AbsoluteTemperature {archetypal}

Global Absolute Temperature data set for Northern Hemisphere 1969-2013

Description

It is a subset from the data set which was used for publication [1], i.e. the Global Absolute Temperature for Northern Hemisphere (1800-2013) with only complete yearly observations included. Here we have kept the years 1969-2013.

Usage

data("AbsoluteTemperature")

Format

A data frame with 155862 observations on the following 18 variables.

Year

an integer vector of observation years from 1969 to 2013

Jan

numeric vector of monthly average temperature for January

Feb

numeric vector of monthly average temperature for February

Mar

numeric vector of monthly average temperature for March

Apr

numeric vector of monthly average temperature for April

May

numeric vector of monthly average temperature for May

Jun

numeric vector of monthly average temperature for June

Jul

numeric vector of monthly average temperature for July

Aug

numeric vector of monthly average temperature for August

Sep

numeric vector of monthly average temperature for September

Oct

numeric vector of monthly average temperature for October

Nov

numeric vector of monthly average temperature for November

Dec

numeric vector of monthly average temperature for December

long

a numeric vector for the geographical longitude: positive values for eastings

lat

a numeric vector for the geographical latitude: positive values for northings

h

a numeric vector for the altitude in metrs

stid

an integer vector with the station identity number

z

an integer vector with the relevant climate zone:

• 1, Tropical Zone

• 2, Subtropics

• 3, Temperate zone

• 4, Cold Zone

Details

That data set was the output of the procedure described in [1]. Initial data set was downloaded from [2] at 2014-12-17.

References

[1] Demetris T. Christopoulos. Extraction of the global absolute temperature for Northern Hemisphere using a set of 6190 meteorological stations from 1800 to 2013. Journal of Atmospheric and Solar-Terrestrial Physics, 128:70 - 83, 3 2015. doi:10.1016/j.jastp.2015.03.009

[2] Met Office Hadley Centre observations datasets, station data sets,
http:///www.metoffice.gov.uk/hadobs/crutem4/data/station_files/CRUTEM.4.2.0.0.station_files.zip
(last visited 17.12.14)

Examples

#
######################################
## Load absolute temperature data set:
######################################
#
data("AbsoluteTemperature")
df=AbsoluteTemperature
## Find proportions for climate zones
pcs=table(df$z)/dim(df)[1]
## Choose an approximate size of the new sample and compute resample sizes
N=1000
resamplesizes=as.integer(round(N*pcs))
sum(resamplesizes)
## Create the grouping matrix
groupmat=data.frame("Group_ID"=1:4,"Resample_Size"=resamplesizes)
groupmat
## Simple resampling:
resample_simple <- grouped_resample(in_data = df,grp_vector = "z",
grp_matrix = groupmat,replace = FALSE, option = "Simple", rseed = 20191119)
cat(dim(resample_simple),"\n")
## Dirichlet resampling:
resample_dirichlet <- grouped_resample(in_data = df,grp_vector = "z", 
grp_matrix = groupmat, replace = FALSE, option = "Dirichlet", rseed = 20191119)
cat(dim(resample_dirichlet),"\n")
#
#########################################
## Reproduce the results of 2015 article
#########################################
##
data("AbsoluteTemperature")
dh=AbsoluteTemperature
## Create yearly averages for every station
dh$avg = rowMeans(df[,month.abb[1:12]])
head(dh)
## Compute mean average of every year for all Northern Hemisphere
dagg=data.frame(aggregate(avg~Year,dh,function(x){c(mean(x),sd(x))}))
## Find used stations per year
daggn=aggregate(stid ~ Year,dh,length)
head(daggn)
tail(daggn)
## Combine all in a data frame
dagyears=data.frame(dagg$Year,daggn$stid,dagg$avg[,1],dagg$avg[,2])
colnames(dagyears)=c("Year","Nv","mu","Smu")
head(dagyears)
tail(dagyears)
#
## Compare with Table 7 (Columns: Year, Nv, mu_bar, Smu_bar), page 77 of article
## Extraction of the global absolute temperature for Northern Hemisphere 
## using a set of 6190 meteorological stations from 1800 to 2013
## https://doi.org/10.1016/j.jastp.2015.03.009
## and specifically the years 1969--2013