In article ,
Scott W writes:
I have modified the spreadsheet and used Kelvin instead of mean
temp. I have divided snow lying by average mean Kelvin then
multiplied by 100 to give it a chunky figure. The temperature stats
refer to the meteorological winter - December, January, February.
The snowfall stats refer to October to May. I realise this is not
consistent but I was merely trying to give a 'perception' of each
winter. One could argue that I should include temp stats and
rainfall to go with the snowfall data ie October to May - but then
this would introduce its own inconsistencies in not being
'meteorological winter'. With a couple of exceptions all my
snowfall occurs December to March. Further feedback welcomed.

The trouble with dividing by degrees Kelvin is that there will then be
very little difference between cold winters and mild ones. Dividing by
274 (1C) in one case and 278 (5c) in the other won't affect the result
that much. So whereas dividing by the Celsius temperature meant that
temperature tended to dominate over snowfall, dividing by the Kelvin
value will result in the reverse.

If you want both snowfall and temperature to have roughly equal weight,
then I think you need to experiment until you get something that "feels"
right. I'm not sure that dividing one value by the other is the way to
go. If you find that the median number of days with snow lying is 10,
say, and the median (or mean - it won't make much difference here)
Celsius temperature over all winters is 4, say, then how about an index
L-(10/4)*T, where L is the number of days with snow lying and T the mean
Celsius temperature of the winter in question? That looks as if it might
give reasonable weightings to the two factors, and will mean that the
median winter will have an index of zero. (I think that for days of snow
lying the median value is more "typical" than the mean, as the mean is
bumped up by the occasional very snowy winter like 1962-3.)

On second thoughts my suggestion would probably still over-emphasise
snowfall in relation to temperature, as the number of days of snow lying
can be anywhere between zero and 60-70, whereas the limits on winter
mean temperature are probably between about zero and 6-7. So the range
of values of the former is about ten times that of the latter. To
compensate for that, a possible index might be L - 10*T. So a very mild
and non-snowy winter would have a value of about -60 or -70, and a very
cold and snowy one like 1962-3 would have a value of +60 or +70. An
average winter would be about 10 - 10*4 = -30. If you'd rather the
average index was close to zero you could use 30 + L - 10*T.
--
John Hall "He crams with cans of poisoned meat
The subjects of the King,
And when they die by thousands G.K.Chesterton:
Why, he laughs like anything." from "Song Against Grocers"