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Atmospheric Radiative Transfer Inversion L1-416

Environmental ScienceAtmospheric opticsδ=5 · challengingL_DAG = 4📋 Stub — not mineable
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Unclaimed Principle — open for contribution

This Principle is declared in the catalog but has no reference solver, no pinned dataset, and is not registered on-chain. There is no reward pool. Submitting a cert against this Principle today will record the cert for reproducibility but pay zero PWM.

To claim it as a Bounty #7 contribution: open a PR adding (1) a reference solver, (2) ≥1 dataset pinned to IPFS, (3) updates to the L3 manifest with dataset CIDs. After verifier-agent triple-review, the founders' 3-of-5 multisig signs PWMRegistry.register() and the Principle becomes mineable.

Forward model E

Atmospheric Radiative Transfer Inversion: Atmospheric RT inversion: retrieve temperature, ozone, and trace gas profiles from hyperspectral satellite radiances. The forward operator produces the measurement through a 3-node primitive DAG (S.rt.disort_solver…); recovery is posed as a nonlinear_inverse problem. Difficulty tier delta=5 with effective condition number kappa_eff~500; cloud_contamination, nonLTE_effect set the accuracy floor at the Omega boundary. See the forward_model field for the closed-form equation.

L-DAG

S.rt.disort_solver -> L.linear_op -> O.optimal_estimation.rodgers
S.rt.disort_solverL.linear_opO.optimal_estimation.rodgers

Well-posedness W

Existence:
true
Uniqueness:
true
Stability:
conditional
κ:
10000

Existence of the recovered 1D_atmospheric_profile is guaranteed within the declared Omega bounds. Uniqueness holds on the measurement-supported subspace; out-of-support modes are controlled by declared priors. Stability is conditionally stable (kappa_eff ~= 500); cloud_contamination dominates the stability cliff; the remaining mismatch parameters contribute higher-order bias terms. Thermal gaussian sets the irreducible data-fidelity floor.

Solvability C

Solver class:
classical [optimal_estimation_Rodgers or NLLS_Marquardt]
Convergence rate q:
2
Complexity:
O(N_layers ** 2 * N_nu) per Jacobian calculation per iteration

Specs (0)

No L2 specs registered yet for this principle.