Abstract
TanSat is the 1st Chinese carbon dioxide (CO2) measurement satellite, launched in 2016. In this study, the University of Leicester Full Physics (UoL‐FP) algorithm is implemented for TanSat nadir mode XCO2 retrievals. We develop a spectrum correction method to reduce the retrieval errors by the online fitting of an 8th order Fourier series. The spectrum‐correction model and its a priori parameters are developed by analyzing the solar calibration measurement. This correction provides a significant improvement to the O2 A band retrieval. Accordingly, we extend the previous TanSat single CO2 weak band retrieval to a combined O2 A and CO2 weak band retrieval. A Genetic Algorithm (GA) has been applied to determine the threshold values of post‐screening filters. In total, 18.3% of the retrieved data is identified as high quality compared to the original measurements. The same quality control parameters have been used in a footprint independent multiple linear regression bias correction due to the strong correlation with the XCO2 retrieval error. Twenty sites of the Total Column Carbon Observing Network (TCCON) have been selected to validate our new approach for the TanSat XCO2 retrieval. We show that our new approach produces a significant improvement on the XCO2 retrieval accuracy and precision when compared to TCCON with an average bias and RMSE of −0.08 ppm and 1.47 ppm, respectively. The methods used in this study can help to improve the XCO2 retrieval from TanSat and subsequently the Level‐2 data production, and hence will be applied in the TanSat operational XCO2 processing.
Highlights
Carbon Dioxide (CO2) has been recognized as the most important greenhouse gases causing climate change due to the rise in anthropogenic emissions since the industrial revolution
Accurate measurement of atmospheric CO2 in order to reduce the uncertainties of CO2 fluxes is a key requirement for meeting the “measurable, reportable and verifiable” mitigation commitments of the United Nations Framework Convention on Climate Change (UNFCCC) that is aimed at avoiding disastrous consequences caused by climate change
The University of Leicester Full Physics (UoL‐FP) is an XCO2 retrieval algorithm based on the Optimal Estimation Method (OEM) that has been originally developed for the NASA Orbiting Carbon Observatory (OCO) mission (Bösch et al, 2006), and has been extensively used for XCO2 retrievals from Gases Observing Satellite (GOSAT) (Cogan et al, 2012)
Summary
Carbon Dioxide (CO2) has been recognized as the most important greenhouse gases causing climate change due to the rise in anthropogenic emissions since the industrial revolution. The European Space Agency (ESA) SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) (Bovensmann et al, 1999) on board the ENVIronmental SATellite (ENVISAT) that launched in 2002 and operated until 2012, was the first space‐borne instrument to provide SWIR hyperspectral measurements of CO2 (Bösch et al, 2006; Buchwitz et al, 2005; Heymann et al, 2015; Reuter et al, 2011), followed by the Greenhouse Gases Observing Satellite (GOSAT) from Japan (Kuze et al, 2009) and the Orbiting Carbon Observatory‐2 (OCO‐2) from the U.S (Crisp et al, 2008), launched in 2009 and 2014, respectively These missions have significantly contributed to the effort to obtain global CO2 measurements from space (Eldering, O’Dell, et al, 2017; Yokota et al, 2009) and subsequently for carbon flux studies (Eldering, Wennberg, et al, 2017; Feng et al, 2017; Hakkarainen et al, 2016, 2019; Maksyutov et al, 2013; Yang et al, 2017).
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