When I examined the Global temperature graph from Hadcrut from 1880 to 2008 I found the two more or less sustained periods the temperatures went up were from 1911 to 1944 and 1976 to 2008. Now according to IPCC and HADcrut the temperature changes after 1950 are due to CO2 (anthropogenic), and those before natural. So I computed the trend from 1911 to 1944 which came to +0.161C/Decade and that from 1976 to 2008 which came to +0.168C/decade. No anthropogenic signature seems to be discernable there. Can you check my figures and comment on this? Thanks

I needed to check the facts in the debate whether Global temperatures have stopped increasing since 1998. So I computed the trend from 1998 to 2008(using the slope of the linear regression line) I found that HADcrut gave a trend of -0.006C/decade, UAH -0.05C/decade and GISS +0.1C/decade.

I also heard that the 1998 temperatures were abnormally high because of the biggest el nino ever and 2008 had a el nina bringing the temperatures down and thus the trend is distorted.

Then I plotted the Graph of the slopes of the Global temperature curve from 1976 to 2005, against the years. I found in every case (HADcrut, GISS and UAH), this curve slopes downwards from 1992 and the downward slope increases from 1999.

What is the significance of this? Does this mean that the warming is slowing? And even reversing as it crosses the 0 line into negative territory?

I will be grateful for your feedback.

Which is precisely the point I wished to make. The majority of the greenhouse approach is to accept a theory then look for support for it. This mistake is as old as science, yet people persist. This time they maintain the rage by saying that the sky will fall in or some similar major catastrophe will happen. Do you notice the expressions of dismay by some writers who discovered that 2006 globally (by present methods of estimation) was cooler than 2005 and only the 11th hottest year in their data set? Do you notice how many people concentrate on disaster if there is climate change, rather than on benefit? I have seen this politicisation of science before after our company found the Ranger uranium mines in 1969. Ignorance has held this country’s nuclear program back by a quarter of a century, which could run into half a century. At least we substituted nuclear around the world with our uranium instead of coal and oil, saving some 500 million tonnes of CO2 by my rough count, at essentialy no harm to anyone. Geoff.

A good suggestion Geoff.

An indication of what will be observed can be related by those who have an outside temperature reading device in their car as we do.

For example, just yesterday, between 2:15 and 4:15 I drove 185 km from Marulan NSW to Sydney’s lower north shore. When we started out, I noted that the temperature was 26 Deg C. It progressively dropped to 19 Deg C, then increased to a peak of 31 Deg. Around Liverpool it was around 26 Deg C again, then as we passed Sydney Airport it increased to 30 Deg C. As we passed along the Eastern Distributor to the east of the city centre, the temperature dropped back to 24 Deg C, increasing to 26 Deg C when we arrived home.

While at the upper end of the normal range fluctuation, the experience yesterday was not unusual. I also note that temperatures in the far west of sydney are generally both higher and lower than they are on the coast.

This is suggesting that your proposed exercise will find a great deal more complexity in the temperature isobars and will demonstrate the folly of trying to use 1200km square grids.

When mathematicians are presented with sparse data, or data irregularly distributed, they often have to interpolate values between data points. This involves some assumptions. One of these is, “How far distant can a point be before it loses its predictive power for the reference point?” This applies to global temperatures, rainfall, humidity, cloud cover etc. It is more or less a trivial exercise that need not last for more than a year or two, to lay out a grid of say 100 x 100 weather stations in and around a large city preferebly one with hills and water (Say San Francisco or Sydney). From readings taken at each of the 10,000 points, at the same time of day, several times a day and night, one could work well-known mathematics that estimate predictability and uniformity and hence allow the drawing of contour lines for visual presentation. This would be a trivial cost to execute and it would take a geat deal of ucertainty out of current guesses. The whole complex would need to be the size of the artificial cells that currently break up the globe for modelling purposes. It would in turn place limits on cell sizes that were meaningful, not just wishful.

I see exercises like this as far far more important than economists like stern whipping up the hysteria at a hugely grater cost of a hugely lower knowledge base. It’s a bit like learning the alphabet before making words.

Other errors introduced by any bias in sampling can only be identified by redoing the work without the bias, or at least portions of the work (say Australia) and deriving a correction factor to be applied.

By the way, the cool graphic in #30 above suggested to me no samples in Australia in March 1850.
Joe E