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<title>GrADS Function: aave</title>
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<H2><b>aave()</b></H2><p>This function takes an areal average over an X-Y region. The syntax is:
<p>
<code>aave(<i>expr, xdim1, xdim2, ydim1, ydim2</i>)</code>
<p>
where:
<ul>
<code><i>expr</i> </code>- any valid GrADS expression <br>
<code><i>xdim1</i> </code>- starting X dimension expression <br>
<code><i>xdim2</i> </code>- ending X dimension expression <br>
<code><i>ydim1</i> </code>- starting Y dimension expression <br>
<code><i>ydim2</i> </code>- ending Y dimension expression <br>
</ul>
<p>
For global averaging, a shorthand may be used:
<ul>
<code>aave(<i>expr</i>, global)</code> or <br>
<code>aave(<i>expr</i>, g)</code>
</ul>
is the same as
<ul>
<code>aave(<i>expr</i>, lon=0, lon=360, lat=-90, lat=90)</code>
</ul>
<p>
<H3>Usage Notes</H3>
<ol>
<li>In the absence of missing data values, <code>aave</code> gives the
same result as nested <code><a href="gradfuncave.html">ave</a></code>
functions in the X and Y dimensions. The expression
<p>
<code>ave(ave(<i>expr</i>,x=1,x=72),y=1,y=46)</code>
<p>
will produce the same numerical result as
<p>
<code>aave(<i>expr</i>,x=1,x=72,y=1,y=46)</code>
<p>
but the <code>aave</code> function is faster more efficient.
<li>When there are missing data values, the <code>aave</code> function
does <i><b>not</b></i> return the same result as nested <a
href="gradfuncave.html"><code>ave</code></a> functions. To
see this, consider the small grid:
<pre>
6 18 3 5
10 10 10 10
12 U U U
</pre>
where U represents the missing data value. If we apply nested
<code><a href="gradfuncave.html">ave</a></code> functions, the inner
<code><a href="gradfuncave.html">ave</a></code> will provide row
averages of 8, 10, and 12. When the outside
<code><a href="gradfuncave.html">ave</a></code> is applied,
the result will be an average of 10. When <code>aave</code> is used, all
the values participate equally (in this case, we are assuming no weights
applied to the final average), and the result is 84/9 or about 9.33.
<br>
<br>
<li>The <code>aave</code> function assumes that the world
coordinates are longitude in the X dimension and latitude in the Y
dimension, and does weighting in the latitude dimension by the
difference between the sines of the latitude at the northern and
southern edges of the grid box. For areal averaging without latitude weighting,
use the <a href="gradfuncamean.html"><code>amean</code></a> function.
<br>
<br>
<li>Both the <code>aave</code> and <a
href="gradfuncamean.html"><code>amean</code></a> functions use
appropriate weighting to account for unevenly spaced grids.<br>
<br>
<li>The <code>aave</code> function always does its average to the exact
boundaries specified, in world coordinates. This is somewhat different
from the <a href="gradfuncave.html"><code>ave</code></a> function, where
the <code>-b</code> flag is used
to get this behavior. If the boundaries specified via the dimension
expressions do not fall on grid boundaries, then the boundary values are
weighted appropriately in the average.<br>
<br>
<li>If grid coordinates are used in the dimensions expressions,
then they are converted to world coordinates to determine the exact boundary values. This conversion is done using the scaling of the default
file. Note that the conversion is done using the outside grid
box boundary, rather than the grid box center. For example:
<p><code>asum(expr,x=1,x=72,y=1,y=46)</code>
<p> Here the boundary would be determined by using the X grid values ranging from 0.5 to
72.5 and Y grid values ranging from 0.5 to 46.5. These four grid boundary values would be converted to world coordinates using the scaling information from the default file. If
we assume that <code>x=1</code> is 0 degrees longitude and <code>x=72</code> is 355 degrees longitude, then the averaging
boundary would be -2.5 to 357.5 degrees, which would cover the
earth. In the Y dimension, when the boundary is beyond the pole, the <code>asum</code> function recognizes this and weights
appropriately.
</ol>
<p>
<H3>Examples</H3>
<ol>
<li>See the <a href="gradfunctloop.html"><code>tloop</code></a> function
for an example of creating a time
series of area averages.
<br><br>
<li>An example of taking an area average of data only over land, given
a
mask grid: <p>
<code>aave(maskout(p,mask.3(t=1)),x=1,x=72,y=1,y=46) </code><p>
In this case, it is assumed the mask grid has negative values at ocean
points. <p>
</ol>
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