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A2: ID.10643 CO2 from Space
Monitoring Carbon Dioxide from space: instrument design, retrieval algorithm, Cal/Val and application
1Institute of Atmospheric Physics, Chinese Academy of Sciences, China, People's Republic of; 2Earth Observations Science Group, University of Leicester, Leicester, UK; 3School of GeoSciences, University of Edinburgh, Edinburgh, UK;
China’s carbon dioxide observation satellite (TanSat) is a carbon dioxide observation satellite funded and supported by the Ministry of Science and Technology of the People’s Republic of China and the Chinese Academy of Sciences. The launching date is planning in 2016.
TanSat will carry two key instruments: a hyperspectral grating spectrometer for the column-averaged dry-air mixing ratio of CO2 (XCO2) and a wide field-of-view moderate-resolution polarization imaging spectrometer for cloud and aerosol observations. Hyperspectral measurements in O2A (0.76μm) band, 1.61 and 2.04μm CO2 band will be used for approaching XCO2, and surface carbon flux will be constrained by highly precision XCO2 data.
TanSat XCO2 retrieval algorithm and Application of TanSat algorithm on GOSAT Observation (ATANGO) has been improved this year. Global retrieval experiment has been carried out on GOSAT L1B 161160 data of 2012, and well compared with GOS_OCFP product validated using The Total Column Carbon Observing Network (TCCON) measurements in cooperation with University of Leicester. The retrieved XCO2 agree well with TCCON measurements in a low bias of 0.15 ppm and RMSE of 1.48 ppm, and captured the seasonal variation and increasing of XCO2 in Northern and Southern Hemisphere respectively as other measurements. The surface carbon flux inversion and satellite sampling method has been analyzed by using PyOSSE with the cooperation with University of Edinburgh.
Surface CO2 and CH4 Fluxes Over China: Trends and Inter-annual Variations Inferred From GOSAT Proxy XCH4:XCO2 Retrievals
1School of GeoSciences, University of Edinburgh, Edinburgh, UK; 2Earth Observations Science Group, University of Leicester, Leicester, UK; 3Key Laboratory of the Middle Atmosphere and Global Environmental Observation, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China;
Top-down flux inversions have been used to infer surface CO2 and CH4 fluxes from the observed variations of atmospheric CO2 and CH4 concentrations, which has led to substantial improvements in our understanding of the global carbon cycle. Most of top-down inversions rely on the in-situ observation network with sparse and unevenly distributed spatial coverage. As a result, the inferred surface fluxes have limited temporal and spatial resolutions, with large uncertainty over many regions critical to global carbon cycle.
Recently, space-based instruments such as the JAXA GOSAT, the NASA OCO-2 satellite and the upcoming Chinese TanSat, have been developed to measure column dry-air mole fraction of the targeted greenhouse gases (such as XCO2 or XCH4) with unprecedented precision. However inversion experiments for assimilating full physical XCO2 and XCH4 retrievals showed that the inferred surface fluxes can be comprised by varied observation coverage, and by small uncharacterized biases, reflecting the complexity in accurately modelling the radiative transfer in the atmosphere, particularly in the presence of cloud and aerosol scattering.
Fraser et al (2014) demonstrated the possibility for simultaneously inferring regional CO2 and CH4 ﬂux estimates from the GOSAT XCH4:XCO2 ratio retrieved using the proxy approach. The proxy retrieval approach ﬁts CO2 and CH4 gases in nearby spectral windows, and is considered to be less sensitive to the ﬁtting artefacts common to both gases, e.g. scattering from aerosol and clouds. As a result, the proxy data product is simpler than the full physics retrieval approach, with more useable retrievals over geographical regions that are compromised by seasonal aerosol and clouds, such as China.
We report a recent experiment for assimilating GOSAT XCH4:XCO2 proxy retrievals by the University of Leicester to simultaneously estimate monthly CH4 and CO2 fluxes for about 6 years from 2009 to 2014. We compare the resulting fluxes with the prior estimates as well as with the fluxes inferred from the in-situ observations only. It is found that over China, the annual net CO2 and CH4 emissions inferred from the GOSAT XCH4:XCO2 ratios are significantly lower than both the prior estimates and the ones inferred from in-situ observations. We also find that the ratio inversions show a much smaller increase trend for CH4 fluxes over China than the inversions based on in-situ observations only.
We validate our resulting fluxes by comparing the posterior model CO2 and CH4 simulations with independent observations, including the network designed for supporting the Chinese TanSat mission.
Space-based Greenhouse Gas Observations over China
1EOS Group, Department of Physics and Astronomy, University of Leicester, Leicester, United Kingdom; 2School of GeoSciences, University of Edinburgh, Edinburgh, United Kingdom; 3Key Laboratory of the Middle Atmosphere and Global Environmental Observation, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China;
CO2 and CH4 are the most important anthropogenic greenhouse gases and the increase in their atmospheric concentrations is the main driver for the observed trend in surface temperature. However, our understanding of global sources and sinks of CO2 and CH4 and the coupling with climate change is still insufficient due to limitations in the surface monitoring network.
Satellite remote sensing can provide global and densely sampled observations of CO2 and CH4 which fill the gaps in surface networks and which can help to develop reliable estimates of regional surface fluxes.
However, accurate retrievals of atmospheric CO2 and CH4 columns from passive satellite sensors is a major challenge in the presence of high aerosol load as is often the case in Eastern Asia. Furthermore, the existing validation network TCCON (Total Column Carbon Observing Network) does currently not include any stations in China. Thus, current satellite retrievals are uncertain for this key region.
We will present results for CO2 and CH4 obtained from the Japanese GOSAT satellite from a retrieval algorithm with a new approach to constrain aerosols. Specifically, we use aerosol information from the ECMWF MACC model which has been constraint with MODIS data. We will compare the retrieved CO2 and CH4 columns to ground-station data from Chinese partner to Aeronet aerosol data for China. Finally, we will test model calculations constrained with surface data using the Geos-Chem model and Carbontracker-China.
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Conference: 2016 Dragon 3 Final Results Symposium
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