Studies Regarding the Ensquared Energy of a Geostationary Hyperspectral Infrared Sounder

Details

• Journal Title:
  IEEE Transactions on Geoscience and Remote Sensing
• Personal Author:
  Li, Zhenglong ; Schmit, Timothy J. ; Li, Jinlong ; Li, Jun ; Heidinger, Andrew K.
• NOAA Program & Office:
  CIMSS (Cooperative Institute for Meteorological Satellite Studies) ; NESDIS (National Environmental Satellite, Data, and Information Service) ; STAR (Center for Satellite Applications and Research)
• Description:
  Compared with low Earth orbit (LEO) satellites, the high altitude from geostationary Earth orbit (GEO) satellites leads to increased diffraction effects on hyperspectral infrared (HIR) sounders, which reduces the ensquared energy (EE) within the satellites’ field of view (FOV) and increases the pseudo noise of the measurements. To help understand how the instrument performance is affected by EE for the Geostationary Extended Observations Sounder (GXS), a point spread function (PSF) is used to simulate the contribution of each location within and outside of an FOV ( 4× 4 km at nadir). The PSF is applied to the Moderate Resolution Imaging Spectroradiometer (MODIS) airborne simulator (MAS) data with a spatial resolution of 50 m, to determine an appropriate EE for GXS. Although wavenumber dependent, an EE of 70% is recommended, which ensures that all GXS channels have pseudo noise less than the instrument specifications. Regardless of the EE value, the pseudo noise reduces the precision of the temperature and moisture sounding retrievals in the troposphere. Even with an EE of 70%, the pseudo noise slightly increases the root-mean-square error (RMSE) by 3%–4% for temperature and by 1%–4% for relative humidity. If an EE of 70% is difficult to meet, due to cost for example, a lower EE can be a good tradeoff with only a slight degradation in the sounding retrieval quality, which may be overcome with spatial averaging using the inverted cone method. An EE of 50% would lead to an RMSE increase of about 6% for temperature and 3%–6% for relative humidity.
• Keywords:
  Atmospheric Science Remote Sensing Atmospheric Science Remote Sensing
• Source:
  IEEE Transactions on Geoscience and Remote Sensing, 61, 1-9
• DOI:
  https://doi.org/10.1109/tgrs.2023.3271931
• ISSN:
  0196-2892 ; 1558-0644
• Format:
  PDF
• Publisher:
  Institute of Electrical and Electronics Engineers (IEEE)
• Document Type:
  Journal Article
• Funding:
  Grant no. NA20NES4320003
• Rights Information:
  Accepted Manuscript
• Compliance:
  Submitted
• Main Document Checksum:
  urn:sha-512:4fb2813b6d54572a49cdf93f743bf998f272ce520cf2c9aae18cf38dd07c15d60477986f47262fc0b5d8e1d8ffb90d24979af0d68f52a5f8013bea16b9258d00
• Download URL:
  https://repository.library.noaa.gov/view/noaa/70960/noaa_70960_DS1.pdf
• File Type:
  [PDF - 1.15 MB ]