Takes in a matrix and returns a SpatialPolygon
object
representing regions fitting some criteria. Typically these regions are
either where the sea ice concentration is above a certain level or
where there is land.
get_region(dat, dat_type, level = NULL, my_land_mat = land_mat,
my_all_regions = all_regions, use_all = FALSE, land_ind = FALSE,
xmn = -3850, xmx = 3750, ymn = -5350, ymx = 5850)
matrix of one of the allowed data types ("gfdl", "bootstrap", or "simple) (see details)
string indicating the format of the data: either "gfdl", "bootstrap", or "simple" (see details)
concentration level of interest
binary matrix specifying land locations
SpatialPolygons
object specifying region that will
be considered
boolean, if true indicates to use the full area (overrides
land_mat
)
boolean, if true indicates that the region of interest is the land
min x dimension (defaults to value for polar stereographic grid: -3850)
max x dimension (defaults to value for polar stereographic grid: 3750)
min y dimension (defaults to value for polar stereographic grid: -5350)
max y dimension (defaults to value for polar stereographic grix: 5850)
region of interest as a SpatialPolygons
object
For datType = "simple"
the values in the dat
matrix
are indicators of whether the grid box contains ice (1: ice-covered,
0: no ice, NA: land). If datType = "gfdl"
or
datType = "bootstrap"
, the values in the matrix correspond
to the raw ice concentrations values observed or predicted
(including indicators for missing data, land etc.). If
datType = "gfdl"
, the predictions are formatted as in the
CM2.5 Forecast-oriented Low-Ocean Resolution (FLOR) model produced
by the National Oceanic and Atmospheric Administration<U+2019>s Geophysical
Fluid Dynamics Laboratory converted to a Polar Stereographic grid
(Vecchi et al. 2014; Msadek et al. 2014). If
datType = "bootstrap"
the array values are formatted the same
as the ice concentration values obtained from the National
Aeronautics and Space Administration (NASA) satellites Nimbus-7
SMMR and DMSP SSM/I-SSMIS and processed by the bootstrap algorithm.
Bootstrap sea ice concentration: Comiso, J., 2017: Bootstrap sea ice concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS. version 3. Boulder, Colorado USA: NASA National Snow and Ice Data Center Distributed Active Archive Center
CM2.5 Forecast-oriented Low-Ocean Resolution (FLOR) model:Vecchi, Gabriel A., et al. "On the seasonal forecasting of regional tropical cyclone activity." Journal of Climate 27.21 (2014): 7994-8016.
Msadek, R., et al. "Importance of initial conditions in seasonal predictions of Arctic sea ice extent." Geophysical Research Letters 41.14 (2014): 5208-5215.
# NOT RUN {
obs_example <- get_region(dat = obsFeb2012, dat_type = "bootstrap", level = 15)
plot(land, col = 'grey', border = FALSE)
plot(obs_example, col = "lightblue", add = TRUE)
# }
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