bomregions2021 {DAAG}

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))