Vekstsesong

Klimadata er prossesert av Markus F. Isaksen og dokumenteres i på en annen side. Her tar vi bare inn dataene og plotter de.

Disse dataene er klippet slik at det bare kommer fra fjellarealer.

Gjennomsnittlig lengde på vekstsesong

Dette er definert som antall dager med middeltemperature over 5 grader C.

Import

dat <- read_excel("P:/41201042_okologisk_tilstand_fastlandsnorge_2020_dataanaly/fjell2021/data/Klima/Vekstsesong/growthSeason_med.xlsx")

dat$year <- as.numeric(dat$year)
dat$value <- as.numeric(dat$value)

summary(dat$value)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   19.00   74.00   86.00   85.18   99.50  132.00

dat <- dat[dat$year>1960,]

dat$reg  <- as.factor(dat$reg)
table(dat$reg)

## 
## Midt-Norge Nord-Norge  Sørlandet Vestlandet  Østlandet 
##         60         60         60         60         60

Regner ut referanseverdien og 2SD av denne.

ref <- aggregate(data = 
      dat[dat$year %between% c(1961, 1990),],
                 value~reg,
                 FUN = mean)

upp <- aggregate(data = 
      dat[dat$year %between% c(1961, 1990),],
                 value~reg,
                 FUN = sd)
upp$value <- upp$value*2
ref$upp <- upp$value
rm(upp)

Trender

regOrder = c(
  "Nord-Norge",
  "Midt-Norge",
  "Østlandet",
  "Vestlandet",
   "Sørlandet"
             )

dat$ref <- ref$value[match(dat$reg, ref$reg)]
dat$diff <- dat$value-dat$ref
dat$col <- ifelse(dat$diff<0, "one", "two")

gg <- ggplot(data = dat,
       aes(x = year, y = diff))+
  geom_bar(stat="identity", aes( fill = col))+
  geom_hline(data = ref,
        aes(yintercept = -upp),
        linetype=2)+
  geom_hline(data = ref,
        aes(yintercept = upp),
        linetype=2)+
  geom_hline(yintercept = 0)+
  geom_smooth(data = dat,
       aes(x = year, y = diff))+
  scale_fill_hue(l=70, c=60)+
  theme_bw(base_size = 20)+
  ylab("Vekstsesong (antall dager)\n avvik fra 1961-1990")+
  xlab("")+
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))+
  #scale_x_continuous(breaks = brk, labels = lab)+
  guides(fill="none")+
  facet_wrap( .~ factor(reg, levels = regOrder),
              ncol=3)

png("../output/paavirkningsindikatorer/facet plot/vekstsesong normalisert tiddserie med barplot.png", 
    units="in", width=10, height=7, res=300)
gg
dev.off()

Stiplalinja er 2sd under forrige normalperioden.

Her er en forenklet figur i ØT-stilen.

Tbl <- dat
Tbl <- select(Tbl, reg, diff , year)
regOrder = c("Østlandet","Sørlandet","Vestlandet","Midt-Norge","Nord-Norge")
Tbl <- Tbl[order(match(Tbl$reg,regOrder),Tbl$year),]
minyear <- 1958
maxyear <- 2021
upperYlimit <- 80
lowYlimit   <- -40
yStep <- 40
move <- 0.2
legendPosition <- "top"
legendInset = 0
horizontal = TRUE
legendTextSize = 1.25
colours = c("#2DCCD3", "#004F71", "#7A9A01", "#93328E", "#FFB25B")
# Create loop factors
  uniq1 <- unique(unlist(Tbl$year))
  uniq2 <- unique(unlist(Tbl$reg))
  
  
  ### PLOT first Norway
  
  # Subset for region 'E'
  Norge <- subset(Tbl, reg=="Østlandet")

png("../output/paavirkningsindikatorer/enkel stil/vekstsesong.png", 
    units="in", width=12, height=7, res=300)  
  par(mar=c(4.5,6.5,2,2))
 # Plot for region = 'Norge'
  plot(
    Norge$diff~Norge$year, 
    ylab="Vekstsesong (antall dager)\navvik fra normalperioden (1961-1990)",
    xlab="",
    main="",
    xlim=c(minyear, maxyear),
    ylim=c(lowYlimit, upperYlimit),
    cex.main=1,
    cex.lab=1.5,
    cex.axis=1.5,
    type="n", 
    frame.plot=FALSE,
    axes=FALSE
  )
  
  # Axis 1 options
  axis(side=1, at=c(seq(1960, 2020, by=10)), cex.axis=1.5) 
  
  
  # Axis 2 options
  axis(side=2, at=seq(lowYlimit, upperYlimit, yStep), 
       labels=seq(lowYlimit, upperYlimit, yStep), 
       cex.axis=1.5)
  
  
  # Add lines
  lines(Norge$year+(move*(-2.5)), Norge$diff, col=colours[5], lwd=2, lty=1) 
  
  # Save temp points for later addition to plot
  temppoints <- data.frame(year = Norge$year, med = Norge$diff)
  
  
  
  # Empty temporary points data frame
  temppoints3 <- data.frame()
  
  
  
  ### Then plot loop per region
  for(n in 1:(length(uniq2)-1)){
    
    # Subset for region i
    quants <- subset(Tbl, reg==uniq2[n])
    
    # Add lines
    lines(quants$year+move*(n-2.5), quants$diff, col=colours[n], lwd=2, lty=1) 
    
    # Save temp points for later addition to plot
    temppoints2 <- data.frame(year = quants$year, med = quants$diff, reg = uniq2[n])
    temppoints3 <- rbind(temppoints3, temppoints2)
    
  }
  
 # # Add points for regions
 # for(n in 1:(length(uniq2)-1)){
 #   temppoints4 <- temppoints3[temppoints3$reg==uniq2[n],]
 #   points(temppoints4$year+move*(n-2.5),temppoints4$diff, pch=21, bg=colours[n], cex=1.5)
 # }
 # 
 # # Add points for Norge
 # points(temppoints$year+(move*(-2.5)),temppoints$diff, pch=21, bg=colours[5], cex=1.5)
  
  # Add legend to plot
  legend(legendPosition, legendPositionY, legend = regOrder, col = c(colours[5], colours[1:4]), 
         #bg = c(colours), 
         pch=16, lty=2,
         lwd=1.5, bty="n", inset=legendInset, title="", horiz = horizontal,
         cex=legendTextSize)
  
  # add reference line
  abline(h=0, col="black", lwd=2, lty=2)

dev.off()