Chesapeake data set {OceanView}

Particle transport in Chesapeake Bay

Description

Chesapeake is a list with the bathymetry of Chesapeake Bay, Mid-Atlantic Bight and the initial position of the particles.

Ltrans is an array with output of the Lagrangian Transport model (Ltrans v.2) from Chesapeake Bay mouth, at 37 dgN in the Mid-Atlantic Bight (Schlag and North, 2012).

Usage

data(Chesapeake)
data(Ltrans)

Format

• Chesapeake is a list with the bathymetry of the area. There are 154 x-values, at 77 y-values.

  It contains:

  • lon, the longitude, (154 x 77), dg East.

  • lat, the latitude, (154 x 77), dg North.

  • depth, the bathymetry (154 x 77), metres.

  • init, the initial condition of the particles, a (608 x 4) matrix with (lon, lat, depth, source) values.

• Ltrans contains output of the Lagrangian particle transport model, in the Chesapeake mouth area. 608 particles were released in two square regions, and their positions followed over 108 output steps. It is an array of dimension (608 x 4 x 108), and which contains for each of the 608 particles, and at each of the 108 output steps the following:

  • lon, the longitude of each particle.

  • lat, the latitude of each particle.

  • depth, the depth of each particle.

  • source, the square region of release, either 1 or 2.

Author(s)

Karline Soetaert <[e-mail]>

References

Schlag, Z. R., and E. W. North. 2012. Lagrangian TRANSport model (LTRANS v.2) User's Guide. University of Maryland Center for Environmental Science, Horn Point Laboratory. Cambridge, MD. 183 pp.

North, E. W., E. E. Adams, S. Schlag, C. R. Sherwood, R. He, S. Socolofsky. 2011. Simulating oil droplet dispersal from the Deepwater Horizon spill with a Lagrangian approach. AGU Book Series: Monitoring and Modeling the Deepwater Horizon Oil Spill: A Record Breaking Enterprise.

See Also

Sylt3D for output of a 3-D hydrodynamical model, GETM.

Oxsat for a 3-D data set, package plot3D.

tracers2D for plotting time series of tracer distributions in 2D

tracers3D for plotting time series of tracer distributions in 3D

Examples

# save plotting parameters
 pm <- par("mfrow")
 mar <- par("mar")
   
## =============================================================================
## Show bathymetry and initial distribution of particles
## =============================================================================  

 par(mfrow = c(1, 1))

 lon <- Chesapeake$lon
 lat <- Chesapeake$lat
 depth <- Chesapeake$depth
 init  <- Chesapeake$init
 
 image2D(z = depth, x = lon, y = lat, clab = c("depth", "m"), 
   xlab = "lon", ylab = "lat")

# position of particles 
 with (init, scatter2D(lon, lat, colvar = source, pch = 16, cex = 0.5, 
   col =  c("green", "orange"), add = TRUE, colkey = FALSE))

 par (mar = c(2, 2, 2, 2))
# same, as persp plot
 persp3D(x = lon, y = lat, z = -depth, scale = FALSE, 
   expand = 0.02, main = "initial particle distribution", 
   plot = FALSE)

 points3D(x = init$lon, y = init$lat, z = -init$depth, 
  colvar = init$source, col = c("green", "orange"), 
  pch = 16, cex = 0.5, 
  add = TRUE, colkey = FALSE, plot = FALSE)

## Not run: 
   plotdev(lighting = TRUE, lphi = 45)

## End(Not run) 
 plotrgl(lighting = TRUE, smooth = TRUE)

## =============================================================================
## Tracer output in 3D, traditional device
## =============================================================================  
## Not run: 
 par(mfrow = c(2, 1), mar = c(2, 2, 2, 2)) 
 for (i in c(50, 100))
   tracers3D(Ltrans[, 1, i], Ltrans[, 2, i], Ltrans[, 3, i], 
             colvar = Ltrans[ ,4, i], col = c("green", "orange"),
             pch = 16, cex = 0.5, 
             surf = list(x = lon, y = lat, z = -depth, scale = FALSE, 
               expand = 0.02, colkey = FALSE, shade = 0.3, 
               colvar = depth), colkey = FALSE,
             main = paste("time ", i))

## End(Not run)

## =============================================================================
## Tracer output in 3D, using rgl
## =============================================================================  

 persp3D(x = lon, y = lat, z = -depth, colvar = depth, scale = FALSE, 
   expand = 0.02, main = "particle distribution", plot = FALSE)

 plotrgl(lighting = TRUE, smooth = TRUE) 
 
# you may zoom to the relevant region, or cut a region
# cutrgl()  
 for (i in seq(1, 108, by = 4)) {
   tracers3Drgl(Ltrans[, 1, i], Ltrans[, 2, i], Ltrans[, 3, i], 
             colvar = Ltrans[ ,4, i], col = c("green", "orange"),
             main = paste("time ", i))
# remove # to slow down
#   Sys.sleep(0.1)  
 }  

# using function moviepoints3D
## Not run: 
 persp3Drgl(x = lon, y = lat, z = -depth, colvar = depth, scale = FALSE, 
   expand = 0.02, main = "particle distribution", 
   lighting = TRUE, smooth = TRUE) 

 nt <- dim(Ltrans)[3]  # number of time points
 np <- dim(Ltrans)[1]  # number of particles
 
 times <- rep(1:nt, each = np)
 
 moviepoints3D(x = Ltrans[, 1, ], y = Ltrans[, 2, ], z = Ltrans[, 3, ], 
               t = times, colvar = Ltrans[ ,4, ], col = c("green", "orange"),
               cex = 5, ask = TRUE)


## End(Not run)
## =============================================================================
## Tracer output in 2D, traditional device
## =============================================================================  

 par(mfrow = c(2, 2)) 
 for (i in seq(10, 106, length.out = 4)) 
   tracers2D(Ltrans[, 1, i], Ltrans[, 2, i],  
             colvar = Ltrans[ ,4, i], col = c("green", "orange"),
             pch = 16, cex = 0.5, 
             image = list(x = lon, y = lat, z = depth), colkey = FALSE,
             main = paste("time ", i))

## =============================================================================
## Tracer output in 2D, rgl
## =============================================================================  
 
 image2Drgl (x = lon, y = lat, z = depth)
 for (i in seq(1, 108, by = 3)) {
   tracers2Drgl(Ltrans[, 1, i], Ltrans[, 2, i],  
             colvar = Ltrans[ ,4, i], col = c("green", "orange"))
# remove # to slow down
#   Sys.sleep(0.1)  
 }  

# reset plotting parameters
 par(mar = mar)
 par(mfrow = pm)