{weatherOz} facilitates access to and download of weather and climate data for Australia from Australian data sources. Data are sourced from from the Western Australia Department of Primary Industries and Regional Development (DPIRD) and the Scientific Information for Land Owners (SILO) API endpoints and the Australian Government Bureau of Meteorology’s (BOM) FTP server.
The package queries the APIs or an FTP server and returns data as a data frame or radar and satellite imagery in your R session. Observation data from DPIRD’s weather station network are available via the Weather 2.0 Open API initiative. SILO data is available from Queensland’s Long Paddock initiative (Jeffery et al. 2001) and are spatially and temporally complete, covering all Australia and few nearby islands (112 to 154 degrees longitude, -10 to -44 degrees latitude), with resolution 0.05° longitude by 0.05° latitude (approximately 5 km × 5 km). Visit the SILO website for more details about how the data is prepared and which climate data are available. Agriculture bulletins, radar imagery, satellite imagery and seven-day forecasts are available from the Bureau of Meteorology (BOM) via an anonymous FTP server.
Access to DPIRD API requires an API key. Apply for an API key by submitting the DPIRD API registration form. Access to the SILO API is conditioned to supplying a valid email address with the user query. Follow the API Terms and Conditions for the DPIRD and SILO APIs.
Observation data from the DPIRD’s weather station network is also available via a web interface. The data available is a mirror of the DPIRD Weather 2.0 API endpoints. Rainfall estimates are also available at virtual stations (i.e., where no observational data is present) and is sourced from the Doppler radar service provided by the Australian Government Bureau of Meteorology (BOM) under license.
Installation instructions
You can install the stable version of {weatherOz} from CRAN like so:
install.packages("weatherOz")You can install the development version of {weatherOz} like so:
install.packages("weatherOz", repos = "https://ropensci.r-universe.dev")A Note on API Keys
The examples in this README assume that you have stored your API key in your .Renviron file. {weatherOz} will prompt you to set up your API keys automatically if you haven’t. For more information on the preferred method for setting up your API keys, see Chapter 8 in “What They Forgot to Teach You About R” by Bryan et al. for more on storing details in your .Renviron if you are unfamiliar.
To get a DPIRD API key, you can use get_key() and it will direct you to the form to request a key and provides instructions for setting it up so that it’s available in your R session and {weatherOz} will automatically find it. If you have already set up an API key, this will return that value for you.
get_key(service = "DPIRD")You only need to provide an e-mail address for the SILO API. Using get_key() will provide you with instructions on what format to use in your .Renviron so that {weatherOz} will auto-recognise it and if you have already set up an API key, this will return that value for you.
get_key(service = "SILO")Note that you do not need to do this separately, any function requiring an API key will prompt you if you don’t have one set.
Example 1
Source wind and erosion conditions for daily time interval from the DPIRD Weather 2.0 API.
library(weatherOz)
wd <- get_dpird_summaries(
station_code = "BI",
start_date = "20220501",
end_date = "20220502",
interval = "daily",
values = c(
"wind",
"erosionCondition",
"erosionConditionMinutes",
"erosionConditionStartTime"
)
)
wd
#> Key: <station_code>
#> station_code station_name longitude latitude year month day date
#> <fctr> <char> <num> <num> <int> <int> <int> <Date>
#> 1: BI Binnu 114.6958 -28.051 2022 5 1 2022-05-01
#> 2: BI Binnu 114.6958 -28.051 2022 5 1 2022-05-01
#> 3: BI Binnu 114.6958 -28.051 2022 5 2 2022-05-02
#> 4: BI Binnu 114.6958 -28.051 2022 5 2 2022-05-02
#> erosion_condition_minutes erosion_condition_start_time wind_avg_speed
#> <int> <POSc> <num>
#> 1: 0 <NA> 10.85
#> 2: 0 <NA> 13.06
#> 3: 7 2022-05-02 15:01:00 15.57
#> 4: 7 2022-05-02 15:01:00 17.70
#> wind_height wind_max_direction_compass_point wind_max_direction_degrees
#> <int> <char> <int>
#> 1: 3 SSW 200
#> 2: 3 SSW 205
#> 3: 10 SSW 194
#> 4: 10 SSW 193
#> wind_max_speed wind_max_time
#> <num> <POSc>
#> 1: 31.82 2022-05-01 17:28:00
#> 2: 38.52 2022-05-02 16:07:00
#> 3: 34.88 2022-05-01 17:34:00
#> 4: 40.10 2022-05-02 16:31:00Example 2
Source data from latitude and longitude coordinates anywhere in Australia (interpolated/gridded data - SILO API) for Southwood, QLD for max and min temperature and rainfall.
library(weatherOz)
wd <- get_data_drill(
latitude = -27.85,
longitude = 150.05,
start_date = "20221001",
end_date = "20221201",
values = c(
"max_temp",
"min_temp",
"rain"
)
)
head(wd)
#> longitude latitude year month day date air_tmax air_tmax_source
#> <num> <num> <num> <num> <int> <Date> <num> <int>
#> 1: 150.05 -27.85 2022 10 1 2022-10-01 25.1 25
#> 2: 150.05 -27.85 2022 10 2 2022-10-02 22.6 25
#> 3: 150.05 -27.85 2022 10 3 2022-10-03 24.0 25
#> 4: 150.05 -27.85 2022 10 4 2022-10-04 25.7 25
#> 5: 150.05 -27.85 2022 10 5 2022-10-05 22.3 25
#> 6: 150.05 -27.85 2022 10 6 2022-10-06 24.4 25
#> air_tmin air_tmin_source elev_m extracted rainfall rainfall_source
#> <num> <int> <char> <Date> <num> <int>
#> 1: 9.8 25 254.5 m 2024-11-17 0.9 25
#> 2: 11.7 25 254.5 m 2024-11-17 0.0 25
#> 3: 7.8 25 254.5 m 2024-11-17 0.0 25
#> 4: 10.6 25 254.5 m 2024-11-17 0.0 25
#> 5: 13.3 25 254.5 m 2024-11-17 0.0 25
#> 6: 14.7 25 254.5 m 2024-11-17 1.8 25Notes on Data and API Endpoints
Note that most of the data are not static and may be replaced with improved data. Also please note that SILO may be unavailable between 11am and 1pm (Brisbane time) each Wednesday and Thursday to allow for essential system maintenance.
Please also note that not all exposed endpoints of the DPIRD APIs have associated functions. Development is ongoing. While we are responsive to user requests, we don’t make any commitments about speed of delivery.
References
Jeffrey, S.J., Carter, J.O., Moodie, K.B. and Beswick, A.R. (2001). Using spatial interpolation to construct a comprehensive archive of Australian climate data, Environmental Modelling and Software, Vol 16/4, pp 309-330. https://doi.org/10.1016/S1364-8152(01)00008-1.
Code of Conduct
Please note that this package is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.