FeedbackTS (version 1.5)

rain.feedback.stats: Statistics of rain feedback in Australia

Description

Feedback and change-in-feedback statistics based on 88 rainfall data series colllected in 88 sites across Australia.

Usage

data(rain.feedback.stats)

Format

A data frame with 88 observations on the following 8 variables.

Station.number:

a numeric vector providing the identifiers of the meteorological stations.

Keyday.threshold:

a numeric vector providing for each meteorological station the threshold value above which a day is considered as a key day.

Longitude:

a numeric vector with longitudes of the meteorological stations.

Latitude:

a numeric vector with latitudes of the meteorological stations.

Feedback.whole.period:

a numeric vector providing for each meteorological station the temporal average of after-before differences around key days calculated from the whole time series.

Feedback.before.1960:

a numeric vector providing for each meteorological station the temporal average of after-before differences around key days calculated from the time series right-truncated in 1960 (data from year 1960 were excluded).

Feedback.after.or.in.1960:

a numeric vector providing for each meteorological station the temporal average of after-before differences around key days calculated from the time series left-truncated in 1960 (data from year 1960 were kept).

Change.in.feedback:

a numeric vector providing the difference between Feedback.after.or.in.1960 and Feedback.before.1960.

Details

The statistics in this data set were computed using the feedback.stats function.

References

Soubeyrand, S., Morris, C. E. and Bigg, E. K. (2014). Analysis of fragmented time directionality in time series to elucidate feedbacks in climate data. Environmental Modelling and Software 61: 78-86.

Examples

# NOT RUN {
#### load data of feedback and change-in-feedback indices in 88 sites across Australia
data(rain.feedback.stats)

#### spatial coordinates of the 88 sites and corresponding feedback index 
#### computed from the whole data series
coord=rain.feedback.stats[,3:4]
stat1=rain.feedback.stats[["Feedback.whole.period"]]

#### map of feedback index 
map.statistic(coord,stat1,cex.circles=c(3,0.2),
   region=list(border="Australia",xlim=c(110,155)),
   legend=list(x=c(rep(114,3),rep(123,2)),y=-c(37,39.5,42,37,39.5),
      xtext=c(rep(114,3),rep(123,2))+1,ytext=-c(37,39.5,42,37,39.5),digits=2),
   main="Feedback")
# }