A Robust Bad-Pixel Radiance Reconstruction for the Geostationary Environment Monitoring Spectrometer (GEMS)-Influences on Aerosol Retrieval

Heesung Chong, Won Jin Lee, Hyung Sup Jung, Yeseul Cho, Jhoon Kim, Gonzalo Gonzalez Abad

Research output: Contribution to journalArticlepeer-review

Abstract

The Geostationary Environment Monitoring Spectrometer (GEMS), launched in February 2020, performs hourly measurements of earthshine radiances to retrieve column amounts of air pollutants over Asia. However, the charge-coupled device detector of GEMS has bad pixels that exhibit abnormal radiometric responses, which translates to a decrease in the quality of radiance measurements. Permanent bad pixels result in an information gap in the aerosol product at 14.4°N-16.1°N latitudes (e.g., in Manila, the Philippines, and Mainland Southeast Asia), which cannot be filled even with long-term observations owing to the structure of the east-west scanning mechanism of GEMS. Here, we propose a robust method to reconstruct radiances measured inaccurately by the bad pixels, based on spectral correlation induced mainly by the Fraunhofer line structures. The reconstruction aims at the bad pixels in the wavelength range of 485-491 nm, which affects aerosol retrieval. We estimate that uncertainties in the reconstructed optical depths are 2 orders of magnitude smaller than typical aerosol optical depths. Our results demonstrate that the reconstructed radiances effectively restore the physical distributions of visible aerosol indices, improving the determination of aerosol types. Furthermore, the reconstructed radiances enhance retrievals of aerosol layer height (ALH), holding particular significance for the long-term accumulation of ALH data over Southeast Asia using GEMS.

Original languageEnglish
Article number5510315
Pages (from-to)1-15
Number of pages15
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume62
DOIs
StatePublished - 2024

Keywords

  • Aerosol retrieval
  • bad pixels
  • charge-coupled device (CCD) detector
  • data reconstruction
  • Geostationary Environment Monitoring Spectrometer (GEMS)

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