Alternative data injection options are typically used as additional constraints rather than for adjusting the a priori field. It's always best to assimilate all of your data sources simultaneously, so that you don't lose information in a step-wise process and to ensure that the measurement error fields of the respective measurements are properly treated statistically. This, of course, still leaves the problem of having an appropriate a priori field to work with though. The following are some options of passive instruments that provide constraints on electron density but have trouble producing electron density purely on their own:

- For E-region and D region electron density inversion: Spectral Riometer. (Requires electron collision frequency a priori information). See the work of Antti Kero in Norway for examples.

- For F-region density constraints: Redline emission data (Requires good optical forward model). One of Josh Semeter's students (I think it was Michael Hirsh) was working on this. Their work may also be of interest to you.

- GPS Radio Occultation or LEO line-of-sight GPS TEC (depending on how rigorous you want to be). These systems can provide additional vertical structure information (even without using the RO profiles themselves) that you can't get with just ground based systems.

For alternative a priori information:

NeQuick is also an option, but it uses the same foF2 parameterization as the IRI, so there isn't much performance to be gained at high latitudes using that. You could try a full-physics model like the TIEGCM. I'm still working on my electron density model for your a priori information at high latitudes (50N and up). I'll present some of it at CAP-DASP in June.

Thank you for the suggestions and authors. Looking forward to hearing more about your model at CAP-DASP! As you know, I am most interested in the high-latitude F-region.

I thought you might be interested in the following paper:

Spencer, P. S. J. and Mitchell, C. N., 2007. Imaging of fast moving electron-density structures in the polar cap. Annals of Geophysics, 50 (3), pp. 427-434.

It is a paper about applying the CIT MIDAS in the polar region by using a Kalman Filter and the Weimer model as a priori information of the plasma motion.

I hope it is helpful! 

Thank you F. Da Dalt.  I have read that paper before (it was in my JabRef database anyways), but thank you very much for the reminder and adding it to this discussion.  I certainly forgot about it when I posed the question and agree that it is relevant to this topic and worth reading for anyone following this topic that is not familiar with this research.

For CIT using satellite-to-ground links as a primary dataset, the vertical profile is underdetermined. Therefore the datasets you and David suggested should be a good complement to data from Beacons or GPS. You can put these in either as a priori constraints or as observations as long as you account for the uncertainties. If you are using vertical basis functions, it makes sense to adjust these to be consistent with observations of the density-altitude profile before trying to ingest those observations. Zapfe et al. [2006] have a paper on that issue. 

As David mentioned, you need an optical forward model for airglow data, but Link and Cogger's [1988] formulation is quite straightforward for the 630.0-nm redline nightglow emission that occurs in the F-region. I think Tim Duly has coded it into Python with all the necessary supporting empirical models in Pyglow (which is open-access). Ultraviolet data are also available (e.g. 135.6-nm airglow) from DMSP/SSUSI and TIMED/GUVI and soon from NASA's ICON mission. The mutual neutralization term has to be accounted for in order to assimilate 135.6-nm properly. 

None of these datasets are especially good in the E-region (except the ISRs and ionosondes where we have them). This could be a problem for you if you are working at high latitudes, although it is also a problem elsewhere. In the high latitude case, I would suggest adding some a priori constraints from a particle precipitation model. 

Link, R., & Cogger, L. L. (1988). A reexamination of the OI 6300‐Å nightglow. Journal of Geophysical Research: Space Physics, 93(A9), 9883-9892.

Zapfe, B. D., Materassi, M., Mitchell, C. N., & Spalla, P. (2006). Imaging of the equatorial ionospheric anomaly over South America—A simulation study of total electron content. Journal of atmospheric and solar-terrestrial physics, 68(16), 1819-1833.

Excellent. Thank you for your contribution Alex. For those following this discussion, the paper by Zapfe et al. [2006]  is available from:

http://www.cnr.it/istituti/Allegato_6778.pdf?LO=01000000d9c8b7a60900000009000000340d00007b1d9b53000000000100000000000000000000000000000000000000000000000000000000000000000000000000000000000000&type=application/pdf