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Paul Pukite edited this page Jan 18, 2022 · 4 revisions

Sea Level Height

Model fitting to the Sydney, Australia Fort Denison monthly SLH data uses the ENSO driver, meaning that most of the variation is ENSO or SOI related, which makes sense as sea-level height is a tidally driven behavior and partly caused by the inverted barometer effect. The high wavenumber LTE solution plays a significant role in the fast variation.

This shows a clearer and better correlation, with an extra high-K factor included:

with 1/2 as a training interval

Many more SLH data sets from around the world available here: https://www.psmsl.org/ so this is a treasure trove for experimenting

check out: https://geoenergymath.com/2022/01/14/sea-level-height-as-a-proxy-for-enso/ for connection to ENSO

Parameter data saved here:

  -0.00277579118,
   0.01737522639,
  13.52215939742,
   7.07049812928,
  20.29166635260,
   1.54910991190,
   0.08090529775,
  -0.00839731534,
  -0.00220581514,
  -0.00000590198,
  -0.02207020543,
   1.47078366730,
   0.59928953707,
  -0.00000000000,
   0.00000000000,
   0.00109143245,
   0.00000907621,
   0.00023540831,

LP
 182.62323100000,   0.01823848506,  -2.13169833051,
 365.24646200000,   0.01816858900,   1.57472518780,
  31.81209136000,  -0.00012257776,  -0.09531247994,
  27.66676713000,   0.01999326441,   3.66450968932,
  13.77727494000,   0.01900801402,   0.03572875032,
  13.60611041000,  -0.02892551550,  -1.39786020683,
  13.66083077000,   0.19264877086,  -2.84614310553,
  27.21222082000,   0.00104790070,   0.40548664783,
  27.55454988000,  -0.04567948300,  -1.39349814846,
  27.32166155000,   0.00077491143,   0.34553162321,
  13.63341568000,   0.06086449605,  -1.98862613076,
   7.09581061500,  -0.04997361555,  -3.34125599393,
   6.85940288400,  -0.02121447334, -17.59717919035,
   9.55688740100,   0.01372023852,  -7.55926878522,
   9.13295078100,  -0.00627228581,  -0.03569340987,
   9.12456635500,   0.00854457291,  -0.00000000000,
  14.76532679000,  -0.01772367336,  -2.42532381396,
  27.09267692000,   0.01480509973,   7.15353045140,
  29.53065358000,  -0.00000162958,  -0.00000000000,
1616.21559435000,   0.00005157822,   2.12894968335,
3232.43118870000,   0.00000750592,  -0.12390642087,
3396.79209660000,   0.00015041943,   1.19078311762,
6793.58419320000,   0.00005277379,   0.68440015541,

LT
   8.88922533186,   0.77337290280,   0.24817121679,
  42.50412584675,   3.28314380083,  -6.02108500184,
  18.53048420252,   1.17852365824,  -5.12313694978,
15917.42444057464,   5.37761728236,   0.00000000000,

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