Analysis of Recent Trends in Global Mean Surface Temperature: Implications for Achieving the Paris Agreement and Quantification of the Role of Maritime Emissions on Global Warming

Abstract

Understanding how human influence affects various components of Earth’s climate is a crucial economic and social question of our time. In this dissertation, a set of questions relevant to climate policy and regulations are examined using a reduced complexity climate model, the Empirical Model of Global Climate (EM−GC). First, model simulations are performed to quantify the global mean surface temperature (GMST) in this century, using the projections for the Effective Radiative Forcing (ERF) of greenhouse gases (GHGs) and tropospheric aerosols that were introduced by the AR6 Report of the Intergovernmental Panel on Climate Change (IPCC) in 2021. These updated estimates for ERF are found to result in highly elevated projections of the GMST, relative to estimates from simulations based on pre-AR6 ERF datasets, for allfour Shared Socioeconomic Pathway (SSP) scenarios investigated. The SSP2−4.5 scenario, which is considered to be the most consistent with recent trends in anthropogenic emissions of GHGs, offers only 8% chance of limiting the GMST anomaly to the upper limit of 2.0 ⁰C prescribed by the Paris Agreement (PA), relative to pre-industrial conditions. Model simulations are presented to quantify the contributing factors to the record high temperature anomalies observed in 2023 and 2024. The temperature anomalies observed in 2023 and 2024 can be reconstructed using existing trends in the rise of GMST, alongside a combination of short-term natural and anthropogenic factors. The reduced emissions of sulfur from maritime traffic, starting in 2020, is found to have contributed at least 0.028 ⁰C to the GMST, relative to 2019. This estimate was obtained from simulations performed with a new version of the EM−GC model that has been outfitted with an updated ocean module, which is also described in this work. The shift from La Niña to El Niño conditions, combined with a strong Indian Ocean Dipole (IOD) event account for over 50% of the sudden rise in GMST between 2022 and 2023. Short-term variability in the sea surface temperatures (SSTs) of the North Atlantic region were found to have contributed substantially to the GMST anomalies observed in 2023 and 2024, but whether this short-term variability is a direct result of reduced sulfur emissions remains unclear.