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Change","sub_category":"Climate Data Access and Visualization","monthly_downloads":0,"total_dependent_repos":0,"total_dependent_packages":0,"readme":"\u003c!-- badges: start --\u003e\n[![peer-review](https://badges.ropensci.org/357_status.svg)](https://github.com/ropensci/software-review/issues/357)\n[![status](https://joss.theoj.org/papers/3367fdbff2db55a60c1ab7d611017940/status.svg)](https://joss.theoj.org/papers/3367fdbff2db55a60c1ab7d611017940)\n[![CRAN status](https://www.r-pkg.org/badges/version/chirps)](https://cran.r-project.org/package=chirps)\n[![Project Status](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)\n[![DOI](https://zenodo.org/badge/225693680.svg)](https://zenodo.org/badge/latestdoi/225693680)\n[![R-CMD-check](https://github.com/ropensci/chirps/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/ropensci/chirps/actions/workflows/R-CMD-check.yaml)\n[![Codecov test coverage](https://codecov.io/gh/ropensci/chirps/graph/badge.svg)](https://app.codecov.io/gh/ropensci/chirps)\n\u003c!-- badges: end --\u003e\n\n# chirps: Access Climate Hazards Center Datasets \u003cimg align=\"right\" src=\"man/figures/logo.png\"\u003e\n\n## Overview\n\n**chirps** provides access to Climate Hazards Center (CHC) datasets including CHIRPS, CHIRPS v3, CHIRTS-daily, and CHIRTS-ERA5. Data can be retrieved either as extracted values for points and polygons or as native raster products for custom spatial workflows.\n\n## Available Datasets\n\n| Dataset | Variable | Resolution | Period |\n|----------|----------|----------|----------|\n| CHIRPS v2 | Precipitation | 0.05° / 0.25° | 1981–present |\n| CHIRPS v3 | Precipitation | 0.05° | 1981–present |\n| CHIRTS-daily | Tmax, Tmin, RHum, HeatIndex | 0.05° | 1983–2016 |\n| CHIRTS-ERA5 | Tmax, Tmin | 0.05° | 1980–present |\n\n## Applications\n\nThese datasets are commonly used for:\n\n- Crop modeling\n- Climate risk assessment\n- Agricultural monitoring\n- Seasonal analysis\n- Environmental characterization\n- Ecological and biodiversity studies\n\n## Quick start\n\n### From CRAN\n\nThe stable version is available through CRAN.\n\n```r\ninstall.packages(\"chirps\")\n```\n\n### From GitHub\n\nA development version that may have new features or bug fixes is available through GitHub.\n\n``` r\nlibrary(\"remotes\")\n\ninstall_github(\"ropensci/chirps\", build_vignettes = TRUE)\n```\n\n## Example\n\n## Accessing raw raster products\n\nThe package can provide direct access to CHC climate datasets as `terra::SpatRaster` objects. This is useful when working with large spatial datasets or custom extraction workflows.\n\n```r\nlibrary(\"chirps\")\nlibrary(\"terra\")\n\ndates = c(\"2017-11-15\", \"2017-11-20\")\n\n# CHIRPS v2 precipitation\nchirps_v2 = get_chirps_raw(dates = dates, version = \"2.0\")\n\n# CHIRPS v3 precipitation\nchirps_v3 = get_chirps_raw(dates = dates, version = \"3.0\", type = \"sat\")\n\n# CHIRTS-ERA5 minimum temperature\ntmin = get_chirts_era5_raw(dates = dates, var = \"Tmin\")\n\n# CHIRTS-ERA5 maximum temperature\ntmax = get_chirts_era5_raw(dates = dates, var = \"Tmax\")\n```\n\nRaster values can be extracted using functions from the `terra` package. Fetch CHIRPS data from three points across the Tapajós National Forest (Brazil) in January 2017.\n\n```r\nlonlat = data.frame(lon = c(-55.0281, -54.9857, -55.0714),\n                    lat = c(-2.8094, -2.8756, -3.5279))\n\npts = vect(lonlat,\n           geom = c(\"lon\", \"lat\"),\n           crs = \"EPSG:4326\")\n\nrain = extract(chirps_v2, pts)\n```\n\nThe resulting object contains daily values for each location and can be readily converted to a matrix or data frame for further analysis.\n\nThe recommended workflow is to retrieve native raster products using `get_chirps_raw()`, `get_chirts_raw()`, and `get_chirts_era5_raw()`, and then use the `terra` package for extraction and spatial analysis.\n\n### Accessing high-level extraction\n\n`get_chirps()` default procedure will download the COG files from the CHIRPS server and handle it internally using the package `terra`. This is more interesting when dealing with hundreds of points and days. Data can be returned as a matrix using the argument `as.matrix = TRUE`.\n\n```r\nlibrary(\"chirps\")\n\nlonlat = data.frame(lon = c(-55.0281,-54.9857, -55.0714),\n                    lat = c(-2.8094, -2.8756, -3.5279))\n\ndates = c(\"2017-01-01\", \"2017-01-31\")\n\ndat = get_chirps(lonlat, dates, server = \"CHC\", as.matrix = FALSE)\n\n```\n\nFor a faster download of few datapoints (~ 10 datapoints), the argument `server = \"ClimateSERV\"` can be used  \n\n```r\nlibrary(\"chirps\")\n\nlonlat = data.frame(lon = c(-55.0281,-54.9857, -55.0714),\n                    lat = c(-2.8094, -2.8756, -3.5279))\n\ndates = c(\"2017-01-01\", \"2017-01-31\")\n\ndat = get_chirps(lonlat, dates, server = \"ClimateSERV\", as.matrix = FALSE)\n\n```\n\n## Going further\n\nThe full functionality of **chirps** is illustrated in the package vignette. The vignette can be found on the [package website](https://docs.ropensci.org/chirps/) or from within `R` once the package has been installed, e.g. via: \n\n``` r\nvignette(\"Overview\", package = \"chirps\")\n```\n\n## Citing Data\n\nWhile *chirps* does not redistribute data, users should cite the original data providers when using CHIRPS, CHIRTS, CHIRTS-ERA5, or CHIRPS v3 products.\n\nWhen using datasets obtained through this package, please cite the original data providers.\n\n### CHIRPS v3\n\u003e Funk, C., Peterson, P., Harrison, L. et al. (2026). The Climate Hazards Center Infrared Precipitation with Stations, Version 3. Scientific Data, 13, 718. \u003chttps://doi.org/10.1038/s41597-026-07096-4\u003e\n\n### CHIRTS-ERA5\n\u003e CHIRTS-ERA5 Data Repository https://doi.org/10.15780/G2F08J (2025). Data was accessed on [DATE].\n\n### CHIRPS v2\n\u003e Funk C., Peterson P., Landsfeld M., … Michaelsen J. (2015). The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes. *Scientific Data*, 2, 150066. \u003chttps://doi.org/10.1038/sdata.2015.66\u003e\n\n### CHIRTS\n\u003e Verdin, A., Funk, C., Peterson, P., Landsfeld, M., Tuholske, C., and Grace, K. (2020). Development and validation of the CHIRTS-daily quasi-global high-resolution daily temperature data set. Scientific Data, 7, 303.\n\u003chttps://doi.org/10.1038/s41597-020-00643-7\u003e\n\n## Meta\n\n  - Please [report any issues or bugs](https://github.com/ropensci/chirps/issues).\n\n  - License: MIT.\n\n  - Get citation information for *chirps* in R by typing `citation(package = \"chirps\")`.\n\n  - You are welcome to contribute to the *chirps* project. Please read our [contribution guidelines](CONTRIBUTING.md).\n\n  - Please note that the *chirps* project is released with a a [Contributor Code of Conduct](https://ropensci.org/code-of-conduct/). 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