SST Gap-Filling: Does the WGS84 Ellipsoid Improve Results?¶
This project investigates whether accounting for the WGS84 ellipsoid geometry when resampling sea-surface temperature (SST) data to HEALPix improves the accuracy of gap-filling with scattering-transform synthesis (FOSCAT).
Motivation¶
Standard HEALPix assumes the Earth is a perfect sphere. In reality, the Earth is an oblate ellipsoid (equatorial radius ~21 km larger than polar). The healpix-geo and healpix-resample packages extend HEALPix to the WGS84 ellipsoid.
For CMB analysis on the celestial sphere, the spherical assumption is exact. For Earth-observation data like SST, the mismatch between sphere and ellipsoid could introduce systematic biases in HEALPix cell areas and neighbour relationships, potentially degrading gap-filling quality.
Experiment¶
We compare FOSCAT gap-filling RMSE (vs Copernicus Marine L4 reference) using:
Sphere -- standard HEALPix pixelisation
WGS84 -- HEALPix on the WGS84 ellipsoid
See the full analysis in SST Gap-Filling: Does the WGS84 Ellipsoid Improve Results?.
FORRT nanopublication chain¶
The full provenance of this question-rooted study is recorded as a six-step FORRT nanopublication chain on the Science Live platform — research question → declarative answer → FORRT claim → study → outcome → CiTO citations. Each step is independently citable and machine-readable.
Headline assertion — machine-readable: This work
cito:extendschain #3 (fiesta-scattering-sst),cito:usesMethodInDelouis et al. 2022, ANDcito:creditsthe IGARSS 2024 Pangeo tutorialThree relationships in one citation nanopublication: extends the sphere-only baseline at chain #3 to operational resolution with the sphere-vs-WGS84 comparison; uses the FOSCAT scattering method from Delouis 2022; credits Jean-Marc Delouis’s IGARSS 2024 Pangeo tutorial as the SST workflow source.
The five preceding nanopubs build the provenance ladder up to that citation:
| Step | Type | Nanopub URI |
|---|---|---|
| 1 | PCC Research Question | https:// |
| 2 | AIDA sentence (Nanodash namespace) | https:// |
| 3 | FORRT Claim (data quality) | https:// |
| 4 | FORRT Replication Study | https:// |
| 5 | FORRT Replication Outcome (Validated, Moderate) | https:// |
| 6 | CiTO extends chain #3 + usesMethodIn Delouis 2022 + credits IGARSS 2024 tutorial | https:// |
References¶
Delouis, J.-M. et al. (2022). Astronomy & Astrophysics, 668, A122. DOI:10.1051/0004-6361/202244566
- Delouis, J.-M., Allys, E., Gauvrit, E., & Boulanger, F. (2022). Non-Gaussian modelling and statistical denoising of Planck dust polarisation full-sky maps using scattering transforms. Astronomy & Astrophysics, 668, A122. 10.1051/0004-6361/202244566