Data Driven Pathway Analysis and Forecast of Global Warming and Sea Level Rise

Abstract

Abstract Climate change remains a top concern for the world, with its causes, pathways, and forecasts, still subject to debate. In this paper, we present a novel data driven pathway analysis framework to identify the key processes behind the mean global temperature and sea level rise, and to forecast the magnitude of the increases between now and 2100. Based on historical data and dynamic statistical modeling alone, we have confirmed the causal pathways from increased greenhouse gas emissions to increased global mean temperature and sea level, with its intermediate links including humidity, sea ice coverage and glacier volume, but not sunspot numbers. Our results indicate that, if no action is taken to rein in anthropogenic greenhouse gas emissions, the global average temperature is estimated to be 2.79°C higher than its pre-industrial level and the global sea level is expected to be 604 mm above its 2021 mean by 2100. However, if the global community would adhere to the greenhouse gas emission regulations outlined in the 2021 United Nations Conference on Climate Change (COP26), the global temperature would increase to a less threatening 1.58°C above its pre-industrial level, while the sea level increase would reduce to 455 mm above its 2021 mean.