The Greenhouse gases Observing Satellite (GOSAT) is a Japanese satellite that is intended to observe CO2 concentration
from space and to contribute to advancement of research of the source/sink estimation of CO2. The GOSAT main sensor
is a Fourier Transform Spectrometer (FTS) named "TANSO-FTS", which covers a wide terrestrial radiation spectrum
including CO2 absorption bands at 1.6 μm, 2.0 μm, and 15 μm. The former two bands are used to estimate columnar
concentration of CO2; the latter is used to retrieve the vertical profile of CO2 in the upper atmosphere above about 700
hPa pressure level. In addition, another installed on the satellite is an imaging sensor that will be used to detect clouds
and aerosols: Cloud and Aerosol Imager (CAT). The Center for Climate System Research (CCSR) has contracted with
the Japan Aerospace Exploration Agency (JAXA) to develop an algorithm to retrieve CO2 concentration profiles from
data measured by the thermal infrared (TIR) band of the TANSO-FTS sensor. We adopt the maximum a posteriori
method (MAP) to retrieve the vertical profile of atmospheric parameters from thermal infrared spectra. Key techniques
for retrieving CO2 concentrations are 1) reduction of temperature estimation error through channel selection, 2)
optimization of the initial guess for CO2 profile based on the output from a chemical transport model (CTM), and 3)
usage of data from the 1.6 μm band of TANSO-FTS as an additional constraint in retrieval of vertical profiles of CO2.
Although thermal infrared spectrum data have poor vertical resolving power for CO2 concentration in the lower
atmosphere, particularly in the boundary layer, we expect that CO2 amount in the lower atmosphere can be deduced by
substituting the upper level concentration from the columnar concentration estimated from the 1 .6 μm band data.
Reducing temperature and water vapor estimation errors is indispensable for retrieving a CO2 concentration profile or columnar amount from thermal infrared spectrum data because spectral radiance in the thermal infrared region is much more sensitive to temperature and water vapor concentration changes than it is to CO2 concentration changes. This study presents a data analysis procedure to estimate the CO2 columnar amount from the thermal infrared spectrum. The first step retrieves the temperature vertical profile, water vapor vertical profile, and the surface temperature from spectra in the strong absorption bands of CO2 and H2O. Then the spectral biases that are attributable to temperature and water vapor retrieval errors are reduced by comparing observed and synthesized radiances in the atmospheric window region. The final step estimates the CO2 columnar amount from the corrected spectra of a weak absorption band of CO2 that is located around 940 cm-1. This method was applied to analysis of spectrum data from IMG sensor aboard the ADEOS satellite. Some preliminary results are shown.
This study presents an analysis of atmospheric temperature and
water vapor using interferometric monitor for greenhouse gases (IMG)
spectrum data and its retrieval procedure. The IMG is a high-resolution infrared sensor of the Fourier transform spectrometer (FTS) type that was launched aboard the Advanced Earth Observing Satellite (ADEOS) satellite in August 1996. Upwelling infrared radiation from the Earth was measured to examine the effects of greenhouse gases in the troposphere until June 1997. In the procedure to retrieve trace gas profiles from such satellite-based FTS data, accurate information on temperature, water vapor and surface properties is essential for precise retrieval. The instrument line shape (ILS) function, which generally depends on many factors of its sensor system, must also be determined accurately. In order to estimate the optimal ILS function, the "effective optical path difference (OPD)", which is assumed in retrieval analyses, is tuned to obtain the most optimal retrieved results in comparison with the sonde data. This method was applied to IMG spectrum data.
Analytical procedure to derive the ozone concentration profile from the analysis of the high-resolution spectrum data as observed by a space FTS sensor such as Interferometric Monitor for Greenhouse gases (IMG) onboard Advanced Earth Observing Satellite (ADEOS) has been presented. In the procedure, Jacobian matrices were re-calculated for each spectrum considering the cloud top temperature in the instantaneous field of view (IFOV) of the FTS sensor. That was because these cloud parameters seriously affect the elements of the Jacobian matrices sometimes causing the change of the sign of the elements. This method has been applied to the analysis of IMG data that were observed during the northern hemispheric ozone hole like event occurred in 1997 spring. It has been found that the usage of the precise instrumental line shape (ILS) of the sensor is very important to improve the vertical resolution of retrieval by loosening the retrieval constrains.