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  • 1
    In: Atmospheric Measurement Techniques, Copernicus GmbH, Vol. 9, No. 8 ( 2016-08-01), p. 3491-3512
    Abstract: Abstract. We describe a method for removing systematic biases of column-averaged dry air mole fractions of CO2 (XCO2) and CH4 (XCH4) derived from short-wavelength infrared (SWIR) spectra of the Greenhouse gases Observing SATellite (GOSAT). We conduct correlation analyses between the GOSAT biases and simultaneously retrieved auxiliary parameters. We use these correlations to bias correct the GOSAT data, removing these spurious correlations. Data from the Total Carbon Column Observing Network (TCCON) were used as reference values for this regression analysis. To evaluate the effectiveness of this correction method, the uncorrected/corrected GOSAT data were compared to independent XCO2 and XCH4 data derived from aircraft measurements taken for the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project, the National Oceanic and Atmospheric Administration (NOAA), the US Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the Japan Meteorological Agency (JMA), the HIAPER Pole-to-Pole observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. These comparisons demonstrate that the empirically derived bias correction improves the agreement between GOSAT XCO2/XCH4 and the aircraft data. Finally, we present spatial distributions and temporal variations of the derived GOSAT biases.
    Type of Medium: Online Resource
    ISSN: 1867-8548
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2016
    detail.hit.zdb_id: 2505596-3
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  • 2
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 19, No. 10 ( 2019-05-27), p. 7073-7103
    Abstract: Abstract. To investigate the seasonal characteristics of trace gas distributions in the extratropical upper troposphere and lower stratosphere (ExUTLS) as well as stratosphere–troposphere exchange processes, origin fractions of air masses originating in the stratosphere, tropical troposphere, midlatitude lower troposphere (LT), and high-latitude LT in the ExUTLS are estimated using 10-year backward trajectories calculated with European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim data as the meteorological input. Time series of trace gases obtained from ground-based and airborne observations are incorporated into the trajectories, thus reconstructing spatiotemporal distributions of trace gases in the ExUTLS. The reconstructed tracer distributions are analyzed with the origin fractions and the stratospheric age of air (AoA) estimated using the backward trajectories. The reconstructed distributions of SF6 and CO2 in the ExUTLS are linearly correlated with those of AoA because of their chemically passive behavior and quasi-stable increasing trends in the troposphere. Distributions of CH4, N2O, and CO are controlled primarily by chemical decay along the transport path from the source region via the stratosphere and subsequent mixing of such stratospheric air masses with tropospheric air masses in the ExUTLS.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2019
    detail.hit.zdb_id: 2092549-9
    detail.hit.zdb_id: 2069847-1
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  • 3
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 22, No. 10 ( 2022-05-31), p. 6953-6970
    Abstract: Abstract. We analyzed air samples collected on board a C-130 cargo aircraft over the western North Pacific from May 2012 to March 2020 for atmospheric δ(O2 / N2) and CO2 amount fraction. Observations were corrected for significant artificial fractionation of O2 and N2 caused by thermal diffusion during the air sample collection using the simultaneously measured δ(Ar / N2). The observed seasonal cycles of the δ(O2 / N2) and atmospheric potential oxygen (δ(APO)) varied nearly in opposite phase to the cycle of the CO2 amount fraction at all latitudes and altitudes. Seasonal amplitudes of δ(APO) decreased with latitude from 34 to 25∘ N, as well as with increasing altitude from the surface to 6 km by 50 %–70 %, while those of the CO2 amount fraction decreased by less than 20 %. By comparing the observed values with the simulated δ(APO) and CO2 amount fraction values generated by an atmospheric transport model, we found that the seasonal δ(APO) cycle in the middle troposphere was modified significantly by a combination of the northern and southern hemispheric seasonal cycles due to the interhemispheric mixing of air. The simulated δ(APO) underestimated the observed interannual variation in δ(APO) significantly, probably due to the interannual variation in the annual mean air–sea O2 flux. Interannual variation in δ(APO) driven by the net marine biological activities, obtained by subtracting the assumed solubility-driven component of δ(APO) from the total variation, indicated a clear influence on annual net sea–air marine biological O2 flux during El Niño and net air–sea flux during La Niña. By analyzing the observed secular trends of δ(O2 / N2) and the CO2 amount fraction, global average terrestrial biospheric and oceanic CO2 uptakes for the period 2012–2019 were estimated to be (1.8±0.9) and (2.8±0.6) Pg a−1 (C equivalents), respectively.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2022
    detail.hit.zdb_id: 2092549-9
    detail.hit.zdb_id: 2069847-1
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  • 4
    In: Geoscientific Model Development, Copernicus GmbH, Vol. 10, No. 3 ( 2017-03-17), p. 1157-1174
    Abstract: Abstract. A four-dimensional variational (4D-Var) method is a popular algorithm for inverting atmospheric greenhouse gas (GHG) measurements. In order to meet the computationally intense 4D-Var iterative calculation, offline forward and adjoint transport models are developed based on the Nonhydrostatic ICosahedral Atmospheric Model (NICAM). By introducing flexibility into the temporal resolution of the input meteorological data, the forward model developed in this study is not only computationally efficient, it is also found to nearly match the transport performance of the online model. In a transport simulation of atmospheric carbon dioxide (CO2), the data-thinning error (error resulting from reduction in the time resolution of the meteorological data used to drive the offline transport model) is minimized by employing high temporal resolution data of the vertical diffusion coefficient; with a low 6-hourly temporal resolution, significant concentration biases near the surface are introduced. The new adjoint model can be run in discrete or continuous adjoint mode for the advection process. The discrete adjoint is characterized by perfect adjoint relationship with the forward model that switches off the flux limiter, while the continuous adjoint is characterized by an imperfect but reasonable adjoint relationship with its corresponding forward model. In the latter case, both the forward and adjoint models use the flux limiter to ensure the monotonicity of tracer concentrations and sensitivities. Trajectory analysis for high CO2 concentration events are performed to test adjoint sensitivities. We also demonstrate the potential usefulness of our adjoint model for diagnosing tracer transport. Both the offline forward and adjoint models have computational efficiency about 10 times higher than the online model. A description of our new 4D-Var system that includes an optimization method, along with its application in an atmospheric CO2 inversion and the effects of using either the discrete or continuous adjoint method, is presented in an accompanying paper Niwa et al.(2016).
    Type of Medium: Online Resource
    ISSN: 1991-9603
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2017
    detail.hit.zdb_id: 2456725-5
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  • 5
    In: Geoscientific Model Development, Copernicus GmbH, Vol. 10, No. 6 ( 2017-06-15), p. 2201-2219
    Abstract: Abstract. A four-dimensional variational method (4D-Var) is a popular technique for source/sink inversions of atmospheric constituents, but it is not without problems. Using an icosahedral grid transport model and the 4D-Var method, a new atmospheric greenhouse gas (GHG) inversion system has been developed. The system combines offline forward and adjoint models with a quasi-Newton optimization scheme. The new approach is then used to conduct identical twin experiments to investigate optimal system settings for an atmospheric CO2 inversion problem, and to demonstrate the validity of the new inversion system. In this paper, the inversion problem is simplified by assuming the prior flux errors to be reasonably well known and by designing the prior error correlations with a simple function as a first step. It is found that a system of forward and adjoint models with smaller model errors but with nonlinearity has comparable optimization performance to that of another system that conserves linearity with an exact adjoint relationship. Furthermore, the effectiveness of the prior error correlations is demonstrated, as the global error is reduced by about 15 % by adding prior error correlations that are simply designed when 65 weekly flask sampling observations at ground-based stations are used. With the optimal setting, the new inversion system successfully reproduces the spatiotemporal variations of the surface fluxes, from regional (such as biomass burning) to global scales. The optimization algorithm introduced in the new system does not require decomposition of a matrix that establishes the correlation among the prior flux errors. This enables us to design the prior error covariance matrix more freely.
    Type of Medium: Online Resource
    ISSN: 1991-9603
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2017
    detail.hit.zdb_id: 2456725-5
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