What are the greenhouse gas observing system requirements for reducing fundamental biogeochemical process uncertainty? Amazon wetland CH4 emissions as a case study

Understanding the processes controlling terrestrial carbon fluxes is one of the grand challenges of climate science. Carbon cycle process controls are readily studied at local scales, but integrating local knowledge across extremely heterogeneous biota, landforms and climate space has proven to be extraordinarily challenging. Consequently, top-down or integral flux constraints at process-relevant scales are essential to reducing process uncertainty. Future satellite-based estimates of greenhouse gas fluxes – such as CO₂ and CH₄ – could potentially provide the constraints needed to resolve biogeochemical process controls at the required scales. Our analysis is focused on Amazon wetland CH₄ emissions, which amount to a scientifically crucial and methodologically challenging case study. We quantitatively derive the observing system (OS) requirements for testing wetland CH₄ emission hypotheses at a process-relevant scale. To distinguish between hypothesized hydrological and carbon controls on Amazon wetland CH₄ production, a satellite mission will need to resolve monthly CH₄ fluxes at a ∼333km resolution and with a ≤ 10mg CH₄ m⁻² day^₋₁ flux precision. We simulate a range of low-earth orbit (LEO) and geostationary orbit (GEO) CH₄ OS configurations to evaluate the ability of these approaches to meet the CH₄ flux requirements. Conventional LEO and GEO missions resolve monthly ∼333km Amazon wetland fluxes at a 17.0 and 2.7mg CH₄ m⁻² day⁻¹ median uncertainty level. Improving LEO CH₄ measurement precision by 2 would only reduce the median CH₄ flux uncertainty to 11.9mg CH₄ m⁻² day⁻¹. A GEO mission with targeted observing capability could resolve fluxes at a 2.0–2.4mg CH₄ m⁻² day⁻¹ median precision by increasing the observation density in high cloud-cover regions at the expense of other parts of the domain. We find that residual CH₄ concentration biases can potentially reduce the ∼5-fold flux CH₄ precision advantage of a GEO mission to a ∼2-fold advantage (relative to a LEO mission). For residual CH₄ bias correlation lengths of 100km, the GEO can nonetheless meet the  ≤ 10mg CH₄ m⁻² day⁻¹ requirements for systematic biases ≤10ppb. Our study demonstrates that process-driven greenhouse gas OS simulations can enhance conventional uncertainty reduction assessments by quantifying the OS characteristics required for testing biogeochemical process hypotheses.