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Import PRISM daily weather data

Source: R/read_importprism.R
read_importprism.Rd

Download and crop the latest weather rasters from Parameter-elevation Relationship on Independent Slopes Model (PRISM). Summarize by zone and save as CSV.

Usage

read_importprism(
  vars = c("tmin", "tmax", "tdmean", "ppt"),
  vars_ytd = c("ppt"),
  date_beg = as.Date("1981-01-01"),
  date_end = Sys.Date(),
  bbox = sf::st_bbox(sf_zones),
  dir_tif = sub("\\.[^.]*$", "", zonal_csv),
  pfx_tif = "prism_daily_",
  sf_zones,
  fld_zones,
  zonal_fun = "mean",
  zonal_csv,
  redo_zonal = F,
  verbose = F
)

Arguments

vars

character vector of PRISM variables to download and crop. The default is c("tmin", "tmax", "tdmean", "ppt"). See Details for more.

vars_ytd

character vector of PRISM variables to be summed for the year to date, which gets recorded as a new layer with the suffix "ytd". The default is for precipitation c("ppt"), so a layer "pptytd" gets added to PRISM daily rasters.

date_beg

defaults to the start of PRISM daily availability 1981-01-01.

date_end

defaults to today's date, but will be adjusted to the most recently available data, per update schedule. CAUTION: If you try to request the same date-variable in a given day, you will get an error from the PRISM service with a message like "You have tried to download the file PRISM_tdmean_stable_4kmD2_19810101_bil.zip more than twice in one day (Pacific local time). Note that repeated offenses may result in your IP address being blocked."

bbox

bounding box of the spatial extent to crop PRISM daily rasters, which could be bigger than st_bbox(sf_zones).

dir_tif

directory path to store downloaded and cropped PRISM daily rasters (as GeoTIFF) across years with file name of format prism_daily_{month}-{day}.tif. The default path is sub("\\.[^.]*$", "", zonal_csv). Date and version in the raster layers will be compared with the update schedule to determine if it should be updated, otherwise will be skipped.

pfx_tif

prefix for the PRISM daily raster files, appended by the month-day. Defaults to "prism_daily_".

sf_zones

spatial feature object (sf) with zones to extract zonal statistics from PRISM daily weather data

fld_zones

character vector of unique field name(s) in sf_zones to include in extracted zonal statistics

zonal_fun

function to apply to the terra::zonal() function. Defaults to "mean". Other options are "min", "max", "sum", "isNA", and "notNA".

zonal_csv

path to output of zonal statistics (terra::zonal()) as table in CSV format

redo_zonal

logical whether to recalculate the zonal statistics. Defaults to False.

verbose

logical whether to show informative messages on processing

Value

data frame with the following columns:

  • {fld_zones} column(s) specified from input sf_zones

  • {zonal_fun}: value of input function (e.g. "mean") summarizing raster to zone

  • date: date of PRISM daily raster

  • variable: PRISM variable

  • version: PRISM version

  • date_updated: date of PRISM daily raster update

Details

The Parameter-elevation Relationship on Independent Slopes Model (PRISM) is a combined dataset consisting of ground gauge station and RADAR products, at a 4km grid resolution covering the contiguous United States from 1981 to present.

Variables

The available variables (vars) are:

  • tmin: minimum temperature (ºC)

  • tmax: maximum temperature (ºC)

  • tmean: mean temperature (ºC; tmean = mean(tmin, tmax))

  • tdmean: mean dew point temperature (ºC)

  • ppt: total precipitation (mm; rain and snow)

  • vpdmin: daily minimum vapor pressure deficit

  • vpdmax: daily maximum vapor pressure deficit

Updates

The daily PRISM data is available over three stability levels, or 8 versions given by the update schedule:

  • stable: data is considered final and will not change (before 6 months)

  • provisional: data is considered final but may be updated (previous 6 months)

  • early: data is preliminary and may be updated (this month)

Processing details

  1. The PRISM update schedule is downloaded and processed in a data frame to understand the latest date and variable available, along with version and date updated.

  2. Any existing rasters in dir_tif are fetched based on a common naming structure for the raster file name (prism_daily_{month}-{day}.tif) and layer names ({date}_{variable}_v{version}-{date_updated}) into a data frame.

  3. Based on intersecting above with the requested dates, any missing or more recently updated variable-date PRISM rasters are downloaded and cropped to the bounding box (bbox) and written as GeoTIFFs (*.tif). Layers are renamed to include extra information on {version} (1-8) and {date_udpated}.

  4. Summary statistics (based on sf_zones and zonal_fun) are calculated on the cropped PRISM daily rasters.

More on PRISM

For more on Parameter-elevation Relationship on Independent Slopes Model (PRISM), see:

Examples

if (FALSE) { # \dontrun{
# setup output directory and table
dir_tif   <- system.file("prism", package = "tbeptools")
zonal_csv <- system.file("prism/_zones.csv", package = "tbeptools")

# run function for Tampa Bay watersheds for first 3 days and 4 variables
d <- read_importprism(
  vars      = c("tdmean", "ppt"),
  date_beg  = as.Date("1981-01-01"),
  date_end  = as.Date("1981-01-02"),
  dir_tif   = dir_tif,
  sf_zones  = tbsegshed,
  fld_zones = "bay_segment",
  zonal_csv = zonal_csv)

# show raster files, layers and plot
tifs <- list.files(dir_tif, pattern = ".tif$", full.names = T)
basename(tifs)
r <- terra::rast(tifs[1])
r
names(r)
terra::plet(
  r[[3]],
  main  = names(r)[3],
  col   = "Spectral",
  tiles = "CartoDB.DarkMatter")

# show summary by zone
d
} # }