Prediction of Climate and its' Impacts (PCI)
Climate prediction models aim to simulate and forecast changes in the climate based on historical data and artificial intelligence based forecasting models. Prediction of climate is necessary to better understand the parameters influencing and/or accelerating the change and how technological, societal and natural occurrences can affect climate in the short, medium and longer term. This has become particularly important in the past two decades due to progressive increase in the average global temperature and extreme weather events.
To achieve this purpose, the Prediction of Climate and its' Impacts (PCI) research group sets out the following general aims:
- to model and predict climate and climate change at local, regional, national and global levels
- to model and predict how climate change impacts various sectors such as agriculture, environment, water, public health and transportation
- to develop and implement data-driven modelling and optimisation algorithms to predict climate change and its impacts.
The Group aims to address research themes, including:
- to develop numerical models capable of predicting climate at micro and macro levels
- to identify and assess the effect of various sectors on climate (e.g. transportation, agriculture and energy)
- to develop Machine Learning (ML), big data analytics and optimisation algorithms to improve climate forecasting models.