Atmosphere-Land Bridge between the Pacific and Tropical North Atlantic SST's through the Amazon River basin during the 2005 and 2010 droughts.

The present work uses a new approach to causal inference between complex systems called the Recurrence Measure of Conditional Dependence (RMCD) based on the recurrence plots theory, in order to study the role of the Amazon River basin (AM) as a land-atmosphere bridge between the Niño 3.0 region in the Pacific Ocean and the Tropical North Atlantic. Two anomalous droughts in the Amazon River basin were selected, one mainly attributed to the warming of the Tropical North Atlantic (2005) and the other to a warm phase of El Niño-Southern Oscillation (2010). The results of the RMCD analysis evidence the distinctive behavior in the causal information transferred between the two oceanic regions during the two extreme droughts, suggesting that the land-atmosphere bridge operating over the AM is an active hydroclimate mechanism at interannual timescales, and that the RMCD analysis may be an ancillary resort to complement early warning systems.

Constructing regional climate networks in the Amazonia during recent drought events.

Climate networks are powerful approaches to disclose tele-connections in climate systems and to predict severe climate events. Here we construct regional climate networks from precipitation data in the Amazonian region and focus on network properties under the recent drought events in 2005 and 2010. Both the networks of the entire Amazon region and the extreme networks resulted from locations severely affected by drought events suggest that network characteristics show slight difference between the two drought events. Based on network degrees of extreme drought events and that without drought conditions, we identify regions of interest that are correlated to longer expected drought period length. Moreover, we show that the spatial correlation length to the regions of interest decayed much faster in 2010 than in 2005, which is because of the dual roles played by both the Pacific and Atlantic oceans. The results suggest that hub nodes in the regional climate network of Amazonia have fewer long-range connections when more severe drought conditions appeared in 2010 than that in 2005.

Recurrence measure of conditional dependence and applications.

Identifying causal relations from observational data sets has posed great challenges in data-driven causality inference studies. One of the successful approaches to detect direct coupling in the information theory framework is transfer entropy. However, the core of entropy-based tools lies on the probability estimation of the underlying variables. Here we propose a data-driven approach for causality inference that incorporates recurrence plot features into the framework of information theory. We define it as the recurrence measure of conditional dependence (RMCD), and we present some applications. The RMCD quantifies the causal dependence between two processes based on joint recurrence patterns between the past of the possible driver and present of the potentially driven, excepting the contribution of the contemporaneous past of the driven variable. Finally, it can unveil the time scale of the influence of the sea-surface temperature of the Pacific Ocean on the precipitation in the Amazonia during recent major droughts.

Role of hysteresis in stomatal aperture dynamics.

Stomata are pores responsible for gas exchange in leaves. Several experiments indicate that stomata synchronize into clusters or patches. The patches' coordination may produce oscillations in stomatal conductance. Previous studies claim to reproduce some experimental results. However, none was able to explain the variety of behavior observed in the stomatal dynamics. Recently, Ferraz and Prado suggested a realistic geometry of vein distribution. Although it reproduces the patches, no oscillation was observed and the patches remain static. Without exploring significant details, the authors stated that hysteresis in stomatal aperture could explain several experimental features. In this paper, the hysteresis hypothesis is further explored through the concept of hysteretic operators. We have shown that the hysteresis assumption is sufficient to obtain dynamical patches and oscillations in stomatal conductance. The robustness of this hypothesis is tested by using different hysteresis operators. The model analysis reveals a dependence between the period of oscillation in stomatal conductance and the water deficit between the leaf and the environment. This underlying feature of the model might inspire further experiments to test this hypothesis.