###EMANUEL 2005  Accumulated annual duration
 
      ##LOAD HURRICANE DATA
	cwd.data<-"c:/climate/data/hurricane"
	load(file.path(cwd.data,"Track.ATL.tab"))
	dim(Track)
	load(file.path(cwd.data,"hurricane.ATL.tab"))
	dim(hurricane)
	hurricane$id<-10000+hurricane$id
	Track$wind.ms<- 0.5139861 * Track$wind # m sec-1 ##1 knot = 1.15 mph; #1 mi = 1609 m  #1 knot = 1.15* 1609/3600  =  0.5139861 m sec-1

	Track$id<-10000+Track$id
	Track.ATL<-Track;hurricane.ATL<-hurricane

	load(file.path(cwd.data,"Track.WPAC.tab"))
	dim(Track)
	load(file.path(cwd.data,"hurricane.WPAC.tab"))
	dim(hurricane)
	Track$wind.ms<- 0.5139861 * Track$wind # m sec-1
	Track$id<-20000+Track$id
	hurricane$id<-20000+hurricane$id
	Track.WPAC<-Track;hurricane.WPAC<-hurricane

#The accumulated annual duration of storms in the North Atlantic and
#western North Pacific has indeed increased by roughly 60% since
#1949, though this may partially reflect changes in reporting practices,
#as discussed in Methods. 

	Track<-rbind(Track.ATL,Track.WPAC)
	hurricane<-rbind(hurricane.ATL,hurricane.WPAC)

	hurricane$acc_duration<-NA
	temp<-(Track$wind.ms>18)&!is.na(Track$wind.ms)
 	test<-tapply(Track$qtr[temp],Track$id[temp],length)
	x<-as.numeric(names(test));
	temp<-(x<15000);K<-sum(x<15000)
 	hurricane$acc_duration [x[temp]-10000]<-c(test[x[temp]-10000])/4

	temp<-(x>15000)
 	hurricane$acc_duration[hurricane$id>15000][x[temp]-20000]<-c(test[x[temp]-20000])/4

	temp<-(hurricane$id<15000)
	acc_duration.ATL<-tapply(hurricane$acc_duration[temp],hurricane$year[temp],sum,na.rm=T)
	temp<-(hurricane$id>15000);sum(temp)
	acc_duration.WPAC<-tapply(hurricane$acc_duration[temp],hurricane$year[temp],sum,na.rm=T)
	acc_duration.TOT<-tapply(hurricane$acc_duration,hurricane$year,sum,na.rm=T)

	nf<-layout(array(1:3,dim=c(1,3)),widths=c(1.2,1.1,1.1))
	par(mar=c(3,3,1,1))
	plot(1949:2006,acc_duration.ATL[(1949:2006)-1850],type="h",xlim=c(1945,2006),ylim=c(0,300))
	lines(2005:2006,acc_duration.ATL[(2005:2006)-1850],type="h",col="red")
	par(mar=c(3,1,1,1))
	plot(1949:2006,acc_duration.WPAC[(1949:2006)-1944],type="h",xlim=c(1945,2006),ylim=c(0,300))
	lines(2005:2006,acc_duration.WPAC[(2005:2006)-1944],type="h",col="red")
	par(mar=c(3,1,1,1))
	plot(1949:2006,acc_duration.TOT[(1949:2006)-1850],type="h",xlim=c(1945,2006),ylim=c(0,300))
	lines(2005:2006,acc_duration.TOT[(2005:2006)-1850],type="h",col="red")


   ##FIGURE WITH TREND LINES
	nf<-layout(array(1:3,dim=c(1,3)),widths=c(1.2,1.1,1.1))
	par(mar=c(3,3,1,1))
	plot(1945:2006,acc_duration.ATL[(1945:2006)-1850],type="h",xlim=c(1945,2006),ylim=c(0,300))
	lines(2005:2006,acc_duration.ATL[(2005:2006)-1850],type="h",col="red")
	year0<-1949:2004;fm<-lm( acc_duration.ATL[(1949:2004)-1850]~year0);summary(fm); lines(year0,fm$fitted.values)
				fm$fitted.values[2004-1948]/fm$fitted.values[1] #1.158982 

	par(mar=c(3,1,1,1))
	plot(1945:2006,acc_duration.WPAC[(1945:2006)-1944],type="h",xlim=c(1945,2006),ylim=c(0,300))
	lines(2005:2006,acc_duration.WPAC[(2005:2006)-1944],type="h",col="red")
	year0<-1949:2004;fm<-lm( acc_duration.WPAC[(1949:2004)-1944]~year0);summary(fm); lines(year0,fm$fitted.values)
		fm$fitted.values[2004-1948]/fm$fitted.values[1] #0.8605246
		acc_duration.WPAC[2004-1944]/acc_duration.WPAC[1949-1944] #1.658683 

	par(mar=c(3,1,1,1))
	plot(1945:2006,acc_duration.TOT[(1945:2006)-1850],type="h",xlim=c(1944,2006),ylim=c(0,300))
	lines(2005:2006,acc_duration.TOT[(2005:2006)-1850],type="h",col="red")
	year0<-1949:2004;fm<-lm( acc_duration.TOT[(1949:2004)-1850]~year0);summary(fm); lines(year0,fm$fitted.values)
		fm$fitted.values[2004-1948]/fm$fitted.values[1] #0.9324065
		acc_duration.TOT[2004-1850]/acc_duration.TOT[1948-1850] #1.08
		mean(acc_duration.TOT[(2000:2004)-1850])/mean(acc_duration.TOT[(1946:1950)-1850]) # 1.473148
		lines(1946:1950, rep(mean(acc_duration.TOT[(1946:1950)-1850]),5),col="blue",lwd=2)	
		lines(2000:2004, rep(mean(acc_duration.TOT[(2000:2004)-1850]),5),col="blue",lwd=2)