# Coarsening spatial resolution for gridded data

`coarseR.Rd`

`coarseR`

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

function.

## 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`

.

## 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`

.

## 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`

.

## 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.

## Author

Hamada S. Badr <badr@jhu.edu>, Benjamin F. Zaitchik <zaitchik@jhu.edu>, and Amin K. Dezfuli <amin.dezfuli@nasa.gov>.

## See also

`HiClimR`

, `HiClimR2nc`

, `validClimR`

,
`geogMask`

, `coarseR`

, `fastCor`

,
`grid2D`

and `minSigCor`

.

## Examples

```
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
```