IceCast (version 2.1.0)

contour_shift: Apply contour-shifting to bias correct

Description

Apply contour-shifting to bias correct a predicted contour using existing mappings.

Usage

contour_shift(maps, predicted, bc_year, pred_start_year, reg_info, level,
  dat_type_pred, my_land_mat = land_mat, my_land = land,
  n_train_years = NULL)

Arguments

maps

object obtained from the create_mapping function (see details)

predicted

array of predicted values of dimension year x month x longitude x latitude

bc_year

year to be bias-corrected

pred_start_year

year prediction array starts in

reg_info

a reg_info list (see documentation for reg_info)

level

concentration level for which to build contour

dat_type_pred

string indicating the format of the prediction: either "gfdl" or "simple" (see details)

my_land_mat

binary matrix specifying land locations

my_land

SpatialPolygons corresponding to the land

n_train_years

number of years prior to the current year used in fitting the bias correction

Value

SpatialPolygons object of the adjusted region

Details

The map parameter is a list of length four that has the form of a list obtained from running the create_mapping function. The values start_year and endYear give the first and last year that were mapped. The variables obs_list and pred_list are lists of arrays with one 3-dimensional array for each region. The first dimension of each array coresponds to the year, the second dimension corresponds to the lines on which the region is being mapped, and the third dimension corresponds to the variables of interest. The first and second dimension are indexed sequentially. The variables for the third dimension are for the fixed points' x-coordinates, the fixed points' y-coordinates, the mapped points' x-coordinates, the mapped points' y-coordinates, the length of the mapping vectorsin the x-direction, the length of the vectors in the y-direction, and the angles of the mapping vectors. The predicted data array, predicted, should be a single array of dimension: years x longitude (304) x latitude (448). If dat_type_pred = ``simple"}, the values in the array should indicate whether each grid box is categorized to contain ice (1: ice-covered, 0: no ice, NA: land). If \code{dat_type_pred =``gfdl" the values in the predicted array correspond to the raw ice concentrations values predicted (including indicators for missing data, land etc.) 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 and converted to a Polar Stereographic grid (Vecchi et al. 2014; Msadek et al. 2014). Weights for converting to a polar stereograhic grid were obtained from the spherical coordinate remapping and interpolation package (SCRIP) (Jones 1997).

References

Jones, P.W. "A user<U+2019>s guide for SCRIP: A spherical coordinate remapping and interpolation package." Los Alamos National Laboratory, Los Alamos, NM (1997).

Msadek, R., et al. "Importance of initial conditions in seasonal predictions of Arctic sea ice extent." Geophysical Research Letters 41.14 (2014): 5208-5215.

Vecchi, Gabriel A., et al. "On the seasonal forecasting of regional tropical cyclone activity." Journal of Climate 27.21 (2014): 7994-8016.

Examples

# NOT RUN {
adj <- contour_shift(maps = discrep, predicted = emFeb2012, bc_year = 2012,
                     pred_start_year = 1980, reg_info, level = 15,
                     dat_type_pred = "gfdl")
plot(land, col = "grey", border = FALSE)
plot(adj, add = TRUE, col = "blue")
# }