Japan Geoscience Union Meeting 2015

Presentation information

Oral

Symbol A (Atmospheric and Hydrospheric Sciences) » A-AS Atmospheric Sciences, Meteorology & Atmospheric Environment

[A-AS21] Atmospheric Chemistry

Wed. May 27, 2015 4:15 PM - 6:00 PM 201B (2F)

Convener:*Yousuke Sawa(Oceanography and Geochemistry Research Department, Meteorological Research Institute), Nobuyuki Takegawa(Graduate School of Science and Engineering, Tokyo Metropolitan University), Yugo Kanaya(Research Institute for Global Change, Japan Agency for Marine-Earth Science and Technology), Kenshi Takahashi(Research Institute for Sustainable Humanosphere, Kyoto University), Hiroshi Tanimoto(National Institute for Environmental Studies), Chair:Tomoki Nakayama(Solar-Terrestrial Environment Laboratory, Nagoya University)

5:39 PM - 5:42 PM

[AAS21-P22] Comparisons between NICAM-TM and GOSAT/TANSO-FTS TIR CO2 data

3-min talk in an oral session

*Ryo SUGIMURA1, Naoko SAITOH1, Ryoichi IMASU2, Shuji KAWAKAMI3, Kei SHIOMI3, Yosuke NIWA4, Toshinobu MACHIDA5, Yousuke SAWA4, Hidekazu MATSUEDA4 (1.Center for Environmental Remote Sensing, Chiba University, 2.Atmosphere and Ocean Research Institute, The University of Tokyo, 3.Japan Aerospace Exploration Agency, 4.Meteorological Research Institute, 5.National Institute for Environmental Studies)

Keywords:CO2, satellite remote sensing, GOSAT

Greenhouse gases Observing SATellite (GOSAT), which was the first satellite for global observations of greenhouse gases, was successfully launched on 23 January 2009. Our recent analysis suggested that CO2 vertical profiles retrieved from Thermal and Near Infrared Sensor for Carbon Observation (TANSO) - Fourier Transform Spectrometer (FTS) thermal infrared (TIR) band had a negative bias in the middle troposphere. In this study, we globally evaluated the magnitude of the bias through the comparisons between the TIR CO2 data and Nonhydrostatic Icosahedral Atmospheric Model - based Transport Model (NICAM-TM) CO2 data [Niwa et al., 2011]. Furthermore, we calculated a correction factor to modify the bias for each latitude band and applied the latitude-dependent correction factors to the TIR CO2 data on 500 hPa; here, we estimated the correction factors on the basis of comparisons between CO2 profiles observed over airports by Continuous CO2 Measuring Equipment (CME) in Comprehensive Observation Network for Trace gases by Airliner (CONTRAIL) project [Machida et al., 2008] and the coincident TIR CO2 profiles. Then, we analyzed seasonal variations of the modified TIR CO2 data to check the validity of the correction factors estimated here.

Comparisons of the differences of CO2 concentrations on 500 hPa and 200 hPa (500 hPa minus 200 hPa) between TIR CO2 data and NICAM-TM CO2 data showed that the differences of the TIR CO2 data were larger than those of the NICAM-TM CO2 data because of the negative bias of the mid-tropospheric TIR data. The CO2 differences between the two pressure levels of the TIR data were particularly large (~8 ppmv) in low latitudes; this characteristic was not seen both in the NICAM-TM CO2 data and the a priori CO2 data (NIES-TM05). Next, we applied the latitude-dependent correction factors to the TIR CO2 data on 500 hPa, and then compared the CO2 differences on 500 hPa and 200 hPa. In low latitudes (25⁰S-25⁰N), the CO2 differences between the two pressure levels of the TIR data became closer to the CO2 differences of the NICAM-TM CO2 data and the a priori CO2 data when we applied the correction factor estimated over Bangkok. On the other hand, in northern high latitudes (northern latitudes of ~40⁰N), most of the CO2 differences between the two pressure levels of the TIR data were positive unlike the NICAM-TM CO2 and the a priori CO2 data when we applied the correction factor estimated over Amsterdam. In boreal summer, surface CO2 concentrations are lower than middle and upper tropospheric CO2 concentrations; in that sense, the correction factor applied here was not appropriate in northern high latitudes in summer. These results suggest that the magnitude of the negative bias seen in TIR CO2 data would vary depending on seasons as well as regions, and therefore, we should estimate a latitude-dependent correction factor for each season.

Furthermore, we compared time series of TIR CO2 data with those of NICAM-TM CO2 data and the a priori CO2 data for several different regions that were categorized in terms of climatic divisions and latitude bands [Niwa et al., 2011]. Our preliminary results showed that the seasonal variations of the TIR CO2 data in some regions were closer to those of the NICAM CO2 data than of the a priori CO2 data. For future work, we should review how to compare the three CO2 data sets, and then closely analyze the differences in seasonal variations among the three data sets globally.

Acknowledgements
We thank the staff and engineers of Japan Airlines, the JAL Foundation, and JAMCO Tokyo for supporting the CONTRAIL project.