Interannual variability of the atmospheric CO2 growth rate: roles of precipitation and temperature
- 1International Institute for Earth System Science, Nanjing University, Nanjing, China
- 2Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
- 3Department of Atmospheric and Oceanic Science and Earth System Science Interdisciplinary Center, University of Maryland, College Park, Maryland, USA
- 4Nanjing University of Information Science & Technology, Nanjing, China
Abstract. The interannual variability (IAV) in atmospheric CO2 growth rate (CGR) is closely connected with the El Niño–Southern Oscillation. However, sensitivities of CGR to temperature and precipitation remain largely uncertain. This paper analyzed the relationship between Mauna Loa CGR and tropical land climatic elements. We find that Mauna Loa CGR lags precipitation by 4 months with a correlation coefficient of −0.63, leads temperature by 1 month (0.77), and correlates with soil moisture (−0.65) with zero lag. Additionally, precipitation and temperature are highly correlated (−0.66), with precipitation leading by 4–5 months. Regression analysis shows that sensitivities of Mauna Loa CGR to temperature and precipitation are 2.92 ± 0.20 PgC yr−1 K−1 and −0.46 ± 0.07 PgC yr−1 100 mm−1, respectively. Unlike some recent suggestions, these empirical relationships favor neither temperature nor precipitation as the dominant factor of CGR IAV. We further analyzed seven terrestrial carbon cycle models, from the TRENDY project, to study the processes underlying CGR IAV. All models capture well the IAV of tropical land–atmosphere carbon flux (CFTA). Sensitivities of the ensemble mean CFTA to temperature and precipitation are 3.18 ± 0.11 PgC yr−1 K−1 and −0.67 ± 0.04 PgC yr−1 100 mm−1, close to Mauna Loa CGR. Importantly, the models consistently show the variability in net primary productivity (NPP) dominates CGR, rather than heterotrophic respiration. Because previous studies have proved that NPP is largely driven by precipitation in tropics, it suggests a key role of precipitation in CGR IAV despite the higher CGR correlation with temperature. Understanding the relative contribution of CO2 sensitivity to precipitation and temperature has important implications for future carbon-climate feedback using such ''emergent constraint''.