
Detectability of Artificial Ocean Alkalinization and Stratospheric Aerosol Injection in MPI‐ESM
Author(s) -
Fröb Friederike,
Sonntag Sebastian,
Pongratz Julia,
Schmidt Hauke,
Ilyina Tatiana
Publication year - 2020
Publication title -
earth's future
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.641
H-Index - 39
ISSN - 2328-4277
DOI - 10.1029/2020ef001634
Subject(s) - radiative forcing , environmental science , forcing (mathematics) , atmospheric sciences , aerosol , offset (computer science) , climatology , meteorology , computer science , physics , geology , programming language
To monitor the success of carbon dioxide removal (CDR) or solar radiation management (SRM) that offset anthropogenic climate change, the forced response to any external forcing is required to be detectable against internal variability. Thus far, only the detectability of SRM has been examined using both a stationary and nonstationary detection and attribution method. Here, the spatiotemporal detectability of the forced response to artificial ocean alkalinization (AOA) and stratospheric aerosol injection (SAI) as exemplary methods for CDR and SRM, respectively, is compared in Max Planck Institute Earth System Model (MPI‐ESM) experiments using regularized optimal fingerprinting and single‐model estimates of internal variability, while working under a stationary or nonstationary null hypothesis. Although both experiments are forced by emissions according to the Representative Concentration Pathway 8.5 (RCP8.5) and target the climate of the RCP4.5 scenario using AOA or SAI, detection timescales reflect the fundamentally different forcing agents. Moreover, detectability timescales are sensitive to the choice of null hypothesis. Globally, changes in the CO 2 system in seawater are detected earlier than the response in temperature to AOA but later in the case of SAI. Locally, the detection time scales depend on the physical, chemical, and radiative impacts of CDR and SRM forcing on the climate system, as well as patterns of internal variability, which is highlighted for oceanic heat and carbon storage.