# Tutorial

### What is it?

This document presents a brief tutorial for Brian Doty's Grid Analysis and Display System (GrADS). The following sample session will give you a feeling for how to use the basic capabilities of GrADS. This sample session takes about 30 minutes to run through.

### Before you start:download the sample data

You will need the following sample data files in order to go through this tutorial:

`model.ctl` GrADS descriptor file (0.7 kb)
`model.grb` GrADS (GRIB) data file (579 kb)
`model.gmp` GrADS gribmap index file (4 kb)

This data file is described by the data descriptor file `model.ctl`. You may want to look at this file before continuing. The data descriptor file describes the actual data file, which in the case contains 5 days of global grids that are 72 x 46 elements in size.

Please download these 3 files to a local directory before proceeding.

### Sample Session

To start up GrADS, enter:

  `grads`

  If grads is not in your current directory, or if it is not in your PATH somewhere, you may need to enter the full pathname, ie:

  `/usr/homes/smith/grads/grads`

  GrADS will prompt you with a landscape vs. portrait question; just press enter. At this point a graphics output window should open on your console. You may wish to move or resize this window. Keep in mind that you will be entering GrADS commands from the window where you first started GrADS -- this window will need to be made the 'active' window and you will not want to entirely cover that window with the graphics output window.

  In the text window (where you started grads from), you should now see a prompt: `ga->` You will enter GrADS commands at this prompt and see the results displayed in the graphics output window.

  The first command you will enter is:

  `open` `model.ctl`

  You may want to see what is in this file, so enter:

  `query` `file`

  One of the available variable is called `ps`, for surface pressure. We can display this variable by entering:

  `d` `ps`

  `d` is short for `display`. You will note that by default, GrADS will display an X, Y plot at the first time and at the lowest level in the data set.

  Now you will enter commands to alter the `dimension environment`. The `display` command (and implicitly, the access, operation, and output of the data) will do things with respect to the current dimension environment. You control the dimension environment with the `set` command:

  `clear` clears the display
  `set lon -90` sets longitude to 90 degrees West
  `set lat 40` sets latitude to 40 degrees North
  `set lev 500` sets level to 500 mb
  `set t 1` sets time to first time step
  `d z` displays the variable 'z'

  In the above sequence of commands, we have set all four GrADS dimensions to a single value. When we set a dimension to a single value, we say that dimension is "fixed". Since all the dimensions are fixed, when we display a variable we get a single value, in this case the value at the location 90W, 40N, 500mb, and the 1st time in the data set.

  If we now enter:

  `set lon -180 0` X is now a varying dimension
  `d z`

  We have set the X dimension, or longitude, to vary. We have done this by entering two values on the set command. We now have one varying dimension (the other dimensions are still fixed), and when we display a variable we get a line graph, in this case a graph of 500mb Heights at 40N.

  Now enter:

  `clear
  set lat 0 90
  d z`

  We now have two varying dimensions, so by default we get a contour plot. If we have 3 varying dimensions:

  `c
  set t 1 5
  d z`

  we get an animation sequence, in this case through time.

  Now enter:

  `clear
  set lon -90
  set lat -90 90
  set lev 1000 100
  set t 1
  d t
  d u`

  In this case we have set the Y (latitude) and Z (level) dimensions to vary, so we get a vertical cross section. We have also displayed two variables, which simply overlay each other. You may display as many items as you desire overlaid before you enter the `clear` command.

  Another example, in this case with X and T varying (Hovmoller plot):

  `c
  set lon -180 0
  set lat 40
  set lev 500
  set t 1 5
  d z`

  Now that you know how to select the portion of the data set to view, we will move on to the topic of operations on the data. First, set the dimension environment to an Z, Y varying one:

  `clear
  set lon -180 0
  set lat 0 90
  set lev 500
  set t 1`

  Now lets say that we want to see the temperature in Fahrenheit instead of Kelvin. We can do the conversion by entering:

  `display (t-273.16)*9/5+32`

  Any expression may be entered that involves the standard operators of +, -, *, and /, and which involves operands which may be constants, variables, or functions. An example involving functions:

  `clear
  d sqrt(u*u+v*v)`

  to calculate the magnitude of the wind. A function is provided to do this calculation directly:

  `d mag(u,v)`

  Another built in function is the averaging function:

  `clear
  d ave(z,t=1,t=5)`

  In this case we calculate the 5 day mean. We can also remove the mean from the current field:

  `d z - ave(z,t=1,t=5)`

  We can also take means over longitude to remove the zonal mean:

  `clear d z-ave(z,x=1,x=72)
  d z`

  We can also perform time differencing:

  clear
  d z(t=2)-z(t=1)

  This computes the change between the two fields over 1 day. We could have also done this calculation using an offset from the current time:

  `d z(t+1) - z`

  The complete specification of a variable name is:

  `name.file(dim +|-|= value, ...)`

  If we had two files open, perhaps one with model output, the other with analyses, we could take the difference between the two fields by entering:

  `display z.2 - z.1`

  Another built in function calculates horizontal relative vorticity via finite differencing:

  `clear
  d hcurl(u,v)`

  Yet another function takes a mass weighted vertical integral:

  `clear
  d vint(ps,q,275)`

  Here we have calculated precipitable water in mm.

  Now we will move on to the topic of controlling the graphics output. So far, we have allowed GrADS to chose a default contour interval. We can override this by:

  `clear
  set cint 30
  d z`

  We can also control the contour color by:

  `clear set ccolor 3
  d z`

  We can select alternate ways of displaying the data:

  `clear
  set gxout shaded
  d hcurl(u,v)`

  This is not very smooth; we can apply a cubic smoother by entering:

  `clear
  set csmooth on
  d hcurl(u,v)`

  We can overlay different graphics types:

  `set gxout contour
  set ccolor 0
  set cint 30
  d z`

  and we can annotate:

  `draw title 500mb Heights and Vorticity`

  We can view wind vectors:

  `clear
  set gxout vector
  d u;v`

  Here we are displaying two expressions, the first for the U component of the vector; the 2nd the V component of the vector. We can also colorize the vectors by specifying a 3rd field:

  `d u;v;q`

  or maybe:

  `d u;v;hcurl(u,v)`

  You may display pseudo vectors by displaying any field you want:

  `clear
  d mag(u,v) ; q*10000`

  Here the U component is the wind speed; the V component is moisture.

  We can also view streamlines (and colorize them):

  `clear
  set gxout stream
  d u;v;hcurl(u,v)`

  Or we can display actual grid point values:

  `clear
  set gxout grid
  d u`

  We may wish to alter the map background:

  `clear
  set lon -110 -70
  set lat 30 45
  set mpdset nam
  set digsize 0.2
  set dignum 2
  d u`

  To alter the projection:

  `set lon -140 -40
  set lat 15 80
  set mpvals -120 -75 25 65
  set mproj nps
  set gxout contour
  set cint 30
  d z`

  In this case, we have told grads to access and operate on data from longitude 140W to 40W, and latitude 15N to 80N. But we have told it to display a polar stereographic plot that contains the region bounded by 120W to 75W and 25N to 65N. The extra plotting area is clipped by the map projection routine.

  This concludes the sample session. At this point, you may wish to examine the data set further, or you may want to go through the GrADS documentation and try out the other options described there.