Articles | Volume 14, issue 4
Model description paper
21 Apr 2021
Model description paper |  | 21 Apr 2021

HIDRA 1.0: deep-learning-based ensemble sea level forecasting in the northern Adriatic

Lojze Žust, Anja Fettich, Matej Kristan, and Matjaž Ličer

Data sets

NEMO, HIDRA and Tide Gauge Datasets for HIDRA Machine Learning Algorithm Verification L. Žust, M. Kristan, A. Fettich, and M. Licer

NEMO Configuration Namelist L. Žust, A. Fettich, M. Kristan, and M. Licer

Model code and software

lojzezust/HIDRA: HIDRA v1.0.1 L. Žust, A. Fettich, M. Kristan, and M. Licer

Short summary
Adriatic basin sea level modelling is a challenging problem due to the interplay between terrain, weather, tides and seiches. Current state-of-the-art numerical models (e.g. NEMO) require large computational resources to produce reliable forecasts. In this study we propose HIDRA, a novel deep learning approach for sea level modeling, which drastically reduces the numerical cost while demonstrating predictive capabilities comparable to that of the NEMO model, outperforming it in many instances.