From c09ebadd44741091aeebc09f796c86daea6dab31 Mon Sep 17 00:00:00 2001
From: "Jentsch, Helge" <helge.marc.ole.jentsch@uni-hamburg.de>
Date: Fri, 28 Apr 2023 07:20:24 +0000
Subject: [PATCH] Update README.md

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 ## Welcome to the help-page of ClimDatDownloadR
 
+To get started please proceed further down under the update section. 
 
-To get started please proceed [here](./articles/ClimDatDownloadR.html). 
 
+_This R-package was developed as a student project for the masters programm Geography at the Universität Hamburg, Germany._
 
+## Update 09.03.2021
 
+As of today a new alpha version is released. 
+If you want to test the ClimDatDownloadR-package please feel free to install the package via
 
-_This R-package was developed as a student project for the masters programm Geography at the Universität Hamburg, Germany._
+`install.packages("https://gitlab.rrz.uni-hamburg.de/helgejentsch/climdatdownloadr/-/archive/master/climdatdownloadr-master.tar.gz", repos = NULL, type = "source")`
+
+and if you need the dependencies via 
+
+`install.packages(c("gdalUtils", "httr", "ncdf4", "qpdf", "raster", "RCurl", "RefManageR", "rgdal", "stringr", "sf", "sp", "svMisc", "utils"), dependencies = TRUE)`
+
+
+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.  
+```{r setup}
+# install.packages(c("gdalUtils", "httr", "ncdf4", "qpdf", "raster", "RCurl", "RefManageR", "rgdal", "stringr", "sf", "sp", "svMisc", "utils"), dependencies = TRUE)
+# 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.  
+
+## Overview of download-functions
+
+Besides the functions to download the currend climatologies of [Chelsa](http://chelsa-climate.org/) and [WorldClim](https://www.worldclim.org/), described below as [`Chelsa.Clim.download()`](../man/Chelsa.Clim.download.Rd) and [`WorldClim.HistClim.download()`](../man/WorldClim.HistClim.download.Rd), the package offers more download functions.  
+- Beginning with the 'Last Glacial Maximum'-data set (LGM), Chelsa offers a data set with parameters like precipitation, temperature, and also bioclim variables, driven by various models. It can be called with [`Chelsa.lgm.download()`](../man/Chelsa.lgm.download.Rd).  
+- [Chelsa's](http://chelsa-climate.org/) timeseries dataset can be downloaded via the [`Chelsa.timeseries.download()`](../man/Chelsa.timeseries.download.Rd)-function.  
+- For projected climatic conditions both [Chelsa](http://chelsa-climate.org/) and [WorldClim](https://www.worldclim.org/) provide various options. 
+  - [Chelsa's](http://chelsa-climate.org/) options can be downloaded through the functions [`Chelsa.CMIP_5.download()`](../man/Chelsa.CMIP_5.download.Rd) and/or [`Chelsa.CRUts.download()`](../man/Chelsa.CRUts.download.Rd). 
+  - [WorldClim's](https://www.worldclim.org/) options can be downloaded through the functions [`WorldClim.CMIP_5.download()`](../man/WorldClim.CMIP_5.download.Rd) and/or [`WorldClim.CMIP_6.download()`](../man/WorldClim.CMIP_6.download.Rd).  
+
+## 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:  
+```{r setup}
+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:  
+```{r setup}
+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
+  keep.raw.zip = FALSE,
+  delete.raw.data = FALSE,
+  save.bib.file = TRUE
+)
+```
-- 
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