How is climate changing and where with R

Even if global temperature has risen, the magnitude varies from region to region. Here, I use R to investigate how temperature has changed in the last 110 years. The data is from the Climatic Research Unit and you can download it from here.

I have deployed the app to Rstudio (click here) and you can play with it to see how tempreature has been increasing in the last 100 plus years. You can double click over any region of interest (land part only, not oceans) on the map and you will get the trend of annual average temperature for the selected region. More than 95% of climate scientists agree that global warming is happening and we are the cause. See it for yourself on the link below. The data is from the Climatic Research Unit.

The ui.R and server.R codes are included below.

ur.R

library(shiny)
library(shinydashboard)


dashboardPage(
  dashboardHeader(title = 'By Fisseha Berhane'),
  
  dashboardSidebar(width = 100
                  
              
  ),
  
  
  dashboardBody( 
    
    
    tags$h3('How is climate changing and where with',span('R',style="color:blue;font-size:140%"),style="text-align:center;color:#b30000;font-size:200%"),
    br(),
    fluidRow(
      
      column(width = 7,
             
      plotOutput("distPlot",dblclick='plot_dblclick', click = "plot_click")
      
      ),
      
      column(width = 5,
             
             plotOutput('dbclick'))
      )
))

server.R

library(ggplot2)
library(ggmap)
library(maptools)
library(maps)
library(shiny)
library(lubridate)



load("data/cru_1901_2013_tmp_coarser") # I changed the resolution to one by one degree


shinyServer(function(input, output) {
  

  
  output$distPlot <- renderPlot({
    mapWorld <- borders("world", colour="gray50", fill="#cce6ff") # create a layer of borders
    p=ggplot() +   mapWorld
    p=p+ggtitle("Double click over any land part to see \n the temperature trend since 1901")+
      theme(axis.text.y   = element_blank(),
            line = element_blank(),
            axis.text.x   = element_blank(),
            axis.title.y  = element_blank(),
            axis.title.x  = element_blank(),
            panel.grid.major = element_blank(), 
            panel.grid.minor = element_blank(),
            plot.title = element_text(vjust=1.5,size = 18,colour="#663300"),
            panel.border = element_rect(colour = "gray70", fill=NA, size=1))

      
    p
    
  })
  

  
  double_clicked <- reactiveValues(
    
    center = NULL 
  )
  
  # Handle dounle clicks on the plot
  
  observeEvent(input$plot_dblclick, {
    
    double_clicked$center <- c(input$plot_dblclick$x,input$plot_dblclick$y)
    
  })
  

  
  lon_index<-reactive({
    z=double_clicked$center
   which((abs(lon-z[1]))<=1)[1]
    
  })
  
  
  lat_index<-reactive({
    z=double_clicked$center
    which((abs(lat-z[2]))<=1)[1]
    
  })
  
 
  
    
  output$dbclick<-renderPlot({
    
    if(!is.na(lon_index())){
      
    z =tmp[lon_index(),lat_index(),]
    
    monthly=matrix(z,nrow=12)
  
    if(length(na.omit(monthly))>0){
      
      annual_min=apply(monthly,2,min,na.omit=TRUE)
      annual_max=apply(monthly,2,max,na.omit=TRUE)
      annual_ave=apply(monthly,2,mean,na.omit=TRUE)
      
    
    annual=as.data.frame(list(annual_ave=annual_ave,years=unique(year(time))))
    
   q=ggplot(annual,aes(x=years,y=annual_ave))+geom_line()+ ylab(expression("Temperature "*~degree*C))+theme_bw()
  q=q+ggtitle(paste0("Annual Average Temperature Trend at (",lon[lon_index()],", ", lat[lat_index()],")"))+xlab('')+theme(axis.title.y = element_text(size=14,angle=90,hjust=.5,vjust=1),
                    axis.text.y = element_text(colour="darkred",size=16,angle=0,hjust=1,vjust=0),plot.title = element_text(vjust=1.5,size = 15,colour="blue"),
                    axis.text.x = element_text(colour="darkred",size=16,angle=0,hjust=1,vjust=0))+stat_smooth(method='lm',color='darkred')
    
     
   q
    }}  
  })
})