metR

Several functions and utilities that make R better for handling meteorological data in the tidy data paradigm.
https://github.com/eliocamp/metR

Category: Atmosphere
Sub Category: Meteorological Observation and Forecast

Keywords

atmospheric-science ggplot2 r r-package rstats visualization

Keywords from Contributors

visualisation

Last synced: about 18 hours ago
JSON representation

Repository metadata

Tools for Easier Analysis of Meteorological Fields

• Host: GitHub
• URL: https://github.com/eliocamp/metR
• Owner: eliocamp
• Created: 2017-07-05T20:09:40.000Z (almost 8 years ago)
• Default Branch: master
• Last Pushed: 2025-03-20T00:32:31.000Z (about 1 month ago)
• Last Synced: 2025-04-20T09:43:50.161Z (7 days ago)
• Topics: atmospheric-science, ggplot2, r, r-package, rstats, visualization
• Language: R
• Homepage: https://eliocamp.github.io/metR/
• Size: 523 MB
• Stars: 150
• Watchers: 4
• Forks: 25
• Open Issues: 17
• Releases: 19
• Metadata Files:
  • Readme: README.Rmd
  • Changelog: NEWS.md

README.Rmd

          ---
output: github_document
---



```{r, echo = FALSE}
knitr::opts_chunk$set(
    cache = FALSE,
    collapse = TRUE,
    comment = "#>",
    fig.path = "man/figures/"
)
set.seed(42)
```

# metR 



[![R-CMD-check](https://github.com/eliocamp/metR/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/eliocamp/metR/actions/workflows/R-CMD-check.yaml)
[![Coverage status](https://codecov.io/gh/eliocamp/metR/branch/master/graph/badge.svg?token=jVznWTMCpz)](https://app.codecov.io/gh/eliocamp/metR)
[![CRAN status](https://www.r-pkg.org/badges/version/metR)](https://CRAN.R-project.org/package=metR)
[![DOI](https://zenodo.org/badge/96357263.svg)](https://zenodo.org/badge/latestdoi/96357263)



metR packages several functions and utilities that make R better for handling  meteorological data in the tidy data paradigm. It started mostly sa a packaging of assorted wrappers and tricks that I wrote for my day to day work as a researcher in atmospheric sciences. Since then, it has grown organically and for my own needs and feedback from users. 

Conceptually it's divided into *visualization tools* and *data tools*. The former are geoms, stats and scales that help with plotting using [ggplot2](https://ggplot2.tidyverse.org/index.html), such as `stat_contour_fill()` or `scale_y_level()`, while the later are functions for common data processing tools in the atmospheric sciences, such as `Derivate()` or `EOF()`; these are implemented to work in the [data.table](https://github.com/Rdatatable/data.table/wiki) paradigm, but also work with regular data frames. 

Currently metR is in development but maturing. Most functions check arguments and there are some tests. However, some functions might change it's interface, and functionality can be moved to other packages, so please bear that in mind. 

## Installation

You can install metR from CRAN with:

```{r CRAN-installation, eval = FALSE}
install.packages("metR")
```

Or the development version with:

```{r gh-installation, eval = FALSE}
if (!requireNamespace("pak", quietly = TRUE)) {
    install.packages("pak")
}
pak::pak("metR")
```

If you need to read netcdf files, you might need to install the netcdf and udunits2 libraries. On Ubuntu and it's derivatives this can be done by typing 

```
sudo apt install libnetcdf-dev netcdf-bin libudunits2-dev
```

## Citing the package

If you use metR in your research, please consider citing it. You can get citation information with 

```{r}
citation("metR")
```


## Examples

In this example we easily perform Principal Components Decomposition (EOF) on monthly geopotential height, then compute the geostrophic wind associated with this field and plot the field with filled contours and the wind with streamlines.

```{r field}
library(metR)
library(data.table)
library(ggplot2)
data(geopotential)
# Use Empirical Orthogonal Functions to compute the Antarctic Oscillation
geopotential <- copy(geopotential)
geopotential[, gh.t.w := Anomaly(gh)*sqrt(cos(lat*pi/180)),
      by = .(lon, lat, month(date))]
aao <- EOF(gh.t.w ~ lat + lon | date, data = geopotential, n = 1)
aao$left[, c("u", "v") := GeostrophicWind(gh.t.w/sqrt(cos(lat*pi/180)), 
                                                    lon, lat)]

# AAO field
binwidth <- 0.01
ggplot(aao$left, aes(lon, lat)) +
    geom_contour_fill(aes(z = gh.t.w/sqrt(cos(lat*pi/180)), 
                          fill = after_stat(level)), binwidth = binwidth,
                      xwrap = c(0, 360)) +
    geom_streamline(aes(dx = dlon(u, lat), dy = dlat(v)),
                    linewidth = 0.4, L = 80, skip = 3, xwrap = c(0, 360)) +
    scale_x_longitude() +
    scale_y_latitude(limits = c(-90, -20)) +
    scale_fill_divergent_discretised(name = "AAO pattern") +
    coord_polar()
```

```{r timeseries}
# AAO signal
ggplot(aao$right, aes(date, gh.t.w)) +
    geom_line() +
    geom_smooth(span = 0.4)
```

You can read more in the vignettes: [Visualization tools](https://eliocamp.github.io/metR/articles/Visualization-tools.html) and [Working with data](https://eliocamp.github.io/metR/articles/Working-with-data.html).

        

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Owner metadata

• Name: Elio Campitelli
• Login: eliocamp
• Email:
• Kind: user
• Description: PhD Student at University of Buenos Aires
• Website:
• Location: Melbourne, Australia
• Twitter:
• Company:
• Icon url: https://avatars.githubusercontent.com/u/8617595?v=4
• Repositories: 158
• Last ynced at: 2025-04-24T10:05:25.868Z
• Profile URL: https://github.com/eliocamp

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GitHub Events

Total

• Create event: 2
• Release event: 2
• Issues event: 14
• Watch event: 9
• Issue comment event: 8
• Push event: 19
• Pull request event: 1
• Fork event: 3

Last Year

• Create event: 2
• Release event: 2
• Issues event: 14
• Watch event: 9
• Issue comment event: 8
• Push event: 19
• Pull request event: 1
• Fork event: 3

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Committers metadata

Last synced: 5 days ago

Name	Email	Commits
Unknown	e****i@g****m	1060
Teun van den Brand	4****d	5
Paul Murrell	p****l@s****z	1
Paola Corrales	p****s	1
Matt	3****r	1

Committer domains:

• stat.auckland.ac.nz: 1

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Issue and Pull Request metadata

Last synced: 2 days ago

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/eliocamp/metR

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Package metadata

• Total packages: 2
• Total downloads:
  • cran: 5,376 last-month
• Total docker downloads: 42,058
• Total dependent packages: 23 (may contain duplicates)
• Total dependent repositories: 31 (may contain duplicates)
• Total versions: 33
• Total maintainers: 1

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Dependencies

Score: 17.495790391105604