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.
Super-Resolution Electrochemical Impedance Imaging with a 100 × 100 CMOS Sensor Array