INVESTIGADORES
DIAZ Leandro Baltasar
congresos y reuniones científicas
Título:
Disentangling the causes of evapotranspiration long-term changes in southeastern South America
Autor/es:
RUSCICA, ROMINA C.; SÖRENSSON, ANNA A.; DÍAZ, LEANDRO B.; VERA, CAROLINA S.
Reunión:
Conferencia; 13th meeting of the International Conference on Southern Hemisphere Meteorology and Oceanography; 2022
Resumen:
Evapotranspiration shapes climate variability, trends, and extremes; is driven by precipitation and radiation, and constrained by land surface conditions. Modelled evapotranspiration over 1950-2010 and its response to atmospheric variability and land-cover changes are explored in three South American regions: upper and lower La Plata Basin and the South Atlantic Convergence Zone. These regions show notable precipitation trends and variability and have undergone intense land-cover changes since 1950. Evapotranspiration was obtained from a new ensemble of 24 offline South American simulations from stand-alone dynamic global vegetation models in the context of the CLIMAX project (http://www.climax-sa.org). Summer evapotranspiration trends and anomalies in simulations with and without land-cover changes and for the different phases of the subtropical precipitation dipole and as well as the ENSO are explored. Regarding regions, three different results were obtained: (1) In upper La Plata Basin, land-cover changes forced a negative summer evapotranspiration trend; (2) in lower La Plata Basin, evapotranspiration was driven by precipitation variability showing a positive summer trend and marked seasonal anomalies during ENSO and dipole active phases; (3) and in the South Atlantic Convergence Zone, the high evapotranspiration uncertainty across ensemble members impeded finding robust results. Overall, the seasonal cycle of evapotranspiration was more related to the dynamic global vegetation models structure while the evapotranspiration trends were found to be more dependent on the forcing datasets. Our study highlights the importance of using multiple models and atmospheric forcings instead of relying on the results of a single model or forcing.