GPU-Accelerated Deep Learning for Heatwave Prediction and Urban Heat Risk Assessment

ArXi:2605.16435v1 Announce Type: new Heatwaves are an important problem in cities, and climate change makes this problem difficult. In this paper, we present a GPU-based deep learning framework for next-day prediction of urban thermal conditions and for heat risk assessment. The study was carried out in Sarajevo by using MODIS land surface temperature data and Open-Meteo forecast data. We tested several models, including convolutional models and spatiotemporal models. Among them, ConvLSTM with a mixed loss function gave the best results.