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Quantifying Atmospheric CO2 From Space-Based Observations and Air Transport Simulations - Focusing on Ocean and Permafrost

dc.contributor.authorGuan, Yifan
dc.date.accessioned2023-09-22T15:44:44Z
dc.date.available2023-09-22T15:44:44Z
dc.date.issued2023
dc.date.submitted2023
dc.identifier.urihttps://hdl.handle.net/2027.42/178106
dc.description.abstractAtmospheric carbon dioxide (CO2) accounts for the largest radiative forcing among anthropogenic greenhouse gases. There is a pressing need to understand the rate at which CO2 accumulates in the atmosphere, in both the seasonal and the interannual timescales (mainly driven by terrestrial and oceanic carbon flux), because of their relationship with climatic variations that may provide insights into long-term carbon-climate feedback. Given advances in space-based measurements of atmospheric CO2, which enables us to monitor atmospheric CO2 abundance over open ocean, and in techniques to estimate ocean air-sea exchange based on sparse surface ocean observations, we have novel opportunities to refine our understanding of the ocean influence on atmospheric CO2 variation at the interannual timescale. Meanwhile, it remains challenging for current satellite missions to quantify and separate emissions of old carbon from permafrost from labile high-latitude carbon. This dissertation focuses on space- based observations over ocean and permafrost. In the first and second case study on the ocean, we estimate the likely range of IAV in the atmospheric CO2 owing to air-sea carbon exchange by simulating three-dimensional atmospheric CO2 using the GEOS-Chem atmospheric transport model. The ocean carbon fluxes we use are from state-of-the-art products that report calculated air-sea fluxes. In addition to global integration, we separately label CO2 from individual ocean regions, aiming to identify the fingerprints of ocean subregions and the whole ocean on atmospheric total column CO2 dry mole fraction (XCO2). These simulations were analyzed in conjunction with observed atmospheric CO2 IAV from NASAs OCO-2 satellite mission, which detects the combined imprint of the ocean, terrestrial ecosystem, and human activities. The case study on the ocean suggests that OCO-2 IAV provides new opportunities to monitor climate- driven variations in CO2 over open ocean and remote regions; and over remote ocean regions, simulations suggest that ocean fluxes contribute a large proportion of IAV. In the third study, we quantify permafrost-driven atmospheric CO2 enhancement using the GEOS-Chem atmospheric transport model with tagged CO2 species originating from permafrost sources in North America, Europe, and Asia. We then explore the detectability of these perturbations using an Observing System Simulation Experiment based upon a hypothetical satellite mission that employs a multi- spectral imaging spectrometer with channels in the thermal infrared and shortwave infrared, capable of providing two pieces of vertical information about the CO2 abundance. Our analysis points toward and provides preliminary estimates of observational requirements to identify signals from the Northern Permafrost regions using space-based observations.
dc.language.isoen_US
dc.subjectCarbon Cycle
dc.subjectCO2
dc.subjectSatellite Observation
dc.subjectGEOS-Chem Simulation
dc.subjectBiogeochemistry
dc.subjectAtmospheric Sciences
dc.titleQuantifying Atmospheric CO2 From Space-Based Observations and Air Transport Simulations - Focusing on Ocean and Permafrost
dc.typeThesis
dc.description.thesisdegreenamePhDen_US
dc.description.thesisdegreedisciplineClimate and Space Sciences and Engineering
dc.description.thesisdegreegrantorUniversity of Michigan, Horace H. Rackham School of Graduate Studies
dc.contributor.committeememberKeppel-Aleks, Gretchen
dc.contributor.committeememberCory, Rose
dc.contributor.committeememberKort, Eric
dc.contributor.committeememberSteiner, Allison L
dc.subject.hlbsecondlevelAtmospheric, Oceanic and Space Sciences
dc.subject.hlbtoplevelScience
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/178106/1/guanyf_1.pdf
dc.identifier.doihttps://dx.doi.org/10.7302/8563
dc.identifier.orcid0000-0001-8175-3765
dc.identifier.name-orcidGuan, Yifan; 0000-0001-8175-3765en_US
dc.working.doi10.7302/8563en
dc.owningcollnameDissertations and Theses (Ph.D. and Master's)


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