Abstract
Atmospheric CO2 concentrations are sensitive to the effects of climate extremes on carbon sources and sinks of the land biosphere. Therefore, extreme changes of atmospheric CO2 can be used to identify anomalous sources and sinks of carbon. In this study, we develop a spatiotemporal extreme change detection method for atmospheric CO2 concentrations using column-averaged CO2 dry air mole fraction (XCO2) retrieved from the Greenhouse gases Observing SATellite (GOSAT) from 1 June 2009 to 31 May 2016. For extreme events identified, we attributed the main drivers using surface environmental parameters, including surface skin temperature, self-calibrating Palmer drought severity index, burned area, and gross primary production (GPP). We also tested the sensitivity of XCO2 response to changing surface CO2 fluxes using model simulations and Goddard Earth Observing System (GEOS)-Chem atmospheric transport. Several extreme high XCO2 events are detected around mid-2010 over Eurasia and in early 2016 in the tropics. The magnitudes of extreme XCO2 increases are around 1.5–1.8 ppm in the Northern Hemisphere and 1.2–1.4 ppm in Southern Hemisphere. The spatiotemporal pattern of detected high XCO2 events are similar to patterns of local surface environmental parameter extremes. The extreme high XCO2 events often occurred during periods of increased temperature, severe drought, increased wildfire or reduced GPP. Our sensitivity tests show that the magnitude of detectable anomalies varies with location, for example 25% or larger anomalies in local CO2 emission fluxes are detectable in tropical forest, whereas anomalies must be half again as large in mid-latitudes (~37.5%). In conclusion, we present a method for extreme high XCO2 detection, and large changes in land CO2 fluxes. This provides another tool to monitor large-scale changes in the land carbon sink and potential feedbacks on the climate system.
Highlights
The global mean atmospheric CO2 concentration is increasing on average at a rate of 2.38 ppm yr−1 in recent years, due to anthropogenic CO2 emissions in excess of carbon uptake by land and ocean sinks [1]
In contrast to earlier studies, which concentrated on surface environment variables (such as fraction of absorbed photosynthetically active radiation, gross primary production (GPP), surface temperature and so on) [29,30,31], we focus on using atmospheric CO2 concentration for extreme event detection
We aim to develop an approach for detecting spatiotemporal continuum high XCO2 anomalies using satellite XCO2 observations, which are related to terrestrial biosphere anomalies of CO2 uptake and release
Summary
The global mean atmospheric CO2 concentration is increasing on average at a rate of 2.38 ppm yr−1 in recent years, due to anthropogenic CO2 emissions in excess of carbon uptake by land and ocean sinks [1]. Carbon sources/sinks from the terrestrial biosphere contribute most to the inter-annual variability [3]. The change of atmospheric CO2 concentration is impacted by anomalous terrestrial biosphere CO2 uptake or release, caused by anomalous weather events, and intensifying climate changes [5,6]. Understanding the relationship between the CO2 concentration changes response to climate events, makes an important contribution to carbon sources and sinks change detection and forecasting [7]
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