We have a result from night 2456003.

The 5 colored plot frames show the ratio of DS/total-flux for all filters using 4 different scattered-light reduction methods as a function of time. The two red curves are the BBSO method and our logarithmic variant of it. The two blue curves are the EFM and FFM methods. The solid curve in the frames with color is the value expected from a constant-albedo Lambert sphere. The last frame is showing the evolution of airmass with time.

The colored curves show the DS/total flux ratio divided by the mean of the BBSO method curve. The spread (+/- 10 %) is BIAS between the methods – they do not find the same answer.

Note that the slope of the observations match the expected theoretical slope.

The method with least scatter is the FFM, closely followed by the EFM. The two BBSO-like methods are not doing well, with our own logarithmic variation on the BBSO method doing least well.

Of interest is comparing VE1 to IRCUT since these filters are almost identical – the small wiggles in one set of curves do not re-appear in the other filters’ curves. This helps us understand what is geophysical signal and what is observational (and data-reduction method) noise.

VE2 is all over the place! This is probably related to the yet not understood intermittent focusing problem we have with that filter.

I find it very encouraging that the slope in the observations is so close to the theoretically predicted slope: The slope is there because during the observing period the phases of Moon and Earth slightly changed, which alters the illumination of the Moon by the Earth and Sun.

When we reduce more nights of data we will be able to begin to see if this slope is always there or changes sign with rising/setting Moon. If that is no problem we can begin to trust the signal we receive – even if the signal is biased by factors we do not yet understand.

This is a feather in our cap! We now know what nobody else knows: How much of the earthshine-based result is due to method and not geophysics. This will have consequences looking forward when enough data has accumulated and has to be interpreted in terms of climate processes.

I am sure that improvements in our analysis-methods will continue to aggregate and we may see the bias between the methods lessen.