a bias of -6.47 W/m2, and a root mean square error (RMSE) of 84.17 W/m2 for the instantaneous results. Validation at eight high-latitude snow-covered Greenland Climate Network (GC-Net) sites resulted in an R2 of 0.86, a bias of -21.40 W/m2, and an RMSE of 84.77 W/m2. These validation results show that the proposed method is much more accurate than the previous studies (usually with RMSEs of 80-150W/m2). The VIIRS ISR results at seven SURFRAD showed RMSEs of 83.76 W/m2 and 27.78 W/m2 for instantaneous and daily ISR, respectively at SURFRAD sites. Results at 34 BSRN sites showed RMSEs of 106.68 W/m2 and 32.76 W/m2 for instantaneous and daily ISR, respectively at BSRN sites. Validation of instantaneous and daily AHI ISR at eight OzFlux sites shows an R2 of 0.93, a bias of 0.52 W/m2 and an RMSE of 106.52 W/m2 for instantaneous results and an R2 of 0.95, a bias of -0.12 W/m2 and an RMSE of 22.49 W/m2 for daily mean ISR. Validation of instantaneous and daily ABI ISR at seven SURFRAD sites shows an R2 of 0.93, a bias of 8.71 W/m2 and an RMSE of 102.30 W/m2 for instantaneous results and an R2 of 0.95, a bias of -2.38W/m2 and an RMSE of 27.17 W/m2 for daily mean ISR.

Ten years of optimization-based ISR products (OB-Product) in the Amazon

region from MODIS data were produced and compared with existing products. The inter-comparison with CERES-SYN and GLASS ISR products show similar spatial and temporal patterns among the three datasets. Validation of my product at BSRN sites in this area provides an improved accuracy compared to GLASS product and a significant finer resolution compared to CERES-SYN product.