calc.woa: Calculate WOA profile in parallel

In HMMoce: Improved Analysis of Marine Animal Movement Data Using Hidden Markov Models

Description

Calculate Depth-temperature profile based likelihood

Usage

calc.woa(pdt, ptt, woa.data = NULL, dateVec, sp.lim = NULL,
  focalDim = NULL, use.se = TRUE)

Arguments

pdt	input PDT data output from read.wc and extract.pdt
ptt	is unique tag identifier
woa.data	is (typically) a list of monthly global 1/4deg climatology data from WOA13. See get.env.
dateVec	is vector of dates from tag to pop-up in 1 day increments.
sp.lim	is list of limits as list(xmin, xmax, ymin, ymax)
focalDim	is integer for dimensions of raster::focal used to calculate sd() of temperature grid cell. Recommend focalDim = 3 if woa.data = woa.one and 9 if using woa.quarter.
use.se	is logical indicating whether or not to use SE when using regression to predict temperature at specific depth levels.

Details

calc.woa.par calculates likelihood of animal position based on summarized depth-temperature profiles

Tag-based depth-temperature profile summaries are compared to climatological profiles from the World Ocean Atlas (WOA) "matched" to generate position likelihoods. This essentially attempts to estimate animal position based on the water mass it is in, particularly if extensive diving performs thorough sampling of the environment. However, remember the in situ data is being compared to climatological means or the results of an oceanographic model.

Value

raster brick of likelihood

See Also

calc.ohc

HMMoce documentation built on Nov. 17, 2017, 5:57 a.m.