aliceramsden/multiple_gas_inverse_model: multiple_gas_inverse_model v1.0

A top-down inverse model for estimating regional greenhouse gas emissions, using secondary observations for source attribution. A Metropolis-Hastings-style MCMC sampler is used to find most-likely solutions to a cost function, which incorporates: prior estimates of emissions and boundary conditions; emissions sensitivity matrices; observations and their associated uncertainties; and model error hyperparameters. Secondary observations can be either: Mole fractions observations (which require the inclusion of direct emission ratios, to link these observations to emissions of the primary gas) Isotope ratio observations (which require the inclusion of isotopic source signatures, to link these observations to emissions of the primary gas) The model code includes options for: Synthetic data tests, where observations are created from known emissions fields Different prior PDFs Various processing options for the inversion outputs.