Over a million developers have joined DZone.
Platinum Partner

Get Big Climate Data from the KNMI Climate Explorer Web App

· Big Data Zone

The Big Data Zone is presented by Exaptive.  Learn how rapid data application development can address the data science shortage.

You can query global climate data from the KNMI Climate Explorer (the KNMI is the Royal Netherlands Metereological Institute) with R.


Here's a little example how I retreived data for my hometown Innsbruck, Austria and plotted annual total precipitation. You can choose station data by pointing at a map, by setting coordinates, etc.

# get climate (precipitation) data from url:
# http://climexp.knmi.nl/selectstation.cgi?id=someone@somewhere
 
# station INNSBRUCK, FLUGHAFEN (11120), 47.27N, 11.35E:
ibk_dat <- read.table("http://climexp.knmi.nl/data/pa11120.dat", sep = "",
                      row.names = 1, col.names = 0:12)
 
# cut off first and last yr, due to missing data..
ibk_dat <- ibk_dat[c(-1, -50,]
 
# plot yearly sums:
windows(width = 15, height = 5)
plot(rowSums(ibk_dat), type = "s", ylab = "Annual Total Precipitation (mm)",
     xlab = NA, col = "blue", xaxt = "n", lwd = 1.5, las = 2, cex.axis = 0.8,
     main = "INNSBRUCK FLUGHAFEN, 47.27N, 11.35E, 593m, WMO station code: 11120")
axis(1, labels = rownames(ibk_dat), at = 1:nrow(ibk_dat), las = 2, cex.axis = 0.85)
 
abline(h = mean(rowSums(ibk_dat)), col = 1, lty = 2, lwd = 1.2)
text(1250, adj = 0, "Long-term average", cex = 0.75)
arrows(x0 = 2.5, y0 = 1220,
       x1 = 2.5, y1 = 930, length = 0.05)  

 

 

The Big Data Zone is presented by Exaptive.  Learn about how to rapidly iterate data applications, while reusing existing code and leveraging open source technologies.

Topics:

Published at DZone with permission of Kay Cichini , DZone MVB .

Opinions expressed by DZone contributors are their own.

{{ parent.title || parent.header.title}}

{{ parent.tldr }}

{{ parent.urlSource.name }}