of averaging kernels and data

I should find a serious geek blog and get some peer feedback on whether this is an evil data massage (perhaps torturing) technique or not. I am not opposed to averaging kernels themselves. Fact of life is that its not possible to have point measurement instruments all around the globe and up into the atmosphere. Quite a lot of useful data is gleaned by applying various mathematical and statistical data methods to get from ie an increased bending or delay of a radio signal as it goes through the atmosphere to amount of water vapor or CO, CO2, O2 etc etc. There is nothing wrong with applying lots of math and some assumptions to get some information about water vapor etc.

What bugs me is that I learned in the course of doing some work outside my core area that involved averaging kernels that it seems to have become common to apply the averaging kernel which was needed for the SV radio measurement and yields a smoothed profile through the atmosphere *sometimes so smoothed its really only valid as a column total measurement* to OTHER measurements of the substance of interest. Especially if the other method had its own averaging kernel it seems wonky to be applying the averaging kernel for the new instrument being tested to the old data source instead of its own kernel.

I think the clarity that "well this SV technique only gives a very smoothed or column average information about the temperature, water vapor content etc" has too much chance of being lost when smearing out higher resolution data before comparing the two for accuracy. Well only for presenting RMS errors along the profile. First the researcher needs to present those high RMS errors and then they can show that even though the smoothed output fails to catch local maxima and minima the smoothed/column average information is correct --just don't use it for any application where knowing the maxima and its height is important.

LOL, I wonder if I'll read this post 5 years on and wonder what the heck I was writing about. Very inside baseball I think.