My first suspect is the ir_38 that has NaN brightness temperatures over cold clouds at night (due to extra low/negative radiances mostly generated by the ESL correction). This happens more often in the 1km version, while it gets mostly absorbed in the 2km version, but it can happen there as well... An example of this happening on the 2km version is today 05/12 00:00:

Indeed. Here is IR 3.8 for 2024-12-09 04:00 in the North Atlantic:

This is what happens to night microphysics:

Or with our internal RGB, similar to Satpys cloudtop:

Interestingly, this is IR 3.8 with the nir_emissive modifier applied:

Can something like this: #2806
Be implemented for FCI? That would "fix" the problem for qualitative use cases...

Thanks @simonrp84, that looks interesting. Negative radiances are clipped to the lowest non-negative radiance before calibrating to brightness temperature?

Yes. As long as it's an optional feature then it should solve the problem nicely without impacting other uses.

Another MCVE:

import hdf5plugin
from satpy import Scene
from pyresample import create_area_def
from glob import glob
fci_files = glob("/media/nas/x23352/MTG/FCI/L1c-cases/202412090100-atlantic/*BODY*O_0008_003[56].nc")
ar = create_area_def("ofz", 4087, description="oceanographer fracture zone", area_extent=[-4230000, 4675000, -3562000, 5232000], resolution=750)
sc = Scene(filenames={"fci_l1c_nc": fci_files})
sc.load(["cloudtop"])
ls = sc.resample(ar)
ls.save_datasets()

Looks like there are both white and transparent pixels.

As shown in irfanview:

The root cause of both types of pixels is the same: already-low radiance values over cold clouds that get even lower due to the ESL correction and/or noise. Likely, the white pixels are very low radiance values that still have a valid BT (which is going to be extremely cold), and the black pixels are negative radiance pixels that cannot be converted to BTs and hence become NaN/transparent.

For pixels to become white, we'd need extremely cold radiances in all three channels, each of 3.8 µm, 10.5 µm, 12.3 µm. However, on closer inspection, I only see this for 3.8.