[ncl-talk] 4 sub-blocks of a 3D matrix in satellite data

Yang, Xiaoxin yang.1143 at osu.edu
Tue Oct 11 21:43:16 MDT 2016

```Dear Dennis,
Thank you for your reply. It is said that each observation has an averaging kernel matrix. The grid_pressure_composite includes 34 levels, with index 0 to 16 referring to hdo and the remaining levels to h2o. Hdo and h2o vapor mixing ratio are retrieved simultaneously.
Each averaging kernel matrix has 4 sub-blocks correspond to the HDO/H2O ratio estimate , the H2o estimate and then the cross-terms.
The guide also explains that if the matrix is 32x32 then there are 4 components that are each 16x16 elements long.
Yet I still felt uncertain about the structure. Will this clarification help you in figuring out the structure of the sub block of the 3D matrix?

TES-Aura satellite data for HDO:

Not sure what to say.  We have not seen these files. Certainly, I have not read any documentation. Does the indexing in the documentation you read say it is 1- or 0-based?

On Tue, Oct 11, 2016 at 4:27 PM, Yang, Xiaoxin <yang.1143 at osu.edu<mailto:yang.1143 at osu.edu>> wrote:
Dear all,
I’m processing the TES-Aura satellite data for HDO, but could not figure out the structure of the 4 sub-blocks of a 3D matrix, i.e., averagingkernel(grid-targets*grid_pressure_composite*grid_pressure_composite).

As is stated in the guide, the averagingkernel consists of 4 sub-blocks of the matrix [0,0],[1,0],[0,1] and [1,1]. Subblock [0,0] ranges from indices ns to 16, and subblock[1,1] ranges from indices 17+ns to 33…

Should it be something like this?

ak=F->AveragingKernel(vid,:,:) ; vid means valid observation meeting certain criteria
ak at _FillValue = -999
;averaging kernel for HDO

But the result of the corrected HDO using this averaging kernel does not seem right. Hope you would offer me more suggestions on this.
Thank you very much.
Best,
Xiaoxin

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