easyclimate

Easy access to high-resolution daily climate data for Europe.
https://github.com/verughub/easyclimate

Category: Climate Change
Sub Category: Climate Data Access and Visualization

Keywords

climate-data europe r-package

Keywords from Contributors

ecoinformatics

Last synced: about 3 hours ago
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Repository metadata

Easy access to high-resolution daily climate data for Europe

• Host: GitHub
• URL: https://github.com/verughub/easyclimate
• Owner: VeruGHub
• License: gpl-3.0
• Created: 2019-11-08T09:56:39.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2026-01-12T08:49:45.000Z (4 days ago)
• Last Synced: 2026-01-12T18:28:23.802Z (4 days ago)
• Topics: climate-data, europe, r-package
• Language: R
• Homepage: https://verughub.github.io/easyclimate/
• Size: 56.5 MB
• Stars: 50
• Watchers: 8
• Forks: 2
• Open Issues: 9
• Releases: 2
• Metadata Files:
  • Readme: README.Rmd
  • Changelog: NEWS.md
  • License: LICENSE.md

README.Rmd

          ---
output: github_document
---



```{r, include = FALSE}
library(knitr)
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  cache = TRUE
)

```

# `easyclimate` 

# Easy access to high-resolution daily, monthly and annual climate data for Europe



`r badger::badge_cran_release()` ![Badge CRAN release](https://img.shields.io/github/r-package/v/VeruGHub/easyclimate)  [![Project Status: Active -- The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active) [![R-CMD-check](https://github.com/VeruGHub/easyclimate/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/VeruGHub/easyclimate/actions/workflows/R-CMD-check.yaml) [![Badge CRAN logs](https://cranlogs.r-pkg.org/badges/grand-total/easyclimate)](https://cran.r-project.org/package=easyclimate)



Get high-resolution (1 km) daily, monthly and annual climate data (precipitation, and average, minimum and maximum temperatures) for Europe from the European climatic database hosted at the [Institute of Silviculture, University of Natural Resources and Life Sciences, Vienna, Austria](https://boku.ac.at/en/oekb/wald). Data are currently available from 1950 to 2024.

This climatic dataset was originally built by [A. Moreno & H. Hasenauer](https://doi.org/10.1002/joc.4436) and further developed by W. Rammer, C. Pucher & M. Neumann (see [this document](https://github.com/VeruGHub/easyclimate/blob/master/inst/Description_Evaluation_Validation_Downscaled_Climate_Data_v2.pdf) for more details on the development and characteristics of the climatic dataset, and [this document](https://doi.org/10.6084/m9.figshare.22962671.v1) for the updates of the last version - v4).

In this R package we implemented [Cloud-Optimised Geotiffs](http://cogeo.org/) so that we can obtain daily, monthly and climate data for thousands of sites/dates within seconds/minutes, without having to download huge rasters. But if you need to obtain data for large areas, please download the rasters from the FTP server () and extract the values locally rather than using this package, so as not to saturate the file server. For that, you may use a FTP client such as [FileZilla](https://filezilla-project.org/).

Please, be aware that data will be updated in an annual basis and values for past years might have small adjustments according to the annual spring releases of [E-OBS data](https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles). If you need to guarantee reproducibility of your analyses, please save the data locally as some data might change without notice after such updates.

For a detailed description of {easyclimate}, please read [this paper](https://doi.org/10.1016/j.envsoft.2023.105627) (open access version [here](https://doi.org/10.32942/osf.io/mc8uj)) or visit the package [website](https://verughub.github.io/easyclimate/).

## Installation

Stable version from [CRAN](https://cran.r-project.org/package=easyclimate):

```{r, eval = FALSE}
install.packages("easyclimate")
```

Development version from [GitHub](https://github.com/VeruGHub/easyclimate):

```{r, eval = FALSE}
# install.packages("remotes")
remotes::install_github("VeruGHub/easyclimate")
```

Development version from [R-universe](https://verughub.r-universe.dev/easyclimate):

```{r, eval = FALSE}
install.packages('easyclimate', 
                 repos = c('https://verughub.r-universe.dev', 'https://cloud.r-project.org'))
```

## Examples

### Obtain a data frame of climatic values

To obtain a data frame of daily and monthly climatic values for point coordinates:

```{r example_daily, message = FALSE}
library(easyclimate)

coords <- data.frame(lon = -5.36, lat = 37.40)

prec_daily <- get_daily_climate(coords, 
                                period = "2001-01-01:2001-01-03", 
                                climatic_var = "Prcp")
```

```{r echo = FALSE}
kable(prec_daily)
```

```{r example_monthly, message = FALSE}
prec_monthly <- get_monthly_climate(coords,
                                    period = "2001-01:2001-03",
                                    climatic_var = "Prcp")
```

```{r echo = FALSE}
kable(prec_monthly)
```




### Obtain a raster of climatic values

To obtain a (multi-layer) raster of daily climatic values for an area:

```{r message = FALSE, warning = FALSE, fig.width = 8, fig.height = 3}
library(terra)

## Download the polygon contour of a region
sobrarbe <- mapSpain::esp_get_comarca(comarca = "Sobrarbe")

## Coordinates must be in lonlat 
sobrarbe <- project(vect(sobrarbe), "EPSG:4326")

## Download Tmax values for that region between 1st and 3rd May 2020
sobrarbetemp <- get_daily_climate(
  coords = sobrarbe,
  climatic_var = "Tmax",
  period = "2020-05-01:2020-05-03",
  output = "raster"
)
```

The output (`sobrarbetemp`) is a SpatRaster with 3 layers (for each of 3 days):

```{r}
sobrarbetemp
```

Let's make a map. First using terra:

```{r map_terra, eval = FALSE}
plot(sobrarbetemp, col = rev(RColorBrewer::brewer.pal(9, "RdYlBu")), 
     smooth = TRUE, nc = 3)
```

![](man/figures/README-map_terra.png)

Now using ggplot2 and tidyterra:

```{r map_ggplot, message = FALSE, fig.width = 8, fig.height = 3}
library(ggplot2)
library(tidyterra)

ggplot() +
  geom_spatraster(data = sobrarbetemp) +
  facet_wrap(~lyr, ncol = 3) +
  scale_fill_distiller(palette = "RdYlBu", na.value = "transparent") +
  geom_spatvector(data = sobrarbe, fill = NA) +
  labs(fill = "Maximum\ntemperature (ºC)") +
  scale_x_continuous(breaks = c(-0.25, 0, 0.25)) +
  scale_y_continuous(breaks = seq(42.2, 42.8, by = 0.2)) +
  theme_minimal()
```


 Visit the articles of the [package website](https://verughub.github.io/easyclimate/) for more extended tutorials!




## CITATION

If you use {easyclimate}, please cite both the appropriate data source and the package as:

```{r echo = FALSE, results = 'asis', cache = FALSE}
print(citation("easyclimate"), style = "text")
```

        

---

Owner metadata

• Name: Verónica Cruz-Alonso
• Login: VeruGHub
• Email:
• Kind: user
• Description:
• Website:
• Location:
• Twitter:
• Company: @HarvardUniversity
• Icon url: https://avatars.githubusercontent.com/u/29353892?u=cdc4b010c701a63244e240d35d29929af4219545&v=4
• Repositories: 5
• Last ynced at: 2024-06-11T15:56:20.025Z
• Profile URL: https://github.com/VeruGHub

---

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---

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Last synced: 2 days ago

Name	Email	Commits
Pakillo	f****c@g****m	146
VeruGHub	v****z@u****s	98
smiromero	s****o@g****m	7
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• uah.es: 1

---

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Last synced: 9 days ago

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Package metadata

• Total packages: 3
• Total downloads:
  • cran: 227 last-month
• Total dependent packages: 0 (may contain duplicates)
• Total dependent repositories: 0 (may contain duplicates)
• Total versions: 6
• Total maintainers: 1

---

Dependencies

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