The Greenhouse gases Observing SATellite (GOSAT) has operated for about seven years since its launch on January 23, 2009. From GOSAT observational data, the column-averaged concentrations of major greenhouse gases (GHGs), namely carbon dioxide (CO₂) and methane (CH₄), were retrieved (precisions: 0.5% and 0.7%, respectively). Using the retrieved concentrations (Level 2 data product), the monthly surface fluxes of CO₂ and CH₄, on sub-continental and ocean-basin scales, were estimated (Level 4 data). The CH₄ flux estimates and the model-simulated three-dimensional GHG distributions for the first four years of GOSAT operation (2009 – 2013) are now available. Also, the CO₂ flux estimates over the same period will soon be available. The Level 2 column concentration data were also utilized to understand GHGs’ temporal and spatial changes. The number of Level 2 data over south eastern Asia and Oceania is not large because of frequent cloud coverage over these regions throughout a year. For increasing the data number, we modified the instrument’s surface scanning patterns to observe locations with high clear-sky probabilities. We will show preliminary results obtained after the scanning pattern modification.

Obtaining quality estimates of surface GHG fluxes for frequently cloud-covered regions in Asia and Oceania only from the satellite GHG data can be quite challenging; thus combined use of GHG data from multiple measurement platforms, which include satellites, ground-based monitoring stations, ships, and aircrafts, is considered to be optimal. We will show a plan of a sample pilot project in Indonesia.

Here, we will present a summary of seven-year-long GHG observation by GOSAT and surface GHG flux estimation, focusing the Asia and Oceania regions. We will also explain the status of  GOSAT data product distribution and a future GOSAT observation plan over Asia and Oceania.

Fossil fuel combustion, deforestation, and other human activities emit ~40 billion tons of carbon dioxide (CO₂) to the atmosphere annually, increasing its burden by 1%/year. Over half of these emissions are removed by poorly understood sinks. Precise space-borne measurements offer a global approach to help better constrain the sources and sinks of atmospheric CO₂.

The 2014 launched Orbiting Carbon Observatory-2 (OCO-2) is the first NASA satellite deployed specifically to measure atmospheric column-averaged CO₂ dry air mole fraction (XCO2) at high enough sensitivity, accuracy, and resolution to globally characterize CO₂ regional sources and sinks.  OCO-2 measures the absorption of reflected sunlight in three bands (0.760μm oxygen A-Band, CO₂ bands near 1.61μm and 2.06μm) at unprecedented spatial resolution.  It collects almost one million soundings each day along a < 10.6 km swath in either nadir or glint mode, yielding up to 25% sufficiently cloud free scenes for precise XCO2estimates. A sounding selection algorithm selects the best 6%, spatially representative data.

Since 2009, the OCO-2 team closely collaborated with the Japanese GOSAT team in calibration, retrieval, and validation of data products against internationally accepted standards. In target mode, thousands of soundings are collected over 23 Total Carbon Column Observing Network (TCCON) stations for validation purposes.  OCO-2 encourages initiatives to establish ground-based validation stations in Asia that follow internationally accepted standards. We are collaborating with the GOSAT-2 team and others to establish the first tropical Asia TCCON station in the Philippines.

Almost 2 years of observations clearly show robust features of the atmospheric carbon cycle, such as the intense northern hemisphere spring drawdown and enhanced CO₂ over regions with intense fossil fuel combustion, such as the east coast of China and the U.S. in the fall and early winter, when the north-south XCO2 gradient is small. OCO-2 data are free to access and use.

The carbon dioxide (CO₂) retrieval algorithm based on optimal estimation method was developed and its performance was analyzed. In sensitivity analysis using simulated radiance spectra at difference surface and atmospheric conditions, the aerosol-related parameters such as total Aerosol Optical Depth (AOD) and aerosol optical properties are the most important factor in CO₂ retrieval, resulting in errors up to 6.5 ppm by inaccurate aerosol optical information. These errors are caused by the simplified aerosol assumptions in the forward model, which only represent a subset of three potential aerosol optical properties, and can be also increased in CO₂ retrieval using real-spectra. As aerosols in the atmosphere are highly variable in their amount, vertical distribution and optical properties, their effect can be under-constrained (Frankenberg et al., 2012). In this study, to reduce the errors caused by the simplified aerosol assumptions, modification of aerosol-related parameters in the forward model have been applied in CO₂retrieval algorithms, presenting by 12 parameters consisting of the vertical profile in terms of central height and width, aerosol size distribution and refractive index parameters as their optical parameters. The CO₂ retrievals with two different approaches in handling aerosol information have been analyzed using the Greenhouse Gases Observing SATellite (GOSAT) spectra over East-Asia and evaluated through the comparison with collocated ground-based observations at several Total Carbon Column Observing Network (TCCON) sites. These results can improve the accuracy of CO₂ retrieval algorithm taking into account aerosol information and provide useful information to reduce uncertainty and increase data availability.

The monitoring of full-column CO2 mixing ratios from space, using measurements of reflected solar radiation in near-IR bands that are sensitive to CO2 all the way to the surface, commenced in 2009 with the launching of the GOSAT satellite and was enhanced in 2014 when the OCO-2 satellite started operations. The spatial and temporal coverage of these data are dense enough to permit the estimation of the surface sources and sinks of CO2 on scales of 100s of km, fine enough to shed light on the processes controlling the amount of anthropogenic CO2 remaining in the atmosphere after the natural sinks take up their share. These processes must be understood better if we are to be able to predict the course of future global warming with the necessary accuracy.

These satellite data are affected by systematic errors, however, that limit their potential if the errors are not carefully identified and removed before the data are used to infer fluxes. Here we examine recent flux inversion results obtained using GOSAT and OCO-2 column CO2 measurements and assess what aspects of the results may be considered robust with respect to these systematic errors. In particular, we consider the constraint on the tropical land biosphere that the satellite data provide: the tropical forests are thought to be key for modulating future climate change, but are currently poorly-observed by in situ measurements -- clouds currently limit the satellites' direct view of these areas, but observations over the tropical oceans may provide useful information. We examine the interannual variability in the global carboncycle observed from space across the past seven years and comment on the response to the recent strong El Nino event that Nature has considerately sent our way.  The benefits of the satellite data are assessed with respect to independent CO2 measurements of high accuracy.

In the context of climate change and global warming, greenhouse gases (GHGs) emission receives a considerable attention. Of many natural GHG sources, wetlands play an important role in modulating the concentrations of GHGs in the atmosphere. To understand the key factors controlling GHGs emission in the temperate wetlands. This study aims to continuously monitoring greenhouse gases (CO₂, CH₄, and N₂O) emitted from a subtropic natural wetland located at the Minjing estuary in the coastal region of southeastern China. A self-designed floating chamber-based sampler was applied to on-site collect GHGs emitted from three different environments (i.e. plants, mudflats, and river water) of the estuary. The concentrations of CO₂, CH₄, and N₂O were further measured with an automated nondispersive infrared (NDIR) continuous GHG monitoring instrument. This study revealed that the emission fluxes of GHGs for three environments were ordered as river water > mudflats > plants. The presence of plants could significantly reduce CH₄ emissions. The ratios of the highest and the lowest GHG emission fluxes fromPhragmites australis varied from 0.09 to 0.14, which were much lower than the ratios observed in the river water, where Phragmites australis emitted greenhouse gases using the convective mechanism.  

After 5 years development, The Chinese carbon dioxide observation satellite (TanSat), the first scientific experimental CO₂ satellite of China, step into the pre-launch phase. The characters of carbon dioxide spectrometer (CDS) and Cloud and Aerosol Polarization  Imager（CAPI）have been optimized during themanufacture. CDS and CAPI have finished laboratory test and calibration. After a series of test and calibration in laboratory, the instrumental performances meet the design requirements. The two scientific satellite payload have been integrated into the satellite system. TanSat will be launched on August 2016.

To speed the scientific application of TanSat observation, the XCO₂ retrieval algorithm has been developed and applied on GOSAT observation to evaluate the performance of algorithm. Validated with TCCON measurements, its product achieves a 1.5 ppm precision. A Chinese carbon cycle data- assimilation system Tan-Tracker is developed based on the atmospheric chemical transport model GEOS-Chem. A validation network has been established around China to support a series of CO₂ satellite of China, which mainly based on IFS-125HR measurements.

Remote sensing of the greenhouse gases has been successfully performed by the Greenhouse Gases Observing SATellite "IBUKI" (GOSAT) which was launched in January 2009. It, for the first time, retrieved the column loading of CO2 and CH4 within the accuracy of 1%. MOEJ, NIES, and JAXA are now planning the follow-on mission GOSAT2, to carry FTS2 and CAI2, which are improved versions of the Fourier transform spectrometer, TANSO-FTS, and Cloud and Aerosol Imager (CAI) on board the GOSAT satellite. Enhanced sensitivity and an intelligent pointing mechanism of FTS2 makes the GOSAT2 have more observations of greenhouse gases. The CAI2 is also enhanced with a two viewing geometry and 8 wavelength bands including 340nm and 380nm which are effective to detect anthropogenic aerosols, which is added as one of the GOSAT mission objectives. We like to introduce the current status of the GOSAT2 mission and to discuss the future greenhouse gases measurement strategy in collaboration with other greenhouse gas measurement satellites.

Point sources of carbon dioxide (CO₂) are localized emission features covering spatial domains of less than 50 km diameter, including cities and transportation networks, and fossil fuel production, upgrading and distribution infrastructure. Anthropogenic CO₂ sources increasingly upset the natural balance between natural carbon sources and sinks resulting in an atmospheric CO₂ growth of about 1% per year. Mitigation of resulting climate change impacts requires management of these emissions, which itself requires monitoring data in sufficient temporal and spatial resolution at global coverage. Space-borne measurements offer opportunities to detect, quantify, and analyze small scale and point source emissions anywhere on Earth.

NASA’s first satellite dedicated to atmospheric CO₂ observation, the Orbiting Carbon Observatory (OCO-2), launched in July 2014 and now leads the afternoon constellation of satellites (A-Train). It has a continuous swath of > 10 km in width and eight footprints across which can cross-cut coincident emission plumes to provide momentary plume cross sections. OCO-2 data demonstrate that we can detect localized source signals in the form of urban total column averaged CO₂ enhancements of ~2 ppm against suburban and rural backgrounds. In addition, OCO-2’s multi-sounding swath observing geometry can reveal intra-urban spatial structures reflected in XCO2 data, previously unobserved from space. Compared to single-shot GOSAT soundings which detected urban/rural differences (Kort et al., 2012) in Megacities, the OCO-2 swath geometry opens up the path to future capabilities enabling urban tomography of greenhouse gases using to hundreds of soundings over a city at each satellite overpass.

For singular point sources like volcanoes and coal fired power plants, we have developed data discovery tools as well as a proxy detection method for plumes using SO₂-sensitive TIR imaging spectrometers (ASTER). This approach offers a path toward automating plume detections with subsequent matching and mining of OCO-2 data, for enhanced detection efficiency and validation.

We introduced a dual-THz-band SIS (Superconductor- Insulator-Superconductor) heterodyne radiometer system which is under developing for the atmospheric profiling synthetic observation system project (APSOS). This THz system is intended to have a durable and compact design to meet the challenging requirements of remote operation at Tibetan Plateau. The system as well as its major components such as antenna tipping, quasi-optics, cryogenics, SIS mixers and FFTS backend will be discussed thoroughly. Some scientific simulation focusing on the atmospheric profiling components at THz bands will also be investigated.

We compare model-derived global atmospheric concentrations of greenhouse gases CO₂ and CH₄ with satellite-obtained column-averaged concentrations XCO₂ and XCH₄. These concentrations are simulated with the atmospheric chemical transport model (ACTM) based on the Center for Climate System Research/National Institute for Environmental Studies/Frontier Research Center for Global Change (CCSR/NIES/FRCGC) atmospheric general circulation model (AGCM) [Numaguti et al., 1995]. The model spatial resolutions are horizontally T42 and T106 truncation and vertically 32 levels up to 7 hPa. We also implement the stratospheric correction to these ACTM simulations of CO₂ and CH₄ that yields age-corrected model distributions [Ostler et.al., 2015], because trends in stratospheric age are not considered [Engel et al., 2009; Mahieu et al.,2014]. The results from the ACTM simulations are compared with observational data of the GOSAT and OCO-2 retrievals. Both XCO₂ and XCH₄ concentrations are retrieved from GOSAT soundings using the RemoTec algorithm [Butz et al., 2009] and from OCO-2 using ACOS algorithm [Crisp et. al., 2012]. We also compare the results with the ground-based observational data of the Total Carbon Column Observing Network (TCCON) retrievals. We show that the model captures observed trend, seasonal cycles and interhemispheric gradients at most sampled locations. The model-observation agreements are best for CO₂, because the simulation uses fossil fuel inventories and an inverse model estimate of non-fossil fuel fluxes. A correlation between the simulated and observed columns depends on the various types of the model horizontal resolutions. The correlation of CH₄, particularly at tropical and extratropical sites, has been attributed to the uncertainties in surface emissions and loss by hydroxyl radicals. The transport processes in troposphere and stratosphere are represented by a comparison between the model-observation agreements with and without the age correction.