imgrid2 - Interpolates image data to master grid

SYNOPSIS

imgrid2  [ parameter=value ... ]  [ inputfile outputfile ]

Parameters are: master_file, grid_spacing, variables, z_index, eff_radius, guess_file, guess_vars.

DESCRIPTION

imgrid2 generates images from 2-D data. The function makes image transformation to the master grid, using Barnes Objective Analysis algorithm. This function is ideal for looking at DMSP mission sensors data.

Data should have at least 2 dimensions (line, sample). In addition, it may have a third dimension (e.g. height). z_index specifies the horizontal layer in such dimension, if one exists. It will be ignored for 2-D variables.

There is one input file: the TeraScan dataset that contains the data to be regridded.

There is one output file: the TeraScan output image dataset. The output image file will have the same earth transform data as the master dataset, modified to account for the grid_spacing parameter.

PARAMETERS

master_file

This is the filename of the master dataset. The earth location transform of the master dataset is used to convert the (line, sample)'s of input image to the master coordinates. See the description of master on how to generate master datasets.

Valid responses are any TeraScan dataset that contains an earth transform.

The default is [ Master ].

grid_spacing

grid_spacing specifies the resolution of the image grid relative to the master grid. If you want the image grid to have the same number of lines and samples as the master grid, then specify 1. If you want the image grid to have one-fourth the resolution, then specify grid_spacing to be 4.

The valid range is [ >= 1 ].

The default is [ 1 ].

variables

The image variable name. Can be any valid variable name as long as it exists in the dataset.

There is no default. More than one variable may be specified.

z_index

This is a secondary index that is used only for 3-dimensional datasets. It usually represents depth or altitude, but is not restricted to these dimensions. This value is indexed starting at 1. Value 0 means that all depths of the variable will be used. In the latter case, the output variable will also be 3-dimensional, so the burst function needs to be applied later to enable displaying the data from each level.

The valid range is [ >= 0 ].

The default is [ 0 ].

eff_radius

Effective radius for the weight function w = exp(-(R/Reff)^2), where R is the distance between the output grid point and the data location. eff_radius is expressed in terms of the average spacing distance in the input data. The optimal value is equal to sqrt(5.052)*2/Pi, which is approximately equal to 1.431.

The valid range is [ > 0. ]. The default is [ 1.431 ].

guess_file

This is the filename of the first-guess dataset. The dimensions have to be the same as in the output file. Therefore, it is natural to assume that this file was generated by running imgrid2 with the same master_file and grid_spacing parameters, but with a different input image and, probably, no first-guess file.

Valid responses are any TeraScan dataset.

The default is no guess file.

guess_vars

The guess-file variable name. This can be any valid variable name as long as it exists in the guess-file and has the right dimensions.

There is no default. The number of variables has to be the same as the one for variables.

EXAMPLES

Generate a TeraScan image dataset containing the SSM/T1 data. Select heights level 3. Specify that the image grid have one-tenth the resolution of the Master.

[1] % imgrid2
imgrid2
in/out files   : char(255) ? f11.92351.1415_t1 f11.92351.1415_t1.SCal
master_file    : char(255) ? [Master] SouthCalif
grid_spacing   : int       ? [1] 10
variables      : char(255) ? press_heights
z_index        : int       ? [1] 3
eff_radius     : real      ? [1.43091]
guess_file     : char(255) ? []

f11.92351.1415_t1: 132/168 points fit into SouthCalif

REFERENCES

Barnes,S.L., 1964: A technique for maximizing details in numerical weather map analysis. J.Appl.Meteor., 3, 396-409

Koch,S.E., M. DesJardins and P.J.Kochin, 1983: An interactive Barnes objective map analysis scheme for use with satellite and conventional data. J.Climate Appl.Meteor., 22, 1487-1503

Seaman, R.S., 1989: Tuning the Barnes objective analysis parameters by statistical interpolation theory. J.Atmos.Ocean.Technol., 6, 993-1000

SEE ALSO

imgrid, burst


Last Update: $Date: 1999/05/10 20:14:20 $