INCIHUSA   20883
INSTITUTO DE CIENCIAS HUMANAS, SOCIALES Y AMBIENTALES
Unidad Ejecutora - UE
artículos
Título:
Snowpack variations since AD 1150 in the Andes of Chile and Argentina (30-37 S) inferred from rainfall, tree-ring and documentary records
Autor/es:
MASIOKAS, M.H.; VILLALBA, R.; CHRISTIE, D.; BETMAN, E.; LUCKMAN, B.H.; LE QUESNE, C.; PRIETO, M.R.; MAUGET, S.
Revista:
JOURNAL OF GEOPHYSICAL RESEARCH
Editorial:
AMER GEOPHYSICAL UNION
Referencias:
Año: 2012 vol. 117 p. 1 - 11
ISSN:
0148-0227
Resumen:
The Andean snowpack is the main source of freshwater and arguably the single most important natural resource for the populated, semi-arid regions of central Chile and central-western Argentina. However, apart from recent analyses of instrumental snowpack data, very little is known about the long term variability of this key natural resource. Here we present two complementary, annually-resolved reconstructions of winter snow accumulation in the southern Andes between 30°?37°S. The reconstructions cover the past 850 years and were developed using simple regression models based on snowpack proxies with different inherent limitations. Rainfall data from central Chile (very strongly correlated with snow accumulation values in the adjacent mountains) were used to extend a regional 1951?2010 snowpack record back to AD 1866. Subsequently, snow accumulation variations since AD 1150 were inferred from precipitation-sensitive tree-ring width series. The reconstructed snowpack values were validated with independent historical and instrumental information. An innovative time series analysis approach allowed the identification of the onset, duration and statistical significance of the main intra- to multi-decadal patterns in the reconstructions and indicates that variations observed in the last 60 years are not particularly anomalous when assessed in a multi-century context. In addition to providing new information on past variations for a highly relevant hydroclimatic variable in the southern Andes, the snowpack reconstructions can also be used to improve the understanding and modeling of related, larger-scale atmospheric features such as ENSO and the PDO.