Outdoor air temperature in Finland

This page is a knowledge crystal of subtype variable. The page identifier is Op_en2959
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Question

What are the outdoor air temperatures in Finland previously, now and in the future in different climate areas?

Answer

+ Show code- Hide code library(OpasnetUtils) library(ggplot2) objects.latest("Op_en2959", code_name = "temperatures") ggplot(subset(temperdays@data, Time %in% c("2013", "2030", "2050")), aes(x = Temperature, y = Result, color = Time, group = Time))+geom_line()

Rationale

Data from Statistics Finland:

• Current temperature, wind, and solar radiation
• Future temperature, wind, and solar radiation
• The data contains the following parameters: Timestep Year Month Day Time Temperature(°C) Relative_humidity(%) Wind_direction(degrees) Wind_speed(m/s) Direct_normal_solar_radiation(W/m2) Diffuse_horisontal_radiation(W/m2) Global_horisontal_radiation(W/m2)

Calculations

+ Show code- Hide code ## This is code is Op_en2959/temperatures [[Outdoor air temperature in Finland]] library(OpasnetUtils) ta <- opbase.data("Op_en2959", subset = "Vantaa") # [[Outdoor air temperature in Finland]] levels(ta$Year)[as.numeric(as.character(levels(ta$Year))) < 2015] <- "2012" ta$Date <- as.POSIXct(paste(ta$Year, ta$Month, ta$Day, sep = "-")) days <- aggregate(ta[c( "Temperature" # We only need temperature, but it is easy to take any other variable as well. # "Relative_humidity", # "Wind_direction", # "Wind_speed", # "Direct_normal_solar_radiation", # "Diffuse_horisontal_radiation", # "Result" # Global_horizontal_radiation )], ta[c("Date", "Year")], FUN = mean) colnames(days)[colnames(days) == "Temperature"] <- "Result" days$Temperature <- cut(days$Result, breaks = seq(-30, 33, 3)) temperatures <- Ovariable("temperatures", data = aggregate(days["Result"], days[c("Temperature", "Year")], FUN = mean)) temperdays <- Ovariable("temperdays", data = aggregate(days["Result"], days[c("Temperature", "Year")], FUN = length)) years = data.frame(Time = 1985:2070, Year = c(rep("2012", 36), rep("2030", 20), rep("2050", 30))) temperatures@data <- merge(temperatures@data, years) temperatures@data$Year <- NULL temperdays@data <- merge(temperdays@data, years) temperdays@data$Year <- NULL objects.store(temperatures, temperdays) cat("Objects temperatures, temperdays stored.\n") #ggplot(hours, aes(x = Time, y = Result))+geom_line() + geom_point(data = days, aes(x = Date, y = Result, colour = "Daily mean", size = 2)) #ggplot(hours, aes(x = Time, y = Result))+geom_point()

See also

• CLAIH assessment