Satwind thinning in JEDI with Gaussian Thinning function

First observation: The Gaussian Thinning function's impact on assimilated ob density is different depending on when the function is called in the QC YAML. Using the same QC filter:

  - filter: Gaussian Thinning
    horizontal_mesh: 200
    vertical_mesh: 10000

I tried putting this in the obs pre filters section and then again in the obs post filters section. Results on AHI/Himawari WVCT satwinds:

pre-filter: 2507 obs assimilated, 45771 obs thinned, 1589 obs rejected, 49867 total post-filter: 3241 obs assimilated, 31950 obs thinned, 14676 obs rejected, 49867 total

By placing the same Gaussian Thinning filter in the post rather than pre filter section, 29% more satwinds are assimilated, 43% fewer satwinds are thinned, and nearly 10 times more satwinds are rejected. I believe this drastic difference in outcome is a function of the sequencing between thinning and QC. As a pre-filter, the sequence is thin-->QC, and as a post-filter (at the end of the list of post-filters), the sequence is QC-->thin. So as a pre-filter thinning is applied to all observations prior to QC and then QC is applied to what's left, which is why so many obs are thinned and so few are rejected. As a post-filter, QC is applied first to all observations and then thinning is applied to what's left. The post-filter version is more true to GSI's thinning methodology, where thinning is applied just before exiting setupw.f90 following all QC filters. However, it is worth noting that with these mesh-grids, which are identical to the meshes applied in GSI, we are still getting far fewer observations assimilated and too many thinned:

GSI: 6450 obs assimilated, 28630 obs thinned, 3619 obs rejected

It's also worth recognizing that the thinned ob-count is not unique in either GSI or UFO. In GSI, thinned observations appear to be dropped from the diag file entirely, so the number of thinned winds needs to be inferred by comparing a thinned-GSI experiment and a non-thinned-GSI experiment. In UFO, thinning as a pre-filter will apply an EffectiveQC value of 16 to the thinned obs and then QC will not be further applied, which is why the number of rejected obs changes based on where the thinning filter is applied - you end up thinning otherwise-rejected obs in a pre-filter and only thin otherwise-accepted obs in a post-filter.

NOAA-EMC / GDASApp

Satwind thinning in JEDI with Gaussian Thinning function #1143