Extract Weather From SILO Data Drill Using Australian GPS Coordinates

A modified wrapper version of weatherOz::get_data_drill that allows for fetching many geophysical points or a single geophysical point. Extracts interpolated weather data from the SILO API from the gridded data, PatchedPointData, data set.

Usage

extract_data_drill(
  xy,
  locations = NULL,
  lonlat = NULL,
  start_date,
  end_date,
  values = "all",
  api_key = weatherOz::get_key(service = "SILO")
)

Arguments

xy: A list or data.frame object with names containing pairings of longitude and latitude values expressed as decimal degree values in that order. A data.frame may also be an sf points object. See Details for more.
locations: The column in which the location names are located as an Integer value. Defaults to 1.
lonlat: A vector of integer values indicating the column index in which the longitude and latitude values are contained. Defaults to 2:3.
start_date: A character string or Date object representing the beginning of the range to query in the format “yyyy-mm-dd” (ISO8601). Data returned is inclusive of this date.
end_date: A character string or Date object representing the end of the range query in the format “yyyy-mm-dd” (ISO8601). Data returned is inclusive of this date. Defaults to the current system date.
values: A character string with the type of weather data to return. See Available Values for a full list of valid values. Defaults to all with all available values being returned.
api_key: A character string specifying a valid email address to use for the request. The query will return an error if a valid email address is not provided.

Value

A data.table::data.table() with the weather data queried with the weather variables in alphabetical order. The first eight columns will always be:

longitude,
latitude,
elev_m (elevation in metres),
date (ISO8601 format, YYYYMMDD),
year,
month,
day,
extracted (the date on which the query was made)

Available Values

all: Which will return all of the following values
rain (mm): Rainfall
max_temp (degrees C): Maximum temperature
min_temp (degrees C): Minimum temperature
vp (hPa): Vapour pressure
vp_deficit (hPa): Vapour pressure deficit
evap_pan (mm): Class A pan evaporation
evap_syn (mm): Synthetic estimate¹
evap_comb (mm): Combination (synthetic estimate pre-1970, class A pan 1970 onwards)
evap_morton_lake (mm): Morton's shallow lake evaporation
radiation (Mj/m²): Solar exposure, consisting of both direct and diffuse components
rh_tmax (%): Relative humidity at the time of maximum temperature
rh_tmin (%): Relative humidity at the time of minimum temperature
et_short_crop (mm): FAO56⁴ short crop
et_tall_crop (mm): ASCE⁵ tall crop⁶
et_morton_actual (mm): Morton's areal actual evapotranspiration
et_morton_potential (mm): Morton's point potential evapotranspiration
et_morton_wet (mm): Morton's wet-environment areal potential evapotranspiration over land
mslp (hPa): Mean sea level pressure

Value information

Solar radiation: total incoming downward shortwave radiation on a horizontal surface, derived from estimates of cloud oktas and sunshine duration³.

Relative humidity: calculated using the vapour pressure measured at 9am, and the saturation vapour pressure computed using either the maximum or minimum temperature⁶.

Evaporation and evapotranspiration: an overview of the variables provided by SILO is available here, https://data.longpaddock.qld.gov.au/static/publications/Evapotranspiration_overview.pdf.

Data codes

Data codes Where possible (depending on the file format), the data are supplied with codes indicating how each datum was obtained.

0: Official observation as supplied by the Bureau of Meteorology
15: Deaccumulated rainfall (original observation was recorded over a period exceeding the standard 24 hour observation period)
25: Interpolated from daily observations for that date
26: Synthetic Class A pan evaporation, calculated from temperatures, radiation and vapour pressure
35: Interpolated from daily observations using an anomaly interpolation method
75: Interpolated from the long term averages of daily observations for that day of year

xy

xy as a List Object

If xy is a list object, each individual vector's items should be named “x” (longitude) and “y” (latitude), respectively. The list item names should be descriptive of the individual vectors and will be included in a “location” column of the output.

xy as a Data Frame Object

If xy is a data.frame, it should be a three column object with the first column being the location name, the second longitude and the third, latitude both as decimal degrees in numeric format.

xy as an sf Object

If xy is an sf object, it should only be point geometry. If the data are projected, they will be reprojected to "EPSG:4326", Geographic Coordinate System WGS 84 before the extraction.

References

Rayner, D. (2005). Australian synthetic daily Class A pan evaporation. Technical Report December 2005, Queensland Department of Natural Resources and Mines, Indooroopilly, Qld., Australia, 40 pp.
Morton, F. I. (1983). Operational estimates of areal evapotranspiration and their significance to the science and practice of hydrology, Journal of Hydrology, Volume 66, 1-76.
Zajaczkowski, J., Wong, K., & Carter, J. (2013). Improved historical solar radiation gridded data for Australia, Environmental Modelling & Software, Volume 49, 64–77. DOI: doi:10.1016/j.envsoft.2013.06.013 .
Food and Agriculture Organization of the United Nations, Irrigation and drainage paper 56: Crop evapotranspiration - Guidelines for computing crop water requirements, 1998.
ASCE’s Standardized Reference Evapotranspiration Equation, proceedings of the National Irrigation Symposium, Phoenix, Arizona, 2000.
For further details refer to 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, Volume 16/4, 309-330. DOI: doi:10.1016/S1364-8152(01)00008-1 .

Author

Adam H. Sparks, adamhsparks@gmail.com

Examples

if (FALSE) { # \dontrun{
# Source data from a list of latitude and longitude coordinates in NSW
# and WA
locs <- list(
  "Merredin" = c(x = 118.28, y = -31.48),
  "Corrigin" = c(x = 117.87, y = -32.33),
  "Tamworth" = c(x = 150.84, y = -31.07)
)

wd <- extract_data_drill(
  xy = locs,
  start_date = "20211001",
  end_date = "20211201",
  values = "all",
  api_key = "your_api_key"
)
} # }