On 26/02/2019 10:15, Martin Brown wrote:
On 26/02/2019 09:57, N_Cook wrote:
y=2.483612 + 0.053029*x^1.575023

Just because you can obtain a model fit with 6 significant figures shown
in each coefficient doesn't mean that they are right.

I'd be very surprised if anything more than the first two leading digits
were even in the right ballpark.

Instead of using R^2 as a measure of goodness of fit why don't you try
and do it using the actual residuals of the data and an estimate of the
noise to compute chi-squared. Then you can do a proper analysis and see
just how uncertain each of your coefficients are. IOW how well defined
each of them is with the others sat on their respective peak value.


Its too early to have any confidence in this sort of stuff. I'm
interested how the estimations vary over time, uing the same baseload of
data , 2003 to early 2018 , and seeing how updates vary the output using
the same treatment each time.
If only the likes of Aviso would move away from linear "fit" I would not
feel being obliged to do any of this. I still have not found anyone
publishing similar results, using the Jason dataset (I have little
confidence in the Attica/Saral concept of calibration).
So far its been consistent ranking of curve types,
linear,exponential,quadratic, indicial, will that remain so?
After all they have big machines they can plug in full datasets and
churn away.
Incidentally has anyone found where the Jason-3 data is supposed to be
on the copernicus.eu site?

from Aviso "update" of 18 May 2019
https://www.aviso.altimetry.fr/en/da...ts-images.html
Using their reference plot ,lo-res,data to extend the Jason 3 data to 16
March 2019, giving gradient (cm/yr) of 0.354 and y intercept of 7.10 cm
at 2017.0. For Aviso having gradient of 3.54 mm/yr and intercept of
7.12cm, requiring me to delete 2 of the earlier, ie cross-over with
Jason-2 , datapoints.
Having to subtract the specious IMHO 0.3mm/yr since 1993 of GIA as well
as lo resolution.
I've no idea why they've stopped the hi-res filtered outputs , "updated
" to 3 weeks before the previous update in Feb 2019, so still only to
Nov 2018 on the J3 only plot.
Its those filtered dotted outputs that go into the reference plot and
also my curve-fit trend plots.
They've revisioned the whole J3 plot again (more ammo for the CC
opposition) , the increase in gradient from 3.12 to 3.54 due to
down-sizing the earlier values, the March 2019 value being much the same
as the Nov 2018 values.
Results of curve-fitting , the (poor data Nov 2018 to 16 March 2019) and
back to 2003.0 gives a gradient of nearly 3.36 mm/yr of straight line
fit, purely coincidence , as
Aviso uses the earlier Topex+Poseidon plots , affected by Pinatubo,
to give their gradient of 3.36.
For x = year - 2000 and y as cm SLR
in order of R^2, goodness of fit
linear "fit"
y=1.417612 + 0.335194 * x
r*r = 0.985164
aviso reference gradient 0.336
year Sea Level Rise (cm)
2020 8.12
2050 18.18
2100 34.94

Exponential fit
Y = 1.851812 -10.336718 *(1-Exp(0.024110*x))
r*r = 0.987186
year Sea Level Rise (cm)
2020 8.26
2050 26.02
2100 106.7

Quadratic fit
Y = 1.907679 + 0.233504*x + 0.004195*x^2
year Sea Level Rise (cm)
2020 8.25
2050 24.07
2100 67.2

Best fit still , Indicial
Y = 2.146249 + 0.131066* x ^ 1.281649
r*r = 0.987498
year Sea Level Rise (cm)
2020 8.24
2050 21.87
2100 50.1

I won't be repeating an adjustement using the Steven Nerem adjustment
plot , as the early Jason-3 data has been revisioned , so would have to
await their revisioning, to make much sense. The Aviso revisioning of J3
output on 07 Dec 2018 probably nullified/degraded my previous
Nerem-adjusted processing as well.

Summary in May 2019, all are best fit by r*r are Indicial Power curves
to year 2100 using Dec 2017 data of May2017 , J1+J2 only , data to 05
Feb 2018 SLR to 2100 , 56.2
J1+J2+J3 data to 25 May 2018 to 2100 , 57.1 cm
data to 02 Aug 2018 to 2100 , 50.5 cm
Update to 01 Sep 2018, public output 07 Dec 2018
to year 2100 , 49.0 cm
Update to 01 Oct 2018, public output 18 Jan 2019
to year 2100 , 50.9 cm
Update to 29 Nov 2018, public output 02 Feb 2019
to year 2100 , 77.4 cm
Update to 16 Mar 2019, public output 18 May 2019
to year 2100 , 50.1 cm (lo-res data for Nov 2018 to Mar 2019)
(02 Feb 2019 output was showing near vertical filtered output, so bound
to be revised down, whether a strong El Nino or not)
While its still possible El Nino is in hiatus and could be rising rather
than having peaked, some recent pixel-counted evaluations for the 3.4
sea-area of NOAA SST anomaly output plots. Last NOAA rolling mean
quarter output, +0.8 but next could easily be up to +0.9, ie 0.85

2019 year-day : El Nino 3.4 anomaly in degree C
91,: Nino +0.93
112, : Nino +0.93
119,: Nino +0.91
126, :Nino +0.89 [1% in 2.25 deg C bin]
129,: Nino +0.87 [0.3% in 2.25 deg C bin ]
133,:Nino +0.88 [0% in 2.25 bin]
136,:Nino +0.80 [0.3% in -0.25 deg C bin]
140,: Nino +0.84
143(23 May 2019) : Nino +0.93

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Thank you.

Looks like full-blown El Nino on the way
My spot evaluations of NOAA "El Nino 3.4" sea-area pixel-counted
evaluations of SST anamoly.
year-day : anomaly as deg C
91,: Nino +0.93
112, : Nino +0.93
119,: Nino +0.91
126, :Nino +0.89 [1% in 2.25 deg C bin]
129,: Nino +0.87 [0.3% in 2.25 deg C bin ]
133,:Nino +0.88 [0% in 2.25 bin]
136,:Nino +0.80 [0.3% in -0.25 deg C bin]
140,: Nino +0.84
143: Nino +0.93
147: Nino +0.89
150: Nino +1.07 [0 in -0.25 deg C bin, 0.7% in 2.25 deg C bin]

NOAA rolling quarter next thursday will probally show up from 0.8 to 0.9
and previous elevated values was a hiatus , not the peak.
Oz assesment
http://www.bom.gov.au/climate/enso/