First Global Carbon Dioxide Maps Produced from TanSat Measurements

Global warming is a major problem, for which carbon dioxide (CO2) is the main greenhouse gas involved in heating the troposphere. However, the poor availability of global CO2 measurements makes it difficult to estimate CO2 emissions accurately. Satellite measurements would be very helpful for understanding the global CO2 flux distribution if the CO2 column-averaged dry-air mole fraction (XCO2) could be measured with a precision of 1–2 ppm (Baker et al., 2010). The Greenhouse Gases Observing Satellite (GOSAT) (Yokota et al., 2009; Yoshida et al., 2013; Kuze et al., 2014) was launched in 2009, followed by the Orbiting Carbon Observatory 2 (OCO-2) (Eldering et al., 2016; Crisp et al., 2017; Bösch et al., 2011) in 2014. Tansat, a Chinese Earth observation satellite dedicated to monitoring CO2, was launched in December 2016 and is the third satellite capable of monitoring greenhouse gases by hyper-spectral nearinfrared/shortwave infrared (NIR/ SWIR) measurement. The TanSat mission was supported by the Ministry of Science and Technology of China, the Chinese Academy of Sciences, and the China Meteorological Administration. TanSat is an agile, sun-synchronous satellite that operates in three observation modes—namely, the nadir, sun-glint, and target modes. The line of sight tracks the principal plain in nadir mode and the glint in sun-glint mode, which increases the incident signal level and guarantees high performance of the charge-coupled device (Liu et al., 2013a; Cai et al., 2014). The Atmospheric Carbon dioxide Grating Spectroradiometer (ACGS) was designed to measure near-infrared/shortwave infrared backscattered sunlight in the molecular oxygen A-band (0.76 μm) and two CO2 bands (1.61 and 2.06 μm) (Wang et al., 2014; Li et al., 2017; Zhang et al., 2017). The Cloud and Aerosol Polarization Imager (CAPI) measures in ultraviolet, visible, and NIR regions to improve the information on aerosol optical properties and the cloud mask for the CDS measurements (Chen et al., 2017a, 2017b; Wang et al., 2017).

[1]  Huifang Zhang,et al.  Monitoring carbon dioxide from space: Retrieval algorithm and flux inversion based on GOSAT data and using CarbonTracker-China , 2017, Advances in Atmospheric Sciences.

[2]  Hang Zhang,et al.  Laboratory spectral calibration of TanSat and the influence of multiplex merging of pixels , 2017 .

[3]  Yi Liu,et al.  Optimization of the instrument configuration for TanSat CO 2 spectrometer , 2013 .

[4]  David Crisp,et al.  The on-orbit performance of the Orbiting Carbon Observatory-2 (OCO-2) instrument and its radiometrically calibrated products , 2016 .

[5]  David Crisp,et al.  Long-Term Vicarious Calibration of GOSAT Short-Wave Sensors: Techniques for Error Reduction and New Estimates of Radiometric Degradation Factors , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[6]  Yi Liu,et al.  Analysis of XCO2 retrieval sensitivity using simulated Chinese Carbon Satellite (TanSat) measurements , 2013, Science China Earth Sciences.

[7]  Gao Minghui,et al.  Prelaunch spectral calibration of a carbon dioxide spectrometer , 2017 .

[8]  Hartmut Boesch,et al.  Global Characterization of CO2 Column Retrievals from Shortwave-Infrared Satellite Observations of the Orbiting Carbon Observatory-2 Mission , 2011, Remote. Sens..

[9]  S. Dance,et al.  Estimating surface CO2 fluxes from space-borne CO2 dry air mole fraction observations using an ensemble Kalman Filter , 2009 .

[10]  Tatsuya Yokota,et al.  Improvement of the retrieval algorithm for GOSAT SWIR XCO2 and XCH4 and their validation using TCCON data , 2013 .

[11]  Scott C. Doney,et al.  Carbon source/sink information provided by column CO 2 measurements from the Orbiting Carbon Observatory , 2008 .

[12]  Liang Feng,et al.  Angular dependence of aerosol information content in CAPI/TanSat observation over land: Effect of polarization and synergy with A-train satellites , 2017 .

[13]  Dongxu Yang,et al.  Aerosol Retrieval Sensitivity and Error Analysis for the Cloud and Aerosol Polarimetric Imager on Board TanSat: The Effect of Multi-Angle Measurement , 2017, Remote. Sens..

[14]  Yi Liu,et al.  A retrieval algorithm for TanSat XCO2 observation: Retrieval experiments using GOSAT data , 2013 .

[15]  Tatsuya Yokota,et al.  Global Concentrations of CO2 and CH4 Retrieved from GOSAT: First Preliminary Results , 2009 .

[16]  Jing Wang,et al.  An advanced carbon dioxide retrieval algorithm for satellite measurements and its application to GOSAT observations , 2015 .

[17]  Rebecca Castano,et al.  The Orbiting Carbon Observatory-2: first 18 months of science data products , 2016 .

[18]  Hongjie Fan,et al.  A cloud detection scheme for the Chinese Carbon Dioxide Observation Satellite (TANSAT) , 2016, Advances in Atmospheric Sciences.

[19]  Q. Wang,et al.  Spectral parameters and signal-to-noise ratio requirement for TANSAT hyper spectral sensor to measure atmospheric CO2 , 2016 .

[20]  Sarah L. Dance,et al.  Estimating surface CO 2 fluxes from space-borne CO 2 dry air mole fraction observations using an ensemble Kalman Filter , 2008 .

[21]  Qian Wang,et al.  Spectral parameters and signal-to-noise ratio requirement for TANSAT hyper spectral remote sensor of atmospheric CO2 , 2014, Asia-Pacific Environmental Remote Sensing.