From: Dennis Shea <shea_at_nyahnyahspammersnyahnyah>

Date: Mon Mar 04 2013 - 14:31:22 MST

Date: Mon Mar 04 2013 - 14:31:22 MST

It applies to EOF patterns generated via the

covariance or correlation matrix.

On 03/01/2013 07:57 PM, åˆ˜æ¯“èµŸ wrote:

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*>
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*>
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*>
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*> hi,
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*>
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*> I have one question about orthogonal of rotated EOFs.
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*>
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*> I repeat the example 5 of EOFs on ncl functions page.
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*>
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*> this code(eof_5.ncl) use the covariance matrix to compute EOFs, then compute the rotated EOFs.
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*>
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*> optEOF = False
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*> optETS = False
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*> eof = eofunc_Wrap(x, neof, optEOF)
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*> eof_ts = eofunc_ts_Wrap (x, eof, optETS)
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*>
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*> eof_rot = eofunc_varimax_Wrap( eof, 1 )
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*> printVarSummary( eof_rot )
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*>
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*> in the function (eofunc_varimax) page, it descript that the result of rotated EOFs are orthonormal for each spatial patterns, and there is some correlation between the time series expansion coefficients for each mode.
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*>
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*> my question is : if I compute EOFs use the correlation matrix, then compute the rotated EOFs, the result is also orthonormal for each spatial patterns, and there is some correlation between the time series expansion coefficients for each mode? I change the code as follows:
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*>
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*> optEOF = true
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*> optEOF@jopt = 1
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*> optETS = True
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*> optETS@jopt = 1
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*> eof = eofunc_Wrap(x, neof, optEOF)
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*> eof_ts = eofunc_ts_Wrap (x, eof, optETS)
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*>
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*> eof_rot = eofunc_varimax_Wrap( eof, 1 )
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*> printVarSummary( eof_rot )
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*>
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*> thanks!
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*>
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*> yun
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*>
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Received on Mon Mar 4 14:31:31 2013

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