EGU2020-4187
https://doi.org/10.5194/egusphere-egu2020-4187
EGU General Assembly 2020
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Capturing the influence of ENSO on land surface variables for Tropical South America

Lina M. Estupinan-Suarez1,2, Alexander Brenning2,3, Fabian Gans1, Guido Kraemer1, Carlos A. Sierra1, and Miguel D. Mahecha1,3,4
Lina M. Estupinan-Suarez et al.
  • 1Max Planck Institute for Biogeochemistry, Hans–Knoell–Str. 10, 07745 Jena, Germany
  • 2Department of Geography, Friedrich Schiller University Jena, Loebdergraben 32, 07743 Jena, Germany
  • 3Michael Stifel Center Jena for Data–Driven & Simulation Science, Ernst–Abbe–Platz 2, 07743 Jena, Germany
  • 4German Centre for Integrative Biodiversity Research (iDiv), Deutscher Platz 5e, 04103 Leipzig, Germany

The response of tropical vegetation to El Niño Southern Oscillation (ENSO) is considered a main driver of global annual atmospheric CO2 concentrations at inter-annual time scales. ENSO warm and cold phases, El Niño and La Niña respectively, cause contrasting climatic conditions along tropical South America. While some regions experience wetter conditions during El Niño, such as  the Pacific coast, others regions such as the Amazon are exposed to warmer and drier climates. Besides this spatial variation, the biospheric response also differs between ENSO type and intensity, overruling of local conditions and ecosystems types. Due to this complexity, there is a lack of understanding on what ecosystems and regions are systematically affected by ENSO and how biospheric variables respond. Here, we analysed the Northern region of tropical South America covering tropical savannas, forests, and mountainous ecosystems in several countries. To do this, we assessed different land surface (e.g. GPP, NDVI,  FPAR, LST) and climate data streams compiled in the regional Earth System Data Lab (ESDL, https://www.earthsystemdatalab.net/) at 1 km and 10 km pixel size from 2001 to 2015. We applied Isomap, a non-linear dimensionality reduction method in the time domain for high dimensional dynamical systems. Our analysis was constrained to the fourth order continental basins and dominant land cover types. Land use change pixels were disregarded. Further, a comparison of ENSO indexes was conducted among basins. We found that isomap components  are able to capture the biosphere variability related to ENSO in basins that have been historically affected such as Magdalena-Cauca valleys and the Caribbean region. Implementation of non-linear methods increases our understanding of ENSO impacts spatially in regions where events intensity and frequency is increasing, and effective ecosystems management is urgent.

How to cite: Estupinan-Suarez, L. M., Brenning, A., Gans, F., Kraemer, G., Sierra, C. A., and Mahecha, M. D.: Capturing the influence of ENSO on land surface variables for Tropical South America, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4187, https://doi.org/10.5194/egusphere-egu2020-4187, 2020.

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