Comment on acp-2022-506

Abstract

The global carbon cycle is experiencing continued perturbations via increases in atmospheric carbon concentrations. Greenhouse gas satellites that are designed to retrieve atmospheric carbon concentrations can help observe seasonal to interannual variations and sources of carbon dioxide. Recent work has shown that these satellites are further applicable beyond their design specifications for directly identifying and quantifying surface emissions at various spatial and temporal scales. For example, simple model translations of atmospheric carbon concentrations to surface carbon exchanges have been used to rapidly estimate surface methane fluxes from satellite observations of methane in the atmosphere. However, less attention has been placed on using satellite column CO2 retrievals to evaluate surface CO2 fluxes from the terrestrial biosphere at shorter timescales without more complex inversion models. Such applications could be useful to monitor, in near-real time, biosphere carbon fluxes during climatic anomalies like drought, heatwaves, and floods, before more complex terrestrial biosphere model outputs become available. Here, we explore the ability of Orbiting Carbon Observatory-2 (OCO-2) satellite retrievals of column-averaged dry air CO2 (XCO2) to directly detect and estimate terrestrial biosphere CO2 flux anomalies using a simple mass balance approach. Using a regional model simulation (CarbonTracker reanalysis) as a testbed, we first demonstrate that a previously developed, simple model can rapidly estimate monthly surface CO2 flux anomalies from atmospheric XCO2 estimates in the Western United States. The method is optimal when the chosen study domain is spatially extensive enough to account for atmospheric mixing and has favorable wind conditions with incoming wind contributions primarily from the same region. While errors in individual satellite measurements partially reduce the ability of OCO-2 satellite XCO2 to estimate more frequent, smaller surface CO2 flux anomalies, we find that OCO-2 XCO2 can often detect and estimate larger surface flux anomalies that are due to droughts and heatwaves. OCO-2 is thus useful for near real time monitoring of the monthly ecosystem behavior and health. Any noise reduction in forthcoming greenhouse gas satellites and/or the existence of large surface carbon anomalies will likely enhance the ability to rapidly estimate surface fluxes at shorter timescales scales.