Engineering topics
Matsunaga, Tsuneo
Publications and source records attributed to Matsunaga, Tsuneo.
Comparing GOSAT Observations of Localized CO2 Enhancements by Large Emitters with Inventory-Based Estimates
We employed an atmospheric transport model to attribute column-averaged CO2 mixing ratios (XCO2) observed by Greenhouse gases Observing SATellite (GOSAT) to emissions due to large sources such as megacities and power plants. XCO2 enhancements estimated from observations were compared to model simulations implemented at the spatial resolution of the satellite observation footprint (0.1deg × 0.1deg). We found that the simulated XCO2 enhancements agree with the observed over several continental regions across the globe, for example, for North America with an observation to simulation ratio of 1.05 +/- 0.38 (p<0.1), but with a larger ratio over East Asia (1.22 +/- 0.32; p<0.05). The obtained observation-model discrepancy (22%) for East Asia is comparable to the uncertainties in Chinese emission inventories (approx.15%) suggested by recent reports. Our results suggest that by increasing the number of observations around emission sources, satellite instruments like GOSAT can provide a tool for detecting biases in reported emission inventories.
The difference between laboratory and in-situ pixel-averaged emissivity: The effects on temperature-emissivity separation
Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a Japanese future imaging sensor which has five channels in thermal infrared (TIR) region. To extract spectral emissivity information from ASTER and/or TIMS data, various temperature-emissivity (T-E) separation methods have been developed to date. Most of them require assumptions on surface emissivity, in which emissivity measured in a laboratory is often used instead of in-situ pixel-averaged emissivity. But if these two emissivities are different, accuracies of separated emissivity and surface temperature are reduced. In this study, the difference between laboratory and in-situ pixel-averaged emissivity and its effect on T-E separation are discussed. TIMS data of an area containing both rocks and vegetation were also processed to retrieve emissivity spectra using two T-E separation methods.
Application of split window technique to TIMS data
Absorptions by the atmosphere in thermal infrared region are mainly due to water vapor, carbon dioxide, and ozone. As the content of water vapor in the atmosphere greatly changes according to weather conditions, it is important to know its amount between the sensor and the ground for atmospheric corrections of thermal Infrared Multispectral Scanner (TIMS) data (i.e. radiosonde). On the other hand, various atmospheric correction techniques were already developed for sea surface temperature estimations from satellites. Among such techniques, Split Window technique, now widely used for AVHRR (Advanced Very High Resolution Radiometer), uses no radiosonde or any kind of supplementary data but a difference between observed brightness temperatures in two channels for estimating atmospheric effects. Applications of Split Window technique to TIMS data are discussed because availability of atmospheric profile data is not clear when ASTER operates. After these theoretical discussions, the technique is experimentally applied to TIMS data at three ground targets and results are compared with atmospherically corrected data using LOWTRAN 7 with radiosonde data.