Hi Fadzil,
All you actually need to do is use numpy.average(), which is numpy's
implementation of the weighted average. It can be shown geometrically that
using the cosine of the latitude as the weights in the weighted average
would give you approximately the area average, though if your SST data has
a grid cell area attribute in the netcdf file, that would be the most
suitable choice to use as your weights. Otherwise, you could determine the
area weighted average as follows:
# numpy is imported as np, lat are the latitudes extracted from the netcdf
file
# First we need to convert the latitudes to radians
latr = np.deg2rad(lat)
# Use the cosine of the converted latitudes as weights for the average
weights = np.cos(latr)
# Assuming the shape of your data array is (nTimes, nLats, nLons)
# First find the zonal mean SST by averaging along the latitude circles
sst = sstv[:]
sst_ave_zonal = sst.mean(axis=2)
# Then take the weighted average of those using the weights we calculated
earlier
sst_ave = np.average(sst_ave_zonal, axis=1, weights=weights)
This should give a time series of global mean SST. Is this what you wanted?
Thanks,
Alex
On Sun, Feb 23, 2014 at 10:28 AM, Fadzil Mnor <fadzilmno...@gmail.com>wrote:
> Hi,
> I just started using Python for the last few weeks, and previously been
> using GrADS for around 4 years.
> I have trouble looking for a simplest way to calculate area average, let
> say I need to calculate a SST over a region of 20S-10N and 130E-170E.
> I know how to get one point values of SST vs Time, as in:
>
> ********************************************************************
> ...
> ...
> f = nc.Dataset('d:/data/sst.mon.mean.nc', 'r')
> sstv = f.variables['sst']
> timev = f.variables['time']
> sst = sstv[:, 35, 100]
> plt.plot(timev,sst)
> plt.show()
> ...
> ...
> ***********************************************************************
> but I couldn't figure out how to get an area average value (...and didn't
> get the right reference in the internet either)
> Something missing, probably because I don't understand enough about
> slicing or something else.
> Can anyone give me a hint ?
>
> Thanks.
>
> Fadzil.
>
>
>
>
>
> ------------------------------------------------------------------------------
> Managing the Performance of Cloud-Based Applications
> Take advantage of what the Cloud has to offer - Avoid Common Pitfalls.
> Read the Whitepaper.
>
> http://pubads.g.doubleclick.net/gampad/clk?id=121054471&iu=/4140/ostg.clktrk
> _______________________________________________
> Matplotlib-users mailing list
> Matplotlib-users@lists.sourceforge.net
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>
--
Alex Goodman
Graduate Research Assistant
Department of Atmospheric Science
Colorado State University
------------------------------------------------------------------------------
Managing the Performance of Cloud-Based Applications
Take advantage of what the Cloud has to offer - Avoid Common Pitfalls.
Read the Whitepaper.
http://pubads.g.doubleclick.net/gampad/clk?id=121054471&iu=/4140/ostg.clktrk
_______________________________________________
Matplotlib-users mailing list
Matplotlib-users@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/matplotlib-users
