Atmospheric CO₂ Observations Reveal Strong Correlation Between Regional Net Biospheric Carbon Uptake and Solar‐Induced Chlorophyll Fluorescence

Abstract

Recent studies have shown the promise of remotely sensed solar‐induced chlorophyll fluorescence (SIF) in informing terrestrial carbon exchange, but analyses have been limited to either plot level (~1 km2) or hemispheric/global (~108 km2) scales due to the lack of a direct measure of carbon exchange at intermediate scales. Here we use a network of atmospheric CO2 observations over North America to explore the value of SIF for informing net ecosystem exchange (NEE) at regional scales. We find that SIF explains space‐time NEE patterns at regional (~100 km2) scales better than a variety of other vegetation and climate indicators. We further show that incorporating SIF into an atmospheric inversion leads to a spatial redistribution of NEE estimates over North America, with more uptake attributed to agricultural regions and less to needleleaf forests. Our results highlight the synergy of ground‐based and spaceborne carbon cycle observations.

Fundamentals of data assimilation applied to biogeochemistry

“…We see similar developments in the estimation of CO 2 fluxes (e.g. Tans et al, 1990vs Chevallier et al, 2010 and ocean productivity (Balkanski et al, 1999cf. Brasseur et al, 2009.…”

“…They are still widely used (e.g. Fang et al, 2014;Fang and Michalak, 2015;Henne et al, 2016;Saeki and Patra, 2017;Chen et al, 2017;Shiga et al, 2018;Wang et al, 2018). Originally Jacobians were generated with multiple forward runs, each run corresponding to a desired source component.…”

“…An overview of the principal ideas of particle filtering and improvements upon the basic filter is given by Doucet et al (2001) while van Leeuwen (2009) reviews its application in geophysical systems. Stordal et al (2011) point to some further generalisations which may combine advantages of the EnKF and particle filter.…”

Fundamentals of Data Assimilation applied to biogeochemistry

“…Classical analytical methods (Section 6.4) were the first workhorse for flux inversions of inert tracers like CO 2 where the problem is linear. They are still widely used (e.g., Fang et al, 2014;Fang and Michalak, 2015;Henne et al, 2016;Saeki and Patra, 2017;Chen et al, 2017;Shiga et al, 2018;Wang et al, 2018). Originally Jacobians were generated with multiple forward runs, each run corresponding to a desired source component.…”

A Lagrangian approach towards extracting signals of urban CO<sub>2</sub> emissions from satellite observations of atmospheric column CO<sub>2</sub> (XCO<sub>2</sub>): X-Stochastic Time-Inverted Lagrangian Transport model (“X-STILT v1”)

“…Previous studies have demonstrated the potential for detecting and deriving urban CO 2 emission signals from satellite CO 2 observations, in the form of XCO 2 enhancements above the background, without making use of much atmospheric transport information (Hakkarainen et al, 2016;Kort et al, 2012;Schneising et al, 2013;Silva and Arellano, 2017;Silva et al, 2013). However, due to this simplification, the linkage between derived urban CO 2 emission signals and upstream sources is tenuous, as downwind XCO 2 can be enhanced not only by near-field upwind urban activities (e.g., traffic, houses, and power plants/industries), but also by regional-scale advection of upwind sources/sinks.…”