How has climate responded to natural perturbations?

Wolff, Eric; Harrison, Sandy P.; Knutti, Reto; Goñi, María Fernanda Sánchez; Wild, Oliver; Daniau, Anne-Laure; Masson‐Delmotte, Valérie; Prentice, I. Colin; Spahni, Renato

doi:10.1017/cbo9780511921155.006

Cited by 2 publications

(2 citation statements)

References 177 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The pollen time series analysed in this example span the interval between 73,000 and 15,000 years before present (BP), thus covering the last glacial period (LGP). The climate during the LGP was characterised by millennial variability with "abrupt" transitions between cold stadials and warm interstadials known as Dansgaard-Oeschger (D-O) cycles (Dansgaard et al, 1993;Wolff et al, 2012). The D-O cycles are characterised by rather fast atmospheric warming events over Greenland of up to 16 • C that occur within a period of approximately 40 years, followed by gradual cooling leading to the cold stadials (?Wolff et al, 2012).…”

Section: Abrupt Climate Changes During the Last Glacialmentioning

confidence: 99%

“…The climate during the LGP was characterised by millennial variability with "abrupt" transitions between cold stadials and warm interstadials known as Dansgaard-Oeschger (D-O) cycles (Dansgaard et al, 1993;Wolff et al, 2012). The D-O cycles are characterised by rather fast atmospheric warming events over Greenland of up to 16 • C that occur within a period of approximately 40 years, followed by gradual cooling leading to the cold stadials (?Wolff et al, 2012). Figure 6 illustrates the variations in the pollen percentages of the temperate forest, a type of vegetation typical of moderate, warm, wet climates.…”

Section: Abrupt Climate Changes During the Last Glacialmentioning

confidence: 99%

See 1 more Smart Citation

BINCOR: An R package for Estimating the Correlation between Two Unevenly Spaced Time Series

Polanco-Martínez¹,

Medina‐Elizalde²,

Goñi³

et al. 2019

The R Journal

View full text Add to dashboard Cite

This paper presents a computational program named BINCOR (BINned CORrelation) for estimating the correlation between two unevenly spaced time series. This program is also applicable to the situation of two evenly spaced time series not on the same time grid. BINCOR is based on a novel estimation approach proposed by Mudelsee (2010) for estimating the correlation between two climate time series with different timescales. The idea is that autocorrelation (e.g. an AR1 process) means that memory enables values obtained on different time points to be correlated. Binned correlation is performed by resampling the time series under study into time bins on a regular grid, assigning the mean values of the variable under scrutiny within those bins. We present two examples of our BINCOR package with real data: instrumental and paleoclimatic time series. In both applications BINCOR works properly in detecting well-established relationships between the climate records compared.

show abstract

Section: Abrupt Climate Changes During the Last Glacialmentioning

confidence: 99%