Does terrestrial drought explain global CO<sub>2</sub> flux anomalies induced by El Niño?

Abstract

Abstract. The El Niño Southern Oscillation is the dominant year-to-year mode of global climate variability. El Niño effects on terrestrial carbon cycling are mediated by associated climate anomalies, primarily drought, influencing fire emissions and biotic net ecosystem exchange (NEE). Here we evaluate whether El Niño produces a consistent response from the global carbon cycle. We apply a novel bottomup approach to estimating global NEE anomalies based on FLUXNET data using land cover maps and weather reanalysis. We analyze 13 years (1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)) of globally gridded observational NEE anomalies derived from eddy covariance flux data, remotely-sensed fire emissions at the monthly time step, and NEE estimated from an atmospheric transport inversion. We evaluate the overall consistency of biospheric response to El Niño and, more generally, the link between global CO 2 flux anomalies and El Niño-induced drought. Our findings, which are robust relative to uncertainty in both methods and time-lags in response, indicate that each event has a different spatial signature with only limited spatial coherence in Amazônia, Australia and southern Africa. For most regions, the sign of response changed across El Niño events. Biotic NEE anomalies, across 5 El Niño events, ranged from -1.34 to +0.98 Pg C yr −1 , whereas fire emissions anomalies were generally smaller in magnitude (ranging from -0.49 to +0.53 Pg C yr −1 ). Overall drought does not appear to impose consistent terrestrial CO 2 flux anomalies during El Niños, finding large variation in globally inCorrespondence to: C. R. Schwalm (cschwalm@clarku.edu) tegrated responses from -1.15 to +0.49 Pg C yr −1 . Despite the significant correlation between the CO 2 flux and El Niño indices, we find that El Niño events have, when globally integrated, both enhanced and weakened terrestrial sink strength, with no consistent response across events.

Evaluating terrestrial CO<sub>2</sub> flux diagnoses and uncertainties from a simple land surface model and its residuals

“…per year using a top-down approach, while Potter et al (2007) estimated uptake of 100 to 200 Pg CO 2 per year over the same period using a bottom-up method. Schwalm et al (2011) found conflicting estimates of global NEE anomalies estimated from upscaled FluxNet observations when compared against top-down inversion anomaly estimates.…”

“…This method could in concept be applied to NEE as well, though the machine learning approach is purely empirical and does not attempt to incorporate any ecological understanding. Schwalm et al (2010) and Schwalm et al (2011) present methods to globally upscale FluxNet observations by plant functional type. These methods depend on the commonly employed assumption that plant functional types are good predictors of landcape NEP.…”

Climate drivers of the terrestrial carbon cycle variability in Europe

“…In agreement with this, the El-Niño event of 2010 was associated with a higher CO 2 source in central Europe than the following La-Niña (negative ENSO) year (Bowman et al 2017), which instead led to very high NPP values across the continent (Bastos et al 2013). As a result, NEE over Europe shows a positive correlation with ENSO, albeit with important differences depending on region, El Niño event and method for calculating NEE (Schwalm et al 2011).…”

Synoptic Meteorology Explains Temperate Forest Carbon Uptake

“…The impact of annual to decadal oscillations in the climate system on terrestrial carbon uptake has been examined on local to global scales. For example, the effect of the phase of the El Niño-Southern Oscillation (ENSO) on global-scale photosynthesis and respiration, with ramifications for the global atmospheric CO 2 growth rate, has been particularly well studied (e.g., Gloor et al, 2018;Schwalm et al, 2011). These oscillations are themselves related to regional variability in multiple meteorological factors that may have additive or interactive effects on ecosystem carbon exchange (e.g., Jones et al, 2001;Knorr et al, 2007;Potter et al, 2003;Wharton et al, 2009).…”