HR: 0800h
AN: A21D-0898    [Abstracts]
TI: Impact of Cloud Occurrence on CO2 Sources/Sinks Inversions Based on Satellite Data
AU: * Saitoh, N
EM: snaoko@ccsr.u-tokyo.ac.jp
AF: Center for Climate System Research, University of Tokyo, General Research Building 5-1-5 Kashiwanoha, Kashiwa, 277-8568 Japan
AU: Taguchi, S
EM: s.taguchi@aist.go.jp
AF: Advanced Industrial Science and Technology, 16-1 Onogawa, Tsukuba, 305-8569 Japan
AU: Imasu, R
EM: imasu@ccsr.u-tokyo.ac.jp
AF: Center for Climate System Research, University of Tokyo, General Research Building 5-1-5 Kashiwanoha, Kashiwa, 277-8568 Japan
AB: The satellite-borne sensors that aim to CO₂ measurements will be set off in the next few years. One of these sensors is the Greenhouse gases Observing Satellite (GOSAT), which is developed by Ministry of the Environment, National Institute for Environ-mental Studies (NIES), and Japan Aerospace Exploration Agency (JAXA), and planed to be lunched in 2008. Nadir sensors including GOSAT are often inhibited from ob-serving tropospheric components with enough accuracy by the occurrence of clouds in their field of view. Although global and high-frequent CO₂ data obtained with satellite sensors are sure to contribute CO₂ sources/sinks inversions when they are incorporated in CTM, such regional lack of CO₂ measurements due to clouds would affect the inver-sion results. In order to assess the impact of cloud occurrence on CO₂ distribution in-ferred from satellite sensors and the "clear sky bias" and "synoptic scale bias" due to clouds, we compared cloud distributions from MODIS cloud products with CO₂ global distributions from the Simulator of Tracer transport of the Atmosphere in Global Scale (STAG) at each season (January/April/July/October); the measurement locations of GOSAT and its field of view were considered in the analysis. In this study, it is implied that some bias would occur in the resultant CO₂ distributions if satellite data with high cloud fraction cannot be used. Development of CTM that can describe detailed CO₂ di-urnal variation due to vegetation is required for further discussion.
DE: 0300 ATMOSPHERIC COMPOSITION AND STRUCTURE
DE: 0319 Cloud optics
DE: 0322 Constituent sources and sinks
DE: 0480 Remote sensing
SC: Atmospheric Sciences [A]
MN: Fall Meeting 2005