createMapping: Map a set of observations and predictions

Description Usage Arguments Details Value References Examples

View source: R/mappings.R

Description

Finds all the mappings for a set of observations and predictions often over multiple years

Usage

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createMapping(startYear, endYear, obsStartYear, predStartYear, observed,
  predicted, regionInfo, month, level, datTypeObs, datTypePred,
  plotting = FALSE, obsOnly = FALSE, predOnly = FALSE, nX = 304,
  nY = 448, xmn = -3850, xmx = 3750, ymn = -5350, ymx = 5850)

Arguments

startYear

first year to be mapped

endYear

last year to be mapped

obsStartYear

year in which observation array starts

predStartYear

year in which prediction array starts

observed

array of observed values of dimension year x longitude x latitude

predicted

array of predicted values of dimension year x longitude x latitude

regionInfo

region information list (see detail)

month

month under consideration

level

concentration level for which to build contour

datTypeObs

string of either "bootstrap" or "simple" indicating the file type of the observation (see details)

datTypePred

string of either "gfdl" or "simple" indicating the file type of the prediction (see details)

plotting

boolean indicatng whether maps should be plotted (defaults to false)

obsOnly

run mapping only for observations

predOnly

run mapping only for predictions

nX

dimension in the x (defaults to value for Northern Polar stereographic grid: 304)

nY

dimension in the y (defaults to value for Northern Polar stereographic grid: 448)

xmn

min x value (defaults to value for Northern Polar stereographic grid: -3850)

xmx

max x value (defaults to value for Northern Polar stereographic grid: 3750)

ymn

min y value (defaults to value for Northern Polar stereographic grid: -5350)

ymx

max y value (defaults to value for Northern Polar stereographic grid: 5850)

Details

The object maps is obtained from running the createMapping function. It is a list of five objects where month, startYear, and endYear give the month, first year, and last year that were mapped. The variables obsList and predList are lists of arrays with one 3-dimensional array for each region. The first dimension is for the year. The other two dimensions are for the fixed points' y-coordinates, the mapped points' x-coordinates, the mapped points' y-coordinates, the length of the mapping vectors in the x-direction, the length of the vectors in the y-direction, and the angles of the mapping vectors.

A region information list is a list of seven objects: regions, startLines, startCoords, out, lines, dist, and loop. The first of these seven items are lists giving information about each of the regions that will be predicted and the seventh is a vector. The package contains a regionInfo object in the regionInfo.rda file, which is typically what is used for all anlaysis. However, it would be possible to redefine the regions if desired by making a new regionInfo object.

The variable regions gives SpatialPolygons objects for each region. The values for startLines and startCoords give the starting line from which each region is mapped and built as a SpatialLines object and a matrix of coordinates respectively. For regions with loop = TRUE, the value for startLines is NULL, and the value for startCoords is simply the coordinates for the centroid repeatedly.

The variable out gives a list of SpatialPolygons objects for each region that is outside the corresponding region, but that border the starting lines. These are used when building new polygons to determine if points are being mapped outside the region of interest.

The lines list gives the SpatialLines objects that correspond to the line on which the regions are mapped and built.

The dist list for each region is a vector which gives the distances of the end and breakpoints for each of the corresponding lines

The loop vector gives a Boolean for each region. The value TRUE indicates that the lines are mapped in a circle around a fixed point. The value FALSE indicates that the lines are mapped along a line on land.

For datTypeObs = "simple" and datTypePred = "simple" the values in the observed and predicted arrays are indicators of whether the grid box contains ice (1: ice-covered, 0: no ice, NA: land). If datTypePred = "gfdl" or datTypeObs = "bootstrap", the values in the observed and predicted arrays correspond to the raw ice concentrations values observed or predicted (including indicators for missing data, land etc.). If datTypePred = "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’s Geophysical Fluid Dynamics Laboratory and converted to a Polar Stereographic grid (Vecchi et al. 2014; Msadek et al. 2014). If datTypeObs = "bootstrap" the array values are assumed to be from the monthly sea ice concentration obtained from the National Aeronautics and Space Administration (NASA) satellites Nimbus-7 SMMR and DMSP SSM/I-SSMIS and processed by the bootstrap algorithm. Weights for converting to a polar stereograhic grid were obtained from the spherical coordinate remapping and interpolation package (SCRIP) (Jones 1997).

Value

map object (see details)

References

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.

National Center for Atmospheric Research, 2017: Earth system grid at NCAR. https://www.earthsystemgrid.org/home.html.

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

Examples

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## Not run: 
createMapping(startYear = 1981, endYear = 1981, obsStartYear = 1981,
             predStartYear = 1980, observed = obsFeb19811982,
             predicted = emFeb19811982, regionInfo = regionInfo, month = 2,
             level = 15, datTypeObs = "bootstrap", datTypePred = "gfdl",
             plotting = TRUE) 
## End(Not run)

hdirector/IceCastV2 documentation built on Dec. 9, 2018, 12:27 a.m.