Synergistic Benefits of Intercomparison between Simulated and Measured Radiances of Imagers Onboard Geostationary Satellites

Su Jeong Lee, Myoung Hwan Ahn

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3 Scopus citations


Observations from geostationary (GEO) satellites with high-spatial and temporal resolutions have been playing a key role in building and improving global weather monitoring systems. In support of the calibration of GEO satellites, the bias characteristics in the infrared channels of four operational GEO imagers-the Advanced Meteorological Imager (AMI) on board the Geostationary Korea Multi Purpose Satellite-2A, the Advanced Himawari Imager (AHI) on the Himawari-8, the Advanced Baseline Imager (ABI) on the Geostationary Operational Environmental Satellite-16, and the Spinning Enhanced Visible and Infrared Imager flying with the Meteosat-11-are examined using two operational numerical weather prediction (NWP) models. The analysis fields from the Unified Model (UM) employed at the Korea Meteorological Administration, Seoul, South Korea, as well as the ECMWF model reanalysis (ERA5) fields are utilized for the simulation of multiple satellites using the same radiative transfer model (RTM) and the observation minus simulation statistics of the four imagers are analyzed over the clear-sky ocean as a function of time, space, observation angles, and scene temperatures. Overall, the biases of the four advanced GEO imagers demonstrate very similar characteristics to each other, although there are a few rather notable exceptions such as a striping issue in AMI, AHI, and ABI. Additionally, this study highlights the synergistic benefits of the intercalibration by revealing features specific to a particular instrument and also by indicating uncertainties of the RTM and the NWP models. It also reveals the relative performance of NWP models, showing that UM fields are overall wetter than ERA5.

Original languageEnglish
Pages (from-to)10725-10737
Number of pages13
JournalIEEE Transactions on Geoscience and Remote Sensing
Issue number12
StatePublished - 1 Dec 2021

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  • Calibration
  • numerical weather prediction (NWP) model
  • remote sensing
  • satellites


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