rdwd: climate data from the German Weather Service
2019-03-17
Vignette Rmd source code (Not on CRAN to reduce load on DWD server through daily new builds and checks of the vignette)
Interactive map vignette
Package structure
To use the observation datasets, rdwd has been designed to mainly do 3 things:
selectDWD: facilitate file selection, e.g. for certain station names (with findID), by geographical location (see map and nearbyStations), by temporal resolution (res = 1/10 minutes, hourly, daily, monthly, annual), variables (var = temperature, rain, wind, sun, clouds, etc) or observation period (per = historical long term records or the current year)
dataDWD: download a file (or multiple files, without getting banned by the FTP-server)
readDWD: read that data into R (including useful defaults for metadata)
selectDWD uses the result from indexFTP which recursively lists all the files on an FTP-server (using RCurl::getURL). As this is time consuming, the result is stored in the package dataset fileIndex. From this, metaIndex and geoIndex are derived.
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Package installation
install.packages("rdwd")
# get the latest development version from github:
berryFunctions::instGit("brry/rdwd")
# For full usage, as needed in indexFTP and metaDWD(..., current=TRUE):
install.packages("RCurl") # is only suggested, not mandatory dependency
On Linux, instead of the last line above, use in the terminal (with lowercase rcurl):
sudo apt-get install r-cran-rcurl
If direct installation from CRAN doesn’t work, your R version might be too old. In that case it is really recommendable to update R. If you can’t update R, try installing from source (github) via instGit as mentioned above. If that’s not possible either, you might be able to source some functions from the package zip folder
Vectorize(source)(dir("path_you_unzipped_to/rdwd-master/R", full=T))
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Basic usage
library(rdwd)
link <- selectDWD("Potsdam", res="daily", var="kl", per="recent")
file <- dataDWD(link, read=FALSE, dir="DWDdata", quiet=TRUE)
clim <- readDWD(file)
str(clim)
## 'data.frame': 550 obs. of 19 variables:
## $ STATIONS_ID: int 3987 3987 3987 3987 3987 3987 3987 3987 3987 3987 ...
## $ MESS_DATUM : POSIXct, format: "2017-09-13" "2017-09-14" ...
## $ QN_3 : int 10 10 10 10 10 10 10 10 10 10 ...
## $ FX : num 21.1 21.2 11.9 6.4 6.6 5.5 6.4 8.7 6.5 5.1 ...
## $ FM : num 7.1 5.8 5 3 2 2.7 2.9 3.5 2.5 1.5 ...
## $ QN_4 : int 3 3 3 3 3 3 3 3 3 3 ...
## $ RSK : num 3.7 1.8 0.2 0 1.1 0 0 1.9 0 0 ...
## $ RSKF : int 6 6 6 0 6 0 0 6 0 0 ...
## $ SDK : num 6.38 2.05 4.93 8.1 8.62 ...
## $ SHK_TAG : int 0 0 0 0 0 0 0 0 0 0 ...
## $ NM : num 4.1 5.8 5.2 3.1 2.7 3.1 3.7 5 6.8 4.2 ...
## $ VPM : num 12.3 12.3 12.2 11 11.1 11.1 11.1 11.8 12.7 12.3 ...
## $ PM : num 989 989 998 1000 1001 ...
## $ TMK : num 13.3 12.3 12.5 11.6 11.8 11.5 11.5 11.8 12.9 13.6 ...
## $ UPM : num 81.1 86 84.2 81.8 82 ...
## $ TXK : num 18.9 15 17 17.6 18.6 17.2 18 16.9 17.1 19 ...
## $ TNK : num 9.1 10 8.9 6.3 6.8 7.2 5.7 7.7 10 10.6 ...
## $ TGK : num 6.7 8.3 5.8 3.9 3 4.2 3.3 4.5 8 6.4 ...
## $ eor : Factor w/ 1 level "eor": 1 1 1 1 1 1 1 1 1 1 ...
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Plotting examples
Recent temperature time series:
par(mar=c(4,4,2,0.5), mgp=c(2.7, 0.8, 0), cex=0.8)
plot(clim[,c(2,14)], type="l", xaxt="n", las=1, main="Daily temp Potsdam")
berryFunctions::monthAxis(ym=TRUE) ; abline(h=0)
mtext("Source: Deutscher Wetterdienst", adj=-0.1, line=0.5, font=3)
Long term climate graph:
link <- selectDWD("Goettingen", res="monthly", var="kl", per="h")
clim <- dataDWD(link, quiet=TRUE)
clim$month <- substr(clim$MESS_DATUM_BEGINN,5,6)
temp <- tapply(clim$MO_TT, clim$month, mean, na.rm=TRUE)
prec <- tapply(clim$MO_RR, clim$month, mean, na.rm=TRUE)
berryFunctions::climateGraph(temp, prec, main="Goettingen")
mtext("Source: Deutscher Wetterdienst", adj=-0.05, line=2.8, font=3)
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Station selection
Weather stations can be selected geographically with the interactive map. All stations within a certain radius around a given lat-long position can be obtained with nearbyStations.
The DWD station IDs can be obtained from station names with
## Potsdam
## 3987
findID("Koeln", exactmatch=FALSE)
## Warning: source -> withVisible -> eval -> eval -> createBerrysVignettes -
## > rmarkdown::render -> knitr::knit -> call_block -> block_exec -> in_dir -
## > evaluate -> evaluate::evaluate -> evaluate_call -> timing_fn -> handle -
## > findID: ID determined from name 'Koeln' has 4 elements (2665, 2666, 2667,
## 2968).
## Koeln-Bonn Koeln-Botanischer Garten Koeln-Porz-Eil
## 2667 2665 2666
## Koeln-Stammheim
## 2968
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Available files
File selection by station name/id and folder happens with selectDWD. It needs an index of all the available files on the server. The package contains such an index (fileIndex) that is updated (at least) with each CRAN release of the package. The selectDWD documentation contains an overview of the FTP folder structure.
If you find the file index to be outdated (Error in download.file … : cannot open URL), please let me know and I will update it. Meanwhile, use current=TRUE in selectDWD:
# all files at a given path, with current file index (RCurl required):
links <- selectDWD(res="monthly", var="more_precip", per="hist", current=TRUE)
fileIndex is created with the function indexFTP used in the last section of rdwd-package.R.
### This chunk is not evaluated ###
# recursively list files on the FTP-server:
files <- indexFTP("hourly/sun") # use dir="some_path" to save the output elsewhere
berryFunctions::headtail(files, 5, na=TRUE)
# indexFTP uses a folder to resume indexing after getting banned:
gridindex <- indexFTP("radolan","ftp://ftp-cdc.dwd.de/pub/CDC/grids_germany/hourly")
gridindex <- indexFTP(gridindex,"ftp://ftp-cdc.dwd.de/pub/CDC/grids_germany/hourly", sleep=1)
# with other FTP servers, this should also work...
funet <- indexFTP(base="ftp.funet.fi/pub/standards/w3/TR/xhtml11/", folder="")
p <- RCurl::getURL( "ftp.funet.fi/pub/standards/w3/TR/xhtml11/",
verbose=T, ftp.use.epsv=TRUE, dirlistonly=TRUE)
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File selection
selectDWD is designed to be very flexible:
# inputs can be vectorized, and period can be abbreviated:
selectDWD(c("Potsdam","Wuerzburg"), res="hourly", var="sun", per="hist")
## [[1]]
## [1] "ftp://ftp-cdc.dwd.de/pub/CDC/observations_germany/climate/hourly/sun/historical/ stundenwerte_SD_03987_18930101_20181231_hist.zip"
##
## [[2]]
## [1] "ftp://ftp-cdc.dwd.de/pub/CDC/observations_germany/climate/hourly/sun/historical/ stundenwerte_SD_05705_19510101_20181231_hist.zip"
If res/var/per are left NA, an interactive selection is opened with the available options for the given station.
# Time period can be doubled to get both filenames:
selectDWD("Potsdam", res="daily", var="kl", per="rh")
## [1] "ftp://ftp-cdc.dwd.de/pub/CDC/observations_germany/climate/ daily/kl/recent/tageswerte_KL_03987_akt.zip"
## [2] "ftp://ftp-cdc.dwd.de/pub/CDC/observations_germany/climate/ daily/kl/historical/tageswerte_KL_03987_18930101_20181231_hist.zip"
There may be a differing number of available files for several stations across all folders. That’s why the default outvec is FALSE (unless per="hr").
lapply(selectDWD(id=c(3467,5116), res="",var="",per=""), substr, 58, 1e4)
## [[1]]
## [1] "/annual/more_precip/historical/jahreswerte_RR_03467_19940101_20181231_hist.zip"
## [2] "/annual/more_precip/recent/jahreswerte_RR_03467_akt.zip"
## [3] "/daily/more_precip/historical/tageswerte_RR_03467_19930601_20181231_hist.zip"
## [4] "/daily/more_precip/recent/tageswerte_RR_03467_akt.zip"
## [5] "/monthly/more_precip/historical/monatswerte_RR_03467_19930601_20181231_hist.zip"
## [6] "/monthly/more_precip/recent/monatswerte_RR_03467_akt.zip"
##
## [[2]]
## [1] "/annual/more_precip/historical/jahreswerte_RR_05116_19930101_20181231_hist.zip"
## [2] "/monthly/more_precip/historical/monatswerte_RR_05116_19920701_20061231_hist.zip"
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