To get started please proceed [here](./articles/ClimDatDownloadR.html).
To get started please proceed [here](./README.md#a-warm-welcome).
_This R-package was developed as a student project for the masters programm Geography at the Universität Hamburg, Germany._
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@@ -21,3 +21,88 @@ I would appreciate your feedback and possible bug reports.
If you find anything, please send an email to [helge.marc.ole.jentsch@uni-hamburg.de](<mailto:helge.marc.ole.jentsch@uni-hamburg.de>)
Thank you very much for using ClimDatDownloadR!
## A warm welcome
Hello and welcome to the ClimDatDownloadR R-package.
With this package **cli**mate **dat**asets provided by [Chelsa](http://chelsa-climate.org/) and [WorldClim](https://www.worldclim.org/) can be automatically **download**ed, clipped, and converted with **R**.
To start, you'll have to install the package and it's dependencies first, if not already done. Then you can activate the package with the `library`-function.
# install.packages("https://gitlab.rrz.uni-hamburg.de/helgejentsch/climdatdownloadr/-/archive/master/climdatdownloadr-master.tar.gz", repos = NULL, type = "source")
library(ClimDatDownloadR)
```
Very well, now that you have the package installed and attached, let's start with the data sets of the climatologies of Chelsa and WorldClim.
## Download Climatologies
In the help pages of [Chelsa.Clim.download()](../man/Chelsa.Clim.download.Rd) and [WorldClim.HistClim.download()](../man/WorldClim.HistClim.download.Rd) you can find further information about the handling of these functions. In fact running the functions all by itself bulk-downloads all the climatology data sets from the servers to your current working directory.
Let's start with a example of the Chelsa climatologies:
```
Chelsa.Clim.download(
# first you'll have to choose your working directory
# don't worry about having a directory for every parameter you want to download
# ClimDatDownloadR sorts this out for you
save.location = "./",
# now you'll have to choose parameters.
# since there is the possibility to download more than one data set
# the parameters must be a string-vector input.
# Single parameters, however, can be just put in as a string.
# the valid parameter inputs can be found in the help (linked s.o.)
parameter = c("temp", "bio"),
# Now, since you chose "temp" and "bio" as input parameters,
# you can specify the months and bioclim-variables to download.
# If you want all of them, just leave the default values.
# It is crutial, however, that the inputs are integer number values.
month.var = c(1), # Here January was chosen to be downloaded for demonstration purposes
bio.var = c(1), # Here the first bioclim-variable was chosen to be downloaded for demonstration purposes
# For Chelsa a newer Version of their climatologies was published in 2019.
# They still got their old version still hosted on their website.
# So you can download it as well, if you want to reproduce some research you base your studies on.
version.var = "1.2", # Here the newer version is chosen
# Now you can choose whether you want the data set clipped
clipping = TRUE, # Here TRUE was chosen to show a basic introduction to the function
# Since "clipping" is enganged now you can specify the extent you want to have for your analysis
# This is possible via the parameters "clip.shapefile", "clip.extent", and "buffer"
clip.extent = c(-9,20,35,80), # Here the extent for Europe was used ...
buffer = 5, # ... with a 5 arc-degree buffer.
# Now, since some might prefer older file formats there is a possibility to convert
# clipped files and raw data into ESRI-ASCII format
convert.files.to.asc = FALSE,
# now you can stack the data ...
stacking.data = FALSE,
# ... and choose if you want to combine the raw data in a .zip-file ...
combine.raw.zip = FALSE,
# and whether raw data should be deleted.
delete.raw.data = FALSE,
# Finally you are presented with the option to save a bibliography file at the save location.
save.bib.file = TRUE
)
```
___
With this showing the basic principle of these functions, here is a example of a WorldClim climatology download:
```
WorldClim.HistClim.download(
# As you can see, the structure of this function is very similar to the Chelsa-function
save.location = "./",
parameter = c("temp", "bio"),
month.var = c(1),
bio.var = c(1),
# Here the resolution of the downloaded data set must be added
# If no input is given all resolutions will be downloaded
resolution = "10m", # here 10 arc-minutes are chosen
# WorldClim also recently had an update to version 2.1
version.var = "2.1", # Here the newer version is chosen
clipping = TRUE,
clip.extent = c(-9,20,35,80),
buffer = 5,
convert.files.to.asc = FALSE,
stacking.data = FALSE,
# here you can choose if you want to keep the downloaded zip-file
