songster

There's no melt yet in the central basin, so the volume is only going up. Every lead that opens at this point implies thicker ice somewhere else. So, in some ways this could even be a good thing for the ice: more ridging/thickening and new ice formation in the leads. However, as you say, there are two big caveats: firstly it's not clear how much the new skim of ice in the leads will have a chance to thicken before the thaw sets in, and so if the leads melt out early there will be more exposed surface water and albedo effects. Secondly, the fact that the leads are opening up at all betrays the fact that the ice is thinner than usual in the first place.

You mean the obvious error that was present in one model but no others, and vanished as soon as I emailed the guy in charge of the page to ask what was up?

Most of those pages link through to charts with the full egg codes, like this for Eastern Greenland (off the first link I gave). http://www.dmi.dk/dmi/en/chart3_2013-01-13-19-50_colour.pdf The egg code tells you age, concentration and thickness, see here for a key: http://www.natice.noaa.gov/products/egg_code.html

Greenland: http://www.dmi.dk/dmi/en/index/gronland/iskort.htm#ugekort http://en.vedur.is/media/hafis/iskort_dmi/dmi_weekly_icechart_bw.pdf Eastern Canadian Arctic and Hudson Bay: http://ice-glaces.ec.gc.ca/app/WsvPrdCanQry.cfm?CanID=11092&Lang=eng Western Canadian Arctic: http://ice-glaces.ec.gc.ca/app/WsvPrdCanQry.cfm?CanID=11081&Lang=eng Alaska and Bering Sea: http://pafc.arh.noaa.gov/ice.php In general, Googling "ice chart" or "egg code" together with the name of the region of interest will find relevant websites.

.. but what you call "setup" of the LI equation" involves adjusting and tweaking parameters! Or, as BW put it in 2009, "fiddle mucking around with constants, multipliers etc" http://forum.netweat...00#entry1517881 At a basic minimum, you have the starting height, the rate of influx, the rate of the leak, the degree to which ice extent affects the leak rate, the degree to which volcanic activity affects the leak rate, and how long the effect of a given volcano persists for. That's six adjustable parameters! They're even listed on the output graphs, such as this one. http://forum.netweat...attach_id=81512 See that list of r, o, i', v' and e'? Those are your adjustments and tweaks! (And you forgot to mention the arbitrary starting value, which I think you were calling h). In fact, it's even more ad hoc than that, since there was also a "Hadley correction" (i.e. tripling the rate of the leak for 6 years) with no justification at all other than making the curves match. Given that this model is fundamentally about energy balance, can you suggest a mechanism which would cause the Earth to triple the rate at which it loses energy into space?

Going back to the initial thread, a further question. How are you dealing with model initialisation? From the very first post here, we see that it takes quite a long time for the model to "settle down" after initialisation. Looking at the second graph on the page, it takes at least 10 cycles to settle down to a steady state, even when forced with a completely steady oscillation. That's simply an artefact based from the fact that you're (arbitrarily) starting with an empty bucket. Obviously the time taken to get to the steady state will depend on the size of the leak relative to the filling rate (i.e. the time constant of the resulting exponential). How have you accounted for this when running the LI model with sunspot data? If you haven't accounted for the arbitrary choice of starting conditions, then the upward rising trend you see could be artefactual, due to initialising the integration at zero. One sensible way to account for it would be to take an average size/length of sunspot cycle and run the LI for a few hundred years using this as a perfectly steady input cycle. Once the LI reaches equilibrium, then you can start integrating over the actual sunspot data, to see how changes in sunspot activity lead to changes in temperature. If you didn't do this, then your model is confounding two things: (1) how changes in in sunspot activity lead to changes in temperature, and (2) the effect of switching on the Sun at time t=0.

You want to use it as a proxy for albedo, but (like it or not), it is also a proxy for temperature, because ice melts when it gets hotter. Agreed that it would be a useful exercise to take it out and see how much it affects the overall fit. It would be good to do this for all the variables: sunspots included.

You're missing my point. One of your input variables (ice extent) is inherently a proxy measure for the output variable (temperature). So what you end up doing is explaining that temperature = temperature, which doesn't explain <i>why</i> anything at all.

It's nothing to do with independence of variables, it's the fact that you're using a proxy for long-term temperature change to try and predict long-term temperature change - explaining one variable in terms of itself. A good fit isn't surprising. It's like trying to model the changing height of the British population over time by using trouser length as an input. Sure it agrees well, but it's not going to tell you anything about what happens in 50 years' time.

If you rerun the LI at any point, can I ask you to try a simple experiment? Run it once using all your inputs, and once leaving out the sunspots. I'd be willing to bet that you can get a good fit (perhaps even equally good) by using just ice extent, ENSO and volcanoes. That's because each of these three inputs captures different aspects of the real-world temperature record. a ) Sea ice extent has a long-term declining trend (with an accelerating decline) which will get fitted to the long-term trend in real-world temperature data b ) ENSO, is a short-term quasi-periodic oscillation, which will get fitted to the (ENSO-caused) short-term oscillation in the real-world temperature data c ) Volcanoes produce irregular pulsatile forcings, which will get fitted to the (volcano-derived) spikes in the real-world data. If you were looking for further variables to add to improve the fit, then sure, the sunspot cycle might improve things a little - however I suspect that aerosol forcings would be even more powerful. Unfortunately, there is a much more serious problem with the model in that ice/albedo is a feedback loop. Yes, ice loss causes increased temperature by increasing energy absorption. However and more problematically, increased temperature also leads to ice loss. In using ice extent as an input to the model, you are thus effectively using the temperature data to explain itself. Let's assume for a moment that your model is entirely correct. Everything is explained by sunspots, ENSO, volcanoes and albedo. Now, I come along with a magic dragon and warm the planet with its fiery breath, melting the polar ice caps. Will your model detect the dragon? I suspect not. The model "sees" the ice cap melting (because you're using ice extent as an input) and thus expects that temperature will rise. Hey presto, this fits very nicely with the observed temperature changes. Therefore the warming is "explained" by the albedo change, and the dragon is just a myth. Fundamentally, you cannot attribute causality this way.

That doesn't answer the question. You could have two years with identical annual extent, but in one year you have a million km^2 less ice in the Arctic during June (affecting albedo) but a million extra km^2 in the Antarctic (not affecting albedo). Total sea ice is not a good proxy for albedo.

How do you account for seasonality if you're looking at the total? Extra ice during a given hemisphere's winter has next to no albedo effect. If ice area is up/down in June/March, it matters whether it's in the North or the South.

To be clear, I'm not the author of the post!

I believe it's because ice has a lower signature than snow. The meltwater from the thaw pulse refreezes in this case as a thin layer of ice a few cm under the surface, which may be visible to the microwave sensor. Additionally, the melting alters the structure of the surface snow itself, rounding off all the sharp angles of the ice crystals - this too may have some effect.

How can you even think ENSO could have any relevance to palaeoclimate? Depending on the configurations of the continents, there wasn't even a SO, let alone an EN.

Rubbish. Temperature was -61c, rising to -53chttp://www.wunderground.com/history/station/04416/2012/12/29/DailyHistory.html?req_city=NA&req_state=NA&req_statename=NA I think you misread the Fahrenheit value as Celsius. A little more attention to detail might be fruitful next time you're looking for sources.

Because presumption is always preferable to evidence.

Fair enough :-)

It's looking very likely that Svalbard will be completely ice free on the shortest day of the year. Has this ever happened before in the history of charting the ice?

I've never even seen someone get a rhetorical question wrong before.

Not a safe assumption. There's a big difference between 2-week old ice and 3-month old ice, so the fact that this year's ice froze over later will mean it's substantially thinner than previous years. By the time of the maximum in Feb-March it'll be a different story, and first-year ice within the main Basin should be comparable to any other year's first-year ice.

Short answer: Your question violates conservation of energy. Long answer: To a first approximation, all energy ends up as heat once it's been used. All the solar panel does is move that heat: rather than heating the desert soil, it heats the air around your house, or around your car, or wherever else the generated electricity is actually used. The only way your question makes sense is if the energy was absorbed and then never used - like a plant absorbing it, storing it as biomass and the biomass then getting fossilised as coal. If anything, solar panels would fractionally increase the proportion of incoming energy that gets absorbed, because solar panels tend to be pretty good at absorbing sunlight (i.e. low albedo). That's what they're for. This effect would of course be offset by the reduction in planetary insulation due to lowered CO2 emissions.

Are they the ones that give Rudolph a red nose?

Precisely so. Additionally, clothes have no effect. It is impossible for clothes to keep you warm, because your body is at 37 degrees C, while the outside of your clothes is at the same temperature as the ambient atmosphere. Your underpants are in breach of the laws of thermodynamics. Perhaps they should be prosecuted?

You do know that it's possible to fit any quasi-periodic signal to any other quasi-periodic signal if you allow for a variable lag, right?