Quantitative Methodology to Predict Global Climate Change Impact on a Sustainable Economy

Barus DS, Muda I, Soemitra A and Sugianto S

Published on: 2023-12-29

Abstract

Global climate change is a major challenge faced by the world today. To deal with it, the development of an accurate and reliable climate prediction model is crucial. This study adopts a quantitative research approach and uses historical climate observation data, satellite data, and data from climate model simulations in the development of predictive models. By using statistical analysis and machine learning techniques, mathematical relationships between climate variables can be identified, and predictions of future climate change can be formulated. The results of the model performance evaluation show that the climate prediction model is successful at reproducing observational data, and has an adequate level of accuracy and reliability. Sensitivity testing and uncertainty analysis provide insight into the important parameters that influence predictive results and the level of uncertainty associated with climate predictions. This research makes an important contribution to the understanding and prediction of global climate change. The climate prediction model that has been developed has the potential to become a valuable tool in facing the challenge of climate change by providing better guidance in policy decision-making and mitigation efforts. However, it should be remembered that climate predictions are subject to a degree of uncertainty, and understanding this uncertainty must be an important part of strategic planning in dealing with future climate change. Economic and ecological development is made in an approach called ecological modernization with the assumption of reducing waste and pollution through technological improvements, improving regulations and markets that are pro-ecological and greening social and corporate values and practices.