library(tidyverse)
library(lubridate)
library(extrafont)
library(hrbrthemes)
extrafont::loadfonts()
library(patchwork)
wdr <- getwd()
#link https://www.ncdc.noaa.gov/cdo-web/datasets/GSOY/locations/CITY:AU000006/detail
Vienna <- readr::read_csv(file=paste0(wdr, "/data/", "Global Summary of the Year Location Details-Vienna-1877315.csv"),
col_types = cols(
.default = col_double(),
STATION = col_character(),
NAME = col_character())) %>%
janitor::clean_names()
fn_f_to_cels <- function(degree_in_f) {
(degree_in_f - 32)*5/9
}
Vienna <- Vienna %>%
mutate_at(vars(starts_with("t")), .funs=list(celsius= ~map_dbl(., fn_f_to_cels)))
# data cleaning (duplicates) ----------------------------------------------
Vienna %>%
group_by(date) %>%
summarise(n_obs=n()) %>%
filter(n_obs>1) %>%
pull(date) -> year_duplicates
Vienna %>%
filter(date %in% year_duplicates) %>%
arrange(date) #two different stations from 1949 to 1954
## # A tibble: 12 x 10
## station name date dx90 tavg tmax tmin tavg_celsius tmax_celsius
## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 AUW000~ VIEN~ 1949 3 49.9 58.8 40.9 9.94 14.9
## 2 AU0000~ WIEN~ 1949 0 50.9 57.5 44.3 10.5 14.2
## 3 AUW000~ VIEN~ 1950 6 49.7 58.7 40.8 9.83 14.8
## 4 AU0000~ WIEN~ 1950 4 50.7 57.3 44.1 10.4 14.1
## 5 AUW000~ VIEN~ 1951 1 50.1 58.6 41.4 10.1 14.8
## 6 AU0000~ WIEN~ 1951 0 51.2 57.4 45 10.7 14.1
## 7 AUW000~ VIEN~ 1952 10 48.3 56.8 39.7 9.06 13.8
## 8 AU0000~ WIEN~ 1952 3 49.7 56 43.4 9.83 13.3
## 9 AUW000~ VIEN~ 1953 2 49.4 58.7 40.2 9.67 14.8
## 10 AU0000~ WIEN~ 1953 1 51 58.4 43.5 10.6 14.7
## 11 AUW000~ VIEN~ 1954 NA NA NA NA NA NA
## 12 AU0000~ WIEN~ 1954 0 48.7 55.6 41.7 9.28 13.1
## # ... with 1 more variable: tmin_celsius <dbl>
Vienna %>%
group_by(station, date) %>%
summarise(n_obs=n()) %>%
ggplot()+
geom_line(aes(x=date,
y=n_obs,
color=station))
#AU000005901 station continuous over entire period;
#AUW00034165 only brief period; remove
Vienna <- Vienna %>%
filter(station=="AU000005901")
# graphs ------------------------------------------------------------------
# > Number days with maximum temperature > 90 F (32.2C) -------------------
plot_line_days <- Vienna %>%
ggplot()+
geom_line(aes(x=date,
y=dx90),
color="orange")+
labs(title="Number of days with maximum temperature > 32.2C per year")+
scale_x_continuous(breaks=seq(1850,2000, 50))+
hrbrthemes::theme_ft_rc()+
theme(panel.grid.minor.y = element_blank(),
panel.spacing = unit(0, "cm"),
plot.title = element_text(colour="#929299"),
plot.margin = unit(c(1,0,0,0), "cm"),
panel.grid.minor.x = element_blank(),
axis.title = element_blank())
# average temperature per year ---------------------------------------------
# > barplot ---------------------------------------------------------------
plot_bar_temp<- Vienna %>%
ggplot()+
labs(title="Average temperature per year (heatmap)")+
geom_bar(aes(x=date,
y=1,
fill=tavg_celsius),
color="transparent",
stat="identity")+
scale_fill_gradient2(low="darkblue", mid="white", high="red",
midpoint = mean(Vienna$tavg_celsius, na.rm = T),
na.value = "grey30", name="°C")+
hrbrthemes::theme_ft_rc()+
theme(panel.grid=element_blank(),
axis.text.y = element_blank(),
axis.title = element_blank(),
legend.position="right",
plot.title = element_text(colour="#929299"),
panel.spacing = unit(0, "cm"),
axis.line.x = element_line(colour="#464950", size = 0.2),
plot.margin = unit(c(1,0,0,0), "cm"),
legend.justification="top")+
guides(fill=guide_colorbar(barwidth=unit(.2, "cm")))
# > line plot -------------------------------------------------------------
plot_line_temp <- Vienna %>%
ggplot()+
labs(title="Average temperature per year")+
geom_line(aes(x=date,
y=tavg_celsius))+
geom_smooth(aes(x=date,
y=tavg_celsius))+
hrbrthemes::theme_ft_rc()+
scale_x_continuous(breaks=seq(1850,2000, 50))+
scale_y_continuous(labels=function(x) paste(x, "C"))+
theme(axis.title = element_blank(),
panel.grid.minor.y = element_blank(),
panel.spacing = unit(0, "cm"),
plot.title = element_text(colour="#929299"),
plot.margin = unit(c(1,0,0,0), "cm"))
# topical nights ----------------------------------------------------------
# > get data --------------------------------------------------------------
Vienna_daily <- readr::read_csv(file=paste0(wdr, "/data/", "NOAA_Temps_Vienna_daily.csv"),
col_types = cols(
.default = col_double(),
DATE=col_date(),
STATION = col_character(),
NAME = col_character())) %>%
janitor::clean_names()
# > data cleaning -----------------------------------------------------------
#check for duplicates
duplicate_years <- Vienna_daily %>%
group_by(date) %>%
summarise(n_obs=n()) %>%
filter(n_obs>1) %>%
mutate(year=lubridate::year(date)) %>%
distinct(year) #years in which more than 1 observatio per year; same issue as above
Vienna_daily %>%
filter(lubridate::year(date) %in% duplicate_years$year) %>%
distinct(station) #again two stations; remove station which operates only for a few years
## # A tibble: 2 x 1
## station
## <chr>
## 1 AUW00034165
## 2 AU000005901
Vienna_daily <- Vienna_daily %>%
filter(station=="AU000005901") #remove station causing additional observations
Vienna_daily %>%
ggplot()+
geom_bar(aes(x=date)) #check = 1 observation for each day
# > analysis --------------------------------------------------------------
#define tropical days = min temp not below 20 °C
Vienna_daily <- Vienna_daily %>%
select(station, date, starts_with("t")) %>%
mutate_at(vars(starts_with("t")), .funs=list(cels=fn_f_to_cels)) %>%
mutate(tropical=case_when(tmin_cels>=20 ~ TRUE,
TRUE ~ as.logical(FALSE)))
skimr::skim(Vienna_daily$tropical)
##
## Skim summary statistics
##
## -- Variable type:logical -------------------------------------------------------------------------------------------------------
## variable missing complete n mean
## Vienna_daily$tropical 0 59995 59995 0.0076
## count
## FAL: 59537, TRU: 458, NA: 0
plot_tropical <- Vienna_daily %>%
mutate(year=lubridate::year(date)) %>%
group_by(year) %>%
summarise(n_tropical=sum(tropical[tropical==TRUE])) %>%
ggplot()+
geom_line(aes(x=year,
y=n_tropical),
color="orange")+
labs(title="Number of 'tropical' nights per year",
subtitle="In a tropical night temperature does not fall below 20 °C.")+
hrbrthemes::theme_ft_rc()+
scale_x_continuous(breaks=seq(1850, 2000, 50))+
theme(axis.title = element_blank(),
panel.grid.minor.y = element_blank(),
panel.spacing = unit(0, "cm"),
plot.title = element_text(colour="#929299"),
plot.margin = unit(c(1,0,0,0), "cm"))
# combine plots -----------------------------------------------------------
combined_plot <- patchwork::wrap_plots(plot_bar_temp,
plot_line_temp,
plot_tropical)+
plot_layout(nrow = 3)+
plot_annotation(title="Temperature dynamics in Vienna, 1850-2017",
caption=paste("source: Global Summary of the Year Location Details, NOAA;\ngraph: Roland Schmidt | @zoowalk | werk.statt.codes"),
theme=hrbrthemes::theme_ft_rc()+theme(plot.title=element_text(color="#929299", size = 24)))
combined_plot
