1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
|
<!--Copyright (C) 1988-2005 by the Institute of Global Environment and Society (IGES). See file COPYRIGHT for more information.--><style type="text/css">
<!--
body {
background-color: #e0f0ff;
}
-->
</style>
<title>eloop function</title><h2><b>eloop</b></h2>
<p>
<code>eloop(<i>expr</i>)</code>
<p>
The <code>eloop</code> function is similar to the <code><a href="gradfunctloop.html">tloop</a></code> function. When displaying a GrADS expression (<code><i>expr</i></code>) with the E (Ensemble) dimension varying, the
<code>eloop</code> function will evaluate the <code><i>expr</i></code> with each designated ensemble member fixed, then reassemble the grids to obtain a final result
that is E-varying.
The <code>eloop</code> function is provided as a way to obtain E-varying results
from functions or expressions that are unable to operate
when E is a varying dimension.
<p>
<h3>Examples</h3>
<p>
<ol>
<li>Suppose you have an ensemble forecast with 15 ensemble members, and you want to evaluate the accuracy of each ensemble member by comparing it to reanalysis. You need to calculate the difference between an E-varying data set (the forecast) with a non-E-varying data set (reanalysis). </li>
<ul>
<p><code>open fcst.ctl<br />
open rean.ctl<br />
set lon -77<br />
set lat 39<br />
set e 1 15<br />
set t 1 last<br />
d eloop(t2m.1-t2m.2(e=1))</code><br />
</p>
</ul>
</ol>
|
