scholarly journals A comparison of posterior atmospheric CO<sub>2</sub> adjustments obtained from in situ and GOSAT constrained flux inversions

2018 ◽  
Vol 18 (16) ◽  
pp. 12011-12044 ◽  
Author(s):  
Saroja M. Polavarapu ◽  
Feng Deng ◽  
Brendan Byrne ◽  
Dylan B. A. Jones ◽  
Michael Neish

Abstract. Posterior fluxes obtained from inverse modelling are difficult to verify because there is no dense network of flux measurements available to evaluate estimates against. Here we present a new diagnostic to evaluate structures in posterior fluxes. First, we simulate the change in atmospheric CO2 fields between posterior and prior fluxes, referred to as the posterior atmospheric adjustments due to updated fluxes (PAAFs). Second, we calculate the uncertainty in atmospheric CO2 fields due solely to uncertainty in the meteorological fields, referred to as the posterior atmospheric adjustments due to imperfect meteorology (PAAMs). We argue that PAAF can only be considered robust if it exceeds PAAM, that is, the changes in atmospheric CO2 between the posterior and prior fluxes should at least exceed atmospheric CO2 changes arising from imperfect meteorology. This diagnostic is applied to two CO2 flux inversions: one which assimilates observations from the in situ CO2 network and the other which assimilates observations from the Greenhouse Gases Observing SATellite (GOSAT). On the global scale, PAAF in the troposphere reflects northern extratropical fluxes, whereas stratospheric adjustments primarily reflect tropical fluxes. In general, larger spatiotemporal variations in PAAF are obtained for the GOSAT inversion than for the in situ inversion. Zonal standard deviations of the PAAF exceed the PAAM through most of the year when GOSAT observations are used, but the minimum value is exceeded only in boreal summer when in situ observations are used. Zonal spatial structures in GOSAT-based PAAF exceed PAAM throughout the year in the tropics and through most of the year in the northern extratropics, suggesting GOSAT flux inversions can constrain zonal asymmetries in fluxes. However, we cannot discount the possibility that these structures are influenced by biases in GOSAT retrievals. Verification of such spatial structures will require a dense network of independent observations. Because PAAF depends on the choice of prior fluxes, the comparison with PAAM is system dependent and thus can be used to monitor a given assimilation system's behaviour.

2018 ◽  
Author(s):  
Saroja M. Polavarapu ◽  
Feng Deng ◽  
Brendan Byrne ◽  
Dylan B. A. Jones ◽  
Micheal Neish

Abstract. The CO2 flux signal is defined as the difference of the four-dimensional CO2 field obtained by integrating an atmospheric transport model with posterior fluxes and that obtained with prior fluxes. It is a function of both the model and the prior fluxes and it can provide insight into how posterior fluxes inform CO2 distributions. Here, we use the GEOS-Chem transport model constrained by either GOSAT or in situ observations to obtain two sets of posterior flux estimates in order to compare the flux signals obtained from the two different observing systems. Flux signals are also computed using two different models. The global flux signal in the troposphere primarily reflects the northern extratropics whereas the global flux signal in the stratosphere mainly reflects tropical contributions. While both observing systems constrain the global budget for 2010 equally well, stronger seasonal variations of the flux signal are obtained with GOSAT. Posterior CO2 distributions obtained with in situ observations better agree with TCCON measurements over an 18-month time period, but GOSAT-informed posterior fluxes better constrain the seasonal cycle at northern extratropical sites. Zonal standard deviations of the flux signal exceed the minimal value (defined by uncertainty in meteorological analyses) through most of the year when GOSAT observations are used, but when in situ observations are used, the minimum value is exceeded only in boreal summer. This indicates a potential for flux estimates constrained by GOSAT data to retrieve spatial structures within a zonal band throughout the year in the tropics and through most of the year in the northern extratropics. Verification of such spatial structures will require a dense network of independent observations.


2014 ◽  
Vol 41 (3) ◽  
pp. 1065-1070 ◽  
Author(s):  
Frédéric Chevallier ◽  
Paul I. Palmer ◽  
Liang Feng ◽  
Hartmut Boesch ◽  
Christopher W. O'Dell ◽  
...  
Keyword(s):  
Co2 Flux ◽  

2020 ◽  
Vol 20 (8) ◽  
pp. 5175-5195
Author(s):  
Jun Park ◽  
Hyun Mee Kim

Abstract. Continuous efforts have been made to monitor atmospheric CO2 mole fractions as it is one of the most influential greenhouse gases in Earth's atmosphere. The atmospheric CO2 mole fractions are mostly determined by CO2 exchanges at the Earth's surface (i.e., surface CO2 flux). Inverse modeling, which is a method to estimate the CO2 exchanges at the Earth's surface, derives surface CO2 fluxes using modeled and observed atmospheric CO2 mole fraction data. Although observation data are crucial for successful modeling, comparatively fewer in situ observation sites are located in Asia compared to Europe or North America. Based on the importance of the terrestrial ecosystem of Asia for global carbon exchanges, more observation stations and an effective observation network design are required. In this paper, several observation network experiments were conducted to optimize the surface CO2 flux of Asia using CarbonTracker and observation system simulation experiments (OSSEs). The impacts of the redistribution of and additions to the existing observation network of Asia were evaluated using hypothetical in situ observation sites. In the case of the addition experiments, 10 observation stations, which is a practical number for real implementation, were added through three strategies: random addition, the influence matrix (i.e., self-sensitivity), and ecoregion information within the model. The simulated surface CO2 flux in Asia in summer can be improved by redistributing the existing observation network. The addition experiments revealed that considering both the distribution of normalized self-sensitivity and ecoregion information can yield better simulated surface CO2 fluxes compared to random addition, regardless of the season. This study provides a diagnosis of the existing observation network and useful information for future observation network design in Asia to estimate the surface CO2 flux and also suggests the use of an influence matrix for designing CO2 observation networks. Unlike other previous observation network studies with many numerical experiments for optimization, comparatively fewer experiments were required in this study. Thus, the methodology used in this study may be used for designing observation networks for monitoring greenhouse gases at both continental and global scales.


2015 ◽  
Vol 17 (3) ◽  
pp. 683-692
Author(s):  
T. J. Boyd ◽  
M. T. Montgomery ◽  
R. H. Cuenca ◽  
Y. Hagimoto

Chlorinated hydrocarbon turnover (mineralization) estimated by CO2 radiocarbon content and respiration rate coupled to ZOI models.


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