Pan American interactions of Amazon precipitation, streamflow, and tree growth extremes

• Autor(a) principal: Stahle, D. W.
• Data de Publicação: 2020
• Outros Autores: Torbenson, M. C. A., Howard, I. M., Granato-Souza, D., Barbosa, A. C., Feng, S., Lopez, L., Villalba, R., Villanueva, J., Fernandes, K.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UFLA
• Texto Completo: http://repositorio.ufla.br/jspui/handle/1/46311
• topic: Amazon; Pan American climate; Tree-ring chronologies; Cedrela odorata; El Niño/Southern Oscillation (ENSO); Amazônia - Precipitação; Clima pan-americano; Dendrocronologia; El Niño Oscilação Sul (ENOS)

Rainfall and river levels in the Amazon are associated with significant precipitation anomalies of opposite sign in temperate North and South America, which is the dominant mode of precipitation variability in the Americas that often arises during extremes of the El Niño/Southern Oscillation (ENSO). This co-variability of precipitation extremes across the Americas is imprinted on tree growth and is detected when new tree-ring chronologies from the eastern equatorial Amazon are compared with hundreds of moisture-sensitive tree-ring chronologies in mid-latitude North and South America from 1759 to 2016. Pan-American co-variability exists even though the seasonality of precipitation and tree growth only partially overlaps between the Amazon and mid-latitudes because ENSO forcing of climate can persist for multiple seasons and can orchestrate a coherent response, even where the growing seasons are not fully synchronized. The tree-ring data indicate that the El Niño influence on inter-hemispheric precipitation and tree growth extremes has been strong and stable over the past 258-years, but the La Niña influence has been subject to large multi-decadal changes. These changes have implications for the dynamics and forecasting of hydroclimatic variability over the Americas and are supported by analyses of the available instrumental data and selected climate model simulations.