scholarly journals Requirements for an Integrated in situ Atlantic Ocean Observing System From Coordinated Observing System Simulation Experiments

2019 ◽  
Vol 6 ◽  
Author(s):  
Florent Gasparin ◽  
Stephanie Guinehut ◽  
Chongyuan Mao ◽  
Isabelle Mirouze ◽  
Elisabeth Rémy ◽  
...  
Keyword(s):  
Atlantic Ocean ◽  
System Simulation ◽  
Simulation Experiments ◽  
Ocean Observing

scholarly journals 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

2019 ◽  
Author(s):  
Jun Park ◽  
Hyun Mee Kim
Keyword(s):  
Carbon Flux ◽  
System Simulation ◽  
Observation System ◽  
In Situ Observation ◽  
Simulation Experiments ◽  
Influence Matrix ◽  
Surface Carbon ◽  
Observation Network ◽  
Simulated Surface

Abstract. 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 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 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, 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 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 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.

scholarly journals Observation system simulation experiments in the Atlantic Ocean for enhanced surface ocean <i>p</i>CO<sub>2</sub> reconstructions

Ocean Science ◽  
2021 ◽  
Vol 17 (4) ◽  
pp. 1011-1030
Author(s):  
Anna Denvil-Sommer ◽  
Marion Gehlen ◽  
Mathieu Vrac
Keyword(s):  
Atlantic Ocean ◽  
System Simulation ◽  
Ocean Surface ◽  
Ocean Model ◽  
Global Ocean ◽  
Observation System ◽  
Simulation Experiments ◽  
Atlantic Sector ◽  
Argo Floats ◽  
Surface Ocean

Abstract. To derive an optimal observation system for surface ocean pCO2 in the Atlantic Ocean and the Atlantic sector of the Southern Ocean, 11 observation system simulation experiments (OSSEs) were completed. Each OSSE is a feedforward neural network (FFNN) that is based on a different data distribution and provides ocean surface pCO2 for the period 2008–2010 with a 5 d time interval. Based on the geographical and time positions from three observational platforms, volunteering observing ships, Argo floats and OceanSITES moorings, pseudo-observations were constructed using the outputs from an online-coupled physical–biogeochemical global ocean model with 0.25∘ nominal resolution. The aim of this work was to find an optimal spatial distribution of observations to supplement the widely used Surface Ocean CO2 Atlas (SOCAT) and to improve the accuracy of ocean surface pCO2 reconstructions. OSSEs showed that the additional data from mooring stations and an improved coverage of the Southern Hemisphere with biogeochemical ARGO floats corresponding to least 25 % of the density of active floats (2008–2010) (OSSE 10) would significantly improve the pCO2 reconstruction and reduce the bias of derived estimates of sea–air CO2 fluxes by 74 % compared to ocean model outputs.

Observation System Simulation Experiments for surface ocean pCO2 reconstructions in the Atlantic Ocean 

2021 ◽  
Author(s):  
Anna Denvil-Sommer ◽  
Marion Gehlen ◽  
Mathieu Vrac
Keyword(s):  
Standard Deviation ◽  
Atlantic Ocean ◽  
Correlation Coefficient ◽  
System Simulation ◽  
Ocean Model ◽  
Observation System ◽  
Simulation Experiments ◽  
Model Reference ◽  
Surface Ocean ◽  
Global Estimates

&lt;p&gt;Global estimates of the ocean carbon sink are released with a yearly frequency as part of the global carbon budget. However, these global estimates hide important spatial and temporal variabilities that can only partly be resolved by direct in situ observations. In this work we explore options for future observational network design combining data streams from various platforms. Our objective is to identify an optimal observational network for surface ocean pCO&lt;sub&gt;2&lt;/sub&gt; in the Atlantic Ocean and the Atlantic sector of the Southern Ocean. For this purpose, eleven Observation System Simulation Experiments (OSSEs) were performed. Each OSSE is a Feed-Forward Neural Network (FFNN) that is based on different data distributions and provides ocean surface pCO&lt;sub&gt;2&lt;/sub&gt; for the period 2008-2010 with a 5-day time interval. Based on the geographical and time positions from three observational platforms, volunteering observing ships (VOS), Argo floats and OceanSITES moorings, pseudo-observations were constructed using the outputs from an online-coupled physical-biogeochemical global ocean model with a 0.25&amp;#186; nominal spatial resolution. The aim of this work was to find an optimal spatial distribution of observations to supplement the widely used Surface Ocean CO&lt;sub&gt;2&lt;/sub&gt; Atlas (SOCAT) and to improve the accuracy of ocean surface pCO&lt;sub&gt;2&lt;/sub&gt; reconstructions. OSSEs showed that the additional data from mooring stations and an improved coverage of the southern Hemisphere with biogeochemical ARGO floats corresponding to at least 25% of the density of active floats (2008-2010) would significantly improve the pCO&lt;sub&gt;2&lt;/sub&gt; reconstruction and reduce the bias of derived estimates of sea-air CO&lt;sub&gt;2&lt;/sub&gt; fluxes by 77%. The use of only SOCAT data results in a correlation coefficient of 0.67 compared to the ocean model output and a 26.08 &amp;#120583;atm standard deviation (25.34 &amp;#120583;atm for the model reference) over the chosen regions. While the best OSSE has a correlation coefficient of 0.85 and 24.89 &amp;#120583;atm for standard deviation. These results are close to the unrealistic benchmark case with total and only Argo float distribution over 2008-2010: 0.87 and 23.79&amp;#120583;atm. The reconstructed average pCO&lt;sub&gt;2&lt;/sub&gt; over the whole region is also close to the model reference, ~370 &amp;#120583;atm and ~371 &amp;#120583;atm, respectively. The integrated air-sea fluxes &lt;em&gt;f&lt;/em&gt;CO&lt;sub&gt;2&lt;/sub&gt; are about -0.83 Pg/yr (best OSSE) and -0.76 Pg/yr (model reference).&amp;#160;&lt;/p&gt;

scholarly journals Observation System Simulation Experiments in the Atlantic Ocean for enhanced surface ocean <i>p</i>CO<sub>2</sub> reconstructions

2021 ◽  
Author(s):  
Anna Denvil-Sommer ◽  
Marion Gehlen ◽  
Mathieu Vrac
Keyword(s):  
Atlantic Ocean ◽  
System Simulation ◽  
Ocean Surface ◽  
Ocean Model ◽  
Global Ocean ◽  
Observation System ◽  
Simulation Experiments ◽  
Atlantic Sector ◽  
Argo Floats ◽  
Surface Ocean

Abstract. To derive an optimal observation system for surface ocean pCO2 in the Atlantic Ocean and the Atlantic sector of the Southern Ocean eleven Observation System Simulation Experiments (OSSEs) were completed. Each OSSE is a Feed-Forward Neural Network (FFNN) that is based on a different data distribution and provides ocean surface pCO2 for the period 2008–2010 with a 5 day time interval. Based on the geographical and time positions from three observational platforms, volunteering observing ships (VOS), Argo floats and OceanSITES moorings, pseudo-observations were constructed using the outputs from an online-coupled physical-biogeochemical global ocean model with 0.25° nominal resolution. The aim of this work was to find an optimal spatial distribution of observations to supplement the widely used Surface Ocean CO2 Atlas (SOCAT) and to improve the accuracy of ocean surface pCO2 reconstructions. OSSEs showed that the additional data from mooring stations and an improved coverage of the Southern Hemisphere with biogeochemical ARGO floats corresponding to least 25 % of the density of active floats (2008–2010) (OSSE 10) would significantly improve the pCO2 reconstruction and reduce the bias of derived estimates of sea-air CO2 fluxes by 74 % compared to ocean model outputs.

scholarly journals Design of the Observing System Simulation Experiments with multi-platform in situ data and impact on fine- scale structures

2020 ◽  
Author(s):  
Barbara Barcelo-Llull ◽  
Ananda Pascual ◽  
Eugenio Cutolo ◽  
Ronan Fablet ◽  
Florent Gasparin ◽  
...  
Keyword(s):  
System Simulation ◽  
Satellite Observations ◽  
Fine Scale ◽  
Simulation Experiments ◽  
Work Plan ◽  
In Situ Data ◽  
Scale Structures

This report presents the work plan of the Task 2.3: Observing System Simulation Experiments: impact of multi-platform observations for the validation of satellite observations

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