variable-resolution costDistance

Increasing the spatial resolution of a wind data set (e.g. by interpolation using downscale) can greatly improve wind connectivity estimates among nearby sites, but can make it computationally impossible to model connectivity over large geographic regions, a trade-off that presents problems for studies that include both nearby and distant site pairs. This function gets around this issue with a hybrid approach, using a broad-scale coarse-resolution wind grid to model wind cost-distance among distant sites, and a separate local-scale high-resolution interpolated grid to model connectivity between each pair of nearby sites.

Usage

vrcd(
  rose,
  ll,
  threshold_km = 30,
  pad = 1,
  max_nodes = 1e+06,
  direction = "downwind",
  method = "bilinear"
)

Arguments

rose: wind_rose.
ll: longitude and latitude of site locations, as a two-column matrix.
threshold_km: a positive number representing the distance threshold, in kilometers. Site pairs closer together than this distance will get a separate local high-resolution connectivity model, while pairs farther apart will be modeled at the resolution of rose.
pad: a positive number indicating how far beyond a pair of sites the modeling domain should extend for local models. This is an expansion factor giving the padding as a fraction of the maximum latitudinal or longitudinal distance between the two sites. The default of 1 is reasonable in most cases; smaller values will increase computational speed but may fail to account for wind routes beyond the bounding box encompassing the site pair.
max_nodes: an integer representing how finely to interpolate wind grids for local site pairs. This represents the number of cells in the high-resolution interpolated grid for each site pair; larger values remove artifacts of the discrete coarse grid more effectively, but have increased computational cost.
direction: either "downwind" or "upwind", indicating whether outbound or inbound connectivity should be computed. In this context, changing this parameter is equivalent to transposing the resulting wind distance matrix.
method: disaggregation method; either "near" or "bilinear'; see disagg for details.

Value

A list of square matrices:

wind_dist: Wind cost-distances between site pairs, in hours if rose has a p = 1. Computed using costDistance.
wind_dist_coarse: Wind cost-distances using the coarse input wind grid (rose); this will differ from wind_dist only for site pairs closer than threshold_km. This is provided for reference, to judge how higher-resolution models impact results relative to the coarse grid.
point_dist: Distances between sites, in km.
cell_dist: Distances between the centroids of the grid cells used to model wind connectivity, in km. For site pairs where this distance deviates from point_dist by a substantial percentage, wind_dist estimates may contain nontrivial rounding noise resulting from the discrete grid.
cell_dist_coarse: Distances between the cell centroids in the coarse-resolution input wind dataset (rose), in km. This is provided for reference, to judge improvements relative to cell_dist.