Coupled Coastal Hazard Prediction System (CCHaPS) Hindcast for Australia
CCHaPS, the Coupled Coastal Hazard Prediction System, is a 2D hydrodynamic and wave model (Semi-implicit Cross-scale Hydroscience Integrated System Model and Wind Wave Model III, SCHISM-WWMIII), configured around the Australian coastline including the Great Barrier Reef, and extending out to deep offshore waters or neighbouring landmasses. The model simulates water levels due to astronomical tides, weather, waves and aspects of wave-flow interaction over multiple decades, allowing for full consideration of the dynamics of extreme sea levels and waves in the Australian region, at high spatial resolution from ~7km off-shore down to ~250m at the coast, and ~100m in major river mouths. The model is run on an unstructured (triangular) grid comprising over 1.4 million nodes, which extends overland up to a 12m elevation contour, to enable modelling of inundation events and sea level rise. The CCHaPS hindcast covers the 40-year period 1981 to 2020. The hindcast is forced with downscaled ERA5 winds and mean sea level pressure produced by BARRA-R2, water levels from ORAS5, tides from TPXOv9.2, and spectral wave forcing from WHACS (see Lineage). The model used is SCHISM-WWMIII v5.9, using ST4 wave physics, run on NCI's Gadi supercomputer. The dataset comprises hourly netCDF data on an unstructured grid, compliant with CF, ACDD and UGRID metadata conventions. A notebook demonstrating how to interact with the data will be attached under Supporting Documentation, and also available via GitHub (see Related Links, LINK TBA). Variables included are: depth (non-time varying), sea surface height, wet-dry node, currents, significant wave height, mean wave direction, peak wave direction, directional spreading, t01 and t02 mean wave period, peak wave period, peak directional spreading, peak direction (rad), and orbital velocity. The data is also stored on CSIRO infrastructure in the {ev-acs-wp3-cchaps} volume, and at NCI in /g/data/ia39/WP3/release/CCHaPS. Examples of how to work with the data in Python are provided in the accompanying notebook "CCHaPS_examples.ipynb" (see Supporting files) A manuscript describing this dataset is in preparation and will be linked to this metadata record in due course.