An April snow depth?

2015_4_25

Update 2: The models have settled now. Still looking cold, but not much snow.

There’ll be some snow this weekend, probably 20+ cm up high, but will it survive until Snowy Hydro’s usual weekly measure on Thursday 30 April?

. . . → Read More: An April snow depth?

Australian snow season start

Spencers Creek season start

Updated:  Rationalise the sub-intervals used for plotting

While we’re waiting for some real snow, I’ve updated the season start chart

. . . → Read More: Australian snow season start

Cloud seeding and snow

Spencers Creek peak snow depth moving average and trend

It’s the stuff of charlatan rainmakers of old — when the weird dance doesn’t cut it, try firing some fancy pyrotechnics skywards and hope for a lucky cloudburst. Those pyrotechnics are not so very far from what Snowy Hydro has been up to for over a decade now, hoping to increase winter snowfall over our alps. But to what effect?

. . . → Read More: Cloud seeding and snow

Season 2015 snow depth prediction

Spencers Creek peak snow depth pre-season prediction for 2015

Updated…

Time to give this a try:   the Spencers Creek season peak snow depth for season 2015 will be  141 ± 44 cm. . . . → Read More: Season 2015 snow depth prediction

Lowest and earliest Arctic sea ice maximum

PIOMAs northern sea ice volume

The northern sea ice has now reached its seasonal maximum extent. This year’s is the lowest and earliest maximum of the satellite era (since 1979).

. . . → Read More: Lowest and earliest Arctic sea ice maximum

Trend significance

Simulated Spencers Creek peak snow depth slope probabilities with nil trend

Updated: happy now; the words “hypothesis” and “null” do not appear (except to discard them).

There’d be no more abused tool in all of science than the linear regression “p-value” for trend significance. Don’t take my word for it; the problem is so severe that some technical journals have actually considered banning publication of p-values.

. . . → Read More: Trend significance

Spencers Creek snow depth prediction model - mark IV

Prediction_v_performance_MkIV

Updated: added residuals plot

I’m really impressed by this. I now have a snow depth prediction model that “explains” 50% of the variance in the Spencers Creek season peak snow depth record (midway between Perisher Valley and Thredbo, from Snowy Hydro). When you consider the vagaries of weather, snowfall, compaction, melt and weekly measurement, that really is a surprising achievement. I sure didn’t expect to get anywhere near it when I started out nearly a decade ago.

. . . → Read More: Spencers Creek snow depth prediction model – mark IV

Volcanoes and snow

Precursor eruption of Pinatubo, June 1991 (USGS)

A precursor eruption of Pinatubo, June 1991 (USGS)

Large volcanic eruptions can affect global climate — ask the folk who starved to death in Europe in 1816, after the massive eruption of Tambora in faraway Indonesia the year before. Explosive eruptions often inject vast quantities of ultrafine material high into the stratosphere, where it spreads around the planet blocking incoming sunlight.

. . . → Read More: Volcanoes and snow

Sunspots and snow

Sunspots_since_1750

Bear with me here. I come from a place with a long history of nutty sunspot-based weather prediction, so I’m well aware of the pitfalls. But our sun really is a very slightly variable star, and aspects of our climate do seem to very slightly vary with its output — particularly snow cover.

. . . → Read More: Sunspots and snow

The frequency of 'records'

Simulated future record temperature years

If you begin monitoring some variable thing over time, initially you’re going to see lots of new extremes — new record highs, for example. As your dataset grows, the frequency of new ‘records’ should decline sharply. If the overall system behavior is static, new records rapidly become very rare indeed, governed by the statistics of the variation. A feature of the 165-year long global temperature series in recent years is that new records highs have not been rare at all.

. . . → Read More: The frequency of ‘records’