Temperatur
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 sommertemperatur
aar_err <- read_excel("P:/41201042_okologisk_tilstand_fastlandsnorge_2020_dataanaly/fjell2021/data/Klima/Gjennomsnitt sommer/meanSummer_med.xlsx")
head(aar_err)## # A tibble: 5 x 5
## area variable norm_med `norm_-2SD` `norm_+2SD`
## <chr> <chr> <chr> <chr> <chr>
## 1 nord-norge meanSummer 8.34891319274902 6.01967116537407 10.678155220124
## 2 midt-norge meanSummer 9.03913021087646 7.05840245733628 11.0198579644167
## 3 østlandet meanSummer 7.33695650100708 5.35622874746689 9.31768425454727
## 4 vestlandet meanSummer 7.26956510543823 5.28883735189805 9.25029285897842
## 5 sørlandet meanSummer 7.88369560241699 5.95869667152147 9.80869453331252Her ser vi medianen og variasjonen til denne variablene under forrige normalperiode 1961-1990. La oss normalisere disse.
names(aar_err) <- c("Region", "variable", "median", "low", "upp")
aar_err$low <- as.numeric(aar_err$low)
aar_err$upp <- as.numeric(aar_err$upp)
aar_err$median <- as.numeric(aar_err$median)
aar_err$low <-
aar_err$low - aar_err$median
aar_err$upp <-
aar_err$upp - aar_err$medianaar <- read_excel("P:/41201042_okologisk_tilstand_fastlandsnorge_2020_dataanaly/fjell2021/data/Klima/Gjennomsnitt sommer/meanSummer_diff.xlsx")
head(aar)## # A tibble: 6 x 7
## year `nord-norge` `midt-norge` østlandet vestlandet sørlandet variable
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <chr>
## 1 1957 0.180 0.465 -0.0641 -0.441 -0.0185 meanSummer
## 2 1958 -0.289 0.274 -0.215 -0.0761 -0.134 meanSummer
## 3 1959 0.253 1.32 1.27 0.863 1.11 meanSummer
## 4 1960 2.16 1.47 0.868 1.21 0.360 meanSummer
## 5 1961 1.25 0.0152 -0.391 -0.855 -0.900 meanSummer
## 6 1962 -1.48 -1.71 -2.06 -1.94 -2.32 meanSummerHer ser vi gjennomsnittlig årsnedbør siste 5 år minus gjennomsnittet i normalperioden.
setDT(aar)
aar <- melt(aar,
measure.vars = names(aar)[2:6],
id.vars = "year",
variable.name = "Region")levels(aar$Region)## [1] "nord-norge" "midt-norge" "østlandet" "vestlandet" "sørlandet"aar$Region <- plyr::revalue(aar$Region,
c("midt-norge"="Midt-Norge",
"nord-norge"="Nord-Norge",
"østlandet"="Østlandet",
"sørlandet"="Sørlandet",
"vestlandet"="Vestlandet"))
aar_err$Region <- plyr::revalue(aar_err$Region,
c("midt-norge"="Midt-Norge",
"nord-norge"="Nord-Norge",
"østlandet"="Østlandet",
"sørlandet"="Sørlandet",
"vestlandet"="Vestlandet"))regOrder = c(
"Nord-Norge",
"Midt-Norge",
"Østlandet",
"Vestlandet",
"Sørlandet"
)
aar$col <- ifelse(aar$value<0, "one", "two")fig_temp <- ggplot()+
geom_bar(data = aar,
aes(x = year,
y = value,
fill=col),
stat="identity")+
geom_smooth(data = aar,
aes(x = year,
y = value))+
ylab("Gj. sommertemperatur (\u00B0C)\navvik fra 1961-1990")+
xlab("Ã…r")+
geom_hline(yintercept=0)+
geom_hline(data = aar_err, aes(yintercept=low), linetype=2)+
geom_hline(data = aar_err, aes(yintercept=upp), linetype=2)+
guides(fill="none")+
theme_bw(base_size = 20)+
theme(
axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))+
facet_wrap(.~factor(Region, levels = regOrder))Eksporter figurer
png("../output/paavirkningsindikatorer/facet plot/sommertemperatur.png",
units="in", width=10, height=7, res=300)
fig_temp
dev.off()
Tbl <- aar
names(Tbl) <- c("year", "reg", "diff", "col")
regOrder = c("Østlandet","Sørlandet","Vestlandet","Midt-Norge","Nord-Norge")
Tbl <- Tbl[order(match(Tbl$reg,regOrder),Tbl$year),]
minyear <- 1958
maxyear <- 2021
upperYlimit <- 6
lowYlimit <- -3
yStep <- 3
move <- 0.2
legendPosition <- "top"
legendInset = 0
horizontal = TRUE
legendTextSize = 1.25
colours = c("#2DCCD3", "#004F71", "#7A9A01", "#93328E", "#FFB25B")
# Create loop factors
uniq1 <- unique(unlist(Tbl$year))
uniq2 <- unique(unlist(Tbl$reg))
### PLOT first Norway
# Subset for region 'E'
Norge <- subset(Tbl, reg=="Østlandet")
png("../output/paavirkningsindikatorer/enkel stil/sommertemperatur.png",
units="in", width=12, height=7, res=300)
par(mar=c(4.5,6.5,2,2))
# Plot for region = 'Norge'
plot(
Norge$diff~Norge$year,
ylab="Gj. sommertemperatur (\u00B0C)\navvik fra 1961-1990",
xlab="",
main="",
xlim=c(minyear, maxyear),
ylim=c(lowYlimit, upperYlimit),
cex.main=1,
cex.lab=1.5,
cex.axis=1.5,
type="n",
frame.plot=FALSE,
axes=FALSE
)
# Axis 1 options
axis(side=1, at=c(seq(1960, 2020, by=10)), cex.axis=1.5)
# Axis 2 options
axis(side=2, at=seq(lowYlimit, upperYlimit, yStep),
labels=seq(lowYlimit, upperYlimit, yStep),
cex.axis=1.5)
# Add lines
lines(Norge$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()
Gjennomsnittlig vintertemperatur
aar_err <- read_excel("P:/41201042_okologisk_tilstand_fastlandsnorge_2020_dataanaly/fjell2021/data/Klima/Gjennomsnitt vinter/meanWinter_med.xlsx")
head(aar_err)## # A tibble: 5 x 5
## area variable norm_med `norm_-2SD` `norm_+2SD`
## <chr> <chr> <chr> <chr> <chr>
## 1 nord-norge meanWinter -9.73777770996094 -13.7265553047341 -5.74900011518778
## 2 midt-norge meanWinter -7.30219793319702 -12.5833931354104 -2.0210027309836
## 3 østlandet meanWinter -10.0911111831665 -15.2347916670446 -4.94743069928845
## 4 vestlandet meanWinter -7.08131885528564 -11.4595302757992 -2.7031074347721
## 5 sørlandet meanWinter -7.86111116409302 -12.2325960347023 -3.48962629348374names(aar_err) <- c("Region", "variable", "median", "low", "upp")
aar_err$low <- as.numeric(aar_err$low)
aar_err$upp <- as.numeric(aar_err$upp)
aar_err$median <- as.numeric(aar_err$median)
aar_err$low <-
aar_err$low - aar_err$median
aar_err$upp <-
aar_err$upp - aar_err$medianaar <- read_excel("P:/41201042_okologisk_tilstand_fastlandsnorge_2020_dataanaly/fjell2021/data/Klima/Gjennomsnitt vinter/meanWinter_diff.xlsx")
head(aar)## # A tibble: 6 x 7
## year `nord-norge` `midt-norge` østlandet vestlandet sørlandet variable
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <chr>
## 1 1957 -1.54 -2.93 -1.82 -0.786 -0.719 meanWinter
## 2 1958 0.877 -0.319 -0.236 -0.0131 0.293 meanWinter
## 3 1959 -0.749 -1.41 -1.08 0.169 -0.249 meanWinter
## 4 1960 1.07 0.657 0.730 1.40 1.84 meanWinter
## 5 1961 -0.733 0.0628 0.632 0.958 0.983 meanWinter
## 6 1962 -1.12 -2.32 -3.01 -2.34 -2.36 meanWinterHer ser vi gjennomsnittlig årsnedbør siste 5 år minus gjennomsnittet i normalperioden.
setDT(aar)
aar <- melt(aar,
measure.vars = names(aar)[2:6],
id.vars = "year",
variable.name = "Region")levels(aar$Region)## [1] "nord-norge" "midt-norge" "østlandet" "vestlandet" "sørlandet"aar$Region <- plyr::revalue(aar$Region,
c("midt-norge"="Midt-Norge",
"nord-norge"="Nord-Norge",
"østlandet"="Østlandet",
"sørlandet"="Sørlandet",
"vestlandet"="Vestlandet"))
aar_err$Region <- plyr::revalue(aar_err$Region,
c("midt-norge"="Midt-Norge",
"nord-norge"="Nord-Norge",
"østlandet"="Østlandet",
"sørlandet"="Sørlandet",
"vestlandet"="Vestlandet"))regOrder = c(
"Nord-Norge",
"Midt-Norge",
"Østlandet",
"Vestlandet",
"Sørlandet"
)
aar$col <- ifelse(aar$value<0, "one", "two")fig_temp <- ggplot()+
geom_bar(stat="identity",
data = aar,
aes(x = year,
y = value,
fill=col))+
geom_smooth(data = aar,
aes(x = year,
y = value))+
ylab("Gj. vintertemperatur (\u00B0C)\navvik fra 1961-1990")+
xlab("Ã…r")+
geom_hline(yintercept=0)+
geom_hline(data = aar_err, aes(yintercept=low), linetype=2)+
geom_hline(data = aar_err, aes(yintercept=upp), linetype=2)+
theme_bw(base_size = 20)+
theme(
axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))+
guides(fill="none")+
facet_wrap(.~factor(Region, levels = regOrder))Eksporter figurer
png("../output/paavirkningsindikatorer/facet plot/vintertemperatur.png",
units="in", width=10, height=7, res=300)
fig_temp
dev.off()
Tbl <- aar
names(Tbl) <- c("year", "reg", "diff", "col")
regOrder = c("Østlandet","Sørlandet","Vestlandet","Midt-Norge","Nord-Norge")
Tbl <- Tbl[order(match(Tbl$reg,regOrder),Tbl$year),]
minyear <- 1958
maxyear <- 2021
upperYlimit <- 12
lowYlimit <- -6
yStep <- 6
move <- 0.2
legendPosition <- "top"
legendInset = 0
horizontal = TRUE
legendTextSize = 1.25
colours = c("#2DCCD3", "#004F71", "#7A9A01", "#93328E", "#FFB25B")
# Create loop factors
uniq1 <- unique(unlist(Tbl$year))
uniq2 <- unique(unlist(Tbl$reg))
### PLOT first Norway
# Subset for region 'E'
Norge <- subset(Tbl, reg=="Østlandet")
png("../output/paavirkningsindikatorer/enkel stil/vintertemperatur.png",
units="in", width=12, height=7, res=300)
par(mar=c(4.5,6.5,2,2))
# Plot for region = 'Norge'
plot(
Norge$diff~Norge$year,
ylab="Gj. vintertemperatur (\u00B0C)\navvik fra 1961-1990",
xlab="",
main="",
xlim=c(minyear, maxyear),
ylim=c(lowYlimit, upperYlimit),
cex.main=1,
cex.lab=1.5,
cex.axis=1.5,
type="n",
frame.plot=FALSE,
axes=FALSE
)
# Axis 1 options
axis(side=1, at=c(seq(1960, 2020, by=10)), cex.axis=1.5)
# Axis 2 options
axis(side=2, at=seq(lowYlimit, upperYlimit, yStep),
labels=seq(lowYlimit, upperYlimit, yStep),
cex.axis=1.5)
# Add lines
lines(Norge$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()