A41I-0169
Characteristics of Four-years of GOSAT/TANSO-FTS TIR V1.0 CO2 and CH4 Products
Thursday, 17 December 2015
Poster Hall (Moscone South)
Naoko Saitoh1, Syuhei Kimoto2, Ryo Sugimura2, Ryoichi Imasu3, Kei Shiomi4, Akihiko Kuze5, Fumie Kataoka6, Robert O Knuteson7, Toshinobu Machida8, Yousuke Sawa9 and Hidekazu Matsuda9, (1)Chiba University, Chiba, Japan, (2)CEReS, Chiba, Japan, (3)University of Tokyo, Bunkyo-ku, Japan, (4)Japan Aerospace Exploration Agency, Kanagawa, Japan, (5)JAXA Japan Aerospace Exploration Agency, EORC, Sagamihara, Japan, (6)RESTEC, Tsukuba, Japan, (7)University of Wisconsin Madison, Madison, WI, United States, (8)NIES National Institute of Environmental Studies, Ibaraki, Japan, (9)Meteorological Research Institute, Ibaraki, Japan
Abstract:
Greenhouse Gases Observing Satellite (GOSAT) was launched on 23 January 2009, and has continued to make global observations, including both nadir and off-nadir measurements, for more than six years since its launch. The thermal infrared (TIR) band of Thermal and Near-infrared Sensor for Carbon Observation Fourier Transform Spectrometer (TANSO-FTS) on board the GOSAT has observed CO2 and CH4 profiles. We have analyzed the four-year data from 2010 through 2013 of the latest released version of the TIR Level 2 (L2) CO2 and CH4 products (V1.0). Comparisons of the TIR upper atmospheric CO2 product with CO2 data from Comprehensive Observation Network for Trace Gases by Airliner (CONTRAIL) aircraft measurements show that the growth rate estimated from the TIR CO2 data is slightly lower than that from the CONTRAIL data. Overall, the TIR V1.0 CO2 product has better quality in the upper troposphere and lower stratosphere than the a priori judging from comparisons with the collocated aircraft data. In spring and summer, however, the quality of the TIR L2 CO2 products became slightly worse than in the other seasons, especially in the low and northern-mid latitudes. This is because the corresponding a priori had a larger bias and the TIR Level 1B (L1B) radiance spectra might have a larger bias in the spring-summer seasons. Here, we have tested several types of correction methods to modify the L1B spectral bias, and then compared CO2 and CH4 concentrations retrieved after applying spectral bias correction factors with coincident CONTRAIL and HIAPER Pole-to-Pole Observation (HIPPO) aircraft data. The comparison results suggest that the L1B spectral bias correction factor should be changed depending on wavelength. In addition, it should be expressed as a function of on-board internal calibration blackbody temperatures. This is because they are weak season-dependent parameters; they were clearly lower in spring and summer.
