2018 snow depth prediction

TL;DR: The Spencers Creek¹ peak snow depth for 2018 will be 201 ± 42 cm.

I predict the season peak snow depth at Spencers Creek using a simple six-parameter multiple regression model based on well-known climatic modes and influences. My mark-V prediction model goes as follows:

Spencers Creek peak depth (cm) = 266 – 16.1 x AAO + 2.56 x SOI – 49.0 x SST_Perth – 84.7 x SST_Tasman + 586 x aerosol + 0.020 x sunspots

The parameters are explained in the notes at the end. Click on the graphs for sources.


Antarctic oscillation (AAO)²

This parameter is tough to predict. AAO is persistent over months, but it can also change suddenly. There is some very limited numerical guidance available from global climate prediction models like the Australian Bureau of Meteorology’s (BOM’s) POAMA model (unfortunately not public). Here’s how AAO is looking (linked image will update):

Antarctic oscillation

My model uses the winter average — the “3-month running mean” to the end of August. Strikes me that this thing may be headed into another of it’s little negative spikes (it’s mostly positive these days — bad for snow — reflecting its long term uptrend). I’m adopting a fairly optimistic choice, -0.5.


Southern oscillation index (SOI)³

SOI reflects ENSO, which models have in neutral territory throughout this year (meaning SOI generally within the range ±10).

Internationally, the various model predictions look like this (remember we want the winter average — ‘JJA’; note that models plotted have widely varying skill):

I’m adopting a winter average SOI of 0, neutral for snow.


Tasman sea surface temperature (Tasman_SST)⁴

Here’s how the winter average has been trending, and how the monthly temperatures have been in the last few years:

Tasman SST winter average trend

Tasman SST monthly trend

The uptrend in Tasman sea surface temperatures is extraordinary, resulting in the warmest Tasman temperatures on record this summer and the hottest summer on record in New Zealand. But that seems to have relented a little in the last few months.

Here’s what NOAA’s CFSv2 model is predicting for winter (anomalies vs 1999-2010, add about 0.5°C for 1951-1980 in our region; will update):

CFSv2 SST anomaly prediction for June-July-August 2015
(vs 1999-2010, add 0.5°C for 1951-1980)

Despite the grim feel, I think we might be ok here. I’m adopting a winter average Tasman SST of +0.9°C, which is about on trend (that’s anomaly vs 1951-1980 detrended about 2020 — i.e. as if the trend line were rotated upwards about 2020).


Perth sea surface temperature (Perth_SST)⁴

Sea surface temperatures in the little box south-east of Perth correlate nearly as strongly with our snowpack depths as do those in the Tasman. Here’s how they’ve been trending; the winter average over the snow depth record, and the monthly temperatures in the last few years:

Perth SST winter trend

Perth SST monthly trend

You can see that the Perth SST shows a weaker uptrend than the Tasman, and that it’s taken quite a dive in the last couple of years, from which it has yet to recover. I’m adopting a fairly bullish 0.0°C (again vs 1951-1980, detrended about 2020).

Southern Hemisphere stratospheric aerosols⁵

There have been quite a few attempts at a decent explosive eruption (including Agung and Sinabung), but nothing solid has eventuated — so far; it’s not too late. Here’s the Mauna Loa Observatory data (Hawaii … no, not quite Southern Hemisphere, and nothing at all to do with the Hawaii eruption, which is irrelevant to us):

Optical thickness is the negative log of transmission, so the left panel is an inverted view. The right panel is a direct stratospheric aerosol measurement by laser probing (LIDAR), unfortunately not up to date. Despite that there’s been a bit of volcanic rumbling, I’m adopting 0.003, the same as last year.



I’m leery of sunspot-weather correlations as you may know — I’ve included them in my model this time just for fun. The latest sunspot count looks like this:

Latest sunspot record — will update

We want the winter average — June, July and August. Obviously that’s going to be very low (bad for snow!!). I’m adopting 10.



In the new mark-V model, those six parameters give a 2018 best-estimate peak snow depth of 201 cm — I think the first time I’ve actually made a greater than 2 m pre-season prediction since I began this game. The one standard deviation (‘±1σ’) error for the new model is 42 cm, so the range 159 – 243 cm would be expected to include about two-thirds of likely outcomes, if the parameters were perfectly known (they aren’t!). The estimated chance that the peak depth will exceed 2 metres is about 51%.

That looks like this:

Spencers Creek peak snow depth pre-season prediction for 2018



  1. Spencers Creek near Charlotte Pass, NSW, Australia, midway between Perisher Valley and Thredbo; data courtesy Snowy Hydro Limited.
  2. Antarctic oscillation (AAO), also called “southern annular mode” or SAM, is a measure of how tightly the circumpolar winds (“polar vortex” in one usage) blow around the pole. A loose pattern (negative AAO) leads to more polar storms reaching southern Australia, and more snow. The winter average AAO is used — the average of June, July and August.
  3. Southern oscillation index (SOI) is the difference between Tahiti and Darwin surface atmospheric pressure expressed as monthly standard deviations times ten. SOI is an indicator of the El Niño Southern Oscillation (ENSO), an east-west quasicycle in equatorial Pacific Ocean surface temperature and wind patterns which correlates with precipitation across much of Australia, including with alpine snow. A positive SOI is associated with more (and wetter) Australian snow. The winter average is used.
  4. My new model splits the local sea surface temperature influence into two zones: north-west Tasman Sea, and western Great Australian Bight:

    SST influence boxes

    Temperatures are HadISST anomalies from the 1951-1980 mean in degrees Celsius, detrended about 2020. The winter average is used. (I detrend the SSTs to make the factors in the model equation appear more sensible. Because of the model linearity, linear detrending doesn’t significantly alter the regression outcome.)

    The influence boxes are:

    • North-west Tasman Sea: latitude 27.5-40°S, longitude 147.5-160°E
    • Western Great Australian Bight: latitude 32.5-37.5°S, longitude 115-122.5°E

    Cool SSTs in both zones correlate strongly with more snow, but unfortunately local SSTs are rising rapidly with global warming, especially in the Tasman.

  5. Stratospheric aerosol optical thickness is the average for the Southern Hemisphere at 550 nm wavelength (green visible light). Large optical thicknesses from big volcanic eruptions correlate with big snow seasons. The winter average is used. More at my post here.
  6. Sunspots indicate a more active sun, more solar output and very slightly warmer conditions on Earth. But, for poorly understood reasons, they are also weakly correlated with increased precipitation in some places, including with increased snowfall. The net effect for us is a slight positive correlation between sunspots and snowpack depth. More here.

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