2026-10-15T01:04:57Z https://www.scidb.cn/oai

10.11922/sciencedb.j00076.00062 2021-04-30T16:09:23Z

2021-04-30 Clear-sky Land Surface Upward Longwave Radiation Dataset based on ABI/GOES-16 doi:10.11922/sciencedb.j00076.00062 en Surface upward longwave radiation (SULR) is one of the four components of the surface radiation budget, which is the surface outgoing thermal radiation in the spectral domain of 4-100 μm. SULR is an indicator of surface thermal conditions and has a great impact on weather, climate, and phenology. The big earth data derived from satellite remote sensing has been an important tool for the studying of earth science. The Advanced Baseline Imager (ABI) onboard the Geostationary Operational Environmental Satellites (GOES-16) has greatly improved temporal and spectral resolutions compared to the imager sensor of the previous GOES series, and is a good data source for the generation of high spatiotemporal resolution SULR. In this study, based on the single-angle hybrid SULR estimation method and an upper hemisphere correction method of the geostationary satellite, we developed a clear-sky land SULR product for GOES-16 with a half-hourly resolution for the period from 1st January 2018 to 30th June 2020. The dataset was validated using in situ measurements from 65 sites from the Ameriflux radiation network. Compared with the Global Land Surface Satellite (GLASS) SULR product that is generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the polar-orbiting Terra and Aqua satellites, the ABI/GOES-16 SULR product has slightly higher accuracy (RMSE (MBE) of 15.9 (-4.4) W/m2 compared with 18.15 (-4.33) W/m2), a spatial resolution of 2 km at nadir (compared with 1 km resolution), and a greatly improved temporal resolution (48 observations compared with 4 times a day). Surface upward longwave radiation; Advanced Baseline Imager; GOES-16; hybrid method; kernel-driven model Boxiong Qin Biao Cao Zunjian Bian Ruibo Li Hua Li Xueting Ran Yongming Du Qing Xiao Qinhuo Liu PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset http://www.doi.org/10.1080/20964471.2021.1912898 Science Data Bank