Calibration and multi-source consistency analysis of reconstructed precipitation series in Portugal since the early 17th century

• Autor(a) principal: Santos, João A
• Data de Publicação: 2015
• Outros Autores: Carneiro, Maria F, Alcoforado, Maria Joao, Leal, Sofia, Luz, Ana L, Camuffo, Dario, Zorita, Eduardo
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10451/28288
• topic: long-term variability; paleoclimatic simulations; Portugal; precipitation proxies; reconstructed precipitation; tree-rings

A calibration of reconstructed winter, spring and autumn precipitation series in Portugal from 1600 onwards is undertaken in the present study using new instrumental sources for the period of 1815–2012. As summer precipitation in Portugal is scarce and irregular, it is not considered. A consistency analysis of the calibrated time series is then undertaken using: (1) precipitation indices for Portugal in 1675–1799; (2) teleconnections between seasonal precipitation and large-scale atmospheric flow; (3) two paleoclimatic experiments (ERIK1 and ERIK2), generated from a global/regional climate model chain (ECHO-G/MM5); and (4) tree-ring records from oak trees in Portugal (Serra do Buçaco). These are the first multi-centennial records of treering growth in Portugal (the earliest series begin in 1675). General agreement is found between indices and calibrated precipitation for their common period on an annual basis. Overall, the atmospheric teleconnection patterns are dynamically coherent between the instrumental and pre-instrumental periods. The inter-annual to inter-decadal variability in the calibrated series reveals similar distributions as in the paleoclimatic simulations. Low-frequency variability in spring precipitation is validated by 12 tree-ring series. This study provides calibrated seasonal precipitation series in Portugal from 1600 onwards, revealing high consistency with several independent sources for winter and spring, enabling future applications to climate research.