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Change","sub_category":"Climate Data Access and Visualization","monthly_downloads":284,"total_dependent_repos":0,"total_dependent_packages":0,"readme":"---\noutput: github_document\n---\n\n\u003c!-- README.md is generated from README.Rmd. Please edit that file --\u003e\n\n```{r, include = FALSE}\nlibrary(knitr)\nknitr::opts_chunk$set(\n  collapse = TRUE,\n  comment = \"#\u003e\",\n  fig.path = \"man/figures/README-\",\n  cache = TRUE\n)\n\n```\n\n# `easyclimate` \u003ca href='https://verughub.github.io/easyclimate/'\u003e\u003cimg src=\"man/figures/easyclimate_logo_small.png\" align=\"right\" height=\"139\"/\u003e\u003c/a\u003e\n\n# Easy access to high-resolution daily, monthly and annual climate data for Europe\n\n\u003c!-- badges: start --\u003e\n\n`r badger::badge_cran_release()` ![Badge CRAN release](https://img.shields.io/github/r-package/v/VeruGHub/easyclimate) \u003ca href=\"https://diffify.com/R/easyclimate\" target=\"_blank\"\u003e\u003cimg src=\"https://diffify.com/diffify-badge.svg\" alt=\"The diffify page for the R package easyclimate\" style=\"width: 100px; max-width: 100%;\"/\u003e\u003c/a\u003e [![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)\n\n\u003c!-- badges: end --\u003e\n\nGet 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.\n\nThis climatic dataset was originally built by [A. Moreno \u0026 H. Hasenauer](https://doi.org/10.1002/joc.4436) and further developed by W. Rammer, C. Pucher \u0026 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).\n\nIn 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 (\u003cftp://palantir.boku.ac.at/Public/ClimateData/\u003e) 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/).\n\nPlease, 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.\n\nFor 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/).\n\n## Installation\n\nStable version from [CRAN](https://cran.r-project.org/package=easyclimate):\n\n```{r, eval = FALSE}\ninstall.packages(\"easyclimate\")\n```\n\nDevelopment version from [GitHub](https://github.com/VeruGHub/easyclimate):\n\n```{r, eval = FALSE}\n# install.packages(\"remotes\")\nremotes::install_github(\"VeruGHub/easyclimate\")\n```\n\nDevelopment version from [R-universe](https://verughub.r-universe.dev/easyclimate):\n\n```{r, eval = FALSE}\ninstall.packages('easyclimate', \n                 repos = c('https://verughub.r-universe.dev', 'https://cloud.r-project.org'))\n```\n\n## Examples\n\n### Obtain a data frame of climatic values\n\nTo obtain a data frame of daily and monthly climatic values for point coordinates:\n\n```{r example_daily, message = FALSE}\nlibrary(easyclimate)\n\ncoords \u003c- data.frame(lon = -5.36, lat = 37.40)\n\nprec_daily \u003c- get_daily_climate(coords, \n                                period = \"2001-01-01:2001-01-03\", \n                                climatic_var = \"Prcp\")\n```\n\n```{r echo = FALSE}\nkable(prec_daily)\n```\n\n```{r example_monthly, message = FALSE}\nprec_monthly \u003c- get_monthly_climate(coords,\n                                    period = \"2001-01:2001-03\",\n                                    climatic_var = \"Prcp\")\n```\n\n```{r echo = FALSE}\nkable(prec_monthly)\n```\n\n\u003cbr\u003e\n\n### Obtain a raster of climatic values\n\nTo obtain a (multi-layer) raster of daily climatic values for an area:\n\n```{r message = FALSE, warning = FALSE, fig.width = 8, fig.height = 3}\nlibrary(terra)\n\n## Download the polygon contour of a region\nsobrarbe \u003c- mapSpain::esp_get_comarca(comarca = \"Sobrarbe\")\n\n## Coordinates must be in lonlat \nsobrarbe \u003c- project(vect(sobrarbe), \"EPSG:4326\")\n\n## Download Tmax values for that region between 1st and 3rd May 2020\nsobrarbetemp \u003c- get_daily_climate(\n  coords = sobrarbe,\n  climatic_var = \"Tmax\",\n  period = \"2020-05-01:2020-05-03\",\n  output = \"raster\"\n)\n```\n\nThe output (`sobrarbetemp`) is a SpatRaster with 3 layers (for each of 3 days):\n\n```{r}\nsobrarbetemp\n```\n\nLet's make a map. First using terra:\n\n```{r map_terra, eval = FALSE}\nplot(sobrarbetemp, col = rev(RColorBrewer::brewer.pal(9, \"RdYlBu\")), \n     smooth = TRUE, nc = 3)\n```\n\n![](man/figures/README-map_terra.png)\n\nNow using ggplot2 and tidyterra:\n\n```{r map_ggplot, message = FALSE, fig.width = 8, fig.height = 3}\nlibrary(ggplot2)\nlibrary(tidyterra)\n\nggplot() +\n  geom_spatraster(data = sobrarbetemp) +\n  facet_wrap(~lyr, ncol = 3) +\n  scale_fill_distiller(palette = \"RdYlBu\", na.value = \"transparent\") +\n  geom_spatvector(data = sobrarbe, fill = NA) +\n  labs(fill = \"Maximum\\ntemperature (ºC)\") +\n  scale_x_continuous(breaks = c(-0.25, 0, 0.25)) +\n  scale_y_continuous(breaks = seq(42.2, 42.8, by = 0.2)) +\n  theme_minimal()\n```\n\n\u003cbr\u003e Visit the articles of the [package website](https://verughub.github.io/easyclimate/) for more extended tutorials!\n\n\u003cbr\u003e\n\n## CITATION\n\nIf you use {easyclimate}, please cite both the appropriate data source and the package 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