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Many Climate Reconstructions Incorrectly Attributed to Temperature Change

Written by Dr Tim Ball, Climatologist


The Intergovernmental Panel on Climate Change (IPCC) set climate research back thirty years, mostly by focusing world attention on CO2 and higher temperature. It was a classic misdirection that required planning. The IPCC was created for this purpose and pursued it relentlessly. Through the World Meteorological Organization (WMO) they controlled national weather offices so global climate policies and research funding were similarly directed.

IPCC’s definition of climate change narrowed the focus to human causes, but they exacerbated it by ignoring, downgrading or misusing variables. Most important and critical was water in all its forms and functions. The obsession restricted focus to higher temperatures and increased CO2, which directed funding of impact analyses, whether economic or environmental to cost only, instead of cost/benefit. Climate studies only considered temperature, usually and incorrectly attributing changes caused by precipitation to temperature. This practice was most evident in paleoclimate reconstructions, either done by IPCC participants or chosen for inclusion in the IPCC Reports.

It is almost a maxim that if the people at the Climatic Research Unit (CRU), who effectively controlled IPCC science, were looking at a topic it was because it posed a threat to their predetermined hypothesis.

Tom Wigley took over from Hubert Lamb as Director of the CRU and guided much of the early research and then remained the major influence as the leaked emails revealed. He completely redirected CRU from Lamb’s objective, which was the need for data before any understanding could occur;

“the first and greatest need was to establish the facts of the past record of the natural climate in times before any side effects of human activities could well be important.”

Lamb was at odds with and appears to regret hiring Wigley and wrote about the different direction Wigley took the Unit. He wrote,

“Professor Tom Wigley, was chiefly interested in the prospect of world climates being changed as a result of human activities, primarily through the burning of wood, coal, oil and gas reserves…”

That became the focus of the CRU and subsequently of the IPCC. It was a predetermined hypothesis that led to manipulated climate science. The leaked CRU emails disclose Wigley as the eminence gris to whom all his old pupils and colleagues at CRU turn to for advice and direction.

A classic danger in climate research and an early threat to claims of a human signal was that they could be dismissed as a result of auto-correlation. The issue was identified in 1944 in Conrad’s classic Methods in Climatology. A 1999 article The Autocorrelation Function and Human Influences on Climate by Tsonis and Elsner commented on Wigley’s attempt to prove a human influence was not due to autocorrelation.

They note,


This (Wigley’s) result is impressive, and there may indeed be a human influence on climate. However, the use of the autocorrelation function as a tool for such comparisons presents a problem. Climate models, whether forced or unforced, constitute dynamical systems. If these models faithfully represent the dynamics of the climate system, then a comparison between an observation and a model simulation should address whether or not these two results have the same dynamical foundation.

In Quantitative approaches in climate change ecology Brown et al., identify the issues.

We provide a list of issues that need to be addressed to make inferences more defensible, including the consideration of (i) data limitations and the comparability of data sets; (ii) alternative mechanisms for change; (iii) appropriate response variables; (iv) a suitable model for the process under study; (v) temporal autocorrelation; (vi) spatial autocorrelation and patterns; and (vii) the reporting of rates of change. While the focus of our review was marine studies, these suggestions are equally applicable to terrestrial studies. Consideration of these suggestions will help advance global knowledge of climate impacts and understanding of the processes driving ecological change.

The two lead items in Brown et als list for resolving problems of auto-correlation are also central to understanding the corruption and misdirection of the IPCC.

(i) data limitations.

As Lamb identified, lack of data was and remains the most serious limitation. The situation is completely inadequate for temperature, supposedly the best measured variable. How can two major agencies HadCRUT and GISS produce such different results,temp anomalies

supposedly from the same data set? Paul Homewood produced the following Table comparing results for four data sources for the period 2002 to 2011.

GISS and UAH differ by 0.36°C, which is enormous in nine years. Compare it to the 0.6°C increase over 140 years, a change the 2001 IPCC claimed was dramatic and unnatural.

Data is even worse spatially and temporally for water in all its forms, especially precipitation. In a classic understatement the 2007 IPCC Report says,

Difficulties in the measurement of precipitation remain an area of concern in quantifying the extent to which global- and regional-scale precipitation has changed.

They also concede that,

For models to simulate accurately the seasonally varying pattern of precipitation, they must correctly simulate a number of processes (e.g., evapotranspiration, condensation, transport) that are difficult to evaluate at a global scale.

The lack of data is worse than temperature and precipitation for all other weather variables. There is insufficient data to determine inferences of auto-correlation.

(ii) alternative mechanisms for change.

Ability to determine mechanisms and their implications is impossible without adequate data. Besides, we don’t understand most mechanisms now so considering alternatives is difficult. Many mechanisms are identified but there are many more still unknown. Donald Rumsfeld’s quote is appropriate.

“… there are known knowns; there are things we know that we know. There are known unknowns; that is to say, there are things that we now know we don’t know. But there are also unknown unknowns – there are things we do not know we don’t know.”

Contradiction between results from different authorities, such as the temperature data, proves the point. The IPCC bypassed the problems with a limited definition that allowed them to ignore most mechanisms. Often the excuse was quite bizarre, such as this from Chapter 8 of the 2007 report.

Due to the computational cost associated with the requirement of a well-resolved stratosphere, the models employed for the current assessment do not generally include the QBO.

IPCC did what Einstein warned against. Everything should be made as simple as possible, but not simpler.

Beyond Auto-correlation?

Autocorrelation is a danger in climatology but what has happened in IPCC goes beyond. In major reconstructions of past climates, temperature series are created from data and processes that are primarily due to precipitation.


Many of them began as chronologic reconstructions. Tree rings began as dendrochronology; an absolute dating method that assumed a new ring is created every year. Age of the Bristlecone Pine made them valuable for this purpose at least. A. E. Douglass founded the discipline of dendrochronology in 1894 and later used tree ring to reconstruct solar cycles and precipitation; the latter became the purpose of all early climate reconstructions.

Available moisture explains most plant growth as farmers and gardeners know. Koppen recognized this in his climate classification system that required classification first on precipitation (B Climate) then on temperature (A,C, and D Climates).

Gross misuse of tree rings to argue the Medieval Warm Period (MWP) didn’t exist was exposed because of inappropriate statistical manipulation. The conclusion used in the 2001 IPCC Science Report claimed the tree rings (the effect) showed no increase in temperature (the cause). In reality with climate change there is a change in all weather variables, hence the auto-correlation problem.

The degree of change to each variable is a function of the latitude as major weather mechanisms migrate toward or away from the poles. For example, during the Ice Ages the Polar climate region expanded primarily at the expense of the middle and low latitude climates, particularly in the desert zone, approximately between 15 and 30° latitude. The low latitude deserts become wet regions in what was traditionally called Pluvials. In the early days it was thought there was no evidence of the Ice Age in the tropical region associated with the Hadley Cell circulation.

Moisture is a controlling factor even in harsh temperature conditions at the tree line. Research at Churchill, Manitoba showed the major predictors of growth were rainfall in the Fall of the preceding year and winter snow amount.

The spruce tree in the photo (Figure 1) is at the tree line at Churchill. It is approximately 100 years old. The lower branches are larger and are on all sides because they are protected from desiccating winter winds by snow; above that powerful persistent arid northeast winds prevent branches growing. Local humor says you cut three trees and tie them together for a complete Christmas tree.

Tree growth, especially annual, is primarily about moisture not temperature. The amount of moisture required by the plant and the amount available both vary with wind speed. At the tree line the ability to trap snow is critical to survival. Small clumps or outliers exist beyond the tree limit as long as they trap snow. Similarly, an open area within the tree limit will remain treeless if denuded of snow by the wind.

spruce tree

Speleology (Stalactites/ Stalagmites)

Stalactites (ceiling) and stalagmites (ground) are another example of precipitation created features claimed to represent temperature. They are created by rainwater, which is a mild carbonic acid because of dissolved atmospheric CO2 that absorbs calcium as it filters through limestone. As the water drips from the ceiling calcium deposits accumulate to create the stalactite. Where it hits the floor more calcium accumulates to create a stalagmite. Growth of both features is a direct result of changes in precipitation at the surface.

Glacial Stratigraphy and Ice Cores

Seasonal or annual records in stratigraphic form are collectively called rhythmites. An early use of rhythmites in climate reconstruction was a specific form called varves and related to annual sedimentary layers in proglacial lakes. In 1910 Swedish scientist Gerard de Geer provided an important chronology for glacial sequences of the Holocene. The thickness of the sediment layer is a result of temperature, but also how much rain fell during the summer that changed the melt rate of the snow and ice.

Seasonal layers in a glacier often reflect temperature change, but are also modified by precipitation. Glacier movement is used as a measure of temperature change, but it is also about precipitation change. Thickness of each layer varies with the amount of snow. (Yes, droughts also occur in winter). When sufficient layers form to about 50 m depth the ice becomes plastic under pressure and flows. Ice is always flowing toward the snout within the glacier. Amount of advance or retreat of the glacier snout is as much about snow accumulation above the permanent snowline as temperature. A snout can advance or retreat without a change in temperature.

Meltwater from a glacier is a function of temperature, but also precipitation. When rain falls on the glacier it increases the melt rate of snow and ice dramatically. This is likely a major explanation for the rapid melt and vast proglacial lakes associated with melt of the ice during the Holocene Optimum. Dynamics of a continental glacier are a slow build up as snow layers accumulate, followed by a relatively rapid melt as snow turns to rain.

The amount of CO2 in the ice crystals varies with the temperature of the water droplet and raindrop, just as seawater CO2 capacity varies. This means glacier meltwater has a higher concentration of CO2 and as it trickles down through the ice layers modifies the ice bubbles as Jaworowski explained in his presentation to the US Senate Committee (March 2004).

This is because the ice cores do not fulfill the essential closed system criteria. One of them is a lack of liquid water in ice, which could dramatically change the chemical composition the air bubbles trapped between the ice crystals. This criterion, is not met, as even the coldest Antarctic ice (down to -73°C) contains liquid water[2]. More than 20 physico-chemical processes, mostly related to the presence of liquid water, contribute to the alteration of the original chemical composition of the air inclusions in polar ice[3].

IPCC maintained focus on the Carbon Cycle, but the Water Cycle is more important, especially as it relates to the dynamics of change. Put a dehydrated rock in a chamber and vary the temperature as much as possible and little happens. Add a few drops of water and the breakdown (weathering) of the rock is dramatic. Any climate experiment or research that excludes water, such as the list of greenhouse gases in dry air, is meaningless. Water exists everywhere on the planet.

Precipitation occurs over the oceans but we have virtually no measures so we cannot determine the diluting effect on the salinity and gaseous content of the critical surface layer. How much does precipitation as a 10 percent carbonic acid solution affect the CO2 measures of that layer? Snowmelt has a higher percentage of CO2 concentration.

Wind speed and direction are major determinant of water distribution in the atmosphere and therefore across the world. It alters the impact of temperature, as we know from wind chill or heat index measures. What is the effect of a small increase in regional, hemispheric or global wind speed on the weather and climate?

Atmospheric pressure varies with temperature that determines the weight of the atmosphere pushing on the surface. How much do these changes affect sea level? We know it is considerable because of storm surges that accompany intense low-pressure systems.

The list of variables unmeasured, unknown or excluded from official IPCC science invalidates their models and their claims. Water in all its forms and functions is the most egregious. It also illustrates the degree of auto-correlation confronting climate research and understanding. It appears Wigley and therefore the IPCC knew of the problems but chose to sidestep them by carefully directing the focus – a scientific sleight of hand.


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    Peter Foster


    Two comments:
    Are you aware of Wakefield’s study of temperatures in Ontario over about 80 years. The daily averages of max and min, showed a steady increase. But when the compnnents were analysed, the min figures showed a steady increase, but the max figures showed constant or a slight decreease. Can model repocate that behaviour? And I wonder how general it is?
    On correlation being misapplied as cause-and-effect, the best demolition I have read is that an analysis of San Francisco fires showed that the greater the number of appliances present, the greater the damage!!!!

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