A dedicated Slack channel has been created for announcements, support and to help build a community of practice around this open source package. You may request an invitation to join from jonathan.callahan@dri.com.
Utilities for working with Remote Automatic Weather Station (RAWS) data
The USFS Pacific Wildland Fire Sciences Lab AirFire team works to model wildland fire emissions and has created the BlueSky Modeling Framework. This system integrates a wide collection of models along a smoke modeling pipeline (fire information > fuel loadings > consumption modeling > emissions modeling > time rate of emissions modeling > plume height estimations > smoke trajectory and dispersion modeling). The resulting model output has been integrated into many different smoke prediction systems and scientific modeling efforts.
The RAWSmet R package is being developed for AirFire to help modelers and scientists more easily work with weather data from RAWS stations across North America.
The package makes it easier to obtain data, perform analyses and generate reports. It includes functionality to:
- access metadata and timeseries data from https://cefa.dri.edu/raws
- access metadata and timeseries data from https://raws.dri.edu
- save and reload .rda versions of these in a rawsDataDir
- determine which locations obtained from metadata are too close to be considered “unique” locations
- convert between UTC and local timezones
- apply various algorithms to the data: rolling means, aggregation, etc.
- provide interactive timeseries and maps through RStudio’s Viewer pane
- create a variety of publication ready maps and timeseries plots
Users will want to install the remotes package to have access to the latest version of the package from GitHub.
The following packages should be installed by typing the following at the RStudio console:
# Note that vignettes require knitr and rmarkdown
install.packages('knitr')
install.packages('rmarkdown')
install.packages('MazamaSpatialUtils')
install.packages('MazamaLocationUtils')
devtools::install_github('MazamaScience/RAWSmet')
Any work with spatial data, e.g. assigning states, counties and timezones, will require installation of required spatial datasets. To get these datasets you should type the following at the RStudio console:
# Install spatial datasets for assigning country, state, timezone and county
library(MazamaSpatialUtils)
dir.create('~/Data/Spatial', recursive = TRUE)
setSpatialDataDir('~/Data/Spatial')
installSpatialData("EEZCountries")
installSpatialData("NaturalEarthAdm1")
installSpatialData("OSMTimezones")
installSpatialData("USCensusCounties")
Data generated with package functions can be be saved and reloaded in a
dedicated directory much the same as the spatialDataDir used above:
library(RAWSmet)
dir.create('~/Data/RAWS', recursive = TRUE)
setRawsDataDir('~/Data/RAWS')
This R package was created by Mazama Science and is being funded by the USFS AirFire Research Team.