On the Ability of Space‐Based Passive and Active Remote Sensing Observations of CO2 to Detect Flux Perturbations to the Carbon Cycle. Issue 2 (29th January 2018)

• Record Type: Journal Article
• Authors: Crowell, Sean M. R.; Randolph Kawa, S.; Browell, Edward V.; Hammerling, Dorit M.; Moore, Berrien; Schaefer, Kevin; Doney, Scott C.
• Is Part Of: Journal of geophysical research. Volume 123:Issue 2(2018)
• Page Start: 1460
• Page End: 1477
• Publication Date: 2018-01-29
• Subjects: ASCENDS -- OCO‐2 -- Permafrost -- Carbon Emissions -- Satellite Remote Sensing -- Fossil Fuel; Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1002/2017JD027836
• Languages: English
• ISSNs: 2169-897X

Abstract

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. Plain Language Summary: Active and passive remote sensors show the potential to provide unprecedented information on the carbon cycle. With the all‐season sampling, active remote sensors are more capable of constraining high‐latitude emissions. The reduced sensitivity to cloud and aerosol also makes active sensors more capable of providing information in cloudy and polluted scenes with sufficient accuracy. These experiments account for errors that are fundamental to the top‐down approach for constraining emissions, and even including these sources of error, we show that satellite remote sensors are critical for understanding the carbon cycle. Key Points: Satellite remote sensors are critical for constraining carbon cycle processes Active remote sensing shows the potential to provide a stronger constraint than passive remote sensing Regional flux perturbations are detectable at the annual and seasonal scales with sufficient precision even in the presence of model errors