Back to Search
Start Over
Long-Term Vicarious Calibration of GOSAT Short-Wave Sensors: Techniques for Error Reduction and New Estimates of Radiometric Degradation Factors.
- Source :
-
IEEE Transactions on Geoscience & Remote Sensing . Jul2014, Vol. 52 Issue 7, p3991-4004. 14p. - Publication Year :
- 2014
-
Abstract
- This work describes the radiometric calibration of the short-wave infrared (SWIR) bands of two instruments aboard the Greenhouse gases Observing SATellite (GOSAT), the Thermal And Near infrared Sensor for carbon Observations Fourier Transform Spectrometer (TANSO-FTS) and the Cloud and Aerosol Imager (TANSO-CAI). Four vicarious calibration campaigns (VCCs) have been performed annually since June 2009 at Railroad Valley, NV, USA, to estimate changes in the radiometric response of both sensors. While the 2009 campaign ( VCC2009) indicated significant initial degradation in the sensors compared to the prelaunch values, the results presented here show that the stability of the sensors has improved with time. The largest changes were seen in the 0.76 μm oxygen A-band for TANSO-FTS and in the 0.380 and 0.674 μm bands for TANSO-CAI. This paper describes techniques used to optimize the vicarious calibration of the GOSAT SWIR sensors. We discuss error reductions, relative to previous work, achieved by using higher quality and more comprehensive in situ measurements and proper selection of reference remote sensing products from the Moderate Resolution Imaging Spectroradiometer used in radiative transfer calculations to model top-of-the-atmosphere radiances. In addition, we present new estimates of TANSO-FTS radiometric degradation factors derived by combining the new vicarious calibration results with the time-dependent model provided by Yoshida (2012), which is based on analysis of on-board solar diffuser data. We conclude that this combined model provides a robust correction for TANSO-FTS Level 1B spectra. A detailed error budget for TANSO-FTS vicarious calibration is also provided. [ABSTRACT FROM PUBLISHER]
Details
- Language :
- English
- ISSN :
- 01962892
- Volume :
- 52
- Issue :
- 7
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Geoscience & Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 101186793
- Full Text :
- https://doi.org/10.1109/TGRS.2013.2278696