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v2.4
2025-09-22 13:04:06
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astsa_2.4.tar.gz

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astsa_build/man/ENSO.Rd

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@@ -27,5 +27,16 @@ In addition, the News and ChangeLog files are at \url{https://github.com/nickpo
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The webpages for the texts and some help on using R for time series analysis can be found at
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\url{https://nickpoison.github.io/}.
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}
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\seealso{\code{\link{soi}}}
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\seealso{\code{\link{soi}, \link{ENSO}, \link{MEI}, \link{MEI2}}
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}
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\examples{
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# ENSO is a standardized index based on the sea level pressure differences between
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# Tahiti and Darwin, Australia. MEI is a similar index based on multiple factors.
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# As opposed to ENSO (and SOI), positive values of MEI correspond to warmer temperatures.
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tsplot(cbind(-ENSO, MEI), col=astsa.col(2*2:1, .6), addLegend=TRUE, spag=TRUE, lwd=1:2)
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tspairs(ts.intersect(-ENSO, MEI), location='top')
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}
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\keyword{datasets}

astsa_build/man/MEI.Rd

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\seealso{\code{\link{soi}, \link{ENSO}, \link{MEI2}}
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}
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\examples{
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tsplot(cbind(MEI,MEI2), spag=TRUE, col=astsa.col(2*2:1, .6), addLegend=TRUE, lwd=2)
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tsplot(cbind(MEI, MEI2), spag=TRUE, col=astsa.col(2*2:1, .6), addLegend=TRUE, lwd=2)
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tspairs(ts.intersect(MEI, MEI2), location='top')
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}
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\keyword{datasets}

astsa_build/man/MEI2.Rd

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Multivariate El Nino/Southern Oscillation Index (version 2)
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}
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\description{
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Bimonthly MEI values, starting with Dec1978/Jan1979 through Apr/May2025.
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Bimonthly MEI values (version 2), starting with Dec1978/Jan1979 through Apr/May2025.
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These data are similar to \code{MEI} and larger values correspond to warmer
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temperatures (unlike \code{soi} and \code{ENSO}).
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}
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\details{
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For details, see \kbd{https://www.psl.noaa.gov/enso/mei} and \code{\link{MEI}}, which is version 1.
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The key differences between MEI version 2 and version 1 are the input variables used, the source of the data, and the dates of the historical record. MEI version 2 relies on reanalysis data using modern numerical weather models to process and combine historical weather observations into a comprehensive, globally complete, and consistent dataset of past weather and climate and satellite data. This eliminates inconsistencies caused by relying on potentially less reliable ship observations, especially in earlier decades. The switch from cloud cover fraction to Outgoing Longwave Radiation (OLR) provides a more direct and accurate measurement of atmospheric convection, a critical component of ENSO. Despite the differences in input data, MEI version 2 and the original MEI version 1 are very highly correlated for the overlapping period.
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The key differences between MEI version 2 and version 1 are the input variables used, the source of the data, and the dates of the historical record. MEI version 2 relies on reanalysis data using modern numerical weather models to process and combine historical weather observations into a comprehensive, globally complete, and consistent dataset of past weather and climate and satellite data. This eliminates inconsistencies caused by relying on potentially less reliable ship observations, especially in earlier decades. The switch from cloud cover fraction to Outgoing Longwave Radiation (OLR) provides a more direct and accurate measurement of atmospheric convection, a critical component of ENSO. Despite the differences, MEI version 2 and the original MEI version 1 are very highly correlated for the overlapping period.
2020

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}
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\source{
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\seealso{\code{\link{soi}, \link{ENSO}, \link{MEI}}
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}
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\examples{
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tsplot(cbind(MEI,MEI2), spag=TRUE, col=astsa.col(2*2:1, .6), addLegend=TRUE, lwd=2)
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tsplot(cbind(MEI, MEI2), spag=TRUE, col=astsa.col(2*2:1, .6), addLegend=TRUE, lwd=2)
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tspairs(ts.intersect(MEI, MEI2), location='top')
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}
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\keyword{datasets}

astsa_build/man/soi.Rd

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@@ -23,6 +23,6 @@ In addition, the News and ChangeLog files are at \url{https://github.com/nickpo
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The webpages for the texts and some help on using R for time series analysis can be found at
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\url{https://nickpoison.github.io/}.
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}
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\seealso{\code{\link{rec}, \link{ENSO}}
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\seealso{\code{\link{rec}, \link{ENSO}, \link{MEI}, \link{MEI2}}
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}
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\keyword{datasets}
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\keyword{datasets}

astsa_build/man/tspairs.Rd

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}
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}
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\note{
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Use \code{ts.intersect} if lagged variables are included, otherwise \code{cbind} will work.
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Use \code{\link{lag1.plot}} and \code{\link{lag2.plot}} for lag plots. But if some lagged variables are included, use \code{ts.intersect}. If there are no lagged variables, \code{cbind} will work to combine individual series.
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}
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\value{
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Returns a matrix of scatterplots with time plots or histograms on the diagonal.
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tspairs(diff(log(econ5))[,1:3], col.diag=6, hist=FALSE, pt.size=1.5, lwl=2, gg=TRUE)
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tspairs(cbind(cmort,tempr,part), pch=9, scale=1.1)
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tspairs(ts.intersect(MEI, MEI2), location='top')
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}
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\keyword{ ts }
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