SearcharxivSearch

arXiv · 2509.21957

Toward a digital twin of the Great Barrier Reef: impact of extreme model resolution on tidal simulations

Abstract

Coral reefs are topologically complex environments with a large variation over small spatial-scales. The availability of high resolution data (metre-scale) to study these environments has increased rapidly such that many researchers are actively engaged in creating a `digital twin' of these environments to aid protection and management. However, as with any model, a digital twin will only be as useful as the data used to create it. Previous numerical modelling work on coral reefs has been carried out at a range of resolutions from 10s to 1000s of metres, but to date there has been no comprehensive study on the impact of extreme model resolution at metre-scale. Here, we simulate the Capricorn Bunker region of the GBR in a high resolution, multi-scale model using grid scales of 20,000 m to 5 m and compare that to the models with minimum grid scales of 250 m and 50 m. It is shown that the observable physical processes are best simulated at extremely high resolutions, though the intermediate resolution model performs well also. The low resolution model, whilst using a resolution comparable to a number of previous studies, does not sufficiently capture local-scale processes. Numerical models play a vital role in creating a digital twin of coastal seas as they contain the mathematical representation of the biophysical and chemical processes present but are currently at a coarser resolution than satellite and bathymetric data on which digital twins could be based. Bridging this resolution gap remains a challenge.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Jon Hill, Ana Vila-Concejo, Katherine C. Lee. 2025-09-26. Toward a digital twin of the Great Barrier Reef: impact of extreme model resolution on tidal simulations. https://arxiv.org/abs/2509.21957

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Windowed Envelope Statistics for Time-Domain Significant Wave Height Estimation From HF Radar

Significant wave height (SWH) retrieval from high-frequency (HF) radar typically relies on a weak second-order Doppler continuum that is sensitive to noise, interference, and spectral leakage. This letter presents a Windowed Envelope Statistics Estimator (WESE) that operates directly on beam-formed time-domain voltages. A second-order term obtained from a Neumann expansion of the rough-surface field equation motivates quadratic compensation of localized radar features. WESE extracts the mean, standard deviation, or variance from overlapping windows of the in-phase, quadrature, or envelope-magnitude sequence, followed by quadratic compensation, rank ordering, least-squares regression, and causal smoothing. Evaluation used 335 synchronized hourly observations from a 13.385 MHz, 12-element WERA system at Argentia, Newfoundland and Labrador. The optimal configuration used quadrature variance, a 16-sample window, 896 retained chronological samples, and 30-h smoothing, achieving an RMSE of 0.152 m and a Pearson correlation of 0.978. This represents RMSE reductions of 32.1% and 18.7% relative to previously reported linear and second-order compensated ordered-statistics models, respectively. The results demonstrate robust time-domain SWH estimation without explicit Doppler-spectrum construction.

physics.ao-ph

KiloDA: Reconstructing kilometer-scale near-surface wind states from sparse station observations

Accurate kilometer-scale near-surface winds are important for understanding atmospheric processes over complex terrain, yet remain difficult to reconstruct from sparse and unevenly distributed observations. Here we introduce KiloDA, a diffusion framework for hourly kilometer-scale wind reconstruction from surface stations. KiloDA learns the statistical distribution and spatial structure of wind fields from historical 3-km Weather Research and Forecasting (WRF) model forecasts. At each reconstruction time, no contemporaneous WRF field is used. Instead, station observations provide the only constraints on the current atmospheric state and guide posterior sampling from the learned prior. In idealized WRF experiments, KiloDA recovers localized wind structures when only 0.24% of grid cells are observed and shows an overall advantage over conventional interpolation across terrain conditions and wind speed regimes. This capability largely transfers to real observations. In a fully withheld region, KiloDA reduces the median wind speed root mean square error (RMSE) by 19% relative to ERA5 reanalysis, using only observations outside the region, with the largest improvements over high-elevation and high-relief terrain. A random station holdout further confirms that this advantage extends across different complex-terrain locations and holdout configurations. These results show that historical model archives can provide useful structural knowledge for reconstructing kilometer-scale wind fields from sparse observations without requiring an accurate model estimate of the current atmospheric state.

physics.ao-ph