### ##LOAD DATA ### #this uses BAS scrape for surface and reverse-engineered Steig recon_aws for AWS. Two surface series need to be deducted (Marion, Gough) #version here is not quite file compatible with Steig. See Nic L on Dec 2002 problem # data from Terra Nova Bay appears to be same as Mario_Zucchelli # download.file("http://www.climateaudit.info/data/steig/Data.tab","Data.tab",mode="wb") load("Data.tab") download.file("http://www.climateaudit.info/data/steig/Info.tab","Info.tab",mode="wb") load("Info.tab") download.file("http://www.climateaudit.info/data/steig/recon_aws.tab","recon_aws.tab",mode="wb") load("recon_aws.tab") dimnames(recon_aws)[[2]]=Info$aws_grid$id download.file("http://www.climateaudit.info/data/steig/jeff.tab","temp.dat",mode="wb");load("temp.dat") #matlab compilation #surface surf=Data$surface surf=window(surf,start=1957,end=c(2006,12)) #ends in 2006 per Steig surf <- surf[,-26] #deletes column 26 - Marion surf <- surf[,-17] #deletes column 17 - Gough dim(surf) #600 42 sanom=as.matrix(surf) for (i in 1:42) sanom[,i]=anom(surf[,i],reference=1957:2007) #Steig probably used different reference period and this can be experimented with later (ny=ncol(sanom)) #42 #AWS reverse engineered (rather than READER scrape) anoms =window(recon_aws, start = 1980);dim(anoms) #324 63 dat_aws = window(Data$aws[,colnames(recon_aws)],start=1980,end=c(2006,12)); dim(dat_aws) #324 63 anoms[is.na(dat_aws)] =NA #apply(anoms,2,mean,na.rm=T) #some are zero, some aren't (nx=ncol(anoms)) #63 # combine anomalies anomalies=ts.union(anoms,sanom) dimnames(anomalies)[[2]]=c( dimnames(anoms)[[2]],dimnames(sanom)[[2]]) dim(anomalies) #600 105