Effect of Data Assimilation Parameters on The Optimized Surface CO2 Flux in Asia

Kim, Hyunjung; Kim, Hyun Mee; Kim, Jinwoong; Cho, Chun Ho

doi:10.1007/s13143-017-0049-9

Cited by 10 publications

(14 citation statements)

References 55 publications

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“…CT2013B, developed by the Earth System Research Laboratory (ESRL) at the National Oceanic and Atmospheric Administration (NOAA), was used for this study. CT2013B estimates the surface CO 2 flux using inverse modeling and has been widely used to calculate surface CO 2 fluxes in North America, Europe, and Asia (Peters et al, 2004(Peters et al, , 2005(Peters et al, , 2007(Peters et al, , 2010Kim et al, 2012Kim et al, , 2014aKim et al, , 2014bKim et al, , 2016Kim et al, , 2017Kim et al, , 2018aCheng et al, 2013).…”

Section: Carbontracker and Data Assimilation Methodsmentioning

confidence: 99%

“…28 The experiment that adds 10 observation sites to the existing 18 NOAA observation network sites with the normalized self-sensitivity and ecoregion information (1-2 stations for each ecoregion). By calculating the ensemble mean and perturbation independently, the underestimation of the analysis error covariance could be prevented (Whitaker and Hamill, 2002;Kim et al, 2012). P b H T and HP b H T can be calculated as follows:…”

Section: Necoss1_18mentioning

confidence: 99%

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Design and evaluation of CO2 observation network to optimize surface CO2 fluxes in Asia using observation system simulation experiments

Park

Kim

2020

Atmos. Chem. Phys.

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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.

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Section: Carbontracker and Data Assimilation Methodsmentioning

confidence: 99%

Section: Necoss1_18mentioning

confidence: 99%

Design and evaluation of CO2 observation network to optimize surface CO2 fluxes in Asia using observation system simulation experiments

Park

Kim

2020

Atmos. Chem. Phys.

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“…CT2013B, developed by the Earth System Research Laboratory (ESRL) at the National Oceanic and Atmospheric Administration (NOAA), was used for this study. CT2013B estimates the surface carbon flux using inverse modeling and has been widely used to calculate surface carbon fluxes in North America, 5 Europe, and Asia (Peters et al, 2004(Peters et al, , 2005(Peters et al, , 2007(Peters et al, , 2010Kim et al, 2012Kim et al, , 2014aKim et al, , 2014bKim et al, , 2017Cheng et al, 2013;Kim et al, 2016Kim et al, , 2018aKim et al, , 2018b.…”

Section: Carbontracker and Data Assimilation Methodsmentioning

confidence: 99%

“…To investigate the reduction of uncertainties for each experiment after data assimilation, uncertainty reduction (UR; Peters et al, 2005;Meirink et al, 2008;Chevallier et al, 2009b, Feng et al, 2009Kim et al, 2014a, Kim et al, 2018b was calculated as:…”

Section: Simulated Hypothetical Observation and Experimental Setupmentioning

confidence: 99%

“…Bayesian synthesis (Enting, 2002), four dimensional variational data assimilation methods (4DVar; 10 Chevallier et al, 2009a10 Chevallier et al, , 2009b10 Chevallier et al, , 2010Kou et al, 2017), and Ensemble Kalman Filter (EnKF; Peters et al, 2005Peters et al, , 2007Peters et al, , 2010Feng et al, 2009Feng et al, , 2016Kang et al, 2011Kang et al, , 2012Peylin et al, 2013;Kim et al, 2014aKim et al, , 2014bKim et al, , 2017Kim et al, , 2018aKim et al, , 2018b have been implemented and utilized to conduct inverse modeling. By comparing 13 inverse modeling systems, Peylin et al (2013) showed that simulation results were similar to each other for regions with many observations, but dissimilar for regions with sparse observation 15 coverage (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Design and evaluation of CO2 observation network to optimize surface CO2 fluxes in Asia using observation system simulation experiments

Park¹,

Kim²

2019

Preprint

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Continuous efforts have been made to monitor atmospheric CO2 as it is one of the most influential greenhouse gases in Earth's atmosphere. Inverse modeling, which is one of the methods to 10 carry out such monitoring, derives estimated CO2 mole fractions in the air from calculated surface carbon fluxes using model and observed CO2 mole fraction data. Although observation data is 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 15 paper, several observation network experiments were conducted to optimize the surface carbon flux of Asia using CarbonTracker and observation system simulation experiments (OSSE). 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, 20 the influence matrix (i.e., self-sensitivity), and ecoregion information within the model. The simulated surface carbon 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 carbon fluxes compared to random addition, regardless of the season. This study provides a diagnosis of the existing observation network and useful 25 information for future observation network design in Asia to estimate the surface carbon flux, and also suggests the use of an influence matrix for designing carbon observation networks. Unlike other previous

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High‐resolution atmospheric CO₂ concentration data simulated in WRF‐Chem over East Asia for 10 years

Seo,

Kim,

Kim

2024

Geoscience Data Journal

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In this study, high‐resolution CO2 concentration data were generated for East Asia to analyse long‐term changes in atmospheric CO2 concentrations, as East Asia is an important region for understanding the global carbon cycle. Using the Weather Research and Forecasting model coupled with Chemistry (WRF‐Chem), atmospheric CO2 concentrations were simulated in East Asia at a resolution of 9 km for a period of 10 years (2009–2018). The generated CO2 concentration data include CO2 concentrations, biogenic CO2 concentrations, anthropogenic CO2 concentrations, oceanic CO2 concentrations, biospheric CO2 uptake, biospheric CO2 release and meteorological variables at 3‐h intervals. The simulated high‐resolution CO2 concentrations, biogenic CO2 concentrations and anthropogenic CO2 concentrations are stored in NetCDF‐4 (Network Common Data Form, version 4) format and are available for download at https://doi.org/10.7910/DVN/PJTBF3. The simulated annual mean surface CO2 concentrations in East Asia were 391.027 ppm in 2009 and 412.949 ppm in 2018, indicating an increase of 21.922 ppm over the 10‐year period with appropriate seasonal variabilities. The monthly mean CO2 concentrations in East Asia were verified using surface CO2 observations and satellite column‐averaged CO2 mole fraction (XCO2) from Orbiting Carbon Observatory 2 (OCO‐2). Based on surface CO2 observations and OCO‐2 XCO2 concentrations, the average root‐mean‐square error (RMSE) of the simulated CO2 concentrations in WRF‐Chem was 2.474 and 0.374 ppm, respectively, which is smaller than the average RMSE of the low‐resolution CarbonTracker 2019B (CT2019B) simulation. Therefore, the simulated high‐resolution atmospheric CO2 concentrations in East Asia in WRF‐Chem over 10 years are reliable data that resemble the observed values and could be highly valuable in understanding the carbon cycle in East Asia.

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Effect of Data Assimilation Parameters on The Optimized Surface CO2 Flux in Asia

Cited by 10 publications

References 55 publications

Design and evaluation of CO<sub>2</sub> observation network to optimize surface CO<sub>2</sub> fluxes in Asia using observation system simulation experiments

Design and evaluation of CO<sub>2</sub> observation network to optimize surface CO<sub>2</sub> fluxes in Asia using observation system simulation experiments

Design and evaluation of CO<sub>2</sub> observation network to optimize surface CO<sub>2</sub> fluxes in Asia using observation system simulation experiments

High‐resolution atmospheric CO₂ concentration data simulated in WRF‐Chem over East Asia for 10 years

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Effect of Data Assimilation Parameters on The Optimized Surface CO2 Flux in Asia

Cited by 10 publications

References 55 publications

Design and evaluation of CO&lt;sub&gt;2&lt;/sub&gt; observation network to optimize surface CO&lt;sub&gt;2&lt;/sub&gt; fluxes in Asia using observation system simulation experiments

Design and evaluation of CO&lt;sub&gt;2&lt;/sub&gt; observation network to optimize surface CO&lt;sub&gt;2&lt;/sub&gt; fluxes in Asia using observation system simulation experiments

Design and evaluation of CO&lt;sub&gt;2&lt;/sub&gt; observation network to optimize surface CO&lt;sub&gt;2&lt;/sub&gt; fluxes in Asia using observation system simulation experiments

High‐resolution atmospheric CO2 concentration data simulated in WRF‐Chem over East Asia for 10 years

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Design and evaluation of CO<sub>2</sub> observation network to optimize surface CO<sub>2</sub> fluxes in Asia using observation system simulation experiments

Design and evaluation of CO<sub>2</sub> observation network to optimize surface CO<sub>2</sub> fluxes in Asia using observation system simulation experiments

Design and evaluation of CO<sub>2</sub> observation network to optimize surface CO<sub>2</sub> fluxes in Asia using observation system simulation experiments

High‐resolution atmospheric CO₂ concentration data simulated in WRF‐Chem over East Asia for 10 years