Imputation of Missing Climate Data and Vulnerability Analysis: A Survey

The previous article [65] covered effects of climate change such as global warming and rising sea levels, and investigated time series forecasting models for predicting global temperature anomalies, from statistical models such as ARIMA to large language models (LLMs). Although LLMs have mainly advanced natural language processing, they are gaining importance in time series tasks. Transformer-based foundation models, which form the basis of most LLMs, offer unprecedented capabilities in tasks such as forecasting, classification and trend analysis. Transformer and Patch-Based Time Series Models