Package 'raadtools'

Description

Tools in R for reading, plotting and manipulating spatial data, originally used at the Australian Antarctic Division (AAD).

Details

read functions like readsst will read a data set by date-time vector, with a set of shared arguments that work the same and documented against this dummy function.

Author(s)

Michael D. Sumner [email protected]

Options

Maintainer: Michael D. Sumner [email protected]

See Also

Useful links:

• https://github.com/AustralianAntarcticDivision/raadtools

• Report bugs at https://github.com/AustralianAntarcticDivision/raadtools/issues

Description

Raw list of all files.

Usage

allfiles(...)

Arguments

Value

data.frame with columns fullname with all file paths

Description

A one-row-per-date catalogue of the Antarctic altimetry time series. Each source file found by raadfiles::altimetry_antarctica_files() holds the whole of its own series, one band per date, so this reads the time dimension of each and returns a row per date with the band to read within its file.

Usage

altimetry_antarctica_daily_files()

Value

data.frame of date, fullname, band and root

See Also

read_altimetry_antarctica_daily()

Description

AMPS files

Usage

amps_d1_icefiles(data.source = "", time.resolution = "12hourly", ...)

Arguments

Description

GRIB format metadata from the Antarctic Mesoscale Prediction System (AMPS) files.

Format

amps_metadata A data frame with 8 columns. The columns represent

Details

A snapshot of one 2015-era d1 file, not a current index. The band layout has changed three times since - see the notes at the top of R/amps.R - so readamps_d1wind and readamps_d1ice find their bands by name in the file being read rather than by position in this table.

Examples

print(amps_metadata)
## u_wind_at_900 <- read  ## unfinished

Description

Voyage track data from the Aurora Australis

Format

aurora A data frame with 3 columns. The columns represent

Details

This is a sample of the "Aurora Australis Voyage 3 2012/13 Track and Underway Data".

References

http://gcmd.nasa.gov/KeywordSearch/Metadata.do?Portal=amd_au&MetadataView=Full&MetadataType=0&KeywordPath=&OrigMetadataNode=AADC&EntryId=201213030

Examples

## Not run: 
## These data were obtained like this
base <- "http://gcmd.gsfc.nasa.gov/KeywordSearch/RedirectAction.do?target"
b1 <-   "=F4t70bSf87FLsT1TNxR9TSPS74xbHAdheLQcH5Z5PMmgzJ9t%2Bi%2FEs1e8Fl61"
b2 <-   "MPhKjo9qxb2f9wyA%0D%0AoE1kjJ8AMcpFlMMRH7Z6umgNLsGMnWPeQdU7mZHMp%2"
b3 <-   "FtqMpahIrde%2F%2B9%2FZWAkIFrh2bhIiNfl4I9J%0D%0A5KBX9g5Wf7I9JdOgqY"
b4 <-   "bDdpj0iM1K%2BA%3D%3D"
aurora2013 <- read.csv(paste(base, b1, b2, b3, b4, collapse = ""), stringsAsFactors = FALSE)
aurora2013$DATE_TIME_UTC <- as.POSIXct(aurora2013$DATE_TIME_UTC, tz = "GMT")
## get a daily sample
aurora <- aurora2013[,c("LONGITUDE_DEGEAST", "LATITUDE_DEGNORTH", "DATE_TIME_UTC")]
aurora <- aurora[!duplicated(format( aurora$DATE_TIME_UTC, "%Y-%j")), ]
aurora <- aurora[order(aurora$DATE_TIME_UTC), ]
save(aurora, file = "aurora.rda")

## End(Not run)

Description

Title

Usage

ccmp_files(time.resolution = "6hourly", ...)

Arguments

Value

data frame of file paths

Examples

ccmp_files()

Description

Ocean colour palette for chlorophyll-a.

Usage

chl.pal(x, palette = FALSE, alpha = 1)

Arguments

Details

Flexible control of the chlorophyll-a palette. If x is a single number, the function returns that many colours evenly spaced from the palette. If x is a vector of multiple values the palette is queried for colours matching those values, and these are returned. If x is missing and palette is FALSE then a function is returned that will generate n evenly spaced colours from the palette, as per colorRampPalette.

Value

colours, palette, or function, see Details

References

Derived from http://oceancolor.gsfc.nasa.gov/DOCS/palette_chl_etc.txt.

Examples

## Not run: 
chl <- readchla(xylim = c(100, 110, -50, -40))
## just get a small number of evenly space colours
plot(chl, col = chl.pal(10))
## store the full palette and work with values and colours
pal <- chl.pal()
## the standard full palette
plot(chl, breaks = pal$breaks, col = pal$cols)
## a custom set of values with matching colours
plot(chl, col = chl.pal(pal$breaks[seq(1, length(pal$breaks), length = 10)]))
## any number of colours stored as a function
myfun <- chl.pal()
plot(chl, col = myfun(18))
## just n colours
plot(chl, col = chl.pal(18))

## End(Not run)

Description

Chlorophyll-a for the Southern Ocean

Usage

chlafiles(
  time.resolution = c("weekly", "monthly"),
  product = c("johnson", "oceancolor"),
  platform = c("MODISA", "SeaWiFS"),
  ...
)

Arguments

Details

This function generates a list of available chlorophyll-a files, including SeaWiFS and MODIS.

Value

data.frame

Description

Coastline data set as SpatialPolygons, currently not supported.

Usage

coastmap(
  map = c("world", "world2", "ant_coast", "ant_coast01", "ant_coast10",
    "Countries_hires", "world1", "world360", "cst00_polygon", "cst01_polygon",
    "cst10_polygon"),
  ...
)

Arguments

Details

This function reads and returns a coastline polygon data set, either from the source or serialized cache (.Rdata). Data source locations are controlled by options.

The following named data sets were available.

"world", "world2" - Atlantic and Pacific versions of maptools wrld_simpl ("world1", "world360" are aliases) "ant_coast", "ant_coast01", "ant_coast10" - AAD Antartic coast in full, "1 mill", and "10 mill" resolution ("cst00_polygon", "cst01_polygon", and "cst10_polygon" are aliases) "Countries_hires" - the "CIA" world map exported from the Manifold GIS data set

Value

SpatialPolygonsDataFrame or SpatialPolygons (world1/2)

Description

Each element can be looked up by name, see Examples

Usage

commonprojections

Warning

This should be use only for a convenient reference to look up the projection strings commonly in use. There's no guarantee that this would be appropriate and you should seek cartographic expertise.

References

http://www.spatialreference.org

See Also

crs

Examples

names(commonprojections)
commonprojections[["polar"]]

Description

These were an experiment provided by Stuart Corney of UTAS, consider deprecated.

Usage

cpolarfiles(...)

Arguments

Value

data frame of fullname, date

Examples

cpolarfiles()

Description

Load file names and dates of AVISO current data

Usage

currentsfiles(time.resolution = c("daily", "weekly"), ...)

Arguments

Details

A data.frame of file names and dates

Value

data.frame of file names and dates

See Also

readcurr

Description

This function loads the latest cache of stored files for these products, which are available from http://webdav.data.aad.gov.au/data/environmental/derived/antarctic/

Usage

derivaadcfiles(products, ...)

Arguments

Value

data.frame of file and date

See Also

readderivaadc and derivaadcproducts

Examples

(prods <- derivaadcproducts())
readderivaadc(sample(prods, 1L))

List all derived data products available through readderivaadc

Description

List all derived data products available through readderivaadc

Usage

derivaadcproducts()

Value

character vector of product names

See Also

readderivaadc and derivaadcfiles

Description

This function loads the latest cache of stored files for ice products, currently only daily NSIDC southern hemisphere is available.

Usage

derivicefiles(product = "time_since_melt", ...)

Arguments

Value

data.frame of file and date

Description

Calculate the shortest distance (metres) to a threshold sea ice contour. If in doubt use distance_to_ice_edge, the definition of the edge is not straightforward, especially so for the higher resolution products and near the coast. distance_to_ice_edge computes a single "main" edge at continental scale distance_to_ice computes all distances to any ice at threshold concentration

Usage

distance_to_ice_edge(
  date,
  threshold = 0.15,
  xylim = NULL,
  hemisphere = c("south", "north"),
  product = c("cdr", "nsidc"),
  min_length = NULL,
  returnfiles = FALSE,
  inputfiles = NULL,
  latest = TRUE,
  ...
)

distance_to_ice(
  date,
  threshold = 0.15,
  xylim = NULL,
  hemisphere = c("south", "north"),
  product = c("cdr", "nsidc"),
  returnfiles = FALSE,
  inputfiles = NULL,
  latest = TRUE,
  ...
)

Arguments

Details

The distance is always positive, use readice in the usual way to determine if a location is inside or out of the ice field itself. (If inside means zero distance to ice for you then set it explicitly based on the concentration a point is in.)

The contour is measured as lines, so the distance reported for a cell is its distance to the edge itself and not to the nearest contour vertex.

The sea ice product contoured is whatever readice reads, which is the NOAA/NSIDC Climate Data Record by default; pass product = "nsidc" for NSIDC-0051 v2. Both are 25km products on which a single min_length free distance_to_ice_edge gives a clean continental edge. Finer products (AMSR2 at 3km, say) break the edge into many pieces and are better served by setting min_length to drop the short ones - but they are not available through readice, so contour them directly with terra::as.contour.

Future work may generalize this to other data sources.

Value

SpatRaster of distances (metres) to this date's sea ice edge

Note

beware that any queried location outside of this layer's range will be undetermined, and the external boundary of this layer is not constant with respect to the pole, and that in general a location may be closer to ice in the opposite hemisphere.

The argument hemisphere may be north or south (default is south), but this will only work if your locations are on the actual map, so it's not possible to request the distance to ice in both poles for any point.

Examples

## Not run: 
terra::plot(distance_to_ice(latest = TRUE))
terra::plot(distance_to_ice_edge(latest = TRUE))
## every piece of the edge longer than 500km, rather than just the longest
terra::plot(distance_to_ice_edge(min_length = 5e5))
extract(distance_to_ice, aurora[17:25, ])
extract(distance_to_ice, aurora[17:25, ], hemisphere = "south")
# library(trip)
# extract(distance_to_ice_edge, walrus818[seq(50, 400, by = 20), ], hemisphere = "north")

## End(Not run)

Description

Extract values from a raadtools reader at points that each carry their own date-time. x is a read function such as readsst(), y a data.frame of longitude, latitude and date-time in that column order.

Usage

## S4 method for signature 'function,data.frame'
extract(x, y, ctstime = FALSE, when = "previous", ...)

Arguments

Details

Only the time slices the points actually need are read, and each is read once. The work is done by xyt::extract_xyt(); this is the raadtools front door onto it, so that extract(readsst, xyt) goes on meaning what it has always meant.

xyt takes further arguments that are passed through here: method for the spatial interpolation, fact to aggregate each slice before reading, tolerance to return NA for points that fall too far from any slice in time, and map to spread the reads over mirai daemons. See xyt::extract_xyt().

Value

a numeric vector, one value per row of y

Note

when = "previous" is the default here rather than xyt's own "nearest", because that is what the old findInterval() implementation did and it is what existing results were computed with. The documentation always said "nearest in time", so the two have disagreed for years. Changing the default should be a deliberate decision, not a side effect of this move.

See Also

xyt::extract_xyt(), readsst()

Examples

a <- structure(list(x = c(174, 168, 156, 111, 99, 64, 52, 46, -4,
-15, -30, -38, -47, -62, -87, -127, -145, -160, -161), y = c(-72,
-39, -50, -58, -35, -38, -48, -60, -48, -35, -37, -51, -68, -72,
-69, -54, -40, -49, -54)), .Names = c("x", "y"), row.names = c(NA,
-19L), class = "data.frame")

a$time <- structure(c(5479, 5479, 5479, 5479, 5479, 5479, 5479, 5479, 5479,
5479, 5479, 5489, 5529, 5529, 5529, 5579, 5579, 5579, 5579), class = "Date")
extract(readsst, a)
extract(readsst, a, method = "bilinear")
a$time <-  sort(as.Date("2005-01-01") + sample(c(0, 0, 0, 8, 20, 50), nrow(a), replace = TRUE))
extract(readsst, a)

Description

Provided by Alex Fraser

Usage

fasticefiles(...)

Arguments

Details

This function wraps a raadfiles function fasticefiles, but expands the file list out to individual bands.

Value

data.frame of fullname, date and band

Examples

fraser_fasticefiles()

Description

Load spatial map of fronts data.

Usage

frontsmap(map = c("park", "orsi"))

Arguments

Details

Currently ORSI or PARK is the only supported layers.

"park" = Southern Ocean fronts as determined by Park and Durand, doi: 10.17882/59800

"orsi" - the ORSI fronts derived from the files provided by the WOCE Atlas, see References

Value

SpatialLinesDataFrame

References

http://woceatlas.tamu.edu/Sites/html/atlas/SOA_DATABASE_DOWNLOAD.html

Description

Data frame of file names and dates.

Usage

ghrsstfiles()

Value

data.frame

Description

This function loads the latest cache of stored files for ice products.

Usage

icefiles(
  time.resolution = "daily",
  product = c("cdr", "nsidc"),
  hemisphere = c("south", "north"),
  ...
)

Arguments

Details

The 'fullname' is the path to the source file.

product = "cdr" (the default) is the NOAA/NSIDC Climate Data Record, G02202 V6. product = "nsidc" is NSIDC-0051 v2, which is what icefiles used to return and what read_nsidc_ice_daily still reads.

Value

data.frame of file and date

Examples

## Not run: 
icf <- icefiles()
icf[nrow(icf), ]

## End(Not run)

Description

Read map images.

Usage

imagemap(map = c("ibcso_background_hq"), fact = 1L)

Arguments

Details

The ancient lost art of cartography.

ibcso_background: The IBCSO RGB-map rasterlayer in high resolution

Value

SpatRaster, with R G B bands

References

http://www.ibcso.org/data.html

Description

Voyage track data from the Nuyina

Format

aurora A data frame with 9 columns. The columns represent longitude latitude date_time_utc air_pressure port_longwave_irradiance port_air_temperature precipitation_rate sea_water_salinity sea_water_temperature

Details

This is a sample of the Nuyina underway in 2023.

References

see data-raw for extraction

Examples

range(nuyina$date_time_utc)

Description

This function loads the latest cache of stored files for NASA ocean colour products.

Usage

ocfiles(
  time.resolution = c("daily", "weekly", "monthly", "weekly32"),
  product = c("MODISA", "SeaWiFS", "VIIRS"),
  varname = c("CHL", "RRS", "POC", "KD490", "NPP_PAR", "SNPP_CHL", "SNPP_RRS"),
  type = c("L3m", "L3b"),
  bz2.rm = TRUE,
  ext = c("nc", "main"),
  ...
)

Arguments

Value

data.frame of file and date

Description

Create a grid of query values for of longitude, latitude, and date.

Usage

query_grid(lon, lat, date)

Arguments

Details

This be used as the second argument to extract() for general 'point-in-time' value extraction.

The ouput is a data frame of the grid expanded, a row for every combination of longitude, latitude, date - so can be quite large (!) so be careful with very fine resolution or long series.

Examples

lon <- c(100, 110, 120)
lat <-seq(-60, -40, by = 5)
dts <- seq(as.Date("2002-03-03"), by = "5 days", length.out = 10)
qd <- query_grid(lon = lon, lat = lat, date = dts)
## use bilinear to ensure we get an interpolate value in the grid
qd$sst <- extract(readsst, qd, method = "bilinear")
## ssha
qd$ssha <- extract(readssh, qd, ssha = TRUE, method = "bilinear")
qd$wind_mag <- extract(readwind, qd, magonly = TRUE, method = "bilinear")

Description

Dummy function

Usage

raadtools(
  date,
  time.resolution = "daily",
  lon180 = TRUE,
  setNA = TRUE,
  latest = FALSE,
  returnfiles = FALSE,
  ...
)

Arguments

Description

This function loads the latest cache of stored files for rapid response products.

Usage

rapid_responsefiles(product = c("aqua", "terra"), ...)

Arguments

Details

We acknowledge the use of Rapid Response imagery from the Land Atmosphere Near-real time Capability for EOS (LANCE) system operated by the NASA/GSFC/Earth Science Data and Information System (ESDIS) with funding provided by NASA/HQ.

Value

data.frame of file and date

Examples

## Not run: 
rf <- rapid_responsefiles()
range(rf$date)

## End(Not run)

Description

Read one or more dates of gridded Antarctic sea level anomaly, catalogued by altimetry_antarctica_daily_files().

Usage

read_altimetry_antarctica_daily(
  date,
  xylim = NULL,
  varname = c("sla", "std_sla", "number_sla"),
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Details

The source has no georeference of its own, so the extent and CRS are asserted here: a square of 8750000 m about the pole, in Lambert azimuthal equal area on +lat_0=-90 +lon_0=-90.

Value

SpatRaster with one layer per date, or a data.frame of files if returnfiles = TRUE

See Also

altimetry_antarctica_daily_files()

Examples

## Not run: 
read_altimetry_antarctica_daily(latest = TRUE)

## End(Not run)

Description

Read Antarctic sea ice concentration from AMSR2 sensor at 3.125km resolution.

Usage

read_amsr_ice_3k_daily(
  date,
  xylim = NULL,
  setNA = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

read_amsr2_3k_ice(
  date,
  xylim = NULL,
  setNA = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Details

Data are in Antarctic polar stereographic projection. This is the highest resolution passive microwave sea ice product, available from 2012 onwards. Concentration is returned as a fraction (0-1).

Value

SpatRaster with time dimension set.

See Also

read_amsr_ice_daily for longer time series at 6km

Description

Read Antarctic sea ice concentration from combined AMSR-E (2002-2011) and AMSR2 (2012+) sensors at 6.25km resolution.

Usage

read_amsr_ice_daily(
  date,
  xylim = NULL,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

read_amsr_ice(
  date,
  xylim = NULL,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Details

Data are in Antarctic polar stereographic projection. Both sensor eras are combined into a continuous time series. Concentration is returned as a fraction (0-1); the files that store percentages are scaled down to match.

Value

SpatRaster with time dimension set.

See Also

read_amsr_ice_3k_daily for higher resolution AMSR2 data

Description

Using the TIF files (these are 2012 onwards)

Usage

read_amsr2_ice(
  date,
  xylim = NULL,
  latest = TRUE,
  ...,
  setNA = TRUE,
  returnfiles = FALSE,
  inputfiles = NULL
)

Arguments

Details

This function relies on the file-listing of raadfiles::amsr2_daily_files(). Concentration is returned as a fraction (0-1).

Value

SpatRaster

See Also

raadfiles::amsr2_daily_files

Description

Using the TIF files (these are 2012 onwards)

Usage

read_amsre_ice(
  date,
  xylim = NULL,
  latest = TRUE,
  ...,
  returnfiles = FALSE,
  inputfiles = NULL
)

Arguments

Details

This function relies on the file-listing of raadfiles::amsre_daily_files(). Concentration is returned as a fraction (0-1).

Value

SpatRaster

See Also

raadfiles::amsre_daily_files read_amsr2_ice

Description

read_ccmp picks a sensible default and returns a terra SpatRaster. For the historical defaults pinned explicitly, see read_ccmp_wind_6hourly.

Usage

read_ccmp(
  date,
  time.resolution = c("6hourly"),
  xylim = NULL,
  lon180 = FALSE,
  magonly = FALSE,
  dironly = FALSE,
  uonly = FALSE,
  vonly = FALSE,
  nobsonly = FALSE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Value

SpatRaster, or tibble if returnfiles = TRUE

References

http://www.remss.com

See Also

read_ccmp_wind_6hourly for modern terra-based reader

Description

Read wind velocity from RSS Cross-Calibrated Multi-Platform (CCMP) products.

Usage

read_ccmp_wind_6hourly(
  date,
  time.resolution = "6hourly",
  xylim = NULL,
  lon180 = FALSE,
  magonly = FALSE,
  dironly = FALSE,
  uonly = FALSE,
  vonly = FALSE,
  nobsonly = FALSE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Details

CCMP provides RSS VAM 6-hour analyses starting from NCEP GFS wind analyses. Data contain U (eastward) and V (northward) wind components as subdatasets in the same file. By default both components are returned as a 2-layer SpatRaster. Use the component arguments to return derived quantities:

• magonly = TRUE: wind speed (magnitude), sqrt(U^2 + V^2)

• dironly = TRUE: wind direction (degrees, meteorological: N=0, E=90, S=180, W=270)

• uonly = TRUE: U component only

• vonly = TRUE: V component only

• nobsonly = TRUE: number of observations only

Only one of these flags may be TRUE. When reading multiple dates with the default (both U and V), only one timestep can be read at a time.

Data are 6-hourly on a global 0.25 degree grid.

Value

SpatRaster. If default (no component flag), 2 layers named "U", "V". With a component flag, single layer per date. Time dimension is set.

References

http://www.remss.com

See Also

read_ccmp for legacy interface, ccmp_files for file catalog

Examples

## Not run: 
# Latest wind (U and V)
uv <- read_ccmp_wind_6hourly()

# Wind speed - can read multiple dates
speed <- read_ccmp_wind_6hourly(c("2023-01-15", "2023-01-15 06:00"), magonly = TRUE)

# Number of observations
nobs <- read_ccmp_wind_6hourly("2023-01-15", nobsonly = TRUE)

## End(Not run)

Description

Read Antarctic sea ice concentration from CERSAT SSM/I at 12.5km resolution.

Usage

read_cersat_ice_daily(
  date,
  xylim = NULL,
  setNA = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

read_cersat_ice(
  date,
  xylim = NULL,
  setNA = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Details

Data are in Antarctic polar stereographic projection. This is the longest passive microwave sea ice record, available from 1991 onwards. Concentration is returned as a fraction (0-1).

Value

SpatRaster with time dimension set.

See Also

read_amsr_ice_daily for AMSR data

Description

read_chla_daily picks a sensible default and returns a terra SpatRaster. For the historical defaults pinned explicitly, see read_oc_chl_daily.

Usage

read_chla_daily(
  date,
  time.resolution = "daily",
  xylim = NULL,
  lon180 = TRUE,
  varname = "chlor_a",
  setNA = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

read_chla_weekly(
  date,
  xylim = NULL,
  lon180 = TRUE,
  varname = "chlor_a",
  setNA = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

read_chla_monthly(
  date,
  xylim = NULL,
  lon180 = TRUE,
  varname = "chlor_a",
  setNA = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

read_par(
  date,
  time.resolution = "8D",
  xylim = NULL,
  lon180 = FALSE,
  nobsonly = FALSE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Value

SpatRaster

See Also

read_oc_chl_daily

Description

Read absolute dynamic topography (ADT) from CMEMS SEALEVEL_GLO_PHY_L4 product.

Usage

read_cmems_adt_daily(
  date,
  xylim = NULL,
  lon180 = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

read_adt_daily(
  date,
  xylim = NULL,
  lon180 = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Value

SpatRaster with time dimension set.

See Also

readssh for legacy interface

Description

Read geostrophic current direction derived from ugos and vgos components of CMEMS SEALEVEL_GLO_PHY_L4 product.

Usage

read_cmems_current_direction_daily(
  date,
  xylim = NULL,
  lon180 = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Details

Direction is computed using oceanographic convention: direction the current is flowing TO, in degrees where N=0, E=90, S=180, W=270.

Value

SpatRaster with time dimension set. Values in degrees (0-360).

See Also

readcurr for legacy interface

Description

Read geostrophic current speed (magnitude) derived from ugos and vgos components of CMEMS SEALEVEL_GLO_PHY_L4 product.

Usage

read_cmems_current_speed_daily(
  date,
  xylim = NULL,
  lon180 = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Details

Speed is computed as sqrt(ugos^2 + vgos^2).

Value

SpatRaster with time dimension set. Values in m/s.

See Also

readcurr for legacy interface

Description

Read formal mapping error from CMEMS SEALEVEL_GLO_PHY_L4 product.

Usage

read_cmems_err_daily(
  date,
  xylim = NULL,
  lon180 = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

read_err_daily(
  date,
  xylim = NULL,
  lon180 = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Value

SpatRaster with time dimension set.

Description

Read sea level anomaly (SLA) from CMEMS SEALEVEL_GLO_PHY_L4 product.

Usage

read_cmems_sla_daily(
  date,
  xylim = NULL,
  lon180 = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

read_sla_daily(
  date,
  xylim = NULL,
  lon180 = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Value

SpatRaster with time dimension set.

See Also

readssh for legacy interface

Description

Read eastward geostrophic current velocity (ugos) from CMEMS SEALEVEL_GLO_PHY_L4 product.

Usage

read_cmems_ugos_daily(
  date,
  xylim = NULL,
  lon180 = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

read_ugos_daily(
  date,
  xylim = NULL,
  lon180 = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Value

SpatRaster with time dimension set.

See Also

readcurr for legacy interface with U/V decomposition options

Description

Read eastward geostrophic current anomaly (ugosa) from CMEMS SEALEVEL_GLO_PHY_L4 product.

Usage

read_cmems_ugosa_daily(
  date,
  xylim = NULL,
  lon180 = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

read_ugosa_daily(
  date,
  xylim = NULL,
  lon180 = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Value

SpatRaster with time dimension set.

Description

Read northward geostrophic current velocity (vgos) from CMEMS SEALEVEL_GLO_PHY_L4 product.

Usage

read_cmems_vgos_daily(
  date,
  xylim = NULL,
  lon180 = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

read_vgos_daily(
  date,
  xylim = NULL,
  lon180 = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Value

SpatRaster with time dimension set.

See Also

readcurr for legacy interface with U/V decomposition options

Description

Read northward geostrophic current anomaly (vgosa) from CMEMS SEALEVEL_GLO_PHY_L4 product.

Usage

read_cmems_vgosa_daily(
  date,
  xylim = NULL,
  lon180 = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

read_vgosa_daily(
  date,
  xylim = NULL,
  lon180 = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Value

SpatRaster with time dimension set.

Description

Read geostrophic current velocity from Copernicus/AVISO altimetry products.

Usage

read_copernicus_current_daily(
  date,
  xylim = NULL,
  lon180 = TRUE,
  magonly = FALSE,
  dironly = FALSE,
  uonly = FALSE,
  vonly = FALSE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

read_aviso_current_daily(
  date,
  xylim = NULL,
  lon180 = TRUE,
  magonly = FALSE,
  dironly = FALSE,
  uonly = FALSE,
  vonly = FALSE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Details

Data contain U (eastward) and V (northward) velocity components. By default both components are returned as a 2-layer SpatRaster. Use the component arguments to return derived quantities instead:

• magonly = TRUE: current speed (magnitude), sqrt(U^2 + V^2)

• dironly = TRUE: current direction (degrees, oceanographic convention)

• uonly = TRUE: U component only

• vonly = TRUE: V component only

Only one of these flags may be TRUE. When reading multiple dates with the default (both U and V), only one date can be read at a time - use a component flag to read time series.

Data are on a global 0.25 degree grid. Source orientation varies by file; use lon180 = TRUE (default) to ensure Atlantic-centered output (-180 to 180).

Value

SpatRaster. If default (no component flag), 2 layers named "U", "V". With a component flag, single layer per date. Time dimension is set.

See Also

readcurr for legacy interface

Examples

## Not run: 
# Latest currents (U and V)
uv <- read_copernicus_current_daily()

# Current speed only - can read multiple dates
speed <- read_copernicus_current_daily(c("2023-01-15", "2023-06-15"), magonly = TRUE)

# Direction
dir <- read_copernicus_current_daily("2023-01-15", dironly = TRUE)

## End(Not run)

Description

Global 2.5 Minute Geoid Undulations, a big raster from multiple files. We just create a temporary virtual raster from the source files, and return as a SpatRaster.

Usage

read_geoid(xylim = NULL, force = FALSE)

Arguments

Details

Each file is an ESRI GRID raster data set of 2.5-minute geoid undulation values covering a 45 x 45 degree area. Each raster file has a 2.5-minute cell size and is a subset of the global 2.5 x 2.5-minute grid of pre-computed geoid undulation point values found on the EGM2008-WGS 84 Version web page. This ESRI GRID format represents a continuous surface of geoid undulation values where each 2.5-minute raster cell derives its value from the original pre-computed geoid undulation point value located at the SW corner of each cell.

Value

SpatRaster, longitude latitue grid of geoid level

Examples

## Not run: 
geoid <- read_geoid()

## End(Not run)

Description

Average Lead-Frequency for the Arctic for winter months November-April 2002/03-2018/19 based on daily lead composites as derived from MOD/MYD-29 IST 5 min granules

Usage

read_leads_clim_south(xylim = NULL)

read_leads_clim_north(xylim = NULL)

read_leads_clim(hemisphere = c("south", "north"), xylim = NULL, ...)

References

F. Reiser, S. Willmes, G. Heinemann (2020), A new algorithm for daily sea ice lead identification in the Arctic and Antarctic winter from thermal-infrared satellite imagery, Data subm.

Examples

read_leads_clim()
read_leads_clim_north(xylim = terra::ext(c(-1, 1, -1, 1) * 50000))
south <- read_leads_clim_south()

## hone in on Mawson
pt <- reproj::reproj_xy(cbind(62 + 52/60, -(67 +  36/60)), terra::crs(south), source = "+proj=longlat")
lead <- read_leads_clim_south(xylim = terra::ext(pt[1] + c(-1, 1) * 250000, pt[2] + c(-1, 1) * 250000))
plot(lead, col = grey.colors(100))
abline(v = pt[1], h = pt[2])

Description

Read the Sallee et al. (2013) Southern Ocean Mixed Layer Depth climatology.

Usage

read_mld_climatology(date, xylim = NULL, returnfiles = FALSE, ...)

readmld(date, xylim = NULL, returnfiles = FALSE, ...)

Arguments

Details

This is a monthly climatology (12 layers, one per month) covering the Southern Ocean south of 30S. Data represent typical mixed layer depth for each month, not actual dates.

When a date is provided, the corresponding month is extracted. Multiple dates will return multiple layers (one per unique month).

Value

SpatRaster with one layer per month requested.

References

Sallee, J.-B., et al. (2013). Assessment of Southern Ocean mixed-layer depths in CMIP5 models: Historical bias and forcing response. Journal of Geophysical Research: Oceans, 118.

Examples

## Not run: 
# All 12 months
mld <- read_mld_climatology()

# Just January
mld_jan <- read_mld_climatology("2020-01-15")

# Summer months
mld_summer <- read_mld_climatology(c("2020-12-01", "2020-01-01", "2020-02-01"))

## End(Not run)

Description

Read wind velocity from NCEP2 reanalysis products.

Usage

read_ncep2_wind_6hourly(
  date,
  time.resolution = "6hourly",
  xylim = NULL,
  lon180 = TRUE,
  magonly = FALSE,
  dironly = FALSE,
  uonly = FALSE,
  vonly = FALSE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Details

Data contain U (eastward) and V (northward) wind components stored in separate files. By default both components are returned as a 2-layer SpatRaster. Use the component arguments to return derived quantities:

• magonly = TRUE: wind speed (magnitude), sqrt(U^2 + V^2)

• dironly = TRUE: wind direction (degrees, meteorological: N=0, E=90, S=180, W=270)

• uonly = TRUE: U component only

• vonly = TRUE: V component only

Only one of these flags may be TRUE. When reading multiple dates with the default (both U and V), only one timestep can be read at a time.

Data are 6-hourly on a global 2.5 degree grid (144x73 cells).

Value

SpatRaster. If default (no component flag), 2 layers named "U", "V". With a component flag, single layer per date. Time dimension is set.

See Also

readwind for legacy interface, windfiles for file catalog

Examples

## Not run: 
# Latest wind (U and V)
uv <- read_ncep2_wind_6hourly()

# Wind speed - can read multiple dates
speed <- read_ncep2_wind_6hourly(c("2023-01-15", "2023-01-15 06:00"), magonly = TRUE)

# Direction
dir <- read_ncep2_wind_6hourly("2023-01-15", dironly = TRUE)

## End(Not run)

Description

Read the NOAA/NSIDC Climate Data Record of passive microwave sea ice concentration (G02202 V6, 25km) for a single hemisphere.

Usage

read_nsidc_cdr_daily(
  date,
  hemisphere = c("south", "north"),
  xylim = NULL,
  setNA = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Details

The CDR is what readice and icefiles reach for by default. read_nsidc_ice_daily reads NSIDC-0051 v2 instead, which is the historical default.

A CDR file holds eight subdatasets and concentration is not the first of them - band 1 is cdr_seaice_conc_interp_spatial_flag. This reader addresses cdr_seaice_conc by name, so a positional read cannot silently return a flag layer.

Values are sea ice concentration as a fraction (0-1). When setNA = TRUE, any residual flag value (above 1) is masked; open water is a legitimate 0 and is kept.

The projection is taken from the file. The CDR grids are the same 25km polar stereographic grids as NSIDC-0051, and only if the file declares no CRS at all does this reader fall back to EPSG:3976 (south) or EPSG:3413 (north).

Value

SpatRaster with time dimension, or tibble if returnfiles = TRUE.

See Also

read_nsidc_ice_daily for NSIDC-0051 v2, icefiles for the file listing

Examples

## Not run: 
ice <- read_nsidc_cdr_daily()
ice_n <- read_nsidc_cdr_daily("2023-03-15", hemisphere = "north")

## End(Not run)

Description

Read NSIDC passive microwave sea ice concentration (25km) for a single hemisphere.

Usage

read_nsidc_ice_daily(
  date,
  hemisphere = c("south", "north"),
  xylim = NULL,
  setNA = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Details

Data are returned in the native polar stereographic projection:

• South: EPSG:3976 (WGS 84 / NSIDC Sea Ice Polar Stereographic South)

• North: EPSG:3413 (WGS 84 / NSIDC Sea Ice Polar Stereographic North)

Values are sea ice concentration as a fraction (0-1), as the files store them. When setNA = TRUE, any residual flag value (land, coast, missing, polar hole) is masked to NA; open water is a legitimate 0 and is kept.

The NSIDC archive contains some dates with placeholder files (no ice variable). These are automatically filtered out using an internal index of known bad files. When multiple sensor variables exist in a file, the first is used.

For combined hemisphere output or reprojection to a custom grid, use the legacy readice function with hemisphere = "both".

Value

SpatRaster with time dimension, or tibble if returnfiles = TRUE.

See Also

readice for legacy interface with hemisphere = "both" support, read_nsidc_ice_monthly for monthly data

Examples

## Not run: 
# Latest southern hemisphere ice
ice <- read_nsidc_ice_daily()

# Specific date, northern hemisphere
ice_n <- read_nsidc_ice_daily("2023-03-15", hemisphere = "north")

# Multiple dates
ice <- read_nsidc_ice_daily(c("2023-01-15", "2023-06-15"))

# Without NA masking (keeps special values as raw integers)
ice_raw <- read_nsidc_ice_daily("2023-01-15", setNA = FALSE)

## End(Not run)

Description

Read NSIDC passive microwave sea ice concentration (25km) monthly data.

Usage

read_nsidc_ice_monthly(
  date,
  hemisphere = c("south", "north"),
  xylim = NULL,
  setNA = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Value

SpatRaster with time dimension, or tibble if returnfiles = TRUE.

See Also

read_nsidc_ice_daily for daily data

Examples

## Not run: 
# Latest monthly ice
ice <- read_nsidc_ice_monthly()

## End(Not run)

Description

Read NASA ocean colour chlorophyll-a from L3m (mapped) products. Combines data from SeaWiFS (1997-2010), MODISA (2002+), and VIIRS (2012+) into a continuous time series.

Usage

read_oc_chl_daily(
  date,
  xylim = NULL,
  lon180 = TRUE,
  varname = "chlor_a",
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

read_oc_chl_8day(
  date,
  xylim = NULL,
  lon180 = TRUE,
  varname = "chlor_a",
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

read_oc_chl_monthly(
  date,
  xylim = NULL,
  lon180 = TRUE,
  varname = "chlor_a",
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Details

Data are 4km global mapped products from NASA Ocean Biology Processing Group. When sensor eras overlap, one observation per date is returned (typically MODISA).

To read from a specific sensor only, use ocfiles() to get the file catalog and pass it via inputfiles.

Value

SpatRaster with time dimension set.

See Also

ocfiles for file catalog, read_oc_chl_8day, read_oc_chl_monthly

Examples

## Not run: 
# Latest chlorophyll
chl <- read_oc_chl_daily()

# Earliest (should be SeaWiFS era)
chl_sw <- read_oc_chl_daily(latest = FALSE)

# Specific sensor only
modis_files <- ocfiles("daily", product = "MODISA", varname = "CHL", type = "L3m")
chl_modis <- read_oc_chl_daily("2020-01-15", inputfiles = modis_files)

## End(Not run)

Description

Read Photosynthetically Available Radiation from NASA MODISA L3m products.

Usage

read_oc_par_8day(
  date,
  xylim = NULL,
  lon180 = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Value

SpatRaster with time dimension set.

See Also

read_oc_chl_daily

Description

Read NOAA Optimum Interpolation Sea Surface Temperature (OISST) v2.1 daily data.

Usage

read_oisst_daily(
  date,
  xylim = NULL,
  lon180 = TRUE,
  varname = c("sst", "anom", "err", "ice"),
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Details

OISST files contain four variables:

• sst - sea surface temperature (Celsius)

• anom - SST anomaly from climatology (Celsius)

• err - estimated error standard deviation (Celsius)

• ice - sea ice concentration (percent)

Data are on a global 0.25 degree grid (1440x720). Source files use Pacific-centered longitude (0-360); use lon180 = TRUE (default) to convert to Atlantic-centered (-180 to 180).

Date matching uses a 1.5-day tolerance window - if no file exists within 1.5 days of a requested date, an error is raised.

Value

SpatRaster with time dimension set to file dates, or tibble if returnfiles = TRUE.

See Also

readsst for legacy interface (returns raster objects)

Examples

## Not run: 
# latest SST
sst <- read_oisst_daily()

# specific dates
sst <- read_oisst_daily(c("2023-01-15", "2023-06-15"))

# SST anomaly, cropped to Southern Ocean
anom <- read_oisst_daily("2023-01-15", varname = "anom",
                         xylim = c(-180, 180, -80, -40))

# just get the file list
files <- read_oisst_daily(returnfiles = TRUE)

## End(Not run)

Description

Read NOAA Optimum Interpolation Sea Surface Temperature (OISST) v2.1 monthly data.

Usage

read_oisst_monthly(
  date,
  xylim = NULL,
  lon180 = TRUE,
  varname = c("sst", "anom", "err", "ice"),
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Details

Monthly files contain the same variables as daily files. Date matching uses a 28-day tolerance window.

Value

SpatRaster with time dimension set to file dates, or tibble if returnfiles = TRUE.

See Also

read_oisst_daily for daily data

Examples

## Not run: 
# latest monthly SST
sst <- read_oisst_monthly()

# specific months
sst <- read_oisst_monthly(c("2023-01-01", "2023-06-01"))

## End(Not run)

Description

Read the index of Reference Elevation Model of Antarctica (REMA) tiles, as polygon outlines. Use read_topo with one of the 'rema_' data sets to read the elevation data itself.

Usage

read_rema_tiles(...)

Arguments

Value

SpatVector of REMA tile outlines

See Also

read_topo

Description

Model data read from files managed by sose_monthly_files. Dates are matched to file names by finding the nearest match in time within a short duration. If date is greater than length 1 then the sorted set of unique matches is returned.

Usage

read_sose(
  date,
  time.resolution = c("monthly"),
  varname = "",
  level = 1L,
  setNA = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Details

This function doesn't support xylim, lon180, or more than one date being read.

Value

SpatRaster, one layer per requested level

Examples

## Not run: 
read_sose(varname = "Uvel", level = 1)
read_sose(varname = "SeaIceArea", level = 1, latest = FALSE)
read_sose(varname = "Chl", level = 10, latest = FALSE)


## End(Not run)

Description

Read data from various topography/bathymetry sources.

Usage

read_topo(
  topo = c("gebco_23", "gebco_21", "gebco_19", "gebco_14", "gebco_08", "etopo1",
    "etopo2", "ibcso", "ibcso_is", "ibcso_bed", "smith_sandwell", "kerguelen",
    "cryosat2", "ramp", "rema_8m", "rema_100m", "rema_200m", "rema_1km", "lake_superior",
    "macrie1100m", "macrie2100m"),
  xylim = NULL,
  lon180 = TRUE,
  polar = FALSE,
  resample = "bilinear",
  returnfiles = FALSE,
  ...
)

read_bathy(
  topo = c("gebco_23", "gebco_21", "gebco_19", "gebco_14", "gebco_08", "etopo1",
    "etopo2", "ibcso", "ibcso_is", "ibcso_bed", "smith_sandwell", "kerguelen",
    "cryosat2", "ramp", "rema_8m", "rema_100m", "rema_200m", "rema_1km", "lake_superior",
    "macrie1100m", "macrie2100m"),
  xylim = NULL,
  lon180 = TRUE,
  polar = FALSE,
  resample = "bilinear",
  returnfiles = FALSE,
  ...
)

readtopo(
  topo = c("gebco_23", "gebco_21", "gebco_19", "gebco_14", "gebco_08", "etopo1",
    "etopo2", "ibcso", "ibcso_is", "ibcso_bed", "smith_sandwell", "kerguelen",
    "cryosat2", "ramp", "rema_8m", "rema_100m", "rema_200m", "rema_1km", "lake_superior",
    "macrie1100m", "macrie2100m"),
  xylim = NULL,
  lon180 = TRUE,
  polar = FALSE,
  resample = "bilinear",
  returnfiles = FALSE,
  ...
)

readbathy(
  topo = c("gebco_23", "gebco_21", "gebco_19", "gebco_14", "gebco_08", "etopo1",
    "etopo2", "ibcso", "ibcso_is", "ibcso_bed", "smith_sandwell", "kerguelen",
    "cryosat2", "ramp", "rema_8m", "rema_100m", "rema_200m", "rema_1km", "lake_superior",
    "macrie1100m", "macrie2100m"),
  xylim = NULL,
  lon180 = TRUE,
  polar = FALSE,
  resample = "bilinear",
  returnfiles = FALSE,
  ...
)

Arguments

Details

The following datasets are available via the topo argument:

gebco_23

GEBCO 2023 grid (ice surface), 15 arc-second global

gebco_21

GEBCO 2021 grid

gebco_19

GEBCO 2019 grid

gebco_14

GEBCO 2014 grid

gebco_08

GEBCO 2008 grid, 30 arc-second

etopo1

ETOPO1 1 arc-minute global relief

etopo2

ETOPO2 (historic, deprecated)

ibcso, ibcso_is

IBCSO v2 ice surface, 500m Antarctic

ibcso_bed

IBCSO v2 bedrock

smith_sandwell

Global seafloor from satellite altimetry

kerguelen

Kerguelen Plateau bathymetric grid

cryosat2

CryoSat-2 Antarctic DEM

ramp

RADARSAT Antarctic DEM v2

rema_8m, rema_100m, rema_200m, rema_1km

REMA Antarctic DEMs

lake_superior

Lake Superior bathymetry

macrie1100m, macrie2100m

Macquarie Ridge 100m grids

Value

SpatRaster, or character file path if returnfiles = TRUE

See Also

topofile for file paths only

Examples

## Not run: 
# Read GEBCO 2023
bathy <- read_topo("gebco_23")

# Crop to region
bathy <- read_topo("gebco_23", xylim = c(100, 150, -60, -40))

# Warp to template raster
template <- terra::rast(nrows = 100, ncols = 100,
                        xmin = 100, xmax = 150, ymin = -60, ymax = -40,
                        crs = "EPSG:4326")
bathy <- read_topo("gebco_23", xylim = template)

## End(Not run)

Description

The ICEC field of the AMPS d1 forecast files, as a fraction. This reads from the 00UT and 12UT analysis files only, which is what amps_d1_icefiles selects: the later forecast hours of the pre-2018 files carry no surface fields at all.

Usage

readamps_d1ice(
  date,
  time.resolution = "12hourly",
  xylim = NULL,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Value

SpatRaster, or the file catalogue if returnfiles = TRUE

See Also

readamps_d1wind for the wind fields on the same grid

Examples

## Not run: 
terra::plot(readamps_d1ice(latest = TRUE))

## End(Not run)

Description

Read from The Antarctic Mesoscale Prediction System (AMPS) files. readamps_d1wind reads the "d1" level wind (defaults to 1).

Usage

readamps_d1wind(
  date,
  time.resolution = "4hourly",
  xylim = NULL,
  magonly = FALSE,
  dironly = FALSE,
  uonly = FALSE,
  vonly = FALSE,
  latest = TRUE,
  returnfiles = FALSE,
  level = 1,
  ...,
  inputfiles = NULL
)

readamps_d2wind(
  date,
  time.resolution = "4hourly",
  xylim = NULL,
  magonly = FALSE,
  dironly = FALSE,
  uonly = FALSE,
  vonly = FALSE,
  latest = TRUE,
  returnfiles = FALSE,
  level = 1,
  ...,
  inputfiles = NULL
)

Arguments

Details

readamps_d2wind reads the same fields from the finer "d2" domain.

level 1 is the 10 m wind; 2 onwards are the isobaric levels in file order, starting at 1000 hPa and working up. How many there are varies with the file, and an out of range level is an error rather than a silent substitution.

See amps_metadata for a description of the bands of one 2015-era file. It is a snapshot, not an index: the band layout has changed three times since, so these readers find their bands by name in the file at hand rather than by position in that table.

Data http://www2.mmm.ucar.edu/rt/amps/wrf_grib/, and contain gridded forecast data from the AMPS-WRF model. The 'd1' (domain 1) files were on a 30km grid and are now 24km, while the 'd2' (domain 2) files were 10km and are now 8km; the change happened around 2018-11-16 and the grid comes from each file. The grid domains are shown at http://polarmet.osu.edu/AMPS/ - d2 extends out to southern Australia and the tip of South America, and d1 covers just Antarctica (including Davis) and parts of the Southern Ocean. There are two forecast cycles, starting at 00UT and 12UT daily. Forecasts are for +00, +03, +06, +09, +12 and +15 hours. These steps can be used to see how the wind field is forecast as changing, and to obtain two different data sets each 3 hour timestep (e.g. the +15h forecast for the 00UT run is at the same time as the +03h forecast from the 12UT run). The 00UT and 12UT runs of the pre-2018 files are the only ones that carry the surface fields, so readamps_d1ice reads from those alone.

Value

SpatRaster, or the file catalogue if returnfiles = TRUE

Examples

## Not run: 
af <- amps_d1files()
w <- readamps_d1wind(latest = TRUE, inputfiles = af)
vlen <- function(a, b) sqrt(a * a + b * b)
terra::plot(vlen(w[[1]], w[[2]]))

## the 850 hPa wind rather than the 10 m wind
readamps_d1wind(latest = TRUE, inputfiles = af, level = 8)

## End(Not run)

Description

I don't remember what these are but they were at https://orca.science.oregonstate.edu/

Usage

readcafe(
  date,
  time.resolution = c("monthly"),
  xylim = NULL,
  lon180 = TRUE,
  setNA = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Details

Files are found with raadfiles::cafe_monthly_files().

Examples

readcafe(date = "2010-01-15")

Description

Ocean colour Chlorophyll-a from the NASA L3m (mapped) products, across the SeaWiFS, MODISA and VIIRS eras. This is the legacy front door onto read_oc_chl_daily; use that directly, or read_oc_chl_8day and read_oc_chl_monthly, to pin a particular temporal resolution.

Usage

readchla(
  date,
  product = c("any", "MODISA", "SeaWiFS", "VIIRS"),
  xylim = NULL,
  algorithm = c("nasa"),
  latest = TRUE,
  grid = NULL,
  ...,
  returnfiles = FALSE,
  inputfiles = NULL
)

Arguments

Details

One layer is returned per date. Earlier versions of this function averaged every requested date down into a single layer; to get that, average the result yourself with terra::mean() or terra::app().

Value

SpatRaster

See Also

read_oc_chl_daily for the reader this calls, ocfiles for the repository of data files

Examples

## Not run: 
d <- readchla(c("2003-01-01", "2003-06-01"),
         xylim = terra::ext(100, 150, -70, -30))

## End(Not run)

Description

readcurr picks a sensible default and returns a terra SpatRaster. For the historical defaults pinned explicitly, see the CMEMS current readers:

• read_cmems_ugos_daily - U component

• read_cmems_vgos_daily - V component

• read_cmems_current_speed_daily - current speed

• read_cmems_current_direction_daily - current direction

Usage

readcurr(
  date,
  xylim = NULL,
  lon180 = TRUE,
  magonly = FALSE,
  dironly = FALSE,
  uonly = FALSE,
  vonly = FALSE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

readcurrents(
  date,
  xylim = NULL,
  lon180 = TRUE,
  magonly = FALSE,
  dironly = FALSE,
  uonly = FALSE,
  vonly = FALSE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Value

SpatRaster, or tibble if returnfiles = TRUE

See Also

read_cmems_ugos_daily, read_cmems_vgos_daily, read_cmems_current_speed_daily, read_cmems_current_direction_daily

Description

Derived data are read from files managed by derivaadcfiles.

Usage

readderivaadc(products, xylim = NULL, returnfiles = FALSE, ...)

Arguments

Value

SpatRaster

References

http://data.aad.gov.au/aadc/metadata/metadata.cfm?entry_id=Polar_Environmental_Data

See Also

derivaadcfiles for details on the repository of data files

Examples

## Not run: 
prods <- c("bathymetry","chl_summer_climatology")
x <- readderivaadc(prods)

## End(Not run)

Description

Derived sea ice data is read from files managed by derivicefiles.

Usage

readderivice(
  date,
  time.resolution = c("daily"),
  product = c("time_since_melt"),
  xylim = NULL,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Details

Currently available products are

Dates are matched to file names by finding the nearest match in time within a short duration. If date is greater than length 1 then the sorted set of unique matches is returned.

time_since_melt

32767 (treated as missing data)

32766 = land

32765 = open-ocean zone

-32768 = ice that hasn't melted during the data period

In terms of missing data 32767, in the nc file, so should be NA once read into R): these are either open water in the sea ice zone that hasn't re-frozen during the data period, or missing sea ice data that couldn't be interpolated.

Value

SpatRaster

See Also

derivicefiles for details on the repository of data files

Description

Fast ice data

Usage

readfastice(
  date,
  product = c("circum_fast_ice"),
  xylim = NULL,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Details

High-resolution mapping of circum-Antarctic landfast sea ice distribution, 2000-2018.

Fast ice data on original polar stereographic grid, the product "circum_fast_ice" is 1000m resolution published in Alex Fraser et al. (2020).

Value

SpatRaster, see Details

Circumpolar product from 2020

Classified surface type:

• 0: pack ice or ocean

• 1: continent

• 2: islands

• 3: ice shelf

• 4: fast ice

• 5: manual fast ice edge

• 6: auto fast ice edge

Examples

## read a particular date, it's circumpolar grid with 7 discrete numerc classes
fice <- readfastice("2015-10-01")
## hone in on Davis
ex <- c(1742836L, 3315135L, 129376L, 1136611L)
davis_ice <- terra::crop(fice, terra::ext(1742836, 3315135, 129376, 1136611))
plot(davis_ice >= 4) #, col = c("brown", "white", grey(c(0.2, 0.5, 0.8))), breaks = c(0, 1, 3, 4, 5, 6))

## compare 5 years change
davis_ice2 <- terra::crop(readfastice("2010-10-01"), terra::ext(ex))
par(mfrow = c(2, 1))
plot(davis_ice >= 4)
plot(davis_ice2 >= 4)

Description

Sokolov Rintoul

Usage

readfronts(
  date,
  time.resolution = c("weekly"),
  product = c("sokolov"),
  xylim = NULL,
  lon180 = TRUE,
  setNA = FALSE,
  trim = TRUE,
  returnfiles = FALSE,
  RAT = TRUE,
  ...
)

Arguments

Value

SpatRaster

Examples

## Not run: 
b <- readfronts(c("1993-01-01", "2005-01-02"), lon180 = FALSE)

## End(Not run)

Description

Daily files This dataset contains Backward-in-time FSLE product deduced from DT merged Global Ocean Gridded Absolute Geostrophic Velocities SSALTO/Duacs L4 product (version 2018).

Usage

readfsle(
  date,
  time.resolution = c("daily"),
  xylim = NULL,
  latest = TRUE,
  varname = c("fsle_max", "theta_max"),
  returnfiles = FALSE,
  verbose = TRUE,
  ...,
  inputfiles = NULL
)

Arguments

Value

SpatRaster, or a data.frame of files if returnfiles = TRUE

Description

SST in Kelvin

Usage

readghrsst(
  date,
  time.resolution = c("daily"),
  xylim = NULL,
  lon180 = TRUE,
  varname = c("analysed_sst", "analysis_error", "mask", "sea_ice_fraction"),
  setNA = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Value

SpatRaster, or a data.frame of files if returnfiles = TRUE

Description

readice picks a sensible default and returns a terra SpatRaster. That default is now the NOAA/NSIDC Climate Data Record (G02202 V6), read by read_nsidc_cdr_daily. For the historical defaults pinned explicitly, see read_nsidc_ice_daily and read_nsidc_ice_monthly, which stay on NSIDC-0051 v2.

The hemisphere = "both" functionality (warping both hemispheres to a common grid) is only available through this function.

Usage

readice(
  date,
  time.resolution = "daily",
  product = c("cdr", "nsidc"),
  hemisphere = c("south", "north", "both"),
  xylim = NULL,
  setNA = TRUE,
  rescale = FALSE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL,
  resample = "bilinear"
)

readice_daily(
  date,
  time.resolution = "daily",
  product = c("cdr", "nsidc"),
  hemisphere = c("south", "north", "both"),
  xylim = NULL,
  setNA = TRUE,
  rescale = FALSE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL,
  resample = "bilinear"
)

readice_monthly(
  date,
  time.resolution = "monthly",
  product = "nsidc",
  hemisphere = c("south", "north"),
  xylim = NULL,
  setNA = TRUE,
  rescale = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Value

SpatRaster, or tibble if returnfiles = TRUE

See Also

read_nsidc_cdr_daily for the Climate Data Record reader read_nsidc_ice_daily for the NSIDC-0051 v2 daily reader read_nsidc_ice_monthly for the monthly reader

Description

Read the NSIDC pixel-area files for either hemisphere. Only 25km product is supported. Tool name "psn25area_v3.dat and pss25area_v3.dat": http://nsidc.org/data/polar-stereo/tools_geo_pixel.html#pixel_area.

Usage

readice_area(product = "nsidc", hemisphere = "south", ...)

Arguments

Value

SpatRaster with the area of the cells in m^2

See Also

readice

Examples

readice_area()
readice_area(hemisphere = "north")

Description

Read MODIS Rapid Response RGB images

Usage

readrapid_response(
  date,
  product = c("aqua", "terra"),
  latest = TRUE,
  returnfiles = FALSE,
  ...
)

Arguments

Details

MODIS Rapid Response, Antarctica

Value

SpatRaster

Description

SMAP surface salinity data read from files managed by salfiles.

Usage

readsal(
  date,
  time.resolution = c("daily"),
  xylim = NULL,
  lon180 = TRUE,
  varname = c("sss_smap", "nobs", "sss_ref", "gland", "gice", "surtep"),
  setNA = TRUE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

Value

SpatRaster, or a data.frame of files if returnfiles = TRUE

Description

readssh picks a sensible default and returns a terra SpatRaster. For the historical defaults pinned explicitly, see read_cmems_adt_daily and read_cmems_sla_daily.

Usage

readssh(
  date,
  time.resolution = c("daily"),
  xylim = NULL,
  lon180 = TRUE,
  ssha = FALSE,
  latest = TRUE,
  returnfiles = FALSE,
  verbose = TRUE,
  ...,
  inputfiles = NULL
)

Arguments