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New insights on land surface-atmosphere feedbacks over tropical South America at interannual timescales
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1  Universidad Nacional de Colombia, Sede Medellín, Department of Geosciences and Environment, Facultad de Minas, Medellín, Colombia.


Using monthly data for the period 1979-2010, we study the dynamics and strength of land surface-atmosphere feedbacks (LAFs) among variables involved in the heat and moisture fluxes, at interannual timescales for Tropical South America (TropSA). The variables include precipitation, surface air temperature, specific humidity at 925 hPa, evaporation, and estimates of volumetric soil water content. Using a dimensional reduction, we apply a Maximum Covariance Analysis (MCA) to rank the relative contributions to LAFs and group the time series into Maximum Covariance States (MCS) with common mechanisms among variables. We estimate linear (Pearson correlations) and non-linear (information transfer and causality) coupling metrics among pairs of variables to configure the structure of linkages. The main MCS associated with LAFs over TropSA are strongly influenced by ENSO, and the meridional and equatorial SSTs modes over the Atlantic and Indian Oceans. ENSO favors a unimodal behavior, with center of action in the Amazon River basin, while SSTs over the Tropical North Atlantic result in a dipole between northern and southern TropSA. Results show that soil moisture plays a leading role in regulating heat and water anomalies, and provides the memory of the atmosphere-driven processes and their subsequent influence. Thus, soil moisture is fundamental and leads up to 9 month-lags whereby ENSO enhances the interannual connectivity and memory of LAFs in 25% with respect to the mode influenced by TNA. Within the identified multivariate structure, evaporation and soil moisture enhance the interannual connectivity of the whole set of variables since both variables exhibit more frequent two-way feedbacks with the remaining variables.

Keywords: Soil Moisture, Feedbacks, Tropical South America, Interannual Variability
Comments on this paper
Raquel Nieto
data period
This is an interesting work and the authors explain it with detail.
I have only a question: why the data period stops in 2010?

Juan Bedoya-Soto
Dear Dr. Raquel Nieto,

The data period is a constraint from the ERA Interim Land. This reanalysis product ranges from 1979 to 2010. Although GPCC and ERA Interim offer more recent data, we must use a common period for our analysis.

Thanks for your comment and interest,