Abstract
Abstract. Satellite observations provide spatially resolved global estimates of column-averaged mixing ratios of CO2 (XCO2) over the Earth's surface. The accuracy of these datasets can be validated against reliable standards in some areas, but other areas remain inaccessible. To date, limited reference data over oceans hinder successful uncertainty quantification or bias correction efforts and preclude reliable conclusions about changes in the carbon cycle in some regions. Here, we propose a new approach to analyze and evaluate seasonal, interannual, and latitudinal variations of XCO2 over oceans by integrating cargo-ship (Ship Of Opportunity – SOOP) and commercial aircraft (Comprehensive Observation Network for Trace gases by Airliner – CONTRAIL) observations with the aid of state-of-the art atmospheric chemistry-transport model calculations. The consistency of the “observation-based column-averaged CO2” dataset (obs. XCO2) with satellite estimates was analyzed over the western Pacific between 2014 and 2017, and its utility as a reference dataset evaluated. Our results demonstrate that the new dataset accurately captures seasonal and interannual variations of CO2. Retrievals of XCO2 over the ocean from GOSAT (Greenhouse Gases Observing Satellite: National Institute for Environmental Studies – NIES v02.75; Atmospheric CO2 Observation from Space – ACOS v7.3) and OCO-2 (Orbiting Carbon Observatory, v9r) observations show a negative bias of about 1 part per million (ppm) in northern midlatitudes, which was attributed to measurement uncertainties of the satellite observations. The NIES retrieval had higher consistency with obs. XCO2 at midlatitudes as compared to the other retrievals. At low latitudes, it shows many fewer valid data and high scatter, such that ACOS and OCO-2 appear to provide a better representation of the carbon cycle. At different times, the seasonal cycles of all three retrievals show positive phase shifts of 1 month relative to the observation-based data. The study indicates that even if the retrievals complement each other, remaining uncertainties limit the accurate interpretation of spatiotemporal changes in CO2 fluxes. A continuous long-term XCO2 dataset with wide latitudinal coverage based on the new approach has great potential as a robust reference dataset for XCO2 and can help to better understand changes in the carbon cycle in response to climate change using satellite observations.
Highlights
Efforts to control the accelerated increase of carbon dioxide (CO2) in the atmosphere became a serious international task in the last decades
A high accuracy of the MIROC4-atmospheric chemistry-transport model (ACTM) is indicated by the agreement of simulated “age of air”, which is a diagnostic for atmospheric transport, with that expected from measured sulfur hexafluoride (SF6) and CO2 in the troposphere and stratosphere, respectively (Patra et al, 2018)
The largest seasonal cycle of the CO2 mixing ratio is seen in the Northern Hemisphere (NH) at 20–30◦ N
Summary
Efforts to control the accelerated increase of carbon dioxide (CO2) in the atmosphere became a serious international task in the last decades. Since the beginning of the Industrial Revolution in the 1750s, fossil fuel combustion and other human activities have increased the atmospheric concentration of CO2 from approximately 277 ppm to more than 410 ppm in 2020 (Dlugokencky and Tans, 2021). Less than half of the anthropogenic CO2 emitted each year stays in the atmosphere, as the ocean and land each capture approximately one-fourth (Friedlingstein et al, 2019). A. Müller et al.: Ship-, aircraft-based satellite XCO2 evaluation spheric CO2 substantially and lead to year-to-year variations, which are not yet fully understood (e.g., Friedlingstein et al, 2019; Intergovernmental Panel on Climate Change (IPCC), 2013). As the carbon cycle responds to a changing climate, a comprehensive understanding of changes in CO2 sources and sinks is crucial for the implementation of effective strategies for reducing global warming
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
