Message to all Subscribers/ also! major tremor movement… MT Lassen volcano EQ uptick… 11/6/2020

Arctic Flash Freezing in November

After concerns over lackluster ice recovery in October, November is seeing ice roaring back.  The image above shows the last 10 days adding sea ice at an average rate of 215k km2 per day.  The Russian shelf seas on the right have filled with ice in this period.  On the CanAm side, Beaufort at the top left is iced over, Canadian Archipelago (center left) is frozen, and Baffin Bay is filling from the north down.  Hudson Bay (far left) has grown fast ice around the edges.  A background post is reprinted below, showing that in just 10 days, 2020 has added as much ice as an average 30-day November.

The graph above shows Arctic ice extents growing from Mid-Oct. to Mid-Nov. for the 13-year average and some other notable years.  Note 2020 well below other years in the beginning, and then growing ice rapidly in the last 10 days.  The deficit to average was 2.1M km2, now reduced to 810k km2.  SII and MASIE are closely synchronized, and 2020 is closing in on 2019. 

Background from Previous Post: Arctic October Pent-up Ice Recovery

Some years ago reading a thread on global warming at WUWT, I was struck by one person’s comment: „I’m an actuary with limited knowledge of climate metrics, but it seems to me if you want to understand temperature changes, you should analyze the changes, not the temperatures.“ That rang bells for me, and I applied that insight in a series of Temperature Trend Analysis studies of surface station temperature records. Those posts are available under this heading. Climate Compilation Part I Temperatures

This post seeks to understand Arctic Sea Ice fluctuations using a similar approach: Focusing on the rates of extent changes rather than the usual study of the ice extents themselves. Fortunately, Sea Ice Index (SII) from NOAA provides a suitable dataset for this project. As many know, SII relies on satellite passive microwave sensors to produce charts of Arctic Ice extents going back to 1979.  The current Version 3 has become more closely aligned with MASIE, the modern form of Naval ice charting in support of Arctic navigation. The SII User Guide is here.

There are statistical analyses available, and the one of interest (table below) is called Sea Ice Index Rates of Change (here). As indicated by the title, this spreadsheet consists not of monthly extents, but changes of extents from the previous month. Specifically, a monthly value is calculated by subtracting the average of the last five days of the previous month from this month’s average of final five days. So the value presents the amount of ice gained or lost during the present month.

These monthly rates of change have been compiled into a baseline for the period 1980 to 2010, which shows the fluctuations of Arctic ice extents over the course of a calendar year. Below is a graph of those averages of monthly changes during the baseline period. Those familiar with Arctic Ice studies will not be surprised at the sign wave form. December end is a relatively neutral point in the cycle, midway between the September Minimum and March Maximum.

The graph makes evident the six spring/summer months of melting and the six autumn/winter months of freezing.  Note that June-August produce the bulk of losses, while October-December show the bulk of gains. Also the peak and valley months of March and September show very little change in extent from beginning to end.

The table of monthly data reveals the variability of ice extents over the last 4 decades.

Table 1 Monthly Arctic Ice rates of Extent Changes in M km2. Months with losses in pink, months with gains in blue.

The values in January show changes from the end of the previous December, and by summing twelve consecutive months we can calculate an annual rate of change for the years 1979 to 2019.

As many know, there has been a decline of Arctic ice extent over these 40 years, averaging 300k km2 per year. But year over year, the changes shift constantly between gains and losses.

Moreover, it seems random as to which months are determinative for a given year. For example, much ado has been printed about October 2020 being slower than expected to refreeze and add ice extents. As it happens in this dataset, October has the highest rate of adding ice. The table below shows the variety of monthly rates in the record as anomalies from the 1980-2010 baseline. In this exhibit a red cell is a negative anomaly (less than baseline for that month) and blue is positive (higher than baseline).

Note that the  +/ –  rate anomalies are distributed all across the grid, sequences of different months in different years, with gains and losses offsetting one another.  Yes, October 2020 recorded a lower than average gain, but higher than 2016. The loss in July 2020 was the largest of the year, during the hot Siberian summer.  The bottom line presents the average anomalies for each month over the period 1979-2020.  Note the rates of gains and losses mostly offset, and the average of all months in the bottom right cell is virtually zero.

A final observation: The graph below shows the Yearend Arctic Ice Extents for the last 30 years.

Note: SII daily extents file does not provide complete values prior to 1988.

Year-end Arctic ice extents (last 5 days of December) show three distinct regimes: 1989-1998, 1998-2010, 2010-2019. The average year-end extent 1989-2010 is 13.4M km2. In the last decade, 2009 was 13.0M km2, and ten years later, 2019 was 12.8M km2. So for all the the fluctuations, the net loss was 200k km2, or 1.5%. Talk of an Arctic ice death spiral is fanciful.

These data show a noisy, highly variable natural phenomenon. Clearly, unpredictable factors are in play, principally water structure and circulation, atmospheric circulation regimes, and also incursions and storms. And in the longer view, today’s extents are not unusual.

Illustration by Eleanor Lutz shows Earth’s seasonal climate changes. If played in full screen, the four corners present views from top, bottom and sides. It is a visual representation of scientific datasets measuring Arctic ice extents.

34 Minutes Ago by Ron Clutz

via Science Matters

Bob Ward In Bad Mood–Loses Again

By Paul Homewood

Apparently Bob Ward is in a bad mood again. The reason, as David Rose explains is that he has just lost three complaints to the press regulator, IPSO, one against the Mail and two against the Telegraph!!

The Mail complaint concerned Rose’s article last year, which exposed the pack of lies in the BBC’s Attenborough programme on climate change. In particular, Attenborough’s claim that extreme weather events such as floods and storms have already got worse and more frequent, thanks to global warming, along with wildfires.

As I reported at the time, Attenborough’s claims were totally unfounded and contradicted the clear findings of the IPCC, which concluded that there was no evidence of any general increase in extreme weather events or wildfires.

In his usual rambling way, Ward objected to Rose’s analysis of this issue and other topics included in the programme, such as projected temperature increases, species extinction, corals and the claimed lack of action by the UK government.

On every single point however, IPSO found that Rose’s article was factually accurate, and sent Ward scurrying off with his tail between his legs.

Ward of course is used to losing complaints against the press, not least against the late Booker, who told me he had never lost a single case. But winning is not really Ward’s objective, Instead it is to tie up journalists such as David Rose and his editors in knots, creating much extra unpaid work, in the hope that it will discourage them from reporting on climate change in future.

In contrast of course, Ward gets well paid to by Jeremy Grantham to write his rambling complaints.

It is about time that IPSO refused to accept any further spurious complaints from Ward, which are wasting their time as well.

The IPSO judgment can be read here..

I will have a look at the Telegraph complaints tomorrow.


November 6, 2020 at 01:15PM

Carbon Credits: Irish Farmers Being Paid to Destroy Their Fields

View from the summit of Cuilcagh Mountain. By Carl Meehan – link, CC BY 2.0, link

Guest essay by Eric Worrall

Centuries of efforts to drain swamps to extend arable land in Ireland are being reversed, in an effort to trap more carbon.

Cuilcagh Mountain: Coconut logs form dams to fight climate change

By Conor Macauley
BBC NI Agriculture & Environment Correspondent

On a County Fermanagh mountain, a helicopter has flown in logs made of coconut fibres to help with the fight against climate change. 

They will be used to build dams on Cuilcagh, which will help restore large areas of degraded blanket bog that are currently emitting carbon.

The dams will facilitate the re-wetting of areas which can then be colonised by sphagnum mosses.

That vegetation, layers of which build the peat, will help to trap carbon.

“Peatlands, even though they don’t cover the same area as forests do, they actually contain way more carbon even than the rainforests do across the globe.

Around 18% of the landscape in Northern Ireland – more than 200,000 hectares – is covered by upland blanket bogs, lowland raised bogs and similar wetland habitat.

But for now, much of it is in a degraded state due to things like drainage, wildfires and historic overgrazing.

Read more:

Helicopter over bogland

logs made from coconut fibres

I guess the land belongs to the farmers, so if they want to tear up their farms its their land. And I certainly have no problem with a bit of wetland being preserved in a pristine state for wildlife habitat. But it seems a terrible shame for today’s Irish to suddenly decide to undo centuries of progress to appease the carbon god.

via Watts Up With That?

November 6, 2020 at 12:52PM

The foul-smelling fuel that could power big ships

Design concept

Another attempt to play the imaginary ‘human-caused climate’ game gets underway. This time it’s ammonia (NH3), a compound of nitrogen and hydrogen, used as fuel to appease the legions of carbophobes in power today.
– – –
An enormous engine, the height of three floors, growls loudly at a test centre in Copenhagen.

Nearby a team of engineers supervise it from a control room resembling a ship’s bridge.

Usually such an engine would be propelling a large ship across the sea, but this one is being prepared to take part in a ground-breaking project, says BBC News.

Graph of energy released per litre consumed of various fuels

Engineers want to see if they can make it run on liquid ammonia.

Ammonia has long been a key component in fertiliser, cleaning products and refrigerators.

But in the search for new cleaner fuels, the foul-smelling substance has emerged as a frontrunner to power ocean-going ships.

Around 90% of all goods traded globally are transported by sea. But ships are gas guzzlers. Marine transport produces around 2% of global greenhouse gas emissions.

The International Maritime Organization (IMO) wants to halve emissions by 2050, from 2008 levels. That requires a substantial shift to green technology.

Brian Soerensen, a research and development chief at Man Energy Solutions, says several fuels are being explored: “One of the options we believe will be ammonia. Methanol could be another one, biofuel could be a third.”

Ammonia has an advantage as it contains no carbon, so can burn in an engine without emitting carbon dioxide.

By early 2024, Man Energy Solutions plans to install an ammonia-ready engine on a ship. The first models will be dual-fuel, able to run on traditional marine gas oil as well.

While it is less energy-rich than today’s marine fuels, liquid ammonia is more energy-dense than hydrogen, another zero-emission fuel.

Hydrogen has already powered cars, planes and trains. It’s cheaper to produce than ammonia, but harder to handle as it has to be stored at minus 253C. Ammonia becomes liquid below minus 34C and at higher temperatures if under pressure.

“Ammonia sits very nicely in the middle,” says Dr Tristan Smith, an expert in low carbon shipping from University College London. “It’s not too expensive to store and not too expensive to produce.”

There are challenges. Burning ammonia can create polluting nitrous oxides, therefore the exhaust needs cleaning up. It is also toxic, so requires careful handling and storage.

However, safety know-how and some port infrastructure are already in place, says Mr Soerensen, because the fertiliser industry is well-established.

“It’s being transported seaborne today. We know how to handle ammonia on board a ship, not as a fuel, but as a cargo.”

Full report here.

via Tallbloke’s Talkshop

November 6, 2020 at 12:48PM

Hmm. Odd pattern of Biden-votes fails an easy first test for Tax Fraud

Red Flag anyone?

Tax auditors use Benfords Law to detect fraud. They look at the first digits of the income data and figure out how often the different digits pop up. If the deposits are random we’d see lots of one’s, and less of every other number in an ordered pattern.  Two would be the second most likely, three the third…. and so on down to nine. If there were lots of sevens, say, the Tax Auditor will start hunting there.

So if precincts call in ballot results there is a certain pattern we would expect them to arrive at, and that’s the pattern we see for every candidate, … except Joe R.Biden and Kamala D. Harris.

For some reason their results in Chicago, Milwalkee, and Allegheny were all clumpier, with 2, 3 or even 5 being among the most common for ballot results? Soon someone (or 500 people) will test out and see if Biden and Harris voters were clumpier in all districts or just the states that mattered to the Democrats.

You don’t need a Stats degree, just look at the graphs.

Credit to Smoking Gun of Democrat Cheating, by vbmoneyspender. Thanks to graphs by ‘cjph8914’ on Github. And explained in a twitter thread by StatsguyPhD  who notes the respective p-values in their 16 digit glory:Biden 1.5076774999383611e-27  (note the ‘e’)
Trump 0.00048111250713426005Statsguyphd sedately describes this difference as “extreme” and says “What is undeniable is that the first digit frequencies of Biden’s vote totals is extremely anomalous in comparison to Trump’s. “

So Joe Biden needs to come up with some convincing reasons about why these clumpy voter numbers group the way they do. Readers may want to help them below by dreaming up the best excuses they can think of to explain these patterns.

Do Democrat voters in Chicago vote in class sizes of 30?

Or do these clusters leave the signature mark of the sizes of the packets handed out by the head honcho of vote riggers?

Statsguyphd posts all his code and thoughts here.

Keep reading  →Rating: 9.7/10 (3 votes cast)

via JoNova

November 6, 2020 at 12:40PM

Wind Power At Low Levels Across Most Of Europe

By Paul Homewood

John Constable has written a more detailed critique of the current electricity supply problems, and notes that the high pressure system, which has led to the loss of wind power, is extensive over much of Europe as well:

It’s therefore worth looking at the impact of this on wind power in other countries. Wind is the blue band near the top:





Including the UK, wind power across these six countries is currently running at about 28 GW, well below last year’s average of around 40 GW.

Although wind power in Spain is running about 7 GW above average, it is not enough to offset the shortfalls elsewhere. In the UK alone, wind power is currently generating at 5 GW below Q3 last year.

There is one final consideration. Although wind power in Spain is producing at about 55% of capacity, roughly double the norm, Spain is still relying on gas and coal for a quarter of its power. In other words, they have no “surplus” wind power to sell off.

Why then should they sell their wind power to other countries in Europe, when it would mean they had to ramp up gas power stations in place of it?


November 6, 2020 at 12:33PM