On the Ability of Space‐Based Passive and Active Remote Sensing Observations of CO₂ to Detect Flux Perturbations to the Carbon Cycle

Abstract

Space‐borne observations of CO2 are vital to gaining understanding of the carbon cycle in regions of the world that are difficult to measure directly, such as the tropical terrestrial biosphere, the high northern and southern latitudes, and in developing nations such as China. Measurements from passive instruments such as GOSAT and OCO‐2, however, are constrained by solar zenith angle limitations as well as sensitivity to the presence of clouds and aerosols. Active measurements such as those in development for the Active Sensing of CO2 Emissions over Nights, Days and Seasons (ASCENDS) mission show strong potential for making measurements in the high‐latitude winter and in cloudy regions. In this work we examine the enhanced flux constraint provided by the improved coverage from an active measurement such as ASCENDS. The simulation studies presented here show that with sufficient precision, ASCENDS will detect permafrost thaw and fossil fuel emissions shifts at annual and seasonal time scales, even in the presence of transport errors, representativeness errors, and biogenic flux errors. While OCO‐2 can detect some of these perturbations at the annual scale, the seasonal sampling provided by ASCENDS provides the stronger constraint.

The impact of improved aerosol priors on near-infrared measurements of carbon dioxide

“…In addition to validation against the highly accurate but sparsely located TCCON, a set of global CO 2 models was assembled in order to examine spatial errors. We co-located 30 827 OCO-2 soundings in time and space with a suite of nine global carbon models (Peters et al, 2007;Feng et al, 2011;Baker et al, 2010;Liu et al, 2017;Crowell et al, 2018;Rödenbeck, 2005;Inness et al, 2013;Basu et al, 2013;Schuh et al, 2019). Only points where all the models agreed to within 1 ppm of X CO 2 were used.…”

Space‐Based Observations for Understanding Changes in the Arctic‐Boreal Zone

“…Detecting CH 4 and CO 2 over the ABZ is particularly difficult for passive sensors, which rely on reflected sunlight, because of low sun elevation angles in spring and fall and no sun in winter, and because of atmospheric scatter from clouds and aerosols. Early inversion results from OCO‐2 suggest that it is challenging to accurately infer fluxes in high‐latitude regions because of seasonal changes in coverage (e.g., Crowell et al, ). Although the surface albedo of snow and ice are high in the visible and near infrared regions, they are very low in the SW infrared CO 2 and CH 4 bands, resulting in lower signal‐to‐noise ratios from passive sensors when observing over these surfaces.…”

“…Because they do not depend on reflected sunlight, the planned polar‐orbiting active sensors (i.e., lidar) will significantly augment the data from polar‐orbiting passive sensors in the ABZ by providing more precise CH 4 and CO 2 column data with better temporal coverage and complementary spatial coverage (e.g., Crowell et al, ; Hammerling et al, ; Kawa et al, ; Kawa et al, ). This is important as carbon fluxes in the ABZ occur in all seasons, times of day, and sky conditions (e.g., Oechel et al, ; Treat et al, ; Zona et al, ).…”

The Potential of the Geostationary Carbon Cycle Observatory (GeoCarb) to Provide Multi-scale Constraints on the Carbon Cycle in the Americas

“…where F sun π is the top of atmosphere solar irradiance, and α E is the "effective albedo" that incorporates surface reflectance and attenuation by scatterers: Here α is the MODIS MCD43C3 white sky albedo (Band 6 for CO 2 and Band 7 for CH 4 /CO), m is the airmass factor (i.e., m = 1 cos (SZA) + 1 cos (ZA) for the solar zenith angle SZA and sensor zenith angle ZA), and τ is the OD of clouds and aerosols, taken from 5 • × 5 • monthly histograms of CALIPSO total OD (e.g., as was used in Crowell et al, 2018). The noise is derived from the instrument model:…”