<div dir="ltr"><div><div><a href="http://www.ncl.ucar.edu/Document/Functions/Contributed/runave_n_Wrap.shtml">http://www.ncl.ucar.edu/Document/Functions/Contributed/runave_n_Wrap.shtml</a><br><br></div> let x(time,lat,lon) ->dimension numbers (0,1,2) .<br>. x(time,lev,lat,lon) ->(0,1,2,3)<br><br></div> ; compute unweighted seasonal means<br><div><div><pre> nave = 5 ; 5 months
opt = 0 <br> ndim = 0 ; time dimension<br></pre><pre><br> x = <strong>runave_n_Wrap</strong> (x, nave, opt, 3) ; overwrite 'x'<br> printVarSummary(x)<br></pre><pre> or<br></pre><pre> xSea = <strong>runave_n_Wrap</strong> (x, nave, opt, 3) ; new variable<br> printVarSummary(xSea)<br><br></pre><pre> ; print source months and seasonal averages<br><br> LAT = ... ; arbitrary grid point<br> LON = ... <br> print(x(:,{LAT},{LON})+" "+xSea(:,{LAT},{LON}) )<br><br>---<br></pre><pre>Assuming the monthly data start in Jan ...<br></pre><pre>Say you want the M(arch)A(pril)M(ay)J(une)J(uly) means: <br>Months: Jan=0; Feb=1, Mar=2, April=3, May=4, ....<br></pre><pre> x_MAMJJ = xSea(4::12,:,:) ; extract all M(arch)AMJJ<br> printVarSummary(x_MAMJJ)<br> print("---")<br> print(x_MAMJJ)</pre></div></div></div><div class="gmail_extra"><br><div class="gmail_quote">On Wed, May 17, 2017 at 10:02 PM, Priyanka Silva <span dir="ltr"><<a href="mailto:priyankakeraminiya6@gmail.com" target="_blank">priyankakeraminiya6@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div dir="ltr">Hello, <div>How can I calculate five month seasonal mean. <span style="color:rgb(84,84,84)">Month_to_season computes three-</span><span style="font-weight:bold;color:rgb(106,106,106)">month seasonal mean. Is there any other function to calculate 5 month seasonal mean</span></div><div><span style="color:rgb(84,84,84)"><br></span></div><div><span style="color:rgb(84,84,84)">Thank you. </span></div><div><span style="color:rgb(84,84,84)"><br></span></div></div></div>
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