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This release reorganizes windscape around a simpler workflow:
download wind data or a pre-built wind rose, summarize the wind as a
wind_rose, model connectivity with least-cost or
random-walk functions that take the rose directly, and plot each step
with ggplot2 layers.
cfsr_dl() and cfsr_dl_land() are replaced
by download_wind_data() and
download_land_mask(), which use NCAR’s Geoscience Data
Exchange (see New features).cfsr_usa and katrina datasets replaced by
windscape_example().wind_series() and wind_rose() now require
lon/lat grids with (near-)square cells.wind_series,
wind_field, or wind_rose with [[
or subset(), or combining them with c(), now
returns a plain SpatRaster, since the result no longer has
the object’s structure. Use subset_series() to select time
steps of a series.as_wind_rose() and read_wind_rose() are
merged into wind_rose(), which builds a rose from a
wind_series, or loads a saved rose from an 8-layer raster
or file path. rose() is no longer exported.wind_rose() no longer takes ... (or
cores); it gains filename and
overwrite. trans must be a non-negative number
or an elementwise function of wind speed.wind_rose(): cells missing wind data at any time step
are now NA in all eight layers, and calm time steps (zero
wind speed) contribute no conductance whatever trans is
(previously, with trans = 0, they counted toward one fixed
direction).terra::aggregate(), disagg(),
resample(), and project() now signal an error
on a wind_rose, since they would average conductances
without accounting for cell size. Use downscale(), or
change the grid of the wind_series before building the
rose.least_cost_surface() is renamed
least_cost(), and least_cost_distance() is
renamed pairwise_least_cost(). Both take a
wind_rose directly (a wind_graph built in
advance is still accepted), and least_cost() gains a
direction argument.vrcd() is removed. pairwise_least_cost()
now places sites at their actual locations within grid cells
(snap = FALSE, the default), replacing both
vrcd() and the adjust argument of
least_cost_distance().wind_graph(): wrap now defaults to
NULL, which wraps global grids (spanning 360 degrees of
longitude) automatically.random_walk(): "ratchet" mode removed;
results are now a named list of rasters; arguments reordered (general
arguments before mode-specific ones). The new latitude correction (on by
default) changes results on lon/lat grids.random_walk() results are now per km^2 by default
(density = TRUE).particle_flow() is replaced by
wind_trails(), which traces trails for a given transport
time (hours) or length (distance).tesselate() is removed; global grids now wrap
automatically (see wrap arguments).download_wind_data() downloads hourly wind from NCAR’s
Geoscience Data Exchange, with no account needed: ERA5 (1940 to present;
10 m and 100 m), CFSR (1979-2010), and CFSv2 (2011 to present; 10 m and
pressure levels). Data are clipped to a bounding box on the server, can
be limited to particular days and hours (down
to a single hour), and are saved as one file per month, with downloads
cached so interrupted runs resume. Large requests are split to fit the
server’s size limit.download_land_mask() downloads a land-water layer on
the same grid, e.g. for weight_conductance().wind_series() combines file paths, rasters, or a list
of series into one series that stays on disk.subset_series() selects time steps by month, hour, date
range, or index, and wind_times() returns the time of each
step.wind_field() gains step, to take one time
step of a series as a field, and mean() of a
wind_series gives its mean wind field.windscape_example() loads small example data sets.download_wind_rose() provides pre-built global wind
roses (10 m CFSR, 1979-2010) for any combination of years and calendar
months, optionally cropped to a region, which is read over the internet
without downloading whole files. wind_rose_catalog() lists
the available files and wind_rose_cache() manages
downloaded ones.wind_rose() is about five times faster, processes long
series in chunks of time steps without loading them into memory, and
records n_steps and trans in files written
with filename, so they reload with
wind_rose(file) alone.combine_roses() combines roses built from different
time periods, weighting them by their numbers of time steps.net_flow() returns a rose’s net flow as a
wind_field.least_cost_paths() traces fastest routes between sites
and other points.random_walk() gains mode = "stream"
(steady state of continuous release, returning residence time and
deposition), half_life (deposition),
latitude_correction, direction = "upwind"
(catchments), flux (net flux of material),
source, and wrap.pairwise_random_walk() computes random-walk
connectivity among sets of sites.random_walk_paths() traces flux streamlines between a
source and where its material goes, the random-walk analog of
least_cost_paths().rw_exit_prob() gives each cell’s probability of mass
leaving the domain.rw_self_retention() for leave-one-out corrections of
stream-mode results.geom_wind_arrow() and
geom_wind_trail() for wind fields,
geom_wind_rose() for wind roses, and
geom_wind_path() for paths and trails, with
scale_fill_bearing() and
scale_colour_bearing() for direction-based colors, and
fortify() methods for windscape objects.pairwise_least_cost() (formerly
least_cost_distance(adjust = TRUE)) no longer returns
NaN on the diagonal.gdistance::geoCorrection().These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.