For an expensive simulator inside an MCMC DA setup like this, do you see amortised inference (SBI / neural posterior estimation) as more transformative than surrogating the forward model, since it attacks the per-pixel MCMC bottleneck directly?
A neural operator framing (FNO / DeepONet) mapping environmental forcings to ecosystem state feels appealing for spatial structure. But given your fluid mechanics work with discontinuities, have you found neural operators robust in systems with sharp spatial transitions (which would map to sharp biome boundaries here)?
Happy to share more context if useful. Thank you for your time.
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