Install the latest stable version of cropgrowdays via CRAN with:
You can install the development version of
cropgrowdays from GitLab with:
The cropgrowdays package provides functions to calculate agrometeorological quantities of interest for modelling crop data. Currently, functions are provided for calculating growing degree days, stress days, cumulative and daily means of weather data. Australian meteorological data can be obtained from Queensland Government’s Department of Environment and Science (DES) website. In addition, functions are provided to convert days of the year to dates, and vice-versa.
We recommend using the cropgrowdays package in conjunction with the tidyverse and lubridate packages. Additionally, we also recommend using the furrr package to speed up adding agrometeorological variables to large data frames. For this document, we only use the lubridate package as follows.
Note that if you are not familiar with the lubridate
package, then in order to see which functions are provided and which
functions conflict with other packages, initially it may best not to
suppress messages using suppressMessages.
You can use the get_silodata function to retrieve SILO
weather data from the Queensland Government DES longpaddock website https://www.longpaddock.qld.gov.au.
The SILO (Scientific Information for Land Owners) is a database of Australian climate data hosted by the Science and Technology Division of the Queensland Government’s Department of Environment and Science. These datasets are constructed from Australian Bureau of Meteorology observations and provide national coverage with interpolated infills for missing data. Weather station data is the observed data while the gridded data is interpolated. Typically, for most variables, weather data can be obtained for the period 1 January 1889 to yesterday. Please see https://www.longpaddock.qld.gov.au/silo/about/overview/ for a more in-depth description.
SILO products are provided free of charge to the public for use under the Creative Commons Attribution 4.0 license. However, please note that this is a free service and so a fair-use limit is imposed even if exact limits are not specified.
The boonah dataset contains meteorological SILO data for
the period 1 Jan 2019 to 31 May 2020 obtained from the Longpaddock
Queensland Government DES web site https://www.longpaddock.qld.gov.au for Boonah which is
located at -27.9927 S, 152.6906 E. The data is in APSIM
format and contains temperature, rainfall, evaporation and radiation
variables and the rows are consecutive days during the period. The
weather data set was obtained using
boonah <-
get_silodata(latitude = "-27.9927", longitude = "152.6906",
email = "MY_EMAIL_ADDRESS", START = "20190101", FINISH = "20200531")To obtain gridded data, which is what get_silodata
assumes, you need to supply at least the site latitude and longitude as
well as your email address by replacing MY_EMAIL_ADDRESS
with your email address. The data is freely available under the Creative
Commons 4.0 License. Note that SILO may be unavailable between 11am and
1pm (Brisbane time) each Wednesday and Thursday to allow for essential
system maintenance. Also please note that, by default,
apsim data are retrieved. Most, but not all, of the other
formats are also available. See the help for get_silodata
for details. You can obtain this help using
?cropgrowdays::get_silodata at the R Console prompt or
using your favourite help system.
The data obtained is
## weather data object
print(boonah, n=5)
#: # A tibble: 517 × 10
#: year day radn maxt mint rain evap vp code date_met
#: <int> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int> <date>
#: 1 2019 1 26.2 33.9 16.3 0 7.8 20.6 222222 2019-01-01
#: 2 2019 2 28.2 33.4 17.6 0 7.7 19.8 222222 2019-01-02
#: 3 2019 3 20.5 32.8 16.7 0 6.8 21.9 222222 2019-01-03
#: 4 2019 4 23 32.5 21 2 7.7 22 222222 2019-01-04
#: 5 2019 5 27 33.6 16.8 0 6 21.8 222222 2019-01-05
#: # ℹ 512 more rowsFinally, please note that by default, the APSIM format
is returned and a date column called date_met is appended
to the retrieved data. Many other formats are available and may need to
be processed differently.
Use the get_multi_silodata function to get SILO data for
multiple sites. This is a simple wrapper to get_silodata.
The main differences are that latitude and
longitude are numerical vectors and the new parameter
Sitenameis a character vector of site names or site
labels.
A simple example is:
two_sites <- get_multi_silodata(latitude = c(-27.00, -28.00),
longitude = c(151.00, 152.00),
Sitename = c("Site_1", "Site_2"),
START = "20201101", FINISH = "20201105",
email = "MY_EMAIL_ADDRESS")The retrieved data are:
two_sites
#: # A tibble: 10 × 11
#: year day radn maxt mint rain evap vp code date_met Sitename
#: <int> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int> <date> <chr>
#: 1 2020 306 27.6 31.2 10.2 0 7.6 8.7 222222 2020-11-01 Site_1
#: 2 2020 307 23 31.3 11.8 0 7.2 13.3 222222 2020-11-02 Site_1
#: 3 2020 308 27.2 30.6 14 0 7.2 13 222222 2020-11-03 Site_1
#: 4 2020 309 26.3 32.5 14.4 0 8.8 13.6 222222 2020-11-04 Site_1
#: 5 2020 310 22.9 36.9 16.1 0 10 15.8 222222 2020-11-05 Site_1
#: 6 2020 306 26.6 27.3 9.6 0 7 10.6 222222 2020-11-01 Site_2
#: 7 2020 307 22.7 26.5 12.5 0 6.8 14.2 222222 2020-11-02 Site_2
#: 8 2020 308 28.5 26.4 12.3 0 6.8 11.2 222222 2020-11-03 Site_2
#: 9 2020 309 27.4 28.7 11.3 0 6.8 13.1 222222 2020-11-04 Site_2
#: 10 2020 310 19 33.6 13.5 0 9 17 222222 2020-11-05 Site_2Note that, to obtain gridded data, you need to supply at least each
site’s latitude and longitude as well as your email address by replacing
MY_EMAIL_ADDRESS with your email address. The data is
freely available under the Creative Commons 4.0 License.
The excellent R package bomrang (Adam H. Sparks et al. 2017; Adam H. Sparks et al.
2021), which used to provide forecast, bulletin and historic data
(see https://github.com/ropensci-archive/bomrang/), was
archived after the Australian Bureau of Meteorology appeared to ban
scraping on it’s websites in March 2021. Adam Sparks and team have
produced an R package weatherOz which also
includes a SILO wrapper (see https://github.com/ropensci/weatherOz). Paid services
for some forecast, current and historical weather data for areas of
interest may be available but these are not discussed here.