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Remote SST Forcing and Local Land-Atmosphere Moisture Coupling as Drivers of Amazon Temperature and Carbon Cycle Variability

Presentation Date
Thursday, December 14, 2017 at 12:05pm
New Orleans Ernest N. Morial Convention Center - 293-294



Interannual variability of climatic conditions in the Amazon rainforest is associated with El Niño-Southern Oscillation (ENSO) and ocean-atmosphere interactions in the North Atlantic. Sea surface temperature (SST) anomalies in these remote ocean regions drive teleconnections with Amazonian surface air temperature (T), precipitation (P), and net ecosystem production (NEP). While SST-driven NEP anomalies have been primarily linked to T anomalies, it is unclear how much the T anomalies result directly from SST forcing of atmospheric circulation, and how much result indirectly from decreases in precipitation that, in turn, influence surface energy fluxes. Interannual variability of P associated with SST anomalies lead to variability in soil moisture (SM), which would indirectly affect T via partitioning of turbulent heat fluxes between the land surface and the atmosphere. To separate the direct and indirect influence of the SST signal on T and NEP, we performed a mechanism-denial experiment to decouple SST and SM anomalies. We used the Accelerated Climate Modeling for Energy (ACMEv0.3), with version 5 of the Community Atmosphere Model and version 4.5 of the Community Land Model. We forced the model with observed SSTs from 1982–2016.

We found that SST and SM variability both contribute to T and NEP anomalies in the Amazon, with relative contributions depending on lag time and location within the Amazon basin. SST anomalies associated with ENSO drive most of the T variability at shorter lag times, while the ENSO-driven SM anomalies contribute more to T variability at longer lag times. SM variability and the resulting influence on T anomalies are much stronger in the eastern Amazon than in the west. Comparing modeled T with observations demonstrate that SST alone is sufficient for simulating the correct timing of T variability, but SM anomalies are necessary for simulating the correct magnitude of the T variability. Modeled NEP indicated that variability in carbon fluxes results from both SST and SM anomalies. As with T, SM anomalies affect NEP at a much longer lag time than SST anomalies. These results highlight the role of land-atmosphere coupling in driving climate variability within the Amazon, and suggest that land atmospheric coupling may amplify and delay carbon cycle responses to ocean-atmosphere teleconnections.

Funding Program Area(s)