bomregions2021: Australian and Related Historical Annual Climate Data, by...
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bomregions2021

R Documentation

Australian and Related Historical Annual Climate Data, by Region

Description

Australian regional temperature data, Australian regional rainfall data, and Annual SOI, are given for the years 1900-2021. The regional rainfall and temperature data are area-weighted averages for the respective regions. The Southern Oscillation Index (SOI) is the difference in barometric pressure at sea level between Tahiti and Darwin.

Usage

data("bomregions2021")

Format

These data frames contains the following columns:

Year: Year
seAVt: Southeastern region average temperature (degrees C)
southAVt: Southern temperature
eastAVt: Eastern temperature
northAVt: Northern temperature
swAVt: Southwestern temperature
qldAVt: temperature
nswAVt: temperature
ntAVt: temperature
saAVt: temperature
tasAVt: temperature
vicAVt: temperature
waAVt: temperature
mdbAVt: Murray-Darling basin temperature
ausAVt: Australian average temperature, area-weighted mean
seRain: Southeast Australian annual rainfall (mm)
southRain: Southern rainfall
eastRain: Eastern rainfall
northRain: Northern rainfall
swRain: Southwest rainfall
qldRain: Queensland rainfall
nswRain: NSW rainfall
ntRain: Northern Territory rainfall
saRain: South Australian rainfall
tasRain: Tasmanian rainfall
vicRain: Victorian rainfall
waRain: West Australian rainfall
mdbRain: Murray-Darling basin rainfall
ausRain: Australian average rainfall, area weighted
SOI: Annual average Southern Oscillation Index
sunspot: Yearly mean sunspot number
co2mlo: Moana Loa CO2 concentrations, from 1959
co2law: Moana Loa CO2 concentrations, 1900 to 1978
CO2: CO2 concentrations, composite series
avDMI: Annual average Dipole Mode Index, for the Indian Ocean Dipole, from 1950

Source

Australian Bureau of Meteorology web pages:

Go to the url http://www.bom.gov.au/climate/change/, choose timeseries to display, then click "Download data"

For the SOI data, go to the url http://www.bom.gov.au/climate/enso/.

The CO2 series co2law, for Law Dome ice core data. is from https://data.ess-dive.lbl.gov/portals/CDIAC/.

The Moana Loa CO2 series co2mlo is from Dr. Pieter Tans, NOAA/ESRL (https://gml.noaa.gov/ccgg/trends/)

The series CO2 is a composite series, obtained by adding 0.46 to the Law data for 1900 to 1958, then following this with the Moana Loa data that is avaiable from 1959. The addition of 0.46 brings the average of the Law data into agreement with that for the Moana Loa data for the period 1959 to 1968.

The yearly mean sunspot number is a subset of one of several sunspot series that are available from WDC-SILSO, Royal Observatory of Belgium, Brussels. https://www.sidc.be/silso/datafiles/

The dipole mode index data are from https://ds.data.jma.go.jp/tcc/tcc/products/elnino/index/Readme_iod.txt. Note also https://stateoftheocean.osmc.noaa.gov/sur/ind/dmi.php, which has details of several other such series.

References

D.M. Etheridge, L.P. Steele, R.L. Langenfelds, R.J. Francey, J.-M. Barnola and V.I. Morgan, 1998, Historical CO2 records from the Law Dome DE08, DE08-2, and DSS ice cores, in Trends: A Compendium of Data on Global Change, on line at Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tenn., U.S.A.

Lavery, B., Joung, G. and Nicholls, N. 1997. An extended high-quality historical rainfall dataset for Australia. Australian Meteorological Magazine, 46, 27-38.

Nicholls, N., Lavery, B., Frederiksen, C.\ and Drosdowsky, W. 1996. Recent apparent changes in relationships between the El Nino – southern oscillation and Australian rainfall and temperature. Geophysical Research Letters 23: 3357-3360.

SIDC-team, World Data Center for the Sunspot Index, Royal Observatory of Belgium, Monthly Report on the International Sunspot Number, online catalogue of the sunspot index: https://www.sidc.be/silso/datafiles

Examples

plot(ts(bomregions2021[, c("mdbRain","SOI")], start=1900),
     panel=function(y,...)panel.smooth(bomregions2021$Year, y,...))
avrain <- bomregions2021[,"mdbRain"]
xbomsoi <- with(bomregions2021, data.frame(Year=Year, SOI=SOI,
                cuberootRain=avrain^0.33))
xbomsoi$trendSOI <- lowess(xbomsoi$SOI, f=0.1)$y
xbomsoi$trendRain <- lowess(xbomsoi$cuberootRain, f=0.1)$y
xbomsoi$detrendRain <-
  with(xbomsoi, cuberootRain - trendRain + mean(trendRain))
xbomsoi$detrendSOI <-
  with(xbomsoi, SOI - trendSOI + mean(trendSOI))
## Plot time series avrain and SOI: ts object xbomsoi
plot(ts(xbomsoi[, c("cuberootRain","SOI")], start=1900),
     panel=function(y,...)panel.smooth(xbomsoi$Year, y,...),
     xlab = "Year", main="", ylim=list(c(250, 800),c(-20,25)))
par(mfrow=c(1,2))
rainpos <- pretty(xbomsoi$cuberootRain^3, 6)
plot(cuberootRain ~ SOI, data = xbomsoi,
     ylab = "Rainfall (cube root scale)", yaxt="n")
axis(2, at = rainpos^0.33, labels=paste(rainpos))
mtext(side = 3, line = 0.8, "A", adj = -0.025)
with(xbomsoi, lines(lowess(cuberootRain ~ SOI, f=0.75)))
plot(detrendRain ~ detrendSOI, data = xbomsoi,
     xlab="Detrended SOI", ylab = "Detrended rainfall", yaxt="n")
axis(2, at = rainpos^0.33, labels=paste(rainpos))
with(xbomsoi, lines(lowess(detrendRain ~ detrendSOI, f=0.75)))
mtext(side = 3, line = 0.8, "B", adj = -0.025)
par(mfrow=c(1,1))

DAAG documentation built on May 29, 2024, 9:13 a.m.