rdwd: climate data from the German Weather Service
2018-11-26
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
Intro
The R package rdwd contains code to select, download and read weather data from measuring stations across Germany. The German Weather Service (Deutscher Wetterdienst, DWD) provides over 228 thousand datasets with weather observations through the FTP server online at
ftp://ftp-cdc.dwd.de/pub/CDC/observations_germany/climate.
For data interpolated onto a 1 km raster, including radar data up to the last hour, see ftp://ftp-cdc.dwd.de/pub/CDC/grids_germany/. Management of these (very large!) datasets is not yet included in rdwd. If you want it to be supported, send me a message to boost it up my priority list.
For further details, please consult the DWD FTP server documentation
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 (hourly, daily, monthly), variables (temperature, rain, wind, sun, clouds, etc) or observation period (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=tempdir(), quiet=TRUE)
# tempdir is only for CRAN vignette checks. In real life, use a real folder.
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: "2017-05-25" "2017-05-26" ...
## $ QN_3 : int 10 10 10 10 10 10 10 10 10 10 ...
## $ FX : num 9.7 8.7 8.8 12 7.3 20.3 15.6 9.8 8.2 8.8 ...
## $ FM : num 3.6 3.6 3.4 4.2 2.7 4.1 6 4.1 2.6 3.9 ...
## $ QN_4 : int 3 3 3 3 3 3 3 3 3 3 ...
## $ RSK : num 0 0 0 0 0 0.5 0 0 0 3.8 ...
## $ RSKF : int 0 0 0 0 0 6 0 0 0 6 ...
## $ SDK : num 7.03 9.13 15.78 12.4 12.35 ...
## $ SHK_TAG : int 0 0 0 0 0 0 0 0 0 0 ...
## $ NM : num 5 3.7 0 3.4 4 5.3 5.1 2 1.9 6.3 ...
## $ VPM : num 11.4 13.8 11.9 13.2 16.5 18.4 12.7 8.9 8.8 13.8 ...
## $ PM : num 1009 1009 1011 1007 1002 ...
## $ TMK : num 13.7 17.2 20.2 23.2 23.8 22.3 18.7 15.7 18.6 17.2 ...
## $ UPM : num 73.9 73.3 55 48.6 58.4 ...
## $ TXK : num 18.9 24.9 27.9 32.3 30.6 31.6 24.6 23.6 26.2 22.7 ...
## $ TNK : num 8.3 11.7 12.2 13.2 17.2 18.1 11.2 8.7 10.2 12 ...
## $ TGK : num 4.7 8.2 7.8 10.3 13.9 15.7 8.8 6.4 5.8 8.7 ...
## $ 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(2,4)], 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)
library(berryFunctions)
headtail(clim[!is.na(clim$MO_TT)&!is.na(clim$MO_RR),])
## STATIONS_ID MESS_DATUM_BEGINN MESS_DATUM_ENDE QN_4 MO_N MO_TT MO_TX
## 1 1691 18570101 18570131 5 NA -1.00 NA
## 1932 1691 20171201 20171231 3 7.46 3.78 5.89
## MO_TN MO_FK MX_TX MX_FX MX_TN MO_SD_S QN_6 MO_RR MX_RS eor month
## 1 NA NA NA NA NA NA 5 15.0 NA eor 01
## 1932 1.26 2.77 13 18.4 -2.9 16.3 3 48.8 7.7 eor 12
# as of 2018-03, there are mostly NAs in MO_RR in many stations.
# A message has been sent to DWD.
climateGraph(temp, prec, main="Goettingen 1857:1946")
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.
# 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 for resumed 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_20171231_hist.zip"
##
## [[2]]
## [1] "ftp://ftp-cdc.dwd.de/pub/CDC/observations_germany/climate/hourly/sun/historical/ stundenwerte_SD_05705_19510101_20171231_hist.zip"
# Time period can be doubled to get both filenames:
selectDWD("Potsdam", res="daily", var="kl", per="rh", outvec=TRUE)
## [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_20171231_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.
lapply(selectDWD(id=c(3467,5116)), substr, 58, 1e4)
## Warning: source -> withVisible -> eval -> eval -> createBerrysVignettes -
## > rmarkdown::render -> knitr::knit -> call_block -> block_exec -> in_dir -
## > evaluate -> evaluate::evaluate -> evaluate_call -> timing_fn -> handle -
## > lapply -> selectDWD: in file index 'fileIndex', there are 6 files with ID
## 3467.
## Warning: source -> withVisible -> eval -> eval -> createBerrysVignettes -
## > rmarkdown::render -> knitr::knit -> call_block -> block_exec -> in_dir -
## > evaluate -> evaluate::evaluate -> evaluate_call -> timing_fn -> handle -
## > lapply -> selectDWD: in file index 'fileIndex', there are 3 files with ID
## 5116.
## [[1]]
## [1] "/annual/more_precip/historical/jahreswerte_RR_03467_19940101_20171231_hist.zip"
## [2] "/annual/more_precip/recent/jahreswerte_RR_03467_akt.zip"
## [3] "/daily/more_precip/historical/tageswerte_RR_03467_19930601_20171231_hist.zip"
## [4] "/daily/more_precip/recent/tageswerte_RR_03467_akt.zip"
## [5] "/monthly/more_precip/historical/monatswerte_RR_03467_19930601_20171231_hist.zip"
## [6] "/monthly/more_precip/recent/monatswerte_RR_03467_akt.zip"
##
## [[2]]
## [1] "/annual/more_precip/historical/jahreswerte_RR_05116_19930101_20051231_hist.zip"
## [2] "/daily/more_precip/historical/tageswerte_RR_05116_19920701_20061231_hist.zip"
## [3] "/monthly/more_precip/historical/monatswerte_RR_05116_19920701_20061231_hist.zip"
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