# coarseR: Coarsening spatial resolution for gridded data In HiClimR: Hierarchical Climate Regionalization

## Description

`coarseR` is a helper function that helps coarsening spatial resolution of the input matrix for the `HiClimR` function.

## Usage

 `1` ```coarseR(x = x, lon = lon, lat = lat, lonStep = 1, latStep = 1, verbose = TRUE) ```

## Arguments

 `x` an (`N` rows by `M` columns) matrix of 'double' values: `N` objects (spatial points or stations) to be clustered by `M` observations (temporal points or years). For gridded data, the `N` objects should be created from the original matrix `x0` using `as.vector(t(x0))`, where `x0` is an (`n` rows by `m` columns) matrix, `n = length(unique(lon))` and `m = length(unique(lat))`. `lon` a vector of longitudes with length `N`. For gridded data, the length may have the value (`n`) provided that `n * m = N` where `n = length(unique(lon))` and `m = length(unique(lat))`. `lat` a vector of latitudes with length `N` or `m`. See `lon`. `lonStep` an integer greater than or equal to `1` for longitude step to coarsen gridded data in the longitudinal direction. If `lonStep = 1`, gridded data will not be coarsened in the longitudinal direction (the default). If `lonStep = 2`, every other grid in longitudinal direction will be retained. `latStep` an integer greater than or equal to `1` for latitude step to coarsen gridded data in the latitudinal direction. If `latStep = 1`, gridded data will not be coarsened in the latitudinal direction (the default). If `latStep = 2`, every other grid in latitudinal direction will be retained. `lonStep` and `latStep` are independent so that user can optionally apply different coarsening level to each dimension. `verbose` logical to print processing information if `verbose = TRUE`.

## Details

For high-resolution data, the computational and memory requirements may not be met on old machines. This function enables the user to use coarser data in any spatial dimension:longitude, latitude, or both. It is available for testing or running `HiClimR` package on old computers or machines with small memory resources. The rows of output matrix (`x` component) will be also named by longitude and latitude coordinates. If `lonStep = 1` and `latStep = 1`, `coarseR` function will just rename rows of matrix `x`.

## Value

A list with the following components:

 `lon` longitude mesh vector for the coarsened data. `lat` latitude mesh vector for the coarsened data. `rownum` original row numbers for the coarsened data. `x` coarsened data of the input data matrix `x`.

## References

Hamada S. Badr, Zaitchik, B. F., and Dezfuli, A. K. (2015): A Tool for Hierarchical Climate Regionalization, Earth Science Informatics, 8(4), 949-958, doi: 10.1007/s12145-015-0221-7.

Hamada S. Badr, Zaitchik, B. F., and Dezfuli, A. K. (2014): Hierarchical Climate Regionalization, Comprehensive R Archive Network (CRAN), https://cran.r-project.org/package=HiClimR.

`HiClimR`, `HiClimR2nc`, `validClimR`, `geogMask`, `coarseR`, `fastCor`, `grid2D` and `minSigCor`.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ```require(HiClimR) ## Load test case data x <- TestCase\$x ## Generate longitude and latitude mesh vectors xGrid <- grid2D(lon = unique(TestCase\$lon), lat = unique(TestCase\$lat)) lon <- c(xGrid\$lon) lat <- c(xGrid\$lat) ## Coarsening spatial resolution xc <- coarseR(x = x, lon = lon, lat = lat, lonStep = 2, latStep = 2) lon <- xc\$lon lat <- xc\$lat x <- xc\$x ```

### Example output

```
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HiClimR documentation built on May 31, 2021, 5:07 p.m.