SLICE

SLICE is a React + TypeScript ice-sheet simulator with a 3D-ICE-based Explorer mode. The Explorer catalog and scenario files are generated from Antarctic flowlines under public/data/flowline-catalog.json and public/data/scenarios/flowlines.

Development

npm install
npm run dev

Raw-NC Flowline Generation

This repository includes a raw-data pipeline that rebuilds the Antarctic Explorer dataset from:

• BedMachineAntarctica_V4.nc
• the original Antarctic ice-velocity NetCDF
• imbie_refined_basins_v2.json

Python dependencies live in requirements-flowlines.txt.

Setup

python3 -m venv .venv-flowlines
source .venv-flowlines/bin/activate
pip install -r requirements-flowlines.txt

Build the 70 major basin groups

npm run flowlines:build-groups

This writes scripts/major-basin-groups.json.

Generate the 100 flowlines

source .venv-flowlines/bin/activate
python scripts/generate-antarctica-flowlines.py \
  --bedmachine-nc "/Users/eddie/Library/CloudStorage/OneDrive-UniversityofTasmania/Documents/Antarctica_Dataset/BedMachineAntarctica_V4.nc" \
  --velocity-nc "/Users/eddie/Library/CloudStorage/OneDrive-UniversityofTasmania/Documents/Antarctica_Dataset/antarctic_ice_vel_phase_map_v01_ErrorDel_inpaint_extend_slim_PIGmodified.nc" \
  --basins-json "/Users/eddie/Documents/3d-ice/static/tools/data/imbie_refined_basins_v2.json" \
  --target-lines 100 \
  --spacing-km 2 \
  --output-dir "/Users/eddie/Documents/SLICE/public/data"

The generator:

• downsamples BedMachine from 500 m to a 2 km working grid
• resamples velocity onto the same EPSG:3031 grid
• traces candidate flowlines with bilinear velocity sampling
• guarantees coverage of 70 major basin groups
• exports 100 catalog entries and 100 scenario JSON files
• validates geometry spacing, group coverage, priority basins, and scenario consistency

Outputs

• Catalog: public/data/flowline-catalog.json
• Scenarios: public/data/scenarios/flowlines

Each scenario now includes:

• explicit nx
• bedrock and initial_H
• geometry.spacing_km = 2
• per-point geometry with distance_km, x_m, y_m, lon, lat, bed_m, surface_m, thickness_m, mask, and speed_m_per_yr