Skip to contents

Bin-and-sum footprint gridding

Source: R/13_obs_grid.R
obs_grid_simple.Rd

Bins STILT/HYSPLIT particles into a regular longitude/latitude grid and sums the foot sensitivity values per cell. This is the primary scientific output: no smoothing is applied, no foot is redistributed spatially, and the grid total exactly equals the particle total.

Usage

obs_grid_simple(
  x,
  lon_min,
  lat_min,
  lon_max,
  lat_max,
  res = 0.1,
  n_threads = 1L,
  npar = 1L
)

Arguments

x

A data.table or data.frame with at least the columns lat (degrees), lon (degrees), and foot (sensitivity, ppm / (umol m-2 s-1)).

lon_min

Western edge of the output grid (degrees).

lat_min

Southern edge of the output grid (degrees).

lon_max

Eastern edge of the output grid (degrees).

lat_max

Northern edge of the output grid (degrees).

res

Cell size in degrees. Both longitude and latitude use the same value (square cells). Default 0.1.

n_threads

Number of OpenMP threads passed to the Fortran routine. Default 1L. Increase for large particle sets (> ~50 000 rows); for smaller sets the thread-management overhead outweighs the gain.

npar

Number of particles used for normalization. The output grid is divided by this value to return the average footprint sensitivity. Default 1L.

Value

A named list with three elements:

grid

Numeric matrix of dimension [nlon x nlat] containing the summed foot per cell, divided by npar. Row i corresponds to lon[i], column j to lat[j].

lon

Numeric vector of cell-centre longitudes (length nlon).

lat

Numeric vector of cell-centre latitudes (length nlat).

Note

Particles whose coordinates fall outside the rectangle [lon_min, lon_max) x [lat_min, lat_max) are silently discarded. Add a small buffer to the grid extent if edge particles matter.

See also

obs_grid_kernel for a smoothed alternative, obs_grid_check to compare totals.

Examples

if (FALSE) { # \dontrun{
library(data.table)
dat <- fread("PARTICLE.DAT")
d   <- dat[time %in% sort(unique(time))[1:4]]   # first hour

bs <- obs_grid_simple(
  x         = d,
  lon_min   = floor(min(d$lon))   - 0.1,
  lat_min   = floor(min(d$lat))   - 0.1,
  lon_max   = ceiling(max(d$lon)) + 0.1,
  lat_max   = ceiling(max(d$lat)) + 0.1,
  res       = 0.1,
  n_threads = 4L
)
image(bs$lon, bs$lat, log1p(bs$grid), main = "Bin and sum")
} # }