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Validation of Xco2 Derived from Swir Spectra of Gosat Tanso-fts with Aircraft Measurement Data : Volume 13, Issue 2 (04/02/2013)

By Inoue, M.

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Book Id: WPLBN0003996575
Format Type: PDF Article :
File Size: Pages 44
Reproduction Date: 2015

Title: Validation of Xco2 Derived from Swir Spectra of Gosat Tanso-fts with Aircraft Measurement Data : Volume 13, Issue 2 (04/02/2013)  
Author: Inoue, M.
Volume: Vol. 13, Issue 2
Language: English
Subject: Science, Atmospheric, Chemistry
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Historic
Publication Date:
2013
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

Citation

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Morino, I., Yokota, T., Uchino, O., Miyamoto, Y., Andrews, A. E., Patra, P. K.,...Sawa, Y. (2013). Validation of Xco2 Derived from Swir Spectra of Gosat Tanso-fts with Aircraft Measurement Data : Volume 13, Issue 2 (04/02/2013). Retrieved from http://www.ebooklibrary.org/


Description
Description: National Institute for Environmental Studies (NIES), Tsukuba, Japan. Column-averaged volume mixing ratios of carbon dioxide (XCO2) retrieved from Greenhouse gases Observing SATellite (GOSAT) Short-Wavelength InfraRed (SWIR) observations were compared with aircraft measurements by the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project, the National Oceanic and Atmospheric Administration (NOAA), and the National Institute for Environmental Studies (NIES). Before validation, we investigated the impacts of GOSAT SWIR column averaging kernels (CAK) and the shape of a priori profiles on the calculation of XCO2 based on aircraft measurements (aircraft-based XCO2). The differences between aircraft-based XCO2 with and without the application of GOSAT CAK were evaluated to be less than ±0.4 ppm at most, and less than 0.1 ppm on average. Therefore, we concluded that the GOSAT CAK produces only a minor effect on the aircraft-based XCO2 calculation in terms of the overall uncertainty of GOSAT XCO2.

In this study, two approaches were used to validate GOSAT products (Ver. 02.00). First, we performed a comparison of GOSAT data retrieved within ±2-degree or ±5-degree latitude/longitude boxes centered at each aircraft measurement site and aircraft-based data measured on a GOSAT overpass day (i.e. extraction of temporally matched cases). As this method resulted in no matched data for observation sites where no aircraft measurement was made on the GOSAT overpass day, we also attempted to validate GOSAT products by gap-filling the aircraft-based XCO2 time series through curve fitting. Both methods indicated that GOSAT XCO2 agreed well with aircraft-based XCO2, except that the former is negatively biased by 1–2 ppm with a standard deviation of 1–3 ppm.


Summary
Validation of XCO2 derived from SWIR spectra of GOSAT TANSO-FTS with aircraft measurement data

Excerpt
Matsueda, H., Machida, T., Sawa, Y., Nakagawa, Y., Hirotani, K., Ikeda, H., Kondo, N., and Goto, K.: Evaluation of atmospheric CO2 measurements from new flask air sampling of JAL airliner observations, Pap. Meteorol. Geophys., 59, 1–17, 2008.; Miyamoto, Y., Inoue, M., Morino, I., Uchino, O., Yokota, T., Machida, T., Sawa, Y., Matsueda, H., Sweeney, C., Tans, P. P., Andrews, A. E., and Patra, P. K.: Atmospheric column-averaged mole fractions of carbon dioxide at 53 aircraft measurement sites, Atmos. Chem. Phys. Discuss., 12, 28493–28523, doi:10.5194/acpd-12-28493-2012, 2012.; Morino, I., Uchino, O., Inoue, M., Yoshida, Y., Yokota, T., Wennberg, P. O., Toon, G. C., Wunch, D., Roehl, C. M., Notholt, J., Warneke, T., Messerschmidt, J., Griffith, D. W. T., Deutscher, N. M., Sherlock, V., Connor, B., Robinson, J., Sussmann, R., and Rettinger, M.: Preliminary validation of column-averaged volume mixing ratios of carbon dioxide and methane retrieved from GOSAT short-wavelength infrared spectra, Atmos. Meas. Tech., 4, 1061–1076, doi:10.5194/amt-4-1061-2011, 2011.; Nakakita, E., Ikebuchi, S., Nakamura, T., Kanmuri, M., Okuda, M., Yamaji, A., and Takasao, T.: Short-term rainfall prediction method using a volume scanning radar and grid point value data from numerical weather prediction, J. Geophys. Res., 101, 26181–26197, 1996.; Nakazawa, T., Machida, T., Sugawara, S., Murayama, S., Morimoto, S., Hashida, G., Honda, H., and Itoh, T.: Measurements of the stratospheric carbon dioxide concentration over Japan using a balloon-borne cryogenic sampler, Geophys. Res. Lett., 22, 1229–1232, doi:10.1029/95GL01188, 1995.; Nakazawa, T., Ishizawa, M., Higuchi, K., and Trivett, N. B. A.: Two curve fitting methods applied to CO2 flask data, Environmetrics, 8, 197–218, 1997a.; Nakazawa, T., Morimoto, S., Aoki, S., and Tanaka, M.: Temporal and spatial variations of the carbon isotopic ratio of atmospheric carbon dioxide in the western Pacific region, J. Geophys. Res., 102, 1271–1285, 1997b.; Nakazawa, T., Sugawara, S., Inoue, G., Machida, T., Maksyutov, S., and Mukai, H.: Aircraft measurements of the concentrations of CO2, CH4, N2O, and CO and the carbon and oxygen isotopic ratios of CO2 in the troposphere over Russia, J. Geophys. Res., 102, 3843–3859, 1997c.; Niwa, Y., Machida, T., Sawa, Y., Matsueda, H., Schuck, T. J., Brenninkmeijer, C. A. M., Imasu, R., and Satoh, M.: Imposing strong constraints on tropical terrestrial CO2 fluxes using passenger aircraft based measurements, J. Geophys. Res., 117, D11303, doi:10.1029/2012JD017474, 2012.; NOAA/ESRL Carbon Cycle Greenhouse Gases Aircraft Program, available at: http://www.esrl.no

 

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