IceCast (version 2.1.0)

quick_run: Simple evaluation of contour-shifting

Description

Reads in netCDF files of observations and predictions, performs bias correction, and exports a new netCDF file with bias-corrected predictions

Usage

quick_run(obs_NCDF, pred_NCDF, pred_years, start_year, month, output_file,
  level, dat_type_obs = "bootstrap", n_train_years = NULL)

Arguments

obs_NCDF

filepath for observed data array (see details for info about array structure)

pred_NCDF

filepath for predicted data array (see details for info about array structure)

pred_years

vectors of years for which to make prediction

start_year

first year to use when learning model

month

month of prediction

output_file

filepath for where bias-corrected netCDF file should be stored

level

concentration level for which to build contour

dat_type_obs

string of either "bootstrap" or "simple" indicating the file type of the observation (see details for info about array structure)

n_train_years

number of prior years used in training bias correction

Value

netCDF file of dimension years by longitude (304) by latitude (448) with indicators for where ice is predicted after bias correction. (1: ice-covered, 0: not ice, NA: land). Grid boxes will be categorized as ice if their centers are ice covered (within R the bias-corrected contours are not restricted to align to a grid).

Details

The predicted data array, pred_NCDF, should be a netCDF file with a single array of dimension: years x longitude (304) x latitude (448). The variable should be named ice_ind. The values in the array should indicate whether each grid box is categorized to contain ice (1: ice-covered, 0: no ice, NA: land). The observed data array, obs_NCDF, should be a netCDF file with a single array of dimension: years x longitude (304) x latitude (448). The observed data array, obs_NCDF, can be formatted the same as pred_NCDF if dat_type_obs = "simple". Alternatively, if dat_type_obs = "bootstrap" the array values can be 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. Data should be retained in the same format as given by bootstrap (including indicators for missing data, land etc.). The variable should be named "conc".

References

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

Examples

# NOT RUN {
quick_run(obs_NCDF = "/obs.nc", pred_NCDF = "/pred.nc",
         pred_years = c(2001:2013), start_year = 1980, month = 2,
         output_file = "/outputFile.nc", level = 15, dat_type_obs = "simple")
# }