Carbon dioxide retrieval from OCO-2 satellite observations using the RemoTeC algorithm and validation with TCCON measurements

Wu, Lianghai; Hasekamp, Otto; Hu, Haili; Landgraf, Jochen; Butz, A.; Brugh, Joost aan de; Aben, I.; Pollard, David F.; Griffith, David; Feist, Dietrich G.; Koshelev, Dmitry; Hase, Frank; Toon, G. C.; Ohyama, Hirofumi; Morino, Isamu; Notholt, Justus; Shiomi, Kei; Iraci, L. T.; Schneider, Mat­thias; Mazière, Martine De; Sussmann, Ralf; Kivi, Rigel; Warneke, Thorsten; Goo, Tae‐Young; Té, Yao

doi:10.5194/amt-11-3111-2018

Cited by 60 publications

(55 citation statements)

References 96 publications

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“…Accurate determination of XCO2 from simultaneous three-band retrieval has been demonstrated with measurements from OCO-2 and GOSAT [e.g. [16]]. Observations of the oxygen (O2) A-band in the NIR spectral region are required to determine the effective light propagation in the radiative transfer model used in the retrieval algorithm, making use of the known concentration of the well-mixed oxygen.…”

Section: Spectral Requirements For Xco2 Observationsmentioning

confidence: 99%

The European CO2 Monitoring Mission: observing anthropogenic greenhouse gas emissions from space

Sierk

Bézy

Löscher

et al. 2019

International Conference on Space Optics — ICSO 2018

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Responding to plans of the European Commission for extending the observation capabilities of the Copernicus programme, the European Space Agency (ESA) has initiated Phase A industrial (technical feasibility) studies for several new space-borne Earth Observation missions. High priority is given to a constellation of LEO satellites in Sunsynchronous orbit with the purpose of observing anthropogenic carbon dioxide (CO2) emissions [European Commission, 2017]. The observing system shall acquire images of CO2 concentration in terms of dry air column-averaged mole fractions (XCO2), providing complete global land coverage at high spatial resolution (4 km 2 ) within five days. The demanding requirements call for a payload comprising a combination of multiple instruments, which perform simultaneous measurements. The XCO2 is inferred from reflectance measurements in the Near-Infrared (NIR) and Short-Wave Infrared spectral regions (SWIR). This requires at least three spatially co-registered push-broom imaging spectrometers, measuring spectral radiance and solar irradiance in the NIR (747-773 nm), SWIR-1 (1595-1675 nm) and SWIR-2 (1990SWIR-2 ( -2095 at moderate spectral resolving power (R~5000-7000). In addition, the observations for CO2 concentration will be complemented by Differential Optical Absorption Spectroscopy (DOAS) measurements of nitrogen dioxide (NO2) over the same area. The NO2 measurements in the visible region (400-500 nm) are expected to serve as a tracer for plumes of high CO2 concentration resulting from high temperature combustion, which will facilitate plume identification and mapping. The third component of the payload is a multiple-angle polarimeter (MAP), performing high-precision measurements of aerosol (and cloud) properties. Its measurements of polarized radiance under various observation angles are expected to reduce XCO2 bias error and significantly increase the yield of useful retrievals from the NIR and SWIR spectra. The complex observation architecture, involving multiple instruments and platforms, call for optimized observational requirements, driven by the primary goal of detecting and quantifying point-sources of greenhouse gas emissions. In particular, high single-sounding precision is essential for identifying plumes of elevated CO2 concentration from instantaneous image acquisitions without regional and temporal averaging. This translates into stringent requirements for Signal-to-noise ratio (SNR), as well as spatial co-registration and spectral stability, which drive the instrument design. The presentation will introduce the different elements of the candidate Copernicus mission, in view of the ambitious mission goals. The payload components and observation requirements are addressed with special emphasis on the derivation of the SNR and spectral resolution requirements, which determine the instrument sizing.

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Section: Spectral Requirements For Xco2 Observationsmentioning

confidence: 99%

The European CO2 Monitoring Mission: observing anthropogenic greenhouse gas emissions from space

Sierk

Bézy

Löscher

et al. 2019

International Conference on Space Optics — ICSO 2018

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“…We use the RemoTeC retrieval algorithm (Hasekamp and Butz, 2008;Butz et al, 2009), which has been extensively used for greenhouse gas retrievals from satellite observations like GOSAT, OCO-2 and S5P measurements (Butz et al, 2011;Schepers 30 et al, 2012;Guerlet et al, 2013;Hu et al, 2016;Wu et al, 2018;Hu et al, 2018). The adaptations and first use for OCO-2 measurements are described in Wu et al (2018). There we employed the three-band XCO 2 retrievals which will be used here as a reference to compare against our XCO 2 retrievals from the 2.06 µm band.…”

Section: Retrieval Algorithm and Methodologymentioning

confidence: 99%

“…We do not retrieve the dry air column but compute it using the ECMWF meteorological data. As described in Wu et al (2018), we use a Lambertian reflection model for land surface reflection properties and for ocean surfaces a windspeed driven reflection model of Cox and Munk (1954) combined with an additive wavelength-dependent Lambertian term.…”

Section: Retrieval Algorithm and Methodologymentioning

confidence: 99%

“…In the retrieval, we seek 15 the state vector for which a cost function including the difference between the forward model and measurements and a side constraint is minimized. The same Phillips-Tikhonov regularization scheme as employed in the three-band retrieval is used to solve the minimization problem iteratively (Phillips, 1962;Tikhonov, 1963;Hasekamp and Landgraf, 2005;Wu et al, 2018).…”

Section: Retrieval Algorithm and Methodologymentioning

confidence: 99%

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Full-physics carbon dioxide retrievals from the OCO-2 satellite by only using the 2.06 μm band

Hasekamp

et al. 2019

Preprint

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Abstract. Passive remote sensing of atmospheric carbon dioxide uses spectroscopic measurements of sunlight back-scattered by the Earth's surface and atmosphere. The current state-of-the-art retrieval methods use three different spectral bands, the oxygen A band at 0.76 μm and the weak and strong CO2 absorption bands at 1.61 and 2.06 μm, respectively, to infer information on light scattering and the carbon dioxide column-averaged dry-air mole fraction XCO2. In this study, we propose a one-band XCO2 retrieval technique which uses only the 2.06 μm band measurements from the OCO-2 satellite. We examine the data quality by comparing the OCO-2 XCO2 with collocated ground based measurements from the Total Carbon Column Observing Network (TCCON). Over land and ocean the OCO-2 one-band retrieval shows differences to TCCON observations with a standard deviation of ~ 1.30 ppm and a station-to-station variability of ~ 0.50 ppm. Moreover, we compare one-band and three-band retrievals over Europe,the Middle East and Africa region and see high correlation between the two retrievals with a SD of 0.93 ppm. Compared to the three-band retrievals, using only the 2.06 μm band similar XCO2 retrieval accuracy and precision can be obtained while retaining a similar data yield.

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“…Aside from the sunlight, climates and ecosystems at high latitudes are highly seasonally dependent, so there are a number of seasonal parameters that may produce time-dependent biases at high latitudes if they are not handled properly in retrieval algorithms. In particular, Wu et al (2018) noted time dependent biases at Sodankylä with the RemoTeC/OCO-2 20 retrieval algorithm. Wunch et al (2017b) suggests that there are not enough passable retrievals from ACOS B7 to identify seasonal bias at high latitudes.…”

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confidence: 99%

Quality controls, bias, and seasonality of CO<sub>2</sub> columns in the Boreal Forest with OCO-2, TCCON, and EM27/SUN measurements

Jacobs

Simpson

Wunch

et al. 2020

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Abstract. Seasonal CO2 exchange in the Boreal Forest plays an important role in the global carbon budget and in driving interannual variability in seasonal cycles of atmospheric CO2. Satellite-based observations from polar orbiting satellites like the Orbiting Carbon Observatory-2 (OCO-2) offer an opportunity to characterize Boreal Forest seasonal cycles across longitudes with a spatially and temporally rich dataset, but data quality controls and biases still require vetting at high latitudes. With the objective of improving data availability at northern, terrestrial high latitudes, this study evaluates quality control methods and biases of OCO-2 retrievals of atmospheric column-averaged dry-air mole fractions of CO2 (XCO2) in Boreal Forest regions. In addition to the standard quality control filters recommended for ACOS B8 (B8 QC) and ACOS B9 (B9 QC) OCO-2 retrievals, a third set of quality control filters were specifically tailored to Boreal Forest observations (Boreal QC) with the goal of increasing data availability at high latitudes without sacrificing data quality. Ground-based reference measurements of XCO2 include observations from two sites in the Total Carbon Column Observing Network (TCCON) at East Trout Lake, Saskatchewan, Canada and Sodankylä, Finland. OCO-2 retrievals were also compared to ground-based observations from two Bruker EM27/SUN FTS at Fairbanks, Alaska, United States. EM27/SUN spectrometers that were deployed in Fairbanks were carefully monitored for instrument performance and were bias corrected to TCCON using observations at the Caltech TCCON site. The B9 QC were found to pass approximately twice as many OCO-2 retrievals over land north of 50° N than the B8 QC, and the Boreal QC were found to pass approximately twice as many retrievals in May, August, and September as the B9 QC. While Boreal QC results in a substantial increase in passable retrievals this is accompanied by increases in the standard deviations in biases at Boreal Forest sites from ∼ 1.4 ppm with B9 QC to ∼ 1.6 ppm with Boreal QC. Total average biases for coincident OCO-2 retrievals at the three sites considered did not consistently increase or decrease with different QC methods, and instead responses to changes in QC varied according to site and satellite viewing geometries. Regardless of the quality control method used, seasonal variability in biases was observed, and this variability was more pronounced at the TCCON sites than when comparing to EM27/SUN observations in Fairbanks. Monthly average biases generally varied between −1 ppm and +1 ppm at the three sites considered, with more negative biases in spring (MAM) and autumn (SO), but more positive biases in summer months (JJA). Monthly standard deviations in biases ranged from approximately 1.0 ppm to 2.0 ppm and do not exhibit strong seasonal dependence apart from exceptionally high standard deviation observed with all three QC methods at Sodankylä in June. There was no evidence found to suggest that seasonal variability in bias is a direct result of airmass dependence in ground-based retrievals or of proximity bias from coincidence criteria, but there were a number of retrieval parameters used as quality control filters that exhibit seasonality and could contribute to seasonal dependence in OCO-2 bias. Furthermore, it was found that OCO-2 retrievals of XCO2 without the standard OCO-2 bias correction exhibit almost no perceptible seasonal dependence in average monthly bias at these Boreal Forest sites, suggesting that seasonal variability in bias is introduced by the bias correction. Overall, we found that modified quality controls can allow for significant increases in passable OCO-2 retrievals with only marginal compromises in data quality, but seasonal dependence in biases still warrants further exploration.

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Carbon dioxide retrieval from OCO-2 satellite observations using the RemoTeC algorithm and validation with TCCON measurements

Cited by 60 publications

References 96 publications

The European CO2 Monitoring Mission: observing anthropogenic greenhouse gas emissions from space

The European CO2 Monitoring Mission: observing anthropogenic greenhouse gas emissions from space

Full-physics carbon dioxide retrievals from the OCO-2 satellite by only using the 2.06 μm band

Quality controls, bias, and seasonality of CO<sub>2</sub> columns in the Boreal Forest with OCO-2, TCCON, and EM27/SUN measurements

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Carbon dioxide retrieval from OCO-2 satellite observations using the RemoTeC algorithm and validation with TCCON measurements

Cited by 60 publications

References 96 publications

The European CO2 Monitoring Mission: observing anthropogenic greenhouse gas emissions from space

The European CO2 Monitoring Mission: observing anthropogenic greenhouse gas emissions from space

Full-physics carbon dioxide retrievals from the OCO-2 satellite by only using the 2.06 μm band

Quality controls, bias, and seasonality of CO&lt;sub&gt;2&lt;/sub&gt; columns in the Boreal Forest with OCO-2, TCCON, and EM27/SUN measurements

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Quality controls, bias, and seasonality of CO<sub>2</sub> columns in the Boreal Forest with OCO-2, TCCON, and EM27/SUN measurements