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modd-africa/moddafricaes

Domain:

climate

Record type:

software
Creator:
mod
Host:
Evidence Synthesis for the MoDD Africa Project # moddafricaes : MoDD Africa Evidence Synthesis Tools to collate, analyse and communicate evidence for the **MoDD Africa** project. The package currently focuses on a single end-to-end pipeline for **ERA5-Land** climate reanalysis: derive a study-area bounding box from a shapefile, download hourly NetCDFs from the Copernicus Climate Data Store (CDS), and transform them into analysis-ready Parquet (hourly or monthly) or GeoTIFF (monthly min / max temperature). ## Installation `moddafricaes` is not on CRAN. Pick whichever GitHub-install path matches your tooling: ``` r # 1. pak (recommended; resolves system deps too) # install.packages("pak") pak::pak("modd-africa/moddafricaes") # 2. remotes # install.packages("remotes") remotes::install_github("modd-africa/moddafricaes") # 3. devtools # install.packages("devtools") devtools::install_github("modd-africa/moddafricaes") # 4. A specific branch, tag, or commit pak::pak("modd-africa/moddafricaes@main") pak::pak("modd-africa/moddafricaes@v0.1.0") # 5. From a local clone (e.g. for development) # git clone github.com # cd moddafricaes # R -e 'devtools::install()' # or: pak::local_install(".") ``` You will also need a Copernicus CDS account and an API key exported as `CDS_API_KEY` (see ). ## Functions | Function | Stage | Output | |----|----|----| | `get_bounding_box()` | Setup | `c(N, W, S, E)` numeric vector (CDS) | | `extract_era5land()` | Download | One NetCDF per (year, month) | | `transform_era5land()` | Transform | One Parquet per year (hourly) | | `transform_era5land_monthly()` | Transform | One Parquet (monthly means) | | `transform_era5land_minmax()` | Transform | GeoTIFF stacks of monthly T2m min/max | All bounding boxes throughout the package are in Copernicus CDS order **`c(N, W, S, E)`**, not `sf::st_bbox()`’s `(xmin, ymin, xmax, ymax)`. ## End-to-end example ``` r library(moddafricaes) # 1. Derive a bounding box from any shapefile (zipped shapefiles …