Hammering Global Warming Into Line

Global temp and IPO graph

In my post of 18 Sep 2014 “The record of the IPO”, I showed a graph of the Inter-decadal Pacific Oscillation,plotted as a cumulative sum of anomalies (CUSUM).

Log from 1850 of world surface air temperature and carbon emissionsThis CUSUM plot has a shape that makes it seem that it could be used to straighten the dog-leg (zig-zag) trace of global temperature that we see. A straighter trace of global warming would support the claim that a log-linear growth in carbon dioxide emissions is the main cause of the warming.

My attempt to straighten the trace depends on the surmise (or conjecture) that the angles in the global temperature record are caused by the angles in the IPO CUSUM record. That is, the climatic shifts that appear in the two records are the same shifts.
I have adopted an extremely simple model to link the records:
1. Any global temperature changes due to the Inter-decadal Pacific Oscillation are directly proportional to the anomaly. (See Note 1.);
2. Temperature changes driven by the IPO are cumulative in this time-frame.

To convert IPO CUSUM values to temperature anomalies in degrees, they must be re-scaled. By trial and error, I found that dividing the values by 160 would straighten most of the trace – the part from 1909 to 2008. (See Note 2.) The first graph shows (i) the actual HadCRUT4 smoothed global temperature trace, (ii) the re-scaled IPO CUSUM trace, and (iii) a model global temperature trace with the supposed cumulative effect of the IPO subtracted.


The second graph compares the actual and model temperature traces. I note, in a text-box, that the cooling trend of the actual trace from 1943 to 1975 has been eliminated by the use of the model.
The graph includes a linear trend fitted to the model trace for the century 1909 to 2008, with its equation: y = 0.0088x – 0.9714 and R² = 0.9715.

Continue reading

The record of the IPO

Graphical record of the IPO, plus CUSUM plot and climate shift dates

My post showing shifting trends in world surface temperature and in carbon emissions brought a suggestion from Marvin Shafer that allowing for the PDO could straighten the trend. I think that perhaps it could, but I have tried the IPO (Inter-decadal Pacific Oscillation) rather than the PDO (Pacific inter-Decadal Oscillation). (See below.)

Along the top of the graph I have marked in the climate shifts that prevent the trace of world temperature from being anything like a straight line. The blue line is the IPO, as updated to 2008.
The IPO is positive in the space between the last two climate shifts, negative in the next earlier space, and positive in part of the space before that. By plotting the CUSUM values of the IPO (red), it is clear that the pattern of the IPO relates very closely to the climate shift dates. Four of the seven extreme points of the IPO CUSUM trace match climate shifts. In addition, since 1925, the CUSUM trace between the sharply-defined extreme points has been a series of nearly straight lines. These represent near-constant values of the IPO, a rising line representing a positive IPO and a falling line a negative one.

As shown by the map in the Figure copied below, a positive extreme of the IPO has higher than normal sea surface temperatures in the equatorial parts of the Pacific. Could the transfer of heat from the ocean to the atmosphere be enhanced at such times?

This conjecture is developed in the post “Hammering Global Warming Into Line”.

[Note added August 2019.
The IPO was negative from 1999 to 2014, then became postive again.
The paper by Power et al.(1999) linked below showed that Australian rainfall and its prediction was more closely related to the El Nino-Southern Oscillation (ENSO) when the IPO was negative. Data for Manilla NSW confirms that. See “21-C Rain-ENSO-IPO: Line graphs” and “21-C Rain ENSO IPO: Scatterplot”.]


The PDO and the IPO

The PDO is the Pacific Decadal Oscillation (or Pacific inter-Decadal Oscillation). It is one of a number of climate indicators that rise and fall over periods of a decade or more. These indicators have been introduced by different research groups at different times.
A current list of such indicators is in the contribution of Working Group I to the Fifth Assessment Report (5AR) of the Intergovernmental Panel on Climate Change (IPCC). The list is in Chapter 2 (38MB). It is at the end, in a special section: “Box 2.5: Patterns and Indices of Climate Variability”. Continue reading

Warming and Carbon Emissions: Shifting Trends

Log from 1850 of world surface air temperature and carbon emissions

Trends in global temperature and in carbon emissions changed sharply several times during the last 160 years.
One question is at the heart of concern about human influence on climate: how does global temperature relate to human-caused emissions of carbon dioxide?
This graph shows that relation: it does not explain it.

[This post published 9/05/2014 was made “sticky” during early April 2018 to show the inclusion of Gail Tverberg’s recent graph of world energy consumption.]

Data

I display two well-established data sets:
1. The HadCRUT4 record of estimated global surface air temperature. Values are expressed as the anomaly from 1961-1990 mean values in degrees celsius.(See Note 1. below.)
2. Global Fossil Fuel Carbon Dioxide Emissions, tabulated and graphed as tonnes of carbon (See Note 2. below.)) by the Carbon Dioxide Information Analysis Center, Oak Ridge.(See Note 3. below.)

The format of the data is given in Note 4. below.

Multi-decadal linear trends

Trends in carbon emissions

Throughout this time, the rate of carbon emissions increased exponentially, but at rates that changed abruptly at certain dates. In units of log-cycles per century, the rates were:

From 1850: 1.97 units;
From 1913: 0.28 units;
From 1945: 2.14 units;
From 1973: 0.77 units.

Energy consumption 1820-2010Note added April 2018.
The two episodes of low rate of growth of carbon emissions, from 1913 to 1945 and from 1973 to 2009, relate to times of low growth in world energy consumption. This graph by Gail Tverberg shows that world energy consumption grew so slowly from 1920 to 1940 and from 1980 to 2000 that it did not keep up with the growth of population. Continue reading

Manilla in Global Warming Context: II

Logs of smoothed world and local temperatures. (25/7/14)

This post updates a similar post that was based on data available in July 2011. I now have data from three more years.

World surface air temperature

The blue line shows how the air has warmed and cooled during the 21st century. It is based on GISS, which is one of three century-long records that estimate the surface air temperature of the whole earth. The other two are HadCRUT and NCDC.
Monthly values of GISS vary wildly, and I have smoothed them with a 37-month moving average. Ole Humlum uses 37-month smoothing in many graphs on his website.

The 37-month smoothing allows plotting only up to 18 months ago, in December 2012. As you see, the GISS air temperature anomaly (See Note 1.), when smoothed in this way, moves rather steadily in one direction for years at a time.

The world’s surface air warmed rapidly from early 2000 to late 2002, then warmed slowly to a peak in early 2006. This is the warmest the world surface air has been in hundreds of years. After that peak, the air cooled rapidly by two-thirtieths of a degree to a trough in late 2007. It warmed again slowly to a lower peak in early 2010, steadied for a year, then fell to a trough in January 2012 that was like the previous trough. The air warmed rapidly through 2012. Continue reading

Manilla NSW in Global Warming Context

Logs of smoothed world and local temperatures.

[I posted an Up-dated version of this graph in July 2014]

Up-to -date data on global temperature change can easily be down-loaded from Ole Humlum’s website “climate4you“.
Humlum favours sampling windows 37 months wide. For my own data at Manilla, NSW, I have always used windows about six months wide, which show up Australia’s vigorous Quasi-biennial oscillations of climate. I tried Humlum’s 37-month window on my data, with quite startling results, as shown in the graph above.

Humlum re-presents three records since 1979 of global monthly air surface temperature anomalies:
* HadCRUT3: by the (UK Met Office) Hadley Centre for Climate Prediction and Research, and the University of East Anglia’s Climatic Research Unit (CRU), UK.
* NCDC: National Climatic Data Centre, NOAA, USA.
* GISS: Goddard Institute for Space Studies, Columbia University, New York, NASA, USA.
When smoothed by a 37-month running average, these data sets give very similar results. I use the GISS data because it matches my data best.

The match is very good, particularly in the sharp fall from the maximum in April 2006 to the minimum in September 2007. Where my data begins in September 2000, both curves rise steeply from low values, but mine peaks in August 2001, more than a year before a corresponding peak in global temperature (September 2002). After that, there is a plateau, where the graphs rise together to the highest peak (April 2006).
The other global data sets, HadCRUT and NCDC, have temperature falling or steady along the 2002-2006 plateau.
There are two reasons for plotting my data on a separate axis (on the right). First, the reference periods are different: GISS uses 1951-1980, while I use the decade from April 1999. Second, temperature varies much more at a single station than in the average of many stations around the world. I use a scale six times larger.

It turns out that the cold time in Manilla in late 2007, which I had mentioned in several contexts, was a cold time world-wide.

Home-made thermometer screen

Giant Mixing Bowl Thermometer Screen

I am over the moon at getting agreement between data from my home-made thermometer screen and the best that world climatologists can do. It makes me inclined to believe some of the things they say.


This article and graph were posted on 18th August 2011 in a weatherzone forum: General Weather/ Observations of Climate Variation.