Surface flux inference is a method for determining planetary surface gas fluxes from telescope spectra by inverting a coupled photochemical-climate-model, rather than reading off atmospheric gas abundances directly.
Problem It Addresses
Standard atmospheric retrievals measure the abundance of gases like CH₄ or O₂ in an exoplanet atmosphere. But photochemical reactions, climate feedbacks, and atmospheric escape can dramatically alter abundance regardless of the surface source rate — making abundance an unreliable proxy for biological or geological activity. Surface flux inference bypasses this ambiguity by recovering the rate at which gases are emitted or absorbed at the surface.
Method
A forward-running photochemical-climate-model is used to predict spectra under a range of surface flux scenarios. The model is then inverted against an observed spectrum (Bayesian retrieval) to constrain which surface fluxes are consistent with the data.
Key Results (Wogan et al. 2026)
- Demonstrated on a synthetic 10-transit jwst NIRSpec Prism spectrum of trappist-1-e with an Archean-Earth-like biosphere.
- CH₄ surface flux constrained to within ~1.5 orders of magnitude (68% credible interval).
- ~80% of the CH₄ flux posterior consistent with CH₄-producing metabolism.
- Bottleneck: requires accurate knowledge of the host star’s near-UV spectrum.
See src-biosignature-gas-flux-inference-2026-04.
Significance
Surface flux inference advances beyond the “parallel interpretations” problem flagged by sara-seager et al. (src-jwst-biosignature-prospects-2025): even if atmospheric abundance is ambiguous, the inferred surface flux can assign probabilistic weights to biological vs. abiotic explanations.