I am performing strato-mesospheric ozone retrievals with the OEM implemented directly in ARTS (using the python interface). As my sensor is not changing much with time, I am wondering if there is a way (and if this is worth in terms of computation speed) to reuse the sensor_response matrix (FFT channel response, unbinned) for different measurements which I think was quite straightforward with Qpack.

In Qpack some stuff is made behind the scene. Yes, it can be avoided to recalculate the sensor response. But you need save a number of variables. At least these ones:
sensor_response_f_grid, sensor_response_pol_grid,

Maybe also good to save

And then you just need to import these for a new calculation (or just keep them in memory).

I was trying to write multiple calibrated spectra within the y vector as well as multiple meas. error cov. (Se and inv) blocks before running the OEM which I thought might be the way to go but it seems to treat them as multiple measurements of the same ozone profiles instead. Could somebody confirmed if this is expected and if yes, is there another way to do this kind of parallel OEM retrievals: same sensors, same atmosphere, etc.. just different measurements vectors using OEM from ARTS directly ?

There is no clear cut way inside ARTS to do batch OEM inversions. I am not using Python myself, but is this part not easy to setup on the python side?


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