Abstract

Abstract. El Niño has two different flavors, eastern Pacific (EP) and central Pacific (CP) El Niños, with different global teleconnections. However, their different impacts on the interannual carbon cycle variability remain unclear. Here we compared the behaviors of interannual atmospheric CO2 variability and analyzed their terrestrial mechanisms during these two types of El Niños, based on the Mauna Loa (MLO) CO2 growth rate (CGR) and the Dynamic Global Vegetation Model's (DGVM) historical simulations. The composite analysis showed that evolution of the MLO CGR anomaly during EP and CP El Niños had three clear differences: (1) negative or neutral precursors in the boreal spring during an El Niño developing year (denoted as yr0), (2) strong or weak amplitudes, and (3) durations of the peak from December (yr0) to April during an El Niño decaying year (denoted as yr1) compared to October (yr0) to January (yr1) for a CP El Niño, respectively. The global land–atmosphere carbon flux (FTA) simulated by multi-models was able to capture the essentials of these characteristics. We further found that the gross primary productivity (GPP) over the tropics and the extratropical Southern Hemisphere (Trop + SH) generally dominated the global FTA variations during both El Niño types. Regional analysis showed that during EP El Niño events significant anomalous carbon uptake caused by increased precipitation and colder temperatures, corresponding to the negative precursor, occurred between 30° S and 20° N from January (yr0) to June (yr0). The strongest anomalous carbon releases, largely due to the reduced GPP induced by low precipitation and warm temperatures, occurred between the equator and 20° N from February (yr1) to August (yr1). In contrast, during CP El Niño events, clear carbon releases existed between 10° N and 20° S from September (yr0) to September (yr1), resulting from the widespread dry and warm climate conditions. Different spatial patterns of land temperatures and precipitation in different seasons associated with EP and CP El Niños accounted for the evolutionary characteristics of GPP, terrestrial ecosystem respiration (TER), and the resultant FTA. Understanding these different behaviors of interannual atmospheric CO2 variability, along with their terrestrial mechanisms during EP and CP El Niños, is important because the CP El Niño occurrence rate might increase under global warming.

Highlights

  • The El Niño–Southern Oscillation (ENSO), a dominant yearto-year climate variation, leads to a significant interannual variability in the atmospheric CO2 growth rate (CGR) (Bacastow, 1976; Keeling et al, 1995)

  • Owing to the diffuse light fertilization effect induced by the eruption of Mount Pinatubo in 1991 (Mercado et al, 2009), the Jena CarboScope s81 indicated that the terrestrial ecosystems had an anomalous uptake during the 1991–1992 El Niño event, making the Mauna Loa (MLO) CGR an anomalous decrease

  • We investigate the different impacts of eastern Pacific (EP) and central Pacific (CP) El Niño events on the interannual carbon cycle variability in terms of the composite analysis, based on the longterm MLO CGR and TRENDY multi-model simulations

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Summary

Introduction

The El Niño–Southern Oscillation (ENSO), a dominant yearto-year climate variation, leads to a significant interannual variability in the atmospheric CO2 growth rate (CGR) (Bacastow, 1976; Keeling et al, 1995). Ahlstrom et al (2015) further suggested ecosystems over the semi-arid regions played the most important role in the interannual variability of the land CO2 sink. This ENSO-related interannual carbon cycle variability may be enhanced under global warming, with approximately a 44 % increase in the sensitivity of terrestrial carbon flux to ENSO (Kim et al, 2017). Tropical climatic variations (especially in surface air temperature and precipitation) induced by ENSO and plant and soil physiological responses can largely account for interannual terrestrial carbon cycle variability (Zeng et al, 2005; Wang et al, 2016; Jung et al, 2017). Debates continue regarding which is the dominant climatic mechanism (temperature or precipitation) in the interannual variability of the terrestrial carbon cycle (Wang et al, 2013, 2014, 2016; Cox et al, 2013; Zeng et al, 2005; Ahlstrom et al, 2015; Qian et al, 2008; Jung et al, 2017)

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