4.7 Article

Comparison of XH2O Retrieved from GOSAT Short-Wavelength Infrared Spectra with Observations from the TCCON Network

期刊

REMOTE SENSING
卷 8, 期 5, 页码 -

出版社

MDPI
DOI: 10.3390/rs8050414

关键词

GOSAT; H2O; SWIR; validation

资金

  1. Australian Research Council [DE140100178, DP140101552, DP110103118, DP0879468, LE0668470, LP0562346]
  2. NASA [NNX14AI60G, NNX11AG01G, NAG5-12247, NNG05-GD07G]
  3. NASA Orbiting Carbon Observatory Program
  4. European Union's project InGOS
  5. European Union's project ICOS-INWIRE
  6. Senate of Bremen
  7. New Zealand Foundation of Research, Science and Technology [CO1X0204, CO1X0703, CO1X0406]
  8. New Zealand's National Institute of Water and Atmospheric Research (NIWA)'s Atmosphere Research Programme [3]
  9. Bavarian Ministry of the Environment and Consumer Protection
  10. Australian Research Council [DE140100178] Funding Source: Australian Research Council

向作者/读者索取更多资源

Understanding the atmospheric distribution of water (H2O) is crucial for global warming studies and climate change mitigation. In this context, reliable satellite data are extremely valuable for their global and continuous coverage, once their quality has been assessed. Short-wavelength infrared spectra are acquired by the Thermal And Near-infrared Sensor for carbon Observation-Fourier Transform Spectrometer (TANSO-FTS) aboard the Greenhouse gases Observing Satellite (GOSAT). From these, column-averaged dry-air mole fractions of carbon dioxide, methane and water vapor (XH2O) have been retrieved at the National Institute for Environmental Studies (NIES, Japan) and are available as a Level 2 research product. We compare the NIES XH2O data, Version 02.21, with retrievals from the ground-based Total Carbon Column Observing Network (TCCON, Version GGG2014). The datasets are in good overall agreement, with GOSAT data showing a slight global low bias of -3.1% +/- 24.0%, good consistency over different locations (station bias of -1.53% +/- 10.35%) and reasonable correlation with TCCON (R = 0.89). We identified two potential sources of discrepancy between the NIES and TCCON retrievals over land. While the TCCON XH2O amounts can reach 6000-7000 ppm when the atmospheric water content is high, the correlated NIES values do not exceed 5500 ppm. This could be due to a dry bias of TANSO-FTS in situations of high humidity and aerosol content. We also determined that the GOSAT-TCCON differences directly depend on the altitude difference between the TANSO-FTS footprint and the TCCON site. Further analysis will account for these biases, but the NIES V02.21 XH2O product, after public release, can already be useful for water cycle studies.

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