Physics Informed Deep Learning

Satellite-derived land surface temperature (LST) provides valuable information about urban heat patterns at high spatial resolution. However, observations from thermal infrared satellite sensors are frequently covered by clouds,… more

Interested in AI and Climate Science? Simulating the Earth’s climate with Earth System Models (ESMs) is essential for understanding and predicting climate change — past, present, and future. These physics-based simulations are… more

Global climate models play a vital role in predicting future climate conditions, such as temperature or precipitation. However, their coarse spatial resolution (typically 50–100 km) limits their ability to capture regional climate… more

Although our planet is a sphere and therefor all weather and climate processes operate on sphere, Deep Learning Weather Models very commonly operate on different rectangular projections of the sphere. This introduces increasingly… more