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Changeset 1561 in lmdz_wrf for trunk/tools/documentation/ncmanage
- Timestamp:
- May 10, 2017, 10:18:47 PM (8 years ago)
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- 1 edited
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trunk/tools/documentation/ncmanage/compute_opersvarsfiles.html
r1538 r1561 38 38 'divc',[modval1]: [prevalues] divide by [modval1]<BR> 39 39 'forwrdderiv',[N],[ord],[dim]: un-scaled forward [N]-derivative of order [ord] along dimension [dim] of [var]<BR> 40 'ifreq_anom',[stepdimn],[stepvardimn],[istep]: computing anomalies by substracting sub-means at each<BR> 41 step by averaging from there all values taken every [istep] along dimension [stepdim]. <BR> 42 mean(j) = sum(matA[j+k*istep]_k=0,Nstep)/Nstep; Nstep = len(stepdimn)/istep; j=[0,istep]<BR> 43 [stepdimn]= name of the dimension along which to sample<BR> 44 [stepvardimn]= name of the variable-dimension with the values for [stepdimn]<BR> 45 [istep]= frequency to sample<BR> 46 'ifreq_mean',[stepdimn],[stepvardimn],[istep]: computing sub-means at each step by averaging from <BR> 47 there all values taken every [istep] along dimension [stepdim]. <BR> 48 mean(j) = sum(matA[j+k*istep]_k=0,Nstep)/Nstep; Nstep = len(stepdimn)/istep; j=[0,istep]<BR> 49 [stepdimn]= name of the dimension along which to sample<BR> 50 [stepvardimn]= name of the variable-dimension with the values for [stepdimn]<BR> 51 [istep]= frequency to sample<BR> 52 'ifreq_normmeanstd',[stepdimn],[stepvardimn],[istep]: nbormalizing anomalies by substracting mean(j)/dtsv(j) <BR> 53 sub-stats at each step by averaging from there all values taken every [istep] along dimension[stepdim]. <BR> 54 mean(j) = sum(matA[j+k*istep]_k=0,Nstep)/Nstep; std(j) = std(matA[j+k*istep]_k=0,Nstep); <BR> 55 Nstep = len(stepdimn)/istep; j=[0,istep]<BR> 56 [stepdimn]= name of the dimension along which to sample<BR> 57 [stepvardimn]= name of the variable-dimension with the values for [stepdimn]<BR> 58 [istep]= frequency to sample<BR> 40 59 'inv': inverting [prevalues] (1/[prevalues])<BR> 41 60 'lowthres',[modval1],[modval2]: if [prevalues] < [modval1]; prevalues = [modval2]<BR> … … 49 68 'norm_meanstd',[NOTnormdims]: normalization of data as: (val-<val>)/stdev(val) except along <BR> 50 69 dimensions [NOTnormdims] (':' list of dimension names, or 'any' for using all dimensions)<BR> 51 70 dimensions [NOTnormdims] (':' list of dimension names)<BR> 52 71 'pot': powering with [var] ([prevalues] ** [var])<BR> 53 72 'potc',[modval1]: [prevalues] ** [modval1]<BR> … … 72 91 <DIV CLASS="valins"> 73 92 * Transforming temperature from Kelvin to °C<BR> 74 93 $ python ${pyHOME}/nc_var.py -o compute_opersvarsfiles -S 'west_east|XLONG|-1;south_north|XLAT|-1;Time|Times|3@subc,273.15|wrfout_d01_2001-11-11_00:00:00|T2' -v 'tempC,air!temperature,C'<BR> 75 94 * Computing the x-derivative of first order<BR> 76 95 $ python ${pyHOME}/nc_var.py -o compute_opersvarsfiles -S 'lon|lon|-1;lat|lat|-1;time_counter|time_counter|-1@forwrdderiv,1,1,2|histday.nc|t2m' -v 'tasderiv,x-derivative|of|air|temperature,K' <BR> 77 96 * Normalizing a variable by substracting its mean and weighting by its standard-deviation<BR> 78 97 $ python ${pyHOME}/nc_var.py -o compute_opersvarsfiles -S 'west_east|XLONG|-1;south_north|XLAT|-1;Time|WRFtime|-1@norm_meanstd,Time|wrfout_d01_1995-01-01_00:00:00|T2' -v 'tasnorm,normalized!2m!temperature!substracting!mean!and!weighting!by!standard!deviation,K' <BR> 79 98 * Getting height of the frist level from surface from a WRF file<BR> 80 99 $ python $pyHOME/nc_var.py -o compute_opersvarsfiles -S 'west_east|XLONG|-1;south_north|XLAT|-1;bottom_top_stag|ZNW|1@addc,0|wrfout_d01_1995-01-01_00:00:00|PH%west_east|XLONG|-1;south_north|XLAT|-1;bottom_top_stag|ZNW|1@add|wrfout_d01_1995-01-01_00:00:00|PHB%contoperation@divc,9.81%west_east|XLONG|-1;south_north|XLAT|-1;Time|WRFtime|-1@sub|wrfout_d01_1995-01-01_00:00:00|HGT' -v 'height1lev,height!above!surface!of!first!level,m'<BR> 81 100 * Computing wind-direction from a WRF file<BR> 82 $ python $pyHOME/nc_var.py -o compute_opersvarsfiles -S 'west_east|XLONG|-1;south_north|XLAT|-1;Time|WRFtime|-1@addc,0|wrfout_d01_1995-01-01_00:00:00|V10%west_east|XLONG|-1;south_north|XLAT|-1;Time|WRFtime|-1@arctan|wrfout_d01_1995-01-01_00:00:00|U10%contoperation@mulc,57.2957795131' -v 'wsdir,2m!wind!direction,Degrees' 101 $ python $pyHOME/nc_var.py -o compute_opersvarsfiles -S 'west_east|XLONG|-1;south_north|XLAT|-1;Time|WRFtime|-1@addc,0|wrfout_d01_1995-01-01_00:00:00|V10%west_east|XLONG|-1;south_north|XLAT|-1;Time|WRFtime|-1@arctan|wrfout_d01_1995-01-01_00:00:00|U10%contoperation@mulc,57.2957795131' -v 'wsdir,2m!wind!direction,Degrees' 102 * Computing normalized anomalyes of WRF outputs by the mean and standard deviations of the outputs at the same hour<BR> 103 $ python nc_var.py -o compute_opersvarsfiles -S 'Time|WRFtime|-1;south_north|XLAT|-1;west_east|XLONG|-1@ifreq_normmeanstd,Time,WRFtime,8|/home/lluis/PY/wrfout_d01_1995-01-01_00:00:00|T2' -v 'tas_ifreqnormmeanstd,tas!anomaly!by!substracting!frequency!mean!at!every!8!time-steps,K' 104 83 105 </DIV> 84 106 </BODY>
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