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CO2 concentrations in the upper troposphere were retrieved from thermal infrared spectra as observed by the only spaceborne hyperspectral sounder launched in the 1990s: the Interferometric Monitor for Greenhouse gases (IMG) onboard the Advanced Earth Observing Satellite (ADEOS). First, the effective optical path difference of the IMG was evaluated because the actual instrumental line shape function of the interferometer component has not been evaluated for technical reasons in the orbit. The CO2 retrieval method was based on the maximum a posteriori (MAP) retrieval method and on procedures to decrease errors that obstruct CO2 signal detection. For the retrieval analysis, ERA-40 re-analysis meteorological data were used as temperature field data. A method of selecting effective channels for CO2 retrieval was used to remove channels with a high temperature dependency and to reduce errors in estimating the water vapor, ozone, and surface temperature. Furthermore, uncertainties in temperature and other error factors, which cannot be removed through channel selection, were evaluated and optimized by treating them as components of measurement errors in the MAP retrieval. CO2 retrieval noises of the MAP retrieval were estimated as 2.5 % and 2.0 % at pressure levels of 500 and 300 hPa, respectively. CO2 concentrations retrieved from IMG data were compared with aircraft measurement data. Results showed that the random error in the IMG retrieval was smaller than that estimated as the a posteriori error of the MAP retrieval. No significant biases were shown compared with the margin of random errors. The CO2 retrieval method was applied to IMG data measured in April, 1997. Although assuming a uniform CO2 concentration as a priori, the latitudinal gradient of the zonal mean concentration was consistent with climatological features presented by previous studies at pressure levels of 500 and 300 hPa. These results suggest that thermal infrared observation by the IMG is effective for evaluating the upper tropospheric CO2 concentration in the 1990s. [ABSTRACT FROM AUTHOR]

To discuss the feasibility of the Himawari follow-on program, impacts of a hyperspectral sounder on a geostationary satellite (GeoHSS) is assessed using an observing system simulation experiment. Hypothetical GeoHSS observations are simulated by using an accurate reanalysis dataset for a heavy rainfall event in western Japan in 2018. The global data assimilation experiment demonstrates that the assimilation of clear-sky radiances of the GeoHSS improves the forecasts of the representative meteorological field and slightly reduces the typhoon position error. The regional data assimilation experiment shows that assimilating temperature and relative humidity profiles derived from the GeoHSS improves the heavy rainfall in the Chugoku region of western Japan as a result of enhanced southwesterly moisture flow off the northwestern coast of the Kyushu Island. These results suggest that the GeoHSS provides valuable information on frequently available vertically resolved temperature and humidity and thus improves the forecasts of severe events. [ABSTRACT FROM AUTHOR]

An algorithm based on CO2 slicing, which has been used for cirrus cloud detection using thermal infrared data, was developed for high-resolution radiance spectra from satellites. The channels were reconstructed based on sensitivity height information of the original spectral channels to reduce the effects of measurement errors. Selection of the reconstructed channel pairs was optimized for several atmospheric profile patterns using simultaneous studies assuming a cloudy sky. That algorithm was applied to data by the Greenhouse gases Observing SATellite (GOSAT). Results were compared with those obtained from the space-borne lidar instrument on-board Cloud- Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). Monthly mean cloud amounts from the slicing generally agreed with those from CALIPSO observations despite some differences caused by surface temperature biases, optically very thin cirrus, multilayer structures of clouds, extremely low cloud tops, and specific atmospheric conditions. Comparison of coincident data showed good agreement, except for some cases, and revealed that the improved slicing method is more accurate than the traditional slicing method. Results also imply that improved slicing can detect lowlevel clouds with cloud top heights as low as approximately 1.5 km. [ABSTRACT FROM AUTHOR]

An algorithm based on CO2 slicing, which has been used for cirrus cloud detection using thermal infrared data, was developed for high-resolution radiance spectra from satellites. The channels were reconstructed based on sensitivity height information of the original spectral channels to reduce the effects of measurement errors. Selection of the reconstructed channel pairs was optimized for several atmospheric profile patterns using simultaneous studies assuming a cloudy sky. That algorithm was applied to data by the Greenhouse gases Observing SATellite (GOSAT). Results were compared with those obtained from the space-borne lidar instrument on-board Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). Monthly mean cloud amounts from the slicing generally agreed with those from CALIPSO observations despite some differences caused by surface temperature biases, optically very thin cirrus, multilayer structures of clouds, extremely low cloud tops, and specific atmospheric conditions. Comparison of coincident data showed good agreement, except for some cases, and revealed that the improved slicing method is more accurate than the traditional slicing method. Results also imply that improved slicing can detect low-level clouds with cloud top heights as low as approximately 1.5 km. [ABSTRACT FROM AUTHOR]