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Open AccessArticle

Evaluation of Bias Correction Methods for GOSAT SWIR XH2O Using TCCON data

Satellite Observation Center, National Institute for Environmental Studies (NIES), 16-2 Onogawa, Tsukuba 305-8506, Japan
IMK-IFU, Karlsruhe Institute of Technology, 82467 Garmisch-Partenkirchen, Germany
Institute of Environmental Physics, University of Bremen, Otto-Hahn- Allee 1, 28359 Bremen, Germany
Space and Earth Observation Centre, Finnish Meteorological Institute, Tähteläntie 62, 99600 Sodankylä, Finland
IMK-ASF, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Leopoldshafen, Germany
National Institute of Water and Atmospheric Research Ltd. (NIWA), State Highway 85, Lauder, Omakau, Central Otago 9377, New Zealand
Centre for Atmospheric Chemistry, Faculty of Science, Medicine and Health, University of Wollongong, Northfields Ave, Wollongong NSW 2522, Australia
Atmospheric Science Branch, NASA Ames Research Center, Mail Stop 245-5, Moffett Field, CA 94035, USA
Los Alamos National Laboratory, Los Alamos, NM 87545, USA
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(3), 290;
Received: 19 December 2018 / Revised: 23 January 2019 / Accepted: 29 January 2019 / Published: 1 February 2019
(This article belongs to the Special Issue Remote Sensing of Atmospheric Components and Water Vapor)
This study evaluated three bias correction methods of systematic biases in column-averaged dry-air mole fraction of water vapor (XH2O) data retrieved from Greenhouse Gases Observing Satellite (GOSAT) Short-Wavelength Infrared (SWIR) observations compared with ground-based data from the Total Carbon Column Observing Network (TCCON). They included an empirically multilinear regression method, altitude bias correction method, and combination of altitude and empirical correction for three cases defined by the temporal and spatial collocation around TCCON site. The results showed that large altitude differences between GOSAT observation points and TCCON instruments are the main cause of bias, and the altitude bias correction method is the most effective bias correction method. The lowest biases result from GOSAT SWIR XH2O data within a 0.5° × 0.5° latitude × longitude box centered at each TCCON site matched with TCCON XH2O data averaged over ±15 min of the GOSAT overpass time. Considering land data, the global bias changed from −1.3 ± 9.3% to −2.2 ± 8.5%, and station bias from −2.3 ± 9.0% to −1.7 ± 8.4%. In mixed land and ocean data, global bias and station bias changed from −0.3 ± 7.6% and −1.9 ± 7.1% to −0.8 ± 7.2% and −2.3 ± 6.8%, respectively, after bias correction. The results also confirmed that the fine spatial and temporal collocation criteria are necessary in bias correction methods. View Full-Text
Keywords: GOSAT SWIR XH2O; systematic biases; bias correction; TCCON XH2O; altitude bias correction GOSAT SWIR XH2O; systematic biases; bias correction; TCCON XH2O; altitude bias correction
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Trieu, T.T.N.; Morino, I.; Ohyama, H.; Uchino, O.; Sussmann, R.; Warneke, T.; Petri, C.; Kivi, R.; Hase, F.; Pollard, D.F.; Deutscher, N.M.; Velazco, V.A.; Iraci, L.T.; Podolske, J.R.; Dubey, M.K. Evaluation of Bias Correction Methods for GOSAT SWIR XH2O Using TCCON data. Remote Sens. 2019, 11, 290.

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