Laboratory spectral calibration of TanSat and the influence of multiplex merging of pixels

Zhang, Hang; Zheng, Yufang; Lin, Chao; Wang, Wenquan; Wang, Qian; Li, Shuai

doi:10.1080/01431161.2017.1306142

Cited by 8 publications

(5 citation statements)

References 25 publications

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“…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 CO 2 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(Chen et al, , 2017bWang et al, 2017).…”

Section: The Need For Global Carbon Monitoring From Space and The Tanmentioning

confidence: 99%

First Global Carbon Dioxide Maps Produced from TanSat Measurements

et al. 2018

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Section: The Need For Global Carbon Monitoring From Space and The Tanmentioning

confidence: 99%

First Global Carbon Dioxide Maps Produced from TanSat Measurements

et al. 2018

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“…In the forward model, an ILS function is needed to convolve the simulated spectrum. For details regarding the radiometric calibration of TanSat, please refer to [37,38]. For XCO 2 retrieval, the ILS information for each footprint can be obtained individually from the corresponding fields of the TanSat L1B data.…”

Section: Information Extraction From Tansat L1bmentioning

confidence: 99%

Retrieval and Validation of XCO2 from TanSat Target Mode Observations in Beijing

et al. 2020

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Satellite observation is one of the main methods used to monitor the global distribution and variation of atmospheric carbon dioxide (CO2). Several CO2 monitoring satellites have been successfully launched, including Japan’s Greenhouse Gases Observing SATellite (GOSAT), the USA’s Orbiting Carbon Observatory-2 (OCO-2), and China’s Carbon Dioxide Observation Satellite Mission (TanSat). Satellite observation targeting the ground-based Fourier transform spectrometer (FTS) station is the most effective technique for validating satellite CO2 measurement precision. In this study, the coincident observations from TanSat and ground-based FTS were performed numerous times in Beijing under a clear sky. The column-averaged dry-air mole fraction of carbon dioxide (XCO2) obtained from TanSat was retrieved by the Department for Eco-Environmental Informatics (DEEI) of China’s State Key Laboratory of Resources and Environmental Information System based on a full physical model. The comparison and validation of the TanSat target mode observations revealed that the average of the XCO2 bias between TanSat retrievals and ground-based FTS measurements was 2.62 ppm, with a standard deviation (SD) of the mean difference of 1.41 ppm, which met the accuracy standard of 1% required by the mission tasks. With bias correction, the mean absolute error (MAE) improved to 1.11 ppm and the SD of the mean difference fell to 1.35 ppm. We compared simultaneous observations from GOSAT and OCO-2 Level 2 (L2) bias-corrected products within a ±1° latitude and longitude box centered at the ground-based FTS station in Beijing. The results indicated that measurements from GOSAT and OCO-2 were 1.8 ppm and 1.76 ppm higher than the FTS measurements on 20 June 2018, on which the daily observation bias of the TanSat XOC2 results was 1.87 ppm. These validation efforts have proven that TanSat can measure XCO2 effectively. In addition, the DEEI-retrieved XCO2 results agreed well with measurements from GOSAT, OCO-2, and the Beijing ground-based FTS.

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“…In July 2014, NASA launched the Orbiting Carbon Observatory-2 (OCO-2), which started to provide XCO 2 data products with high quality to the public [8,9]. The Chinese carbon dioxide observation satellite mission (TanSat) began in 2010 and was launched on 22 December 2016 [10][11][12]. Recent studies have released preliminary XCO 2 maps produced from TanSat measurements [13].…”

Section: Introductionmentioning

confidence: 99%

“…f iso (λ), k 1 (λ) and k 2 (λ) represent amplitude factors for the Lambertian, Ross-thick and Li-sparse kernels, respectively. Details of the BRDF equation may be found in Equation(12) in[20] 2. The value left of the symbol "/" is for vegetation surface and the right value is for soil…”

mentioning

confidence: 99%

A Theoretical Analysis for Improving Aerosol-Induced CO2 Retrieval Uncertainties Over Land Based on TanSat Nadir Observations Under Clear Sky Conditions

et al. 2019

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Aerosols significantly affect carbon dioxide (CO2) retrieval accuracy and precision by modifying the light path. Hyperspectral measurements in the near infrared and shortwave infrared (NIR/SWIR) bands from the generation of new greenhouse gas satellites (e.g., the Chinese Global Carbon Dioxide Monitoring Scientific Experimental Satellite, TanSat) contain aerosol information for correction of scattering effects in the retrieval. Herein, a new approach is proposed for optimizing the aerosol model used in the TanSat CO2 retrieval algorithm to reduce CO2 uncertainties associated with aerosols. The weighting functions of hyperspectral observations with respect to elements in the state vector are simulated by a forward radiative transfer model. Using the optimal estimation method (OEM), the information content and each component of the CO2 column-averaged dry-air mole fraction (XCO2) retrieval errors from the TanSat simulations are calculated for typical aerosols which are described by Aerosol Robotic Network (AERONET) inversion products at selected sites based on the a priori and measurement assumptions. The results indicate that the size distribution parameters (reff, veff), real refractive index coefficient of fine mode (arf) and fine mode fraction (fmf) dominate the interference errors, with each causing 0.2–0.8 ppm of XCO2 errors. Given that only 4–7 degrees of freedom for signal (DFS) of aerosols can be obtained simultaneously and CO2 information decreases as more aerosol parameters are retrieved, four to seven aerosol parameters are suggested as the most appropriate for inclusion in CO2 retrieval. Focusing on only aerosol-induced XCO2 errors, forward model parameter errors, rather than interference errors, are dominant. A comparison of these errors across different aerosol parameter combination groups reveals that fewer aerosol-induced XCO2 errors are found when retrieving seven aerosol parameters. Therefore, the model selected as the optimal aerosol model includes aerosol optical depth (AOD), peak height of aerosol profile (Hp), width of aerosol profile (Hw), effective variance of fine mode aerosol (vefff), effective radius of coarse mode aerosol (reffc), coefficient a of the real part of the refractive index for the fine mode and coarse mode (arf and arc), with the lowest error of less than 1.7 ppm for all aerosol and surface types. For marine aerosols, only five parameters (AOD, Hp, Hw, reffc and arc) are recommended for the low aerosol information. This optimal aerosol model therefore offers a theoretical foundation for improving CO2 retrieval precision from real TanSat observations in the future.

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Laboratory spectral calibration of TanSat and the influence of multiplex merging of pixels

Cited by 8 publications

References 25 publications

First Global Carbon Dioxide Maps Produced from TanSat Measurements

First Global Carbon Dioxide Maps Produced from TanSat Measurements

Retrieval and Validation of XCO2 from TanSat Target Mode Observations in Beijing

A Theoretical Analysis for Improving Aerosol-Induced CO2 Retrieval Uncertainties Over Land Based on TanSat Nadir Observations Under Clear Sky Conditions

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