Thanks. Sorry I missed it.
Originally Posted by: Justin W
I can't find the post, I think it might have been two days ago.
Anyway the upshot was this. The function I'm using to model it looks like this:
Aexp(B(t-t0)^2 + C(t-t0)) + F
A: Essentially an integration constant, could be useful to add additional complexities like changes in how testing is conducted.
B: The parameter that 'bends the exponential'. B should be small and negitive, that way the function begins as an exponential but with a slowly decreasing time dependent R0. Initially the function looks like an exponential, later it becomes a Gausian when B dominates over C
C: Related to the initial exponential growth. Should be fit to the beginning of the sustained localized 'exponential' transmission phase. A C value of 0.9 roughly corresponds to an R0 of 2.5
t0: A lag parameter. Just to allow the function to approppiately start at the right time
F: Unphysical constant. Recomment keeping this at 0 ideally.
If you want to model the three day periodicity then you could incoperate a sinusodial variation into A (for example A=0.1cos(2pi/3t) +1 )
2023/2024 Snow days (approx 850hpa temp):
29/11 (-6), 30/11 (-6), 02/12 (-5), 03/12 (-5), 04/12 (-3), 16/01 (-3), 18/01 (-8), 08/02 (-5)
Total: 8 days with snow/sleet falling.
2022/2023 Snow days (approx 850hpa temp):
18/12 (-1), 06/03 (-6), 08/03 (-8), 09/03 (-6), 10/03 (-8), 11/03 (-5), 14/03 (-6)
Total: 7 days with snow/sleet falling.
2021/2022 Snow days (approx 850hpa temp):
26/11 (-5), 27/11 (-7), 28/11 (-6), 02/12 (-6), 06/01 (-5), 07/01 (-6), 06/02 (-5), 19/02 (-5), 24/02 (-7), 30/03 (-7), 31/03 (-8), 01/04 (-8)
Total: 12 days with snow/sleet falling.