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Archive for January, 2008

China and the BBC Warming Bias

2008/01/31 3 comments

(here and here and here some more thoughts on the all-too-apparent bias at the BBC towards global warming and doom-and-gloom news in general)

There is almost no need to comment the following at all…

(1) Almost six years ago
BBC News – Wednesday, 17 July, 2002, 07:53 GMT 08:53 UK
Seven die in Chinese heat wave

[…] The heat has intensified in recent years as a result of the increase in vehicles on the roads, which raise street temperatures.

(2) One year ago
BBC News – Tuesday, 6 February 2007, 12:34 GMT
Climate change ‘affecting’ China – Unseasonably warm weather in north China has been linked to climate change
(page is chock-full of climate change links)

At least 300,000 people in north-west China are short of drinking water because of unseasonably warm weather, which officials link to climate change. Parts of Shaanxi province face drought after January saw as little as 10% of average rainfall, state media say. Frozen lakes are melting and trees are blossoming in the capital Beijing as it experiences its warmest winter for 30 years, the China Daily reported.
[…] The country’s top meteorologist, Qin Dahe, said the recent dry and warm weather in northern China was related to global warming. […]

(3) January 2008
BBC News – Thursday, 31 January 2008, 13:53 GMT
Food warnings amid China freeze – Millions of people have been affected by the severe snow
(not one climate change link in sight)

China is struggling to cope with its worst snowfall in decades, with officials warning of future food shortages as winter crops are wrecked.[…]
Dozens are thought to have died as much of the country endures one of its harshest winters for half a century.

How many people died in the 2007 heatwave? Perhaps…zero.

(4) How about Shaanxi? Sadly, no space for it this year on the BBC (at least, so far). Here’s what is happening though:
rediff – January 30, 2008
Snowstorms paralyse China

[…] In northwestern Shaanxi province alone, 1,200 people were reportedly ill or injured in snow-related incidents […]

UPDATE: This particular post has become quite popular having been linked from “Biased BBC”

HadCRUT Data Rank Analysis (IV)

2008/01/30 4 comments

Click here for HadCRUT Data Rank Analysis (I)
Click here for HadCRUT Data Rank Analysis (II)
Click here for HadCRUT Data Rank Analysis (III)
Click here for HadCRUT Data Rank Analysis (IV)
Click here for Results of HadCRUT Data Rank Analysis (V)

This is the fourth posting in a series analyzing the information that can be obtained from the available HadCRUT data, recently updated to December 2007.

As in the previous blogs, the focus is on rank analysis, since it is widely claimed that global warming can be discerned by the fact that most of the warmest years have occurred very recently.

It is actually possible to obtain a rough indication on what is behind the recorded warming in the HadCRUT data by going one step below the usual globe-averaged, year-averaged figures.

(a) A strong hemispheric component is already visible in the yearly averages of the month-by-month ranks:

Yearly averages of the month-by-month ranks

Note how for example SST/Southern-hemisphere is much more similar to Land/Southern-Hemisphere than to SST/Northern-hemisphere.

(b) Similar considerations apply at a seasonal level. See the graphs for the January-March period:

January-March rankings

Obviously the Jan-Mar period is Southern Summer and Northern Winter. Let’s have a look at the Summer-to-Summer plots then:

Summer-to-summer graphs

I have computed the same graphs for all quarters, and for all seasons.

(c) It always looks more important to be in the same hemisphere, rather than in the same season or the same surface.

But visual inspection may be misleading, so a good round of correlations is in order (for the sake of clarity, the full list is at the end of this entry). These are the results:

(d) Correlation is highest intra-hemispherically (that is, when, say, the Northern Hemisphere’s land temperatures have placed near the top ranks, the NH sea-surface temperatures too have done the same) with a maximum of 98.6% (Southern Hemisphere, local Autumn) and a minimum of around 80% (Northern Hemisphere, local Winter).

(e) Same-season correlations are among the lowest, with a maximum of 74.5% (Spring) and a minimum of 68.8% (Summer).

(f) Among all the season-to-following-season correlations, the lowest values belong to the Oct_Dec-Jan_Mar periods (between 71% for Land, Northern Hemisphere and 80.5% for Land, Southern Emisphere).

(g) There is little, or perhaps even none, appreciable difference between Land and Sea-surface results

Conclusions and working hypotheses for the future will be discussed in next blog in the series.

Correlations

SH SST/Land (V3)
Jan_Mar: 98.40%
Apr_Jun: 98.58%
Jul_Sep: 98.17%
Oct_Dec: 98.28%

NH SST/LAND (V3)
Jan_Mar: 80.89%
Apr_Jun: 93.32%
Jul_Sep: 95.71%
Oct_Dec: 88.70%

SST NH
Jan_Mar/Apr_Jun: 89.06%
Apr_Jun/Jul_Sep: 89.17%
Jul_Sep/Oct_Dec: 90.54%
Jan_Mar/Oct_Dec: 73.89%
Jan_Mar/Jul_Sep: 76.04%
Apr_Jun/Oct_Dec: 83.51%

SST SH
Jan_Mar/Apr_Jun: 89.42%
Apr_Jun/Jul_Sep: 91.10%
Jul_Sep/Oct_Dec: 90.55%
Jan_Mar/Oct_Dec: 75.05%
Jan_Mar/Jul_Sep: 81.82%
Apr_Jun/Oct_Dec: 84.84%

Land NH
Jan_Mar/Apr_Jun: 80.78%
Apr_Jun/Jul_Sep: 88.93%
Jul_Sep/Oct_Dec: 85.48%
Jan_Mar/Oct_Dec: 70.99%
Jan_Mar/Jul_Sep: 74.35%
Apr_Jun/Oct_Dec: 79.26%

Land SH
Jan_Mar/Apr_Jun: 92.07%
Apr_Jun/Jul_Sep: 92.39%
Jul_Sep/Oct_Dec: 92.30%
Jan_Mar/Oct_Dec: 80.51%
Jan_Mar/Jul_Sep: 86.31%
Apr_Jun/Oct_Dec: 87.80%

SST Seasonal NH/SH
Winter: 73.52%
Spring: 74.47%
Summer: 68.76%
Autumn: 73.08%

Land Seasonal NH/SH
Winter: 75.87%
Summer: 71.33%
Spring: 78.98%
Autumn: 75.93%

SST NH/SH
Jan_Mar: 75.03%
Apr_Jun: 79.00%
Jul_Sep: 77.68%
Oct_Dec: 76.93%

Land NH/SH
Jan_Mar : 75.95%
Apr_Jun: 82.84%
Jul_Sep: 77.33%
Oct_Dec: 77.41%:

China: Quasi-Tropical Snowstorm

I know that weather is not climate but this is too good to pass…(thanks to D88 for pointing this out)

The extraordinary 2008 snowstorms in China may have to be remembered also for having reached so far south.

Look at the NOAA’s “current snow” picture for Asia and Europe as it is at the time of writing:

NOAA Current Snow as of Jan 29 2008

The southernmost tongue of white stuff is ominously pointing towards Hong Kong itself. Actually, it can be estimated to have reached the city of Guiyang (26.32N, 106.40E: around 200 miles north of the Tropic of Cancer).

In fact, the current weather forecast for Guiyang is light snow, between 1C and -6C between January 31 and February 2 at least.

Climate-wise, placed at an elevation of 1,100 meters, Guiyang is know for the occasional flurry, although the average January temperature is 10C.

HadCRUT Data Rank Analysis (III)

2008/01/29 4 comments

Click here for HadCRUT Data Rank Analysis (I)
Click here for HadCRUT Data Rank Analysis (II)
Click here for HadCRUT Data Rank Analysis (III)
Click here for HadCRUT Data Rank Analysis (IV)
Click here for Results of HadCRUT Data Rank Analysis (V)

Let’s have a look now at the graphs for yearly averages, ranked from #0 (coldest) to #157 (warmest) for the period 1850-2007. Source is once again the HadCRUT data.

We are looking for trends, so instead of simply taking the published average temperatures for the year, I have averaged the monthly ranking for each year taken into consideration. There is anyway no considerable difference between the results of the two approaches.

Fig. 1: Yearly temperature rankings between 1850 and 2007

Figure 1 above shows the rankings for the whole period. Things to note:

(a) There is a clustering of warmer years during the past 20 years or so. This does suggest an overall warming. Taking the HadCRUT data for good (otherwise there would be no point examining them), it is also possible to say that the “warmest X years happened within the past Y years”.

(b) The steepest gradient IN TERMS OF RANKING  is by far between the cold years around 1910 and the warm years around 1938.

(c) All the graphs end up with a “cap”

Fig. 2: Yearly temperature rankings between 1997 and 2007

To investigate point (c), Figure 2 above shows the rankings for the past 10 years. Things to note:

(d) Only Land/Northern-Hemisphere gives any indication of continuous warming to date.

(e) Temperatures in the Southern Hemisphere have not been warming on a decadal scale.

I have been notoriously bad at making predictions but on the basis of figures 1 and 2 it is plausible that at least for now, and at least everywhere but on Land/Northern-Hemisphere, temperatures have reached a high and may not increase further.

AGW Countermeasures the Perfect Brew for “Unintended Consequences”

2008/01/27 1 comment

Is the fixation on regulating CO2 and in general all “greenhouse gases” a wise path to follow? Apparently not: as it falls exactly within what Alex Tabarrok via Freakonomics considers the domain of the law of unintended consequences:

The law of unintended consequences is what happens when a simple system tries to regulate a complex system. The political system is simple, it operates with limited information (rational ignorance), short time horizons, low feedback, and poor and misaligned incentives. Society in contrast is a complex, evolving, high-feedback, incentive-driven system. When a simple system tries to regulate a complex system you often get unintended consequences […]

The fact that unintended consequences of government regulation are usually (but not always or necessarily) negative is not an accident […]

Does the law of unintended consequences mean that the government should never try to regulate complex systems? No, of course not, but it does mean that regulators should be humble (no trying to remake man and society) and the hurdle for regulation should be high.

Repeat with me: no trying to remake man and society

no trying to remake man and society
no trying to remake man and society
no trying to remake man and society
no trying to remake man and society
no trying to remake man and society
no trying to remake man and society

The Critical Flaw with Catastrophic Global Warming Theory

From the Coyote Blog via Climate Skeptic:

“[…] In sum, to believe catastrophic warming forecasts, one has to believe both of the following:

  1. The climate is dominated by strong positive feedback, despite our experience with other stable systems that says this is unlikely and despite our measurements over the last 100 years that have seen no such feedback levels.
  2. Substantial warming, of 1C or more, is being masked by aerosols, despite the fact that aerosols really only have strong presence over 5-10% of the globe and despite the fact that the cooler part of the world has been the one without the aerosols. […]

When the AGW Revolution Will Come…

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