Reflectance data and thermal parameters

CACK monthly derivative

Bright, R. M. and O’Halloran, T. L. (2019). Developing a monthly radiative kernel for surface albedo change from satellite climatologies of Earth’s shortwave radiation budget: CACK v1.0. Geoscientific Model Development, 12, 3975–3990. Model description, dataset. Underlying radiation products: NASA CERES EBAF.

cack-monthly.bin is an approved derivative of the locally supplied CACK CM monthly 2001–2016 mean: spherical area averages to 2°, quantised at 0.01 W/m² per unit surface albedo, polar-night NaNs converted to zero. It excludes all year-specific and uncertainty variables. cack-monthly.json records hashes, coordinates and conversion choices. The original NetCDF and supplied programs stay local and are excluded from both Git and the site build. The article is distributed under CC BY 4.0; it describes the source product.

FaIR thermal subset

fair-calibration.mjs extracts three jointly retained thermal parameter sets from FaIR’s published calibration 1.4.1 table. The original source’s Apache 2.0 licence is bundled as FaIR-Apache-2.0.txt. Conversion/selection is documented in scripts/REFLECT.md and reproduced by scripts/build_reflect_fair.py. These are deterministic thermal subsets, not the complete calibrated FaIR posterior model. FaIR’s thermal equations are implemented independently in JavaScript with no Python runtime dependency.

Geographic boundary fields and ocean reflection

SpeedyWeatherAssets and ECMWF ERA5 input provenance and quantisation are recorded in boundary-conditions.json; the EUPL 1.2 licence is bundled. ERA5 vegetation data attribution is CC BY 4.0. Jin et al. (2011) ocean reflection is adapted from the pinned SpeedyWeather gm/albedo implementation, with source attribution in jin-ocean.mjs and SpeedyWeather-EUPL-1.2.txt.

The learned land-albedo equations are supplied by Gregory Munday. Boundary input maps initialise their physical inputs; the prescribed albedo map is not used.