Contrasting carbon-climate interactions from interannual to long-term carbon-climate feedbacks across tropical continents
Shuang Ma, Jet Propulsion Laboratory / Caltech, shuang.ma@jpl.nasa.gov (Presenter)
Alexis Anthony Bloom, Jet Propulsion Lab, California Institute of Technology, abloom@jpl.nasa.gov
DAVID LAWRENCE, NCAR, dlawren@ucar.edu
The tropics is not only the dominant driver for the interannual variability of atmospheric CO2, but also drives the uncertainties of carbon-climate feedback predictions in the future. Thus, it is crucial to understand the interactions between carbon cycle and climate from seasonal to interannual time scales and its linkage with past and future carbon-climate feedbacks. Due to lack of observations and deficiencies in traditional optical sensors, even the seasonality of the photosynthesis is controversial. The emerging satellite observations and satellite constrained carbon fluxes, such as solar induced chlorophyll fluorescence (SIF) and net biosphere exchanges
(NBE), provide important new insights on the variability of carbon cycle across tropics. In this project, we propose to combine observations of remote sensing with a hierarchy of terrestrial biogeochemical models to address the following objectives:
1) how humid and seasonal forest, and savanna across tropical continents (tropical South America, Africa, Asia, and Australia) respond to temperature and water anomalies (i.e., drought) from seasonal to interannual time scales?
2) How drought and extreme events manifest in the interannual variability?
3) What are the possible mechanistic processes that control the response of tropical ecosystems to temperature and water anomaly, and how do these processes depend on spatiotemporal scales?
4) What are the quantitative relationships between carbon-climate sensitivities in interannual time scales and the long-term carbon climate feedbacks over the tropical continents?
In this poster presentation, we will report the progress of our team in understanding the first three objectives by analyzing a broad set of observations and results from data-constrained models.
Associated Project(s):
Poster Location ID: 1-34
Presentation Type: Poster
Session: Poster Session 1
Session Date: Tue (May 9) 5:00-7:00 PM
CCE Program: TE