Sunday, 20 December 2015

An unclear result vis-à-vis necessity

Today, the Animal Legal Defense Fund in the United States has ranked the states in order of animal rights.

Although I am sceptical of the arguments of extreme animal rights advocates, I understand that at least in hotter climates with poorer soils there certainly is need for restrictions on animal killing and possibly even on use in some cases (which probably are not found in most of the Western Hemisphere). Nonetheless, the soil map below, which shows lower-fertility and older soils in the South and nutrient-poor parent materials in the central west coast, does suggest that these hotter regions need more regulations on animal use:
This belief of greater regulation in hotter climates is supported by native cultures: generally there were greater taboos on animal food in hotter regions than in cooler ones, and the greatest taboos of all were found in arid desert regions and in southern Australia where poor soils and dry climates (which create alkaline soils that immobilise phosphorus, zinc and copper) severely limit the availability of animal protein. Many primitive peoples in these regions were de jure and/or de facto vegetarians as a means of conservation – it is ironic that vegetarianism is most “trendy” today in some extremely protein-rich regions such as the Pacific Northwest and Germany where diets based upon animal foods cause limited or negligible ecological costs and comparative disadvantages in plant-based food production tend to be very large.
As can be seen from the map above, there does not seem to be a strong relationship between laws and actual ecological need – though I will stress that this is better than the usual result of inverse relationship whereby the best ecological laws found precisely where there exists least need.

In general, the best animal protection laws would be needed in the low-nutrient Southern states and perhaps in the “southwest” (which ecologically includes California and Oregon as well as the states of Arizona, New Mexico, Utah and Nevada normally known as the “Southwest”). As can be seen, some of the relevant states, like Oregon, California, Arizona, Louisiana and Florida, are in the top third, but on the other hand New Mexico, Alabama and Mississippi have laws relatively much poorer than would be required. At the same time, numerous Northeastern states like Maine, Michigan, Illinois, Indiana and Massachusetts are relatively overregulated.

Wednesday, 16 December 2015

Two global temperature databases compared

Perhaps seeking to expand my knowledge of how Australia’s appalling record of the highest per capita greenhouse emissions in the world (in ecological terms, Australians would logically be permitted vastly smaller per capita emissions than Eurasians and Americans since Australia’s ecosystems are based on much slower metabolism) – I have in recent months studied global temperature data and then found two major sets of global temperature maps, both of which date back to 1880. I have shown a comparison for the northern hemisphere winter season of 1933/1934 as an illustration:
Comparison of the GISS and NOAA global temperature anomalies for the season of December 1933, January 1934 and February 1934
The GISS temperature setlist is generally preferable to the NOAA site as the reader can look at natural climate variability at least partially insulated from Australian-made greenhouse pollution. Being restricted to 1961-1990 and 1971-2000 means, the NOAA site cannot give figures relative to something even approaching a genuinely natural average, which is problematic when assessing temperature anomalies for stations with long records. The GISS site also has data for a wider range of stations in most cases, especially in earlier years which are the purest indication of natural variability before Australia’s coal and aluminum industries were developed and bloodlessly took control of the global climate:
Comparative NOAA and GISS temperature anomalies for the winter of 1885/1886. Note that in all three maps large areas have no data. Because Australian land clearing and fossil fuel burning was less developed or not at all, however, these early maps are very valuable as representing the most natural climate variability available.
A problem with the GISS setup that makes NOAA of some use, however, can be seen from their data for the winter of 1940/1941. Actual station data in northern interior British Columbia and northern Alberta (e.g. from Baldonnel) seem to verify the NOAA figures rather than the GISS ones. In Baldonnel, British Columbia the monthly anomalies from December 1940 to February 1941 via-à-vis 1971 to 2000 are:
  • December 1940: +0.542106˚C
  • January 1941: -4.62105˚C
  • February 1941: +2.08500˚C
whilst for Fairview, Alberta the figures are:
  • December 1940: +1.06842˚C
  • January 1941: -3.58˚C
  • February 1941: -0.28˚C
Yet, the GISS maps do not show colder-than-normal temperatures in northern Alberta and northern interior British Columbia in January 1941:
NOAA and GISS temperature data for December 1940, January 1941 and February 1941. Note the negative anomaly in January 1941 – verified by data over northeastern British Columbia and northwestern Alberta – is not shown in GISS.
It’s notable that the stations previously noted do not possess data for the hotter years after 1990, which would add to the negative anomalies.

The subsequent winter of 1941/1942 had a similar problem around the Gulf of Ob and Gulf of Yenisey, which can be verified for the station of Dudinka on the Yenisey River west of Norilsk:
  • December 1941: +1.51052˚C
  • January 1942: +9.47˚C
  • February 1942: +2.62˚C
Global temperature maps for December 1941, January 1942 and February 1942. Note the positive anomaly in the NOAA map but not the GISS map around the Gulf of Ob and Gulf of Yenisey
It’s notable that I have not so far been able to verify major errors in the GISS maps from earlier dates as I have for the World War II years, but this may be because of poorer NOAA data.

All in all, whilst despite these problems GISS is still the best site, NOAA nonetheless has considerable value for earlier years. Those interested in the weather need to know changes in temperature just as they do anthropogenically produced changes in rainfall in southwestern Australia and central Chile, because they demonstrate how unsustainable Australian energy, farming and transport policies have been for over half a century – and without protest from elsewhere in the world.

Sunday, 13 December 2015

Longman reveals – unconsciously – the Enriched World as “circle of exclusive clubs”

Percent of mean national per capita income for each region of the US, 1929-1979
The now-veteran demographer Phillip Longman (he turns sixty in April), whose The Empty Cradle remains the best look – if without likely remedies – at the Enriched and Tropical Worlds’ severe demographic problems, has today showed, without having that aim, just how the Enriched World is becoming nothing except an exclusive club caught in a whirlpool of demographic suicide.

In November’s Washington Monthly, Longman in his new article ‘Bloom and Bust’, has argued that “regional inequality is out of control” after, as the graph on the left shows, having fallen for almost a century and a half until the 1980s. His data show that income inequality in the United States is increasing as
“geography has come roaring back as a determinant of economic fortune, as a few elite cities have surged ahead of the rest of the country in their wealth and income”
and
“only the very rich can still afford to work in Manhattan, much less live there, while increasing numbers of working- and middle-class families are moving to places like Texas or Florida... even though wages in Texas and Florida are much lower.”
Percent of New York mean per capita income for outlying US regions, 1969 to date
Longman then points out that the cities with highest per capita incomes have tended, in fact, to see large net out-migration, whilst areas where per capita incomes are not growing at all have tended to attract most in-migrants.

Longman’s primary argument is that looser enforcement of antitrust legislation and large amounts of financial deregulation during the 1980s and 1990s has led to the consolidation of extremely wealthy businesses in a small number of major cities on the East and Pacific Coast, notably New York, Boston, the San Francisco Bay Area, Washington D.C., Los Angeles and the cities of the Pacific Northwest. He believed the dominance of what he calls “retail goliaths” has meant much less is invested in “flyover” cities of the Plains, Mountain West and the South, with the result that the economies of these cities have severely declined as even new entrepreneurs must move to technology centres like Silicon Valley. Longman quotes Bill Gates to the effect that patent holders’ monopoly power – which he notes was expanded in the 1980s before which the federal government refused to grant any patents for software – makes it more difficult for inventors not allies with the patent holders. (Whilst I understand the value of patents in the context of agriculture, where Australia’s farmers do not pay anything for fertiliser technologies patented overseas but used to farm inherently unsustainable and exceedingly ancient soils, Gates’ and Longman’s criticism has major value.)

The problem is that Longman gives much too little attention to how impossible it is for the middle class – let alone the working masses – to live in such wealthy cities as New York, Boston, the Bay Area, Seattle, Portland and Washington D.C. Demographers ought to know all too well that:
  1. lowest-low fertility is a consequence of family formation being unaffordable due to limited housing space and consequent:
    1. simple unaffordability of housing for all but the very rich
    2. extreme lack of space in housing that is uncomfortable for all but one- or two-person houses and cannot accommodate families
    3. it is clear to me that, despite minor criticisms I received years ago Wendell Cox, many indices like fertility would correlate much better with:
      1. cost of housing per unit of housing space (relative to income) rather than actual total cost (because cheap housing is not useful for families if it be too small for comfort)
      2. cost of housing relative to each individual worker’s income, rather than with total household income (because a single income allows the mother to take more care of children)
      3. such criteria would show more accurately the problems Enriched World cities have with housing space and the need for women to work to gain basic sustenance – and of course this work tends to require high levels of education
  2. that severe land-use restrictions – in lands devoid of unique biodiversity (ice-free only for 15,000 years) and/or low secondary productivity to justify restrictions – create a large part of this housing shortage
  3. that politics in big “imperial cities” tends to be very left-wing due to the concentration of wealthy entrepreneurs there and resultant extreme levels of class resentment
  4. a fourth insight, which Longman does give, is that as the public sector has retreated from providing transport, government regulation of land supply and roads in “imperial cities” has precluded the private sector doing anything to improve mobility
  5. a fifth insight is that many regulations and much government spending in “imperial cities” is designed to help the very poor but:
    1. exacerbates natural flat land scarcity by means of rent control, which often allows less wealthy people who initially lived there to pay very low rents compared to what the market would charge
    2. create a culture of welfare dependency amongst these cities’ less wealthy populations, who obtain more from welfare than they could from modest-paying employment locally
    3. reduces job and trade opportunities by placing wages far above theoretical market levels given the regions’ resource poverty and dense pre-industrial populations, and by means of extreme and usually unnecessary (vis-à-vis Australia or Africa) environmental regulations
Under these conditions, Enriched World cities have no choice but to compete for the most skill-intensive industries extant. Their lands are generally cool, mountainous and pre-industrially densely populated, so they have large comparative disadvantages in agriculture. Glaciers and the Alpine Orogeny have stripped the Enriched World of difficult-to-smelt lithophile metals and preindustrial mining stripped it of easily smelted chalcophile ores, ruling out mining as a long-term base. The dense population and demands for clean air make unskilled labour totally inadequate as an income even with two partners, so that labour- or capital-intensive manufacturing industries also cannot serve as a long-term base for Enriched World economies.

The educational requirements and demographic consequences of an economy based exclusively upon skill-intensive industries have been documented for over a century. In 1900, when among women generally fertility rates were five to six children per lifetime, those of educated women could be as low as a tenth of that: I recall that one survey estimated the few tertiary-educated women produced merely 0.47 children over their lifetime! The situation has changed little in modern times – the difference is that dependence upon skill-intensive industries is now no isolated phenomenon but characterises most corners of the Enriched World and many of the Tropical, making these regions exclusive clubs for the skilled 1 percent or, in the most mountainous or densely populated, much less than that. Even if they had large pre-industrial populations or rapid modern growth, these nations, as shows dramatically by Japan post-1990, will one by one decline in global importance.

Families – who form the next generation – are being forced to move to land-rich regions like the American South or suburban Australia, which is where the future of the world must lie. Despite these regions’ inherently low soil fertility and generally high species diversity, the former trait tends to enhance cooperation and solid families and minimise the class conflict that produces the excessive regulation in cool climates. This sense of community undoubtedly allows tolerance for much lower quality of life via greater emotional support during social or environmental crises, by avoiding heat-of-passion reactions that can disturb relationships even between those who deeply love each other. It is this family-friendly “community culture” that drives migration to places with poor economies, bad climates and low quality of life, and the politics of the cooler and more mountainous regions of the globe make it unlikely to change.

Saturday, 12 December 2015

The generality of precipitation/temperature patterns: North Pacific versus North Atlantic

In a series of earlier blog posts (here and here) it was demonstrated that the relationships between England and Wales Precipitation (EWP) and Central England Temperature (CET) show consistency across months, but that the hotter and cooler parts of the year show different relationships:
  1. a positive CET/EWP relationship exists from November to February and in a minor way for the fiscal year from July to June
  2. a negative CET/EWP relationship exists from April to September
  3. no significant relationship in March and October
Despite the rapid change the globe’s climate due to emissions of greenhouse gases by Australia, South Africa, the Gulf States and to a lesser extent other mineral- and fuel-producing nations, these relationships have not substantially changed since 1974.

In this post I will see if an analogous condition to that of the UK also holds in the only other analogous climate region of the globe – southeastern coastal Alaska. Whilst generally extremely similar to the UK in its ecology and environmental history, there are major geographic differences owing to he extreme height of the coastal mountains, which reach much further above the glacial equilibrium line than does Mount Everest.

At the beginning of this year, southeastern coastal Alaska was divided after an examination of long-term station records into four climate divisions:

  • AK 9: East Gulf (red, on right)
  • AK 10: North Panhandle (blue, on right)
  • AK 11: Central Panhandle (purple)
  • AK 12: South Panhandle (dark green, on right at bottom)
I have chosen to investigate only AK 9 (East Gulf) for this study, to simplify matters because it is the largest and most “central” of Alaska’s six “maritime” or “southern” climatic divisions – which also include AK 8 West Gulf (green, around Kodiak) and AK 13 Aleutians (purple, in far southwest).

Reliable temperature and precipitation data for Alaska go back only to 1925, a little more than a third the length of the EWP data. For this reason, I have decided not to separate years with and without the dominant influence of greenhouse gas emissions by mineral exporting countries like Australia, South Africa and the Gulf monarchies: they are too likely to dominate the sample and the UK experience is that the change in correlation prove insignificant even though the averages do change significantly.

So, here are the scatter plots by months of precipitation versus mean temperature for the East Gulf division of Alaska, extending from Valdez to Sitka:

July:


As we can see here, in this the hottest month of the year, a general negative precipitation versus temperature regime prevails, exactly as seen for EWP versus CET in the United Kingdom over a record three times as long. The major outlier is the very wet July 1958, which was the second wettest on record with an estimated district average of 473.46 millimetres but no cooler than average.

August:

August, still in the hotter part of the year, shows a similar trend to July, which is in strong agreement with our earlier results re the relationship between EWP and CET in the various months. The relationship is not tight, and I have not measured the correlation coefficient. Two Augusts:
  • 1969, the coolest on record but sixteenth driest of 91
  • 1981, the second wettest on record but 0.4˚C hotter than all-series average 
show very distinct departures from the pattern of hot/dry and cool/wet.

September:

Here, we see that the seasonal change from hotter weather being drier to warmer weather being wetter than normal appears to be occurring one month earlier than we saw for the EWP versus CET graph in our earlier blog post. The scatter plot for September in the East Gulf division is basically flat, and is flat even with the extremely cold outlier of September 1992, whose estimated district average precipitation total is near normal.
September 1992 500 millibar chart anomaly vis-à-vis 1880 to 1974 mean. Support for the Twentieth Century Reanalysis Project dataset is provided by the U.S. Department of Energy, Office of Science Innovative and Novel Computational Impact on Theory and Experiment (DOE INCITE) program, and Office of Biological and Environmental Research (BER), and by the National Oceanic and Atmospheric Administration Climate Program Office.
As one can see, the extremely cold polar air over Alaska’s northeastern Gulf coast does not really have a mean onshore flow component, so that the cold was not accompanied by excessive rainfall or snowfall.

October:

In contrast to the CET versus EWP graph, October in southern Alaska already shows very clearly the typical winter pattern whereby precipitation and temperature show a direct correlation. This pattern has long been known via the National Weather Digest (here) for the main city in the region – Juneau – and the figures for October clearly show this pattern extending generally in the region. Cold months of October have anomalous flow from the major cold-air source region of the Yukon.

November:

As the discussed 1986 article about the winter climate of Juneau – located since this year in the Central Panhandle climate division to the southeast of the region graphed – would imply, the direct precipitation/temperature relationship increases in intensity for November.

Two facts one will note with this graph is that there are very few outliers, and that the shape is more curved than linear. The curved concave-down line of best fit implies that the temperature distribution is skewed due to the greater frequency of relatively mild and hyper humid maritime weather vis-à-vis frigid, dry continental conditions. The lack of outliers is such that even November 1956, on the “lower” right, was still warmer than average, and November 2002 at the extreme top was still wetter than average:
November 2002 500 millibar chart anomaly vis-à-vis 1880 to 1974 mean. Support for the Twentieth Century Reanalysis Project dataset is provided by the U.S. Department of Energy, Office of Science Innovative and Novel Computational Impact on Theory and Experiment (DOE INCITE) program, and Office of Biological and Environmental Research (BER), and by the National Oceanic and Atmospheric Administration Climate Program Office.
The key point from this November 2002 chart, which those only familiar with sea level charts might not instantly grasp, is that the powerful anticyclonic anomaly over southeast Alaska is still wetter than average on its warm western side because the anomalous flow is onshore.

December:

December, as the month where the winter solstice occurs, reflects clearly the pattern of mild, hyper-wet weather opposed always to frigid, dry weather. In fact, nothing approaching a moderate outlier can easily be seen here – which suggests much more powerful correlations than for EWP versus CET. The curved, concave-down line of best fit is also more clearly visible than for November, as is the record cold and dry December 1933 with its extremely strong flow from the frigid Yukon:
December 1933 500 millibar chart anomaly vis-à-vis 1880 to 1974 mean. Support for the Twentieth Century Reanalysis Project dataset is provided by the U.S. Department of Energy, Office of Science Innovative and Novel Computational Impact on Theory and Experiment (DOE INCITE) program, and Office of Biological and Environmental Research (BER), and by the National Oceanic and Atmospheric Administration Climate Program Office.
It is noticeable how strong the anomalous flow in December 1933 was vis-à-vis any of the other months whose flow patterns have been diagrammed here.

January:

Vis-à-vis the almost perfect relationship seen in December, January does not show quite so consistent a positive correlation, nor so curved a line of best fit. The line of best fit is much closer to the “familiar” linear shape than for December or even for November. More significantly, the famous month of January 1949 is an extremely powerful outlier being very close to the wettest on record, receiving 703.33 millimetres, but being no warmer than average at -7.9˚C:
January 1949 500 millibar chart anomaly vis-à-vis 1880 to 1974 mean. Support for the Twentieth Century Reanalysis Project dataset is provided by the U.S. Department of Energy, Office of Science Innovative and Novel Computational Impact on Theory and Experiment (DOE INCITE) program, and Office of Biological and Environmental Research (BER), and by the National Oceanic and Atmospheric Administration Climate Program Office.
This anomaly occurred because in January 1949 – as can be seen above – the flow anomaly was westerly (moist) but came from the cold Bering Sea and no warm source was accessible due to the powerful North Pacific anticyclonic anomaly.

This month was the snowiest January on record over Alaska as a whole, and the coldest on record over a large portion of the western United States, where it has been rivalled only by the Januaries of 1916, 1930, 1937, 1950, 1957 and 1969. It was extremely warm, however, over the eastern United States and Eurasia, being almost the “year without a winter” in the UK.

February:

February retains the basic winter scatter-plot pattern we have seen since October – mild and hyper humid versus frigid and dry. If anything, the line of best fit is more akin to the curved December shape than was seen for January.

Although not to the same extent as with December, there are no strong outliers. Even the record wet February 1964 with a strong high-level low pressure anomaly over Alaska itself was warmer than the all-series mean (which more than CET is distorted by greenhouse emissions from Australia and other resource-exporting nations), and the record dry February 1989 (driest for any month throughout this super-humid region) still very cold.
February 1989 500 millibar chart anomaly vis-à-vis 1880 to 1974 mean. Support for the Twentieth Century Reanalysis Project dataset is provided by the U.S. Department of Energy, Office of Science Innovative and Novel Computational Impact on Theory and Experiment (DOE INCITE) program, and Office of Biological and Environmental Research (BER), and by the National Oceanic and Atmospheric Administration Climate Program Office.
Even more than December 1933, we see extremely large heigh anomalies vis-à-vis mild, wet winter months. It is the extreme height anomalies combined with anomalous continental flow that made this month the driest of any month on record over almost all of climate divisions AK 9, AK 10, AK 11 and AK 12, whilst Barrow on the dry, frigid North Slope had its mildest month between November and March on record.

March:

In contrast to the EWP versus CET plot, March does not show any change from the winter months in its precipitation/temperature correlations over southern Alaska. As with October, the graph represents almost a straight line of positive slope, suggesting reduced skew in the temperature distribution but no change regarding the basic contrasts between wet and dry air masses.

April:

With the days becoming longer than the nights, and continental temperatures becoming hotter relative to maritime ones, we should expect that April would show a reversal or weakening of the consistent contrast of warn, hyper-humid maritime months versus frigid, dry continental months that are shown consistently over the East Gulf district between October and March.

In fact, even for April the correlation between precipitation and temperature (coefficient not measured) can be seen from the graph above to be positive. Nonetheless, it is weaker than the correlations we saw between October and March. However, the shape appears to show one key trait found for Juneau by Bradley Colman in the winter but not in the summer: a skewed temperature distribution with the median and mode warmer than the mean.

May:

Here at last we se a more definite transition to the typical hot-season pattern whereby hot months are drier and cool months wetter than the long-term mean.

What is noteworthy is that May gives no appearance of a transitional month, and outliers are not pronounced. Even the record hot and dry May of this year fits a line of best fit dating back to 1925 extremely well – indeed when you see the bullet in the top left, May 2015 fits the line as if there had been no radical man-made climate change as is demonstrated by rainfall and runoff data in southwestern Australia and parts of Chile.

June:

June, like May and July, behaves as one would anticipate from our earlier study of EWP/CET correlations like a typical summer month. Hotter-than-average Junes tend to be dry and cooler-than-average Junes wet over the East Gulf division.

As with May, there are almost no marked outliers, although the line of best fit is a little curved. this curved line, although predicted by Bradley Colman in 1986 for all months in the winter half-year, is emphatically not expected for a summer month. The differences between sea and land temperatures in the summer are less than in the winter months, and it stands tougher to get the southeasterly flow that would be needed for the hottest temperatures in summer, than it is to get frigid winter northeasterlies.

Conclusion:

Even without calculating Spearman ρ and/or Pearson r for each month, in the case of the Alaska East Gulf climate division – and almost certainly all of the maritime North Pacific – it can be concluded that:

  1. a very strong positive relationship between temperature and precipitation is observed in the winter half-yea between October and March
  2. a similarly strong negative relationship between temperature and precipitation is observed in the summer months from May to August
  3. September does not show a significant correlation between temperature and precipitation
  4. April appears to show a slight positive correlation, but it would be interesting to speculate whether longer records would show it as more of a transitional month
  5. Vis-à-vis the EWP and CET areas, climate division AK 9 is similarly located but further north.
  6. This more northerly location may explain why the reversal in correlation coefficients occurs earlier in autumn and later in spring.
  7. The patterns of monthly relationships between precipitation and temperature in southeastern Alaska (north Pacific) almost certainly are analogous to those over the United Kingdom (north Atlantic). The difference in (6) is almost certainly replicated over Scotland.
  8. Analogies between these two coastal regions are likely to be useful if topographic differences are taken into account.

Thursday, 19 November 2015

Evidence for banking on extinction of Sumatran rhinoceros

In a previous post, I argued that contrary to what Robert P. Murphy claims in Chapter 6 of his 2007 The Politically Incorrect Guide to Capitalism, speculators and holders of stockpiles of rhinoceros horn have a very strong incentive to wish for the extinction of these species to increase the value of the horn they presently hold.

The thesis was outlined five years after Murphy’s book in the Oxford Review of Economic Policy’s ‘Banking on Extinction: Endangered Species and Speculation’ by the team of Erwin H. Bulte, Richard D. Horan, and Charles F. Mason. ‘Banking on Extinction’ provided a valuable previous example with the Dutch destruction of nutmeg trees, and also discussed banking upon extinction of less critical species like the sloth bear (Melursus ursinus).

Now,  as the Sumatran rhinoceros is extinct outside Sumatra itself and numbers have fallen almost as low as the Javan Rhinoceros, it has become clear that poachers in the primary horn consuming nations of Vietnam and China are deliberately trying to hunt the species to extinction. Although older articles on rhinoceros population declines argued that the crisis facing the Sumatran Rhinoceros has little to do with poaching and was dictated by large-scale habitat destruction for agriculture, in fact there remains a lot of suitable habitat within the historic range of the Sumatran Rhinoceros that is entirely unoccupied by the species.

The fact that the Javan Rhinoceros was poached in Vietnam until the very last individual was dead implies that those who carry out poaching know their superiors’ demands to ensure that the limited remaining horn of these species will sell for the highest price possible – which even for low-level hunters means greater long-term income as the stockpiled horn sells for prices much higher than the  $75 per gram that Sumatran rhinoceros horn presently sells for. What Sumatran horn will sell for once the species is extinct nobody so far as I am aware has ever estimated, but it could be orders of magnitude higher than the present price which no doubt is depressed by stockpiling in the expectation of extinction. Given the rarity of the commodity even today, and the potency traditional East Asian pharmacists associate with the Asiatic rhinoceros species, it’s possible I feel that post-extinction Sumatran horn could sell for $750 or even $7500 a gram. At such prices, only a tiny amount of horn would make the speculators who hold Sumatran horn stockpiles very rich indeed, and the prestige of the commodity would no doubt rise once it becomes via extinction non-renewable.

‘The Operatives’’ study is a very revealing argument against Austrian School claims that free markets will actually protect endangered species in all situations – exploitation can, and not only on cheap farmland in Australia and Africa, be too efficient an alternative.

Paris still can't get its priorities right

http://www.theaustralian.com.au/news/latest-news/greenhouse-emissions-hit-another-record/story-fn3dxiwe-1227602346053
Although I have tried to avoid following the Paris climate negotiations, it has long been clear to me that there is an extremely basic failure in every climate negotiation since Kyōtō that almost nobody recognises.

This being that most global emissions originate, at root, in the mineral resources of a small number of desert nations, who form a discontinuous rim around the southern and western sides of the Indian Ocean. With the gradual exhaustion of more easily smelted chalcophile mineral resources originating from the younger lands of the remainder of the globe, industry – and most especially high technology – can only become more and more dependent upon these desert Indian Rim countries. Indeed, as oil becomes exhausted and electronic technology more and more important, Australia alone will become more and more exclusively the source of mineral wealth for industry, since the vast majority of important minerals for the electronics sector like sand and lanthanide elements come from Australia,. Among present-day continents Australia is uniquely un-depleted in these elements, and their extreme affinity for oxygen means they concentrate to an extreme extent in ancient continental cratons – the Australian Craton alone has 20 percent of the Earth’s total budget of lanthanide elements.

For various political and geographic reasons, these Indian Rim nations – Australia, New Caledonia, Southern Africa and the Persian Gulf States – have generally the highest per capita greenhouse gas emissions in the world even when indirect emissions are counted elsewhere, with only North America and a few small declining industrial nations comparable:
This map shows the nations with the highest per capita greenhouse gas emissions (note New Caledonia – hard to see here – is one of them and also a major biodiversity hotspot)
Even more critically, most greenhouse emissions and much of the worst pollution from non-Indian Rim nations are dependent upon either:
  1. easily exhaustible and soon-to-be-exhausted deposits of more traditional chalcophile elements like lead, zinc or copper or
  2. fossil fuels or lithophile minerals imported from the desert states of the Indian Rim
Extensive mountain building adds elements normally concentrated in the core and colloquially known as “poor metals” – the lower elements of the boron, carbon, nitrogen and oxygen families along with all of the zinc and copper families – to the continental crust of the Enriched World. Glaciation spreads this enrichment to the more geologically stable Enriched lands located poleward of the Alpine Orogeny. (In fact, the Quaternary appears almost designed to ensure all of the northern hemisphere shares in this “poor metal” enrichment). Although this addition does not come from the core but from the mantle – where these “poor metals” are depleted vis-à-vis solar abundances though to a lesser extent than in Precambrian continental cratons – it is so significant that concentrations of “poor metals” in Enriched World soils are essentially non-overlapping with those in Australian soils.

My brother said that most of Australia‘s greenhouse emissions are the result of China’s industrialisation, but I think he has placed the cart before the horse. The ability to smelt and use abundant lithophile metals with very strong bonds with oxygen and hence enrichment in cratonic crust is the cause of industrialisation in East Asia. Asia industrialised preferentially over Latin America and Africa because of its large and consistently growing comparative disadvantage in agriculture, and its greenhouse pollution is small per capita and largely created from Australian, Southern African and Gulf minerals. For this reason, it is clear to me that China’s and India’s emissions are much more dependent upon Australia than the other way round: Australia could develop its own polluting industry without China or India or Europe so much as existing, but East Asia and Europe without lithophile metallurgy and the “Green Revolution” (a contributing factor to Australian emissions due to permitting even poorer land to be cleared) would lack both adequate raw materials for major manufacturing and the comparative disadvantage in agriculture that encourages its development.

Moreover, even if Australia is extremely unfavourably situated geographically for manufacturing, this could well change if environmental regulations in the Enriched World become tougher and those in Australia do not. There must be a point beyond which lower taxes and fewer regulations would overwhelm Australia’s geographic disadvantages in manufacturing industry, especially since excessive regulation leads to the demographic decline which is already well-advanced in Japan and incipient in the rest of the Enriched and Tropical Worlds – thus overcoming the problem of Australia’s small population.

This is why a mere 26 percent cut in Australian emissions is both inadequate and difficult to maintain in the long term.

The usefulness of per capita emissions is a little arbitrary because of demographic differences and human migration, so that I have felt the need to look for something more genuinely “ecological” as an indication of the sustainable energy consumption of a country. Since soil nutrients determine the quality and amount of energy animal can consume, I feel greenhouse emissions per unit of available soil nutrients (very tough to calculate) Australia would have very limited emissions. Australian soils average an order of magnitude less available phosphorus at the surface than Enriched World soils – and the difference increases with depth – so that per unit of soil fertility Australia’s emissions are certainly much higher than most major European nations (e.g. France, Spain) and incomparably higher than most less-developed nations. This difference is of course much, much more extreme if we consider either:
  1. “poor metal” micronutrients (whose importance to Australia’s ecology has been outlined by Gordon Orians and Antoni Milewski in ‘Ecology of Australia: The Effects of Nutrient-Poor Soils and Intense Fires’)
  2. the large proportion of overseas emissions produced by the use of Australian minerals
and consequently it is clear to me that uniquely large cuts in emissions are needed by Australia and Australia alone to fairly pay the costs of global climate change. In the absence of demands these to be paid by Australia’s polluting industries, we are seeing a rapid escalation of climate change with severe costs for those not responsible.

‘Time’ has knowledge I knew from two decades ago

During my time living at Keilor Downs between 1989 and 1996, perhaps the most memorable incident was when I went to Keilor Downs Plaza to look at the video shop (I was then obsessed with movie ratings and the possibility that violence was due to young children watching violent or rude films – a view I have by no means entirely discarded) and tied as I usually did our pet border collie, Minty, outside the shop.

After a brief stay in the shop – a shop I have no recollection of ever visiting again – I found that Minty had forced the leash loose and had run off. I thought with considerable sense that Minty would go back to our house in Daimler Avenue. When I went back there, my family, including my late uncle and father, said Minty had gone up to the north along Rodney Drive and Belmont Avenue where there were two places I frequently visited. One was a small milk bar, where I often looked at the movie ratings of the VHS tapes in the store as I bought milk. The other was a large reserve at the northern end of Belmont Avenue, where I occasionally played on the swing (and was even then seen as too old for that though I had not put on the vast amount of mass I have now). When I found the playground, Minty had gone and I was very worried.

My assumption was that if Minty had left the park where my family said he had gone, then Minty would have kept walking in the same direction since at the time he had not returned. Thus I kept walking, following my instinct on this line (and my recollections from over two decades ago) up Belmont Avenue and then Copernicus Way, Chichester Drive and up to what was then known to me as Keilor-Melton Road. There was no sign of Minty at the time, and having neither a mobile telephone nor coins for a public phone, I was really worried but I still kept walking, expecting Minty would be somewhere around Calder Park Thunderdome. I never found the dog, and I could not imagine how worried my parents would have been (I had no money and it was the pre-mobile era), but I knew only to keep going and going in hope. By the time I was at Keilor-Melton Road, I did not know whether to walk further north or just keep looking, but there was never a sign of Minty. Eventually, I was so tired I felt I had to walk back home, and I found, to my shock, that Minty had come back soon after I went off looking for him! My mother said he was not a “north-heading dog” as I had naïvely assumed from when she said Minty went after escaping the leash.

Within my family, this story has long been a legend, but the amazing thing is that Time in ‘The Amazing Science Behind Pets That Find Their Way Home’ has shown that the knowledge discovered from this old family incident is widespread. Mummy said to me when I came home very tired that Minty actually knew his way home, and Time’s tale of a dog walking much further than from the park on Belmont Avenue certainly verifies what my mother said to me more than twenty years ago! According to Bonnie Beaver’s research which was quoted in Time, dogs create overlapping scents – which in the case of Minty would no doubt have been acquired while my brother and I walked him to and from the park for a few years before he escaped the leash. No doubt, when Minty escaped the leash he knew where the familiar scent of home was, and went back to that and then to the park on Belmont Avenue.

Wednesday, 18 November 2015

“Bloodworthgrad”, “Lee Ackgrad”: not new ideas

A decade and a half ago, when I became obsessed with Socialist Alternative, Socialist Worker, Militant and Resistance – in the process imagining their membership as comprising a majority of Victoria’s student body rather than merely a tiny number of activists who put posters up everywhere – my brother said consistently that if these Trotskyists came to power they would do the same things that were done in what I then called (and still do as a joke) the ‘Empire of State Capitalist Dictatorship’ (ESCD), ‘State Capitalist Dictatorship of China’ (SCDC), ‘State Capitalist Dictatorship of Korea’ (SCDK) and ‘State Capitalist Satellite of Germany’ (SCSG; German ‘Staatskapitalistischer Satellit Deutschlands’ or ‘S.K.S.D.’). In particular, my brother once spoke of the “Democratic People’s Republic of Australia” and that all Australia’s major cities would be renamed as they were in the Russian empire after the leaders of the revolution like “Bloodworthgrad”, “Lee Ackgrad”, “Bloodworthsk” and so on. (He admitted though that such names would be tongue-twisting to pronounce).

The Trotskyist groups themselves deny this would happen and that with workers controlling the system through workers’ councils under genuine socialism this would not happen unless it was voted for. They believe that all Russia’s place name changes came after Stalin began his counterrevolution and are not a part of true socialism with workers owning the means of production. With age, I have become very sceptical of claims that the violent class struggle and workers’ militia advocated by groups like Socialist Alternative could produce the utopia of equality, abundance and sustainability they claim, but still their ideas are interesting.

A couple of days ago, in a marginally curious mood, I looked in the State Library and found a seemingly interesting book titled Women of the Far Right: the Mothers’ Movement and World War II by one Glen Jeansonne. I retrieved it immediately, although I did not read it until yesterday, but when I had a good look it seemed both interesting and repetitive. Repetitive because it showed these conservative women attacking not only FDR, but also his first Lady Eleanor Roosevelt for being too modern or masculine. Interesting because it showed up many new facts – for instance that Henry Ford was targeted by both the Democrats and Republicans for the 1924 Presidential election!

The most startling thing I have found in a partial read of Jeansonne’s book, however, was quite startling both as a fact and as a memory. It was that when right-wing “Mother’s Movement” activist Elizabeth Dilling went to Russia, she was not only horrified at the shortages of basic goods and the doctrinaire atheism, but also discovered maps where major cities in the US (which were not mentioned in the book) were renamed after Stalinist heroes – exactly like my brother joked would happen if Trotskyists took over in Australia.

It is surprising that no anti-Communist has ever widely publicised this – let alone reveal exactly what names Stalinists would have given major American cities had they become able to execute their plan. If they could have done this, it would be interesting to imagine the response of affected Americans. Would they have been much more appalled than my brother – who took the story as a joke although he still held dogmatically to the idea that a revolution in an advanced or especially in a resource-super-rich nation would have the same result as in more primitive Russia, China, Yugoslavia and Cuba.

Another fact untold by historians found in Women of the Far Right is that opposition to the Vietnam War through wanting the Vietcong to win had a precedent. Numerous anti-Communist and/or anti-Semitic parties during the 1930s and before Pearl Harbor opposed World War II because they wanted the Nazis to win – a story which neither the PIGs nor standard textbooks nor the Trotskyists tells today’s children. Most of the people in Jeansomme’s book fall into this category, and for this reason the book gives a lot of insight as to why the US, Canada and New Zealand did so little to accept Jewish refugees from Europe – only the marginal Trotskyists wanted to remove all restrictions on Jewish immigration and thus prevent the Holocaust, and FDR turned back many Jews to their death (Canada and New Zealand were vastly worse still).

These days, findings so unexpected as the story of Elizabeth Dilling are rare enough to be more shocking than when I first read Socialist Alternative and seemingly discovered that what I was taught about socialism and capitalism in schools was wrong, or the reverse finding from reading Hans Hoppe or Murray Rothbard.

Sunday, 8 November 2015

Monthly and seasonal EWP versus CET graphs: January to June plus fiscal year

In the previous post I had a look at CET versus EWP correlations for the first half the fiscal year (the second half of the calendar year). I will now look at the second half of the fiscal year (first half of the calendar year) to see how the patterns evolve, and as a last step I will see what the results are for the fiscal year as a whole.

January:

As can be seen, a general positive correlation between EWP and CET is evident in January, as in December and November. Outliers from the general pattern of warm, wet Januaries with maritime flow contrasting with cold, dry ones characterised by easterly winds from the continent do occur, but are less distinctive than those for December.

The most notable “cold-wet” outlier is January 1809, with CET of 2.0˚C, estimated Scotland temperature of -1.1˚C, estimated UK mean temperature of 0.9˚C, yet EWP of 134.3 millimetres. There exist other moderate “cold-wet” outliers (forming a semicircle between 100 and 110 millimetres and from 0˚ to 2˚C) in Januaries 1768, 1774, 1789, 1867, 1895, 1942, 1959, along with January 1979 – the coldest month over the contiguous US since before 1880, but very hot in southern Australia due to a super-monsoon and warm in the Far East:
If not to nearly the same extent as December 1886, Januaries 1895 and 1979 were both sunnier than average except in eastern coastal areas. In the southwest Torquay exceeded ninety hours in both months, and was only ten hours shy of the UK record for January in 1979. January 1942, however, was rather gloomy, with only 37 hours sunshine in England and Wales against a virgin mean of 47.7 hours – although 11 Januaries since 1929 have been gloomier. January 1959, however, resembles December 1886 very closely in setting sunshine records, and data from Durham and reports from elsewhere suggest January 1959 is very likely the sunniest since before 1881.

The “warm-dry” outliers of 1898 and 1916 are distinctly different. 1916 was the mildest January on record (though in between a very cold November and snowy, dull March) but was probably the UK’s windiest month since 1871 with gales on 25 days – some destructive even when no rain fell. 1898 was a classic anticyclonic gloom month with little sunshine, but the red diamonds in the upper left (1989, 2005) were ten to fifteen hours sunnier than the mean, and the “winterless winter” of 1948/1949 was extremely sunny.

February:

February shows the familiar pattern from the other winter months of warm, wet, westerly “maritime” months contrasting with cold, dry, easterly “continental” months. Outliers to this pattern are concentrated exclusively in the top left “warm-dry” section of the scatter plot:
  • record warm February 1779 with CET 7.9˚C and EWP of 13.5 millimetres
  • February 1998 with CET 7.3˚C and EWP of 20.4 millimetres
  • February 1790 with CET 6.6˚C and EWP of 20.9 millimetres
  • February 1903 with CET 7.1˚C and EWP of 38.8 millimetres
  • February 1846 with CET 6.4˚C and EWP of 37.1 millimetres
  • February 1815 with CET 6.5˚C and EWP of 44.0 millimetres
The lack of “cold-wet” outliers like January 1809 or December 1886 is highly notable. It is true that February 1900 (CET 2.6˚C; EWP 131 millimetres) was much colder in Scotland than in England, but February 1900 was 2.0˚C warmer than January 1809 at both Edinburgh and Gordon Castle, and not as cold in southern Britain.
Moreover, as can be seen from this precipitation map for the record cold February 1947, these “cold-wet” outliers are only so in the east. Often these supposed outliers are very dry on western slopes which, normally exposed to the westerly winds, are left in a rain shadow (more accurately a snow shadow) that is much stronger than the normall westerly rain shadow on the eatern slopes of temperate zone mountains. The then-record cold “Crimean Winter” February of 1855 was the driest – indeed the driest for any month – between 1845 and 1894 at notoriously wet Seathwaite in the Lakes District, with less than half an inch of water-equivalent precipitation or less than a third the average water equivalent precipitation for all of England and Wales.

Winter:

As can be seen, the winter graph shows a positive correlation between EWP and CET already explained for the individual months and not significantly altered by greenhouse pollution from Australian road transport and coal power. In complete contrast to the February plot, the most notable outliers are of the “cold-wet” type, most notably:
  • 1878/1879 (fourth coldest since 1766; CET 0.62˚C; EWP 250.0 millimetres)
  • 1978/1979 (red diamond; CET 1.58˚C; EWP 335.2 millimetres one of only four winters since 1910 drier in Scotland)
  • 1914/1915 (marginal outlier; CET 4.33˚C; EWP a then-record 423.0 millimetres)
“Warm-dry” outliers are not so pronounced, and include
  • the amazing winter of 1778/1779 (record warm February is earliest surviving record warm month and MSLP was over 1,030 millibars)
  • the second-driest winter in 1857/1858 (as noted earlier, December 1857 was warmer than 1934 or 1974 in Scotland and probably the UK as a whole, whilst its MSLP was comparable to February 1779)
  • the winter of 1988/1989 with CET of 6.52˚C and EWP only 185.5 millimetres. In contrast to December 1857, this winter was warm all though central and northern Eurasia due to a highly positive NAO index

March:

With March, I have noted with yellow diamonds the several very snowy Marches that occurred around a century ago during World War I. These were particularly disruptive in the emergency with cold delaying opening of the growing season in 1917, and causing human disruption during the snowy March 1916 – apart from 1947 the worst March of the twentieth century. That March 1916 and 1919 were exceptionally cold and wet is very clear from this graph.

It is extremely evident that the positive correlation seen for the previous four months has completely disappeared, and that the line looks exceptionally flat, with “outliers” being either warm (1938 and 1957), cold (1785) or wet (1947 and 1981).

It’s possible that the true shape of this curve is a triangle – one sees much more CET ranges in dry Marches (both March 1785 and March 1938 had EWP of under 20 millimetres and March-April EWP under 30 millimetres) – than in most wet Marches, though the two EWP outliers in 1947 and 1981 make claims of a “triangular”-shaped scatter plot look dubious and we can assume that in March EWP and CET show little correlation.

If we look at the red diamonds controlled by Australian greenhouse gas emissions, the conclusion is not really different. Despite the clear presence of several Marches (1990, 1997, 2011) that were both warm and very dry, the silver diamonds in the top left corner (1779, 1938 and 1961) and several cool, wet Marches during the 1970s and early 1980s suggest no fundamental change. However, before 1884 very cold, dry, easterly Marches occurred as not observed since in 1785, 1786, 1807, 1808, 1845 and 1883. Nevertheless, warm, wet, westerly Marches (1903, 1912, 1981) were not observed to oppose them as would be expected if the EWP/CET relationship had changed.

April:

As we can see, for April the EWP versus CET relationship is again negative – as it was from July to September. The line of best fit is less steep than for July and August, but nonetheless not flat like for March.

There exit numerous red diamonds in outlying parts of this graph – both hot and wet. Nevertheless, because the extreme hot outliers of 2007 and 2011 were both exceedingly dry, it is not likely that man-made global warming had altered the shape of the graph at all.

The “cold-dry” outliers of 1837 (coldest April on record) and 1771 (EWP 31.3 millimetes, CET 5.5˚C) are more striking than the “warm-wet” ones of 1792 and 1961 (CETs both 10.0˚C, EWPs 97.7 millimetres in 1792 and 98.1 millimetres in 1961) – the latter being the wettest April on record in southwestern Australia, which has seen huge rainfall declines due to its own greenhouse emissions.

May:

In May we see a clear negative correlation between EWP and CET, as observed in the summer months in our first set of scatter plots. The most striking outlier is the “hot-wet”, non-anthropogenic May 1811 with CET of 12.8˚C but a very wet EWP of 121.9 millimetres – the eighth-wettest on record and one of only four cases where May was the wettest month of the calendar year (the others being 1773, 1820 and 1983). The striking character of 1811 – a cool summer, two cold winters but very hot spring and autumn – is noted in Kirkpatrick Sale’s Rebels Against the Future: The Luddites and Their War on the Industrial Revolution – Lessons for the Computer Age.

The prime “cool-dry” outlier of 1876 (EWP 23.6 millimetres; CET 9.6˚C) featured two very cold days at the beginning but was the beginning of the summer when W.G. Grace hit the first two first-class triple centuries. From the context of a warming world, May 1991 – the third-driest on record but with CET 0.4˚C below the virgin mean of approximately 11.2˚C – is also notable although it was obviously a similar but more eastward Atlantic block to September 1986 which I discussed before.

Spring:

As we would expect, in the spring season over the UK, hotter seasons tend to be drier. It’s notable that here one sees the shift brought about by Australian greenhouse gas emissions much more as the diamonds on the upper right (hot and wet) are almost all red.

In contrast to the numerous moderate “warm-wet” ouliers brought about by man-made global warming, there are two exceedingly marked “cold-dry” outliers from before 1974: the record-cold spring of 1837, which was 0.92˚C colder than the winter of 1833/1834, and the record-dry spring of 1785, the core of easily the driest fiscal year since 1750.
Spring seasonMarch EWPAnomalyApril EWPAnomalyMay EWPAnomalyMarch CETMarch CET AnomalyApril CETApril CET anomalyMay CETMay CET anomaly
178518.8 mm-40.0 mm10.1 mm-48.3 mm25.9 mm-38.4 mm1.2˚C-4.1˚C8.4˚C+0.4˚C12.3˚C+1.1˚C
183730.4 mm-28.4 mm50.4 mm-8.0 mm36.7 mm-27.6 mm2.3˚C-3.0˚C4.7˚C-3.3˚C9.9˚C-1.3˚C

June:

For June, the slope of the EWP versus CET graph is strongly negative, as for all the summer months. Despite two major “hot-wet” outliers since 1974 in 1982 and 2007, there is not the concentration of red diamonds in the upper right that we saw for the spring season. The major “cool-dry” outlier is the foggy, obviously northerly and blocked June 1923, which was very cool over Europe and uniquely wet in Australia, where the Mallee received up to five times its normal rainfall. June 1923 clearly had a large Arctic block causing hot weather in Canada as well as the cool in Europe:
It’s notable that in both May 1991 and June 1923 Scotland was less cool than southern England, no doubt because it was nearer the centre of the block and less exposed to Arctic airflows.

Fiscal Year (July to June):

Although I have not yet calculated the Spearman and Pearson correlation coefficients, the full fiscal year EWP versus CET scatter plot suggest that the positive correlations between November and February outweigh the negative correlations we observe from April to September.

It is possible, though I have not checked, that the choice of the fiscal year over other possible twelve-month ranges affects the result by dividing over two years extreme hot and dry summers like 1826, 1868, 1911, 1921 and 1976. Such dry years as 1826 and 1921 were in fact hot as a whole, despite the association of dryness with cold during the winter, the quintessential “continental” year of 1780 was only 0.11˚ cooler than the 1766 to 1974 average despite an extremely cold January, and 1947 with its long, hot summer was 0.61˚C hotter despite its record cold February.

Compared to the individual months, outliers are more numerous for the whole fiscal year. The very cold year of 1813/1814 and the very dry year of 1784/1785, as well as the very wet anthropogenic years of 2000/2001, 2006/2007 and 2013/2014, especially stand out. The hot, dry anthropogenic years of 1975/1976 and 1991/1992 are also marked outliers, as is the extreme “cold-wet” outlier of 1878/1879, where a CET of 7.30˚C was recorded for the twelve months ending October 1879.

Monthly and seasonal EWP versus CET graphs: July to December

Over the past few months, having studied the EWP and CET series that first interested me about fifteen years ago as a result of my long-term study of old county cricket, I have wanted to be able to plot EWP against CET to see patterns I first noted a year or so ago. These relate to the fact that because easterly continental air over the UK tends to have much greater seasonal variation in temperature, and to be much driest at all seasons, the relationship between rainfall and temperature over the UK is opposite in summer and winter: dry months tend to be hotter-than-normal in summer, but colder-than-normal in winter especially over western slopes.

In these next two posts I will give detailed plots of EWP versus CET for all months and seasons, and for the fiscal year from July to June, consequently updating details to October 2015, a month whose warmth shows Australian greenhouse gas emissions to be taking even firmer control of the climate. I will do them from July to June rather than by the calendar year, since owing to the greater variance in temperature during the northern hemisphere winter the problem of unusually cold or warm seasons being divided between two years is thereby minimised.

I originally intended one post, but will do the first half of the fiscal year in this post and then do January to June and a full fiscal year EWP versus CET graph later.

Graphs are done at intervals of 0.25˚C for the hotter half of the year from April to September and  0.5˚C for the cooler half from October to March to deal with larger mean temperature variance.

To clearly distinguish natural variability I will colour in a dark red all data points beyond 1974 when it became clear man-made greenhouse pollution was controlling the climate, a trend that intensified after the botched Kyōtō Protocol – whose absolutely first priority should have been an absolute and uncompromising zero-emissions target for Australia (both the most infertile and oldest continent, a feature that ought to demand exceedingly low per capita emissions, and the worst per-capita polluter) before any reductions in Europe, East Asia or the Americas were contemplated – untenably allowed the worst polluter the most lenient increase!

July:


As we can see from this scatter plot, in July there is a general trend for drier months to be hotter-than-average. The effects of anthropogenic greenhouse pollution upon these trends is not large, since the red diamonds follow a similar type of pattern to the white ones, only the lower part (very cool Julys) is largely or completely absent.

The major outliers are the “hot-wet” Julys of 1779, 1828 and 1834, and the “cool-dry” Julys of 1913 (EWP 32.6 millimetres; CET 14.6˚C) and 1919 (EWP 57.9 millimetres; CET 13.9˚C). July 1919 was extremely dry in Northern Ireland – it is among the top twenty driest months there since 1910 – and clearly possessed a very striking block over Iceland. This Iceland block drew Arctic air over the UK, which was cooler than normal, but produced conditions settled enough for the UK to be unusually dry except in the east which was on the western side of a low pressure anomaly and most exposed to Arctic air:
July 1913 was a rare summer anticyclonic gloom month, hotter than average in northern Scandinavia but very cool in central continental Europe, and with sunshine not much better than the notorious summer of 1912.

August:

This graph is essentially similar to the one for July. We again see a tendency for hot Augusts to be dry, with that of 1995 hotter and drier than any before Australian greenhouse emissions began to control the climate (and perhaps along with the infamously cold but virtually snowless February 1895 the most purely “continental” month over the UK since 1766).

The notoriously cold and sunless August 1912 is an outlier at the opposite end – it was certainly duller than February 1891, 1907, 1949 or 2008, and possibly duller than Februaries 1887 and 1895 – whilst the anthropogenic August 2004 is a “hot-wet” outlier, as is the extremely hot and thundery August 1997, which actually had a strong pre-anthropogenic parallel in July 1808, a month well-known by historians for its violent thunderstorms and large hail.

Summer:

The summer scatter plot shows essentially the same trends as the July and August plots. The very hot and dry summers of 1976 and 1995 – though already distant as Australian mining and coal control of the climate intensifies – stand out very clearly, as does the hot, dry summer of 1826 when many wells dried up, an occurrence that similar dry summers since like 1870, 1921, 1933 and 1976 did not see.

If anything there are fewer outliers that for the individual summer months, with no real “hot-wet” outlier since Australian greenhouse emissions seized control of the global climate. The main outliers are the “cool-dry” summers of 1972 (EWP 160.3 millimetres; CET 14.19˚C), the above-mentioned 1913 (EWP 114.4 millimetres; CET 14.70˚C) and 1864 (EWP 118.1 millimetres; CET 14.44˚C). 1913 was notable for the worst Sahel drought between 1870 and 1970, and no doubt the midlatitude westerlies were pushed south allowing lower-than-normal pressure over Europe and a persistent block over the north Atlantic.
Temperature anomaly relative to virgin mean for northern summer of 1913. Note that the hot anomaly over West Africa reflects the worst drought (weakest monsoon) over that region during the base period.

September:

Here, we see the inverse correlation between England and Wales Precipitation and Central England Temperature of the hotter months weakening a little. The most notable case of this is the blocked northerly September 1986, which was extremely dry yet very cool. During September 1986 England had such lovely weather – sunny and a perfect 15˚C most days – one wonders why Englishmen moan about their weather until you realise it’s precisely because 90 percent of the world must have worse weather than England, with the result that English people either find the weather boring or are less tolerant of really bad weather! September 1986 is in many respects very similar to the more famous and very cold February of that year – completely blocked and also very wet over the United States.
US precipitation plus US and global temperature (GISS and NOAA) anomalies for February and September 1986. Note the similar cold across Western Europe and the extreme wet over the contiguous US

October:

Here were see a transition to the winter season, as the line of best fit between EWP and CET is very nearly horizontal at CET of about 10˚C. The preponderance of red diamonds near the top shows the influence of Australian greenhouse gas emissions at its peak in the autumn when CO2 and other greenhouse gases are holding heat from the summer sun to the greatest extent.

It might be thought potentially possible in this transitional month that the red diamonds (largely controlled by man-made global warming) would follow a different pattern from the white diamonds largely controlled by natural climatic variability. This does not really seem to be the case on first glance, and even on a brief statistical examination I did not find anything to suggest that there had been a major change since 1974 in either Spearman’s ρ or Pearson’s r.

November:

Here we see that the relationship between EWP and CET has completely reversed from July, August and September. The line of best fit clearly has a positive gradient indicating that warmer Novembers tend to be wetter rather than drier. The record warm Novembers of 1994 (CET 10.1˚C; CEMaxT 12.5˚C) and 2011 (9.6˚C) may not be “warm-dry” outliers since they are so influenced by artificial greenhouse emissions. The record dry November 1945 is definitely a “warm-dry” outlier, although only marginally hotter than the anthropogenically-controlled 1981 to 2010 average:
Novembers 1770 (200.8 mm and CET 5.4˚C), 1910 (128 mm and CET 3.2˚C) and 1807 (115.5 mm and CET 2.9˚C) are “cold-wet” outliers but not extreme, especially the exceedingly wet November 1770 where sample size is so small.

A striking feature is that the “cold-wet” outlier November 1910 was very sunny – possibly the sunniest of the century over the UK with 93 hours over Durham – yet the “warm-dry” outlier 1945 was distinctly dull with only 42 hours of sunshine over England and Wales (virgin mean around 60 hours). This apparent contradiction is not actually even rare, as we will see when discussing December.

Autumn:

The autumn graph shows few startling features, apart from the extreme preponderance of red diamonds near the top of the graph, as it is in this season where the influence of Australian mineral and road pollution is most apparent.

In addition to the hot autumns of 2011, 2006 and 2014, the record wet autumn of 2000 and the record dry autumn of 1978 are also anthropogenic outliers, whilst the record cool autumn 1786 is a natural outlier nearly equalled in 1740 and 1676.

December:

We can see here for December that the positive slope of the line of best fit is more intense than for November, although there are a number of outliers which I will discuss in some detail.

The “warm-dry” outliers are:
  • 1842 (EWP 50.9 millimetres; CET 7.2˚C)
  • 1843 (EWP 18.2 millimetres; CET 7.4˚C)
  • 1857 (EWP 31.0 millimetres; CET 7.3˚C)
    • across the UK as a whole, these last two Decembers may in fact have been warmer than 1934 or 1974, since data suggest Scotland was much more exceptionally warm than central England
  • 1953 (EWP 34.5 millimetres; CET 6.9˚C)
  • 1971 (EWP 37.6 millimetres; CET 6.6˚C)
  • 1988 (EWP 45.7 millimetres; CET 7.5˚C)
It’s notable that, despite being warm and dry which would suggest clear skies and un-wintry conditions, December 1971 was in fact very gloomy with a mere 29.9 hours sunshine over England and Wales, whilst December 1953 was only marginally less gloomy at 32.1 hours sunshine and December 1988 had only 38.4 hours. The median sunshine for England and Wales from 1929 to 1996 was 42.2 hours. The reason for this apparent contradiction of mild, dry months being even gloomier than usual for the UK is “anticyclonic gloom”, whereby persistent anticyclonic control and still conditions – which can be either cold or warm depending on where the airmass originated – lead to dry weather with persistent fog that the weak sun in the UK winter has no hope of lifting. In the past, though not today, anticyclonic gloom could occur in southern Australia, notably in May 1932 which had only 81.1 hours sunshine over Melbourne (average about 134 hours) despite being Victoria’s second-driest May since 1885.

The “cold-wet outliers” are:
  • 1874 (EWP 96.6 millimetres; CET -0.2˚C)
  • 1886 (EWP 145.2 millimetres; CET 1.9˚C)
  • 1981 (EWP 93.3 millimetes; CET 0.3˚C)
It’s amazing, though understandable when one realises how much anticyclonic gloom is the limiting factor on UK sunshine, that the very snowy December 1886 had, according to all available data, much more sunshine over the UK than any December since:
As can be seen, December 1886 was far sunnier than any other December over Durham, with half an hour per day more than the next sunniest (1926). Since December 1886 was a distinctly cold month (CET 1.9˚C; Scotland estimated 0.3˚C; Northern Ireland estimated 2.0˚C) and Durham is on an easterly slope, one would expect with easterly winds an even greater sunshine excess on western slopes, so it seem probable to me than December 1886 would have had over 80 hours UK sunshine, which is more than any November or January since 1881. Figures in the less gloomy southwest would have been logically even higher, and possibly higher than 90 hours with some totals (unrecorded) over 100 – in a month with the lowest pressure recorded in the UK and some of the heaviest snowfall.

The reason such a cold, snowy month was at the same time so abnormally sunny is actually relatively easy to understand: that the disturbed nature of the atmosphere eliminated anticyclonic gloom and allowed the sky to complete clear even during short fine spells. This is quite unlike December 1953 or 1971 or 1988, where stable air and lack of wind meant low cloud never dissipated.

Even December 1981 was no gloomier than the average, whilst very limited reports on 1874 are uncertain. However, the snow-drenched but bright December 1886 is no isolated case: November 1910 (noted above) and January 1959 (second part) were similarly snowy yet exceptionally sunny, and many other cold months were also much sunnier than usual.