Saturday, August 17, 2019

England's Summer Weather

England has some of the oldest weather recordings in the world. This means that when people say things like '1976 summer had X days hot in a row and so climate change isn't real' you can look at a lot of data and see what the overall trends are.

One dataset back to 1878 is the hottest each day got. This is the 'temperatures up to' figure weather forecasts give.
You can see 1976 was hot but also the trend over time. 1976 was very unusual for the 100 previous years. And now it looks fairly normal.

The English dataset goes back to 1659 for average daily temperatures. Here is how those temperatures have changed for June, July, August over that time.



June,July, August Central England average temperature since 1659
total dataset Mean: 15.3
1652-1700: 14.9
1701-1725: 15.2
1725-1750: 15.6
1751-1775: 15.3
1776-1800: 15.6
1801-1825: 15.1
1826-1850: 15.3
1851-1875: 15.3
1876-1900: 15.1
1901-1925: 14.9
1926-1950: 15.6
1951-1975: 15.3
1976-1994: 15:5
1994-2019: 16.0












Wednesday, August 14, 2019

Weather Overflows

Twice recently I have seen weather so unusual that the software designed to show weather failed.

The first was Hurricane Orphelia that went outside the range hurricanes are expected in. It went further north than the software was able to map


The second was this week where Mississippi got so hot (121F) that the temperature map could not show it and flipped over to 000.



Friday, March 22, 2019

Ireland Population Density Maps

Data from https://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/population-distribution-demography/geostat which has population grid at a 1km2 population sizings for all of Europe in 2011. The code is very slightly modified version of the code developed by halhen and p0bs here https://gist.github.com/halhen/659780120accd82e043986c8b57deae0


Color Maps





Joyplots
Where population density is seen as an increase in height.




Other Countries




Wednesday, March 20, 2019

Heatmap of the world

On the 14th of June 2016 I made a heatmap of global temperatures since 1850. This got popular on reddit with 15.4K points


The picture as I said in the first comment on the post was inspired by Ed Hawkins spiral animation of world temperatures and was an attempt to show everything in one picture.
A few outlets picked up the picture. The weather channel put it on facebook without crediting me.
























Tableau I found out last year use it to advertise themselves but with no credit to me the original design

























Ed Hawkins tweeted about the graph


And in June 2016 we discussed further as I switched Time to the Y axis and made other changes. My point is he tweeted about "'heat-map' representation of global temperature changes since 1850" two years before he published his heat map representation (using stripes). My graphs used the Hadcrut-4 and HadCET datasets






In May 2018 he produced a climate graph (below) with only years not months in the heatmap. At no point has he said that my heatmaps (which were inspired by his global temperatures spiral animation) might have inspired him.




I had produced a heatmap graph with lines for years that he saw in Sept 2017


Hawkins graph has deservidely become famous. And heatmaps are one of the most common visualisation types, which is evidence he could have come up with it on his own anyway. I would like if my ones did inspire him that it got mentioned somewhere. But the big deal here is that global warming is being shown in a popular eye catching way.




Monday, February 25, 2019

February is Hot

At the moment it is really hot. 20°C is ridiculously hot for this time of year.

Central England has weather data going back a long time. 1772 for daily average temperature and 1878 for maximum and minimum temperatures on each day.

2 times February the 25th since 1772 had an average temperature for the day above 10°C in Central England 1790 with 10.7°C, and 1922 with 11°C

The maximum temperatures observed in central England on the 25th of February were 1922 with 14.1,1953 with 13.1 and 1976 with 13.1 For those 140 years the maximum daily temperature averaged 6.6C.

I put the code to work all this out here. Graph of Feb 25th max temperature shows how weird 20°C is

It takes a while for the HADCET data to be updated. There is a nearby weatherstation http://www.weathercast.co.uk/world-weather/weather-stations/obsid/99060.html when I figure out the relationship between the two it will be possible to do a comparison between today and all the previous years.

Tuesday, February 05, 2019

English soccer is not normal

Are wins in football normally distributed? If they are not it might affect how we should calculate the probabilities of teams winning.

Baseball wins seem not to follow a normal distribution

There is a great R Package dataset of football results by James Curley here. This engsoccerdata has a function to generate soccer league tables of many countries over a long time period.

       league<-maketable_all(df=england[,])
       
 

team GP W D L gf ga gd Pts Pos

1 Manchester United 962 604 209 149 1856 847 1009 2021 1

and create a new column for the percentage of wins

       league<-league %>% 
    mutate(PercentW = W / GP)

p<-ggplot(data=league, aes(league$PercentW)) + geom_histogram()
#binwidth=20
p<-p + ggtitle("Percentage wins\n in English football league") +   xlab("Percentage Wins") + ylab("Number of Teams")
p<-p+theme_update(plot.title = element_text(hjust = 0.5))
p<-p + theme_bw()
       
 

       library(fitdistrplus)
library(logspline)
x<-league$PercentW
fit.norm <- fitdist(x, "norm")
plot(fit.norm)
       
 

       shapiro.test(x)       
 
Shapiro-Wilk normality test

data: x W = 0.96276, p-value = 0.0006663 Which means English football wins really do not have a normal distribution.

Goals per game are also not normally distributed. But I dont think anyone expectes them to be

       
league<-league %>% 
    mutate(GoalsPgame = gf / GP)
shapiro.test(league$GoalsPgame)

 

Shapiro-Wilk normality test data: x W = 0.92134, p-value = 4.818e-07

And for France

Shapiro-Wilk normality test

data: leagueF$PercentW W = 0.98522, p-value = 0.4699 so French football wins do not have might have (thanks for Paulfor the correction in the comments) a normal distribution. I must check the other leagues in the dataset as behaviour this different is odd.

Thursday, January 10, 2019

The Oldest Irishman Joke

John Scotus Eriugena (c. 815 – c. 877) was on the five punt note. And won a Michael D Higgins look alike competition in 870AD.

The French king sat opposite him and asked.

'Quid distat inter sottum et Scottum?' (What separates a sot [drunkard] from an Irishman?),

Eriugena replied, 'Tabula tantum' (Only a Table).

I think the gag setup still works 1200 years later.

What separates man from the animals?

The Liffey