Researchers
The team: This research is result of a collaboration between the Visual Cognitive Systems Lab, University of Ljubljana, Faculty of Computer and Information Science, the Marine biology station at the National Institute of Biology (NIB) and the Slovenian Environment Agency (ARSO): Lojze Žust & Matej Kristan (FRI), Anja Fettich (ARSO), Matjaž Ličer (NIB)
HIDRA
Quick links: Live predictions
Interactions between atmospheric forcing, topographic constraints to air and water flow, and resonant character of the basin make sea level modelling in the Adriatic a challenging problem. We present HIDRA (HIigh-performance Deep tidal Residual estimation method using Atmospheric data) to address this challenge. HIDRA is a physics-informed deep model for sea-level forecasting, which makes predictions based on ensemble weather forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF) and past 24 hours of sea-level measurements at the Koper Mareographic Station. The model HIDRA1 was trained on a dataset of ECMWF weather forecasts for the years 2006-2016 and Koper sea-level measurements for the same time period. Later versions extended the dataset as well as prediction domains, with HIDRA-D now delivering a dense prediction for the entire Adriatic basin.
Results show that HIDRA matches (and surpasses in some cases) the accuracy of a numerical operational model, while being half million times faster, delivering predictions within less than a second on CPU in ~16 ms on GPU.
Forecasts of the operational HIDRA model in use by the Slovenian Environment Agency are showcased here.
Model architecture
HIDRA uses a novel model architecture to combine the spatio-temporal information from the atmospheric input data and the temporal information from the sea-level measurements input data. More details about the models in the GMD papers listed below.
Code
HIDRA1 is available at Github repository. HIDRA2 is available at Github HIDRA3 is available at Github HIDRA-D is available at Github