Assessment of the Remaining Carbon Budget: Incorporating Arctic Amplification in a Simple Response Model

• Main Author: Johansen, Andreas
• Format: Master Thesis
• Language: English
• Published: UiT The Arctic University of Norway 2020
• Subjects: VDP::Matematikk og Naturvitenskap: 400::Matematikk: 410; VDP::Mathematics and natural science: 400::Mathematics: 410; VDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420::Matematisk modellering og numeriske metoder: 427; VDP::Mathematics and natural science: 400::Information and communication science: 420::Mathematical modeling and numerical methods: 427; EOM-3901; Arctic; Greenland; Climate change; Ice; Ice Sheet; permafrost
• Online Access: https://hdl.handle.net/10037/19118

Remaining carbon budgets (RCBs) quantify the total amount of CO2 that can still be emitted into the atmosphere while keeping the global mean surface temperature below a specific target. However, there is significant uncertainty in RCBs estimates. This thesis develops a Simple Response Model (SRM) to explore the uncertainties in RCBs. We use temperature response functions estimated from multi-box energy-balance models fitted to 4xCO2 runs of 14 Earth System Models (ESMs) to analyze likelihood plots of RCBs. To validate the SRM, we compare the temperature projections with those from the Model for the Assessment of Greenhouse Gas Induced Climate Change (MAGICC). Incorporation of RCBs for Arctic temperature is implemented through an amplification factor ????� = 0.10 + 2.23????� estimated from NASA datatasets. The SRM can incorporate non-linear permafrost feedback as a hyperbolic tangent func- tion. Our results are in line with standard RCB estimates of 580 GtCO2 for the 1.5°C target but find the probabilistic range (90% probability to 10%) to be between 1.2°C-1.9°C, and increases to a range of 1.3°C-2.4°C when including non-linearities for the same RCB. The uncertainty in the budgets increase significantly with less ambitious targets. Uncertainty in Arctic temperature are of particular interest due to the risk of triggering an irreversible transition of the Greenland Ice Sheet. Our SRM agrees well with MAGICC, which validates the accuracy of RCBs in our likelihood plots.