Journal
EARTH AND SPACE SCIENCE
Volume 10, Issue 12, Pages -Publisher
AMER GEOPHYSICAL UNION
DOI: 10.1029/2023EA003126
Keywords
El Nino Southern Oscillation; carbon cycle; New Guinea Rainforest
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This study explores the variations of Solar-Induced Fluorescence (SIF), CO2, and precipitation during El Nino Southern Oscillation (ENSO) events in the tropical Indo-Pacific region compared to other times. The results show that there is less precipitation, more sinking air, lower SIF, and higher carbon dioxide during El Nino events. The spatial analysis suggests that these changes are related to the reduction of photosynthetic activities and an increase in biomass burning, leading to higher atmospheric CO2 levels.
Over the tropical Indo-Pacific, we explore the variations of Solar-Induced Fluorescence (SIF), CO2, and precipitation during El Nino Southern Oscillation (ENSO) events verse other times. Based on various data sets, we analyze the time series of deseasonalized precipitation, vertical velocity, SIF, and CO2 across the Indo-Pacific region. Our analysis reveals that there is less precipitation, more sinking air, lower SIF, and higher carbon dioxide over the Indo-Pacific region during the El Nino events compared to other times. We also explore the spatial patterns of different variables to gain a deeper understanding of their relationships. The spatial analysis suggests that less precipitation resulting from predominant sinking air not only leads to lower SIF values by reducing photosynthetic activities but also triggers more biomass burning, which contribute to an increase in atmospheric CO2 levels across most areas of the Indo-Pacific region. The comparative study between observational analyses and numerical simulation by the NOAA CarbonTracker model indicates that the model can simulate the increase of atmospheric column CO2 during the El Nino event, although there are some difficulties in capturing the correct spatial pattern. The results of this study can significantly enhance our understanding of the spatial-temporal variabilities of atmospheric CO2 concentration and the observational characteristics can be used to enhance models. Furthermore, the complex interactions between ENSO and other variables revealed in this study improve our understanding of how ENSO influences the biosphere and carbon cycle.
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