Archive for the ‘data’ Category

It’s 10 years since the death of John Daly, but we forgot to mark this decadal anniversary back at the end of January. Here is the article by John Izzard originally published at in 2009, which looks back at his life and work. If anyone has a copy of his book “The Greenhouse Trap” please let me know. Google and Amazon aren’t interested (and probably think n0-one else should be either).

John L. Daly (31 March 1943 – 29 January 2004)

Daly-picYesterday I visited John L. Daly’s tiny office where he lived on the outskirts of Launceston. It is about the size of two telephone boxes. His wife, Amy, has kept is just as it was when John died in 2004. His computer, his files, the maps on the wall — his notes, letters, photographs and dairies. She has also kept alive his web-site which he was still updating at the time of his death.

Looking at his scientific work today gives an insight into why the people at the IPCC (Intergovernmental Panel on Climate Change) and the University of East Anglia’s Climatic Research Unit were so annoyed with Daly’s work and why he was such a thorn in the side of their climate theories and research.


Prolific solar-planetary scientist and long-time talkshop friend Nicola Scafetta has a new paper published in Physica A entitled ‘Global temperatures and sunspot numbers. Are they related? Yes, but non linearly. A reply to Gil-Alana et al. (2014)’ which comments on Gil-Alana et al 2014; a paper purporting to dismiss any correlation between solar activity and terrestrial surface temperature. Nicola gently points out the limitations of their methods and patiently explains how the astronomical-solar signal can be found in the data. Here is Figure 3 to whet your appetite:



Fig. 3. (A) Annually solved HadCRUT3 global surface temperature record [34] from 1850 to 2013. (B) Power spectrum density functions calculated using the MEM method (using M = N/2 = 82) and the MTM periodogram f (p) [35,36]: the calculations were made with the SSA–MTM Toolkit. Several spectral peaks (e.g.: at about 9.1, 10.4, 20 and 60 yr) are statistically significant above the 95% confidence level, and their solar, lunar and astronomical origin is explained in the literature (e.g.: Scafetta [10,32,33,25]).

Nicola also provides plots of several of the various solar and temperature related indices and techniques for representing them over a wide range of timescales which clearly demonstrate the plain fact of the close coherence between the activity of our host star which supplies all our energy, and the fluctuations of the lovely moderate temperatures we live in on the surface of our planet.


Thanks to commenter ‘psc3113′ for finding the concluding part of HC Russells’ paper on a lunar 19 year cycle in drought records, taken from The Queenslander (Brisbane, Qld. : 1866 – 1939)  Saturday 4 July 1896. At the conclusion of the article, the probably cause of the 19 year cycle identified is elucidated.

Periodicity of Good and Bad Seasons
(Continued from last Week.)

Hurricanes Come in Droughts.
I should like it to be clearly understood that I do not mean ordinary hurricanes, which are as much parts of ordinary weather conditions in some parts of the world as our southerly winds are here. What I mean are extraordinary hurricanes, those that come at long intervals to terrify mankind by their power for destruction. These are connected with droughts, and, therefore should be discussed here. I had long since observed that the connection between the two was obvious enough sometimes, and during the past year I was reminded of it very often by the frequent reports of heavy gales met with by ships coming to this port, indicating great atmospheric energy. Then on the 3rd January, 1803, came the hurricane over the Tongan group of islands, and not one of the vessels in the harbour rode out the storm; every one of them was wrecked in the harbour before morning, and the wind was of such exceptional violence that after it was over the islands looked as if they had been bombarded.

Then I turned to storms on this coast, some of which were of terrible violence. And as I write, the 28th ‘May, we have the report of a terrible cyclone in America, by which three of the States, Missouri, Illinois, and Indiana were damaged and the city of St. Louis wrecked. and 1300 people killed by falling buildings, and damage to property caused to the extent, estimated, of twenty million dollars; another fragment of the present D drought.


Storm clouds arriving [image credit: Wikipedia]

Storm clouds arriving
[image credit: Wikipedia]

A line from a GWPF report illustrates one of the many problems faced by the UN IPCC in its efforts to understand the world’s climate(s):
‘Facebook has over fifty times more lines of code than climate models.’

Having no way of verifying that, we’ll have to take their word for it, but it’s probably not that surprising. Facebook would be out of business if its code consistently failed to work as expected, but no such problem for climate models it seems.


………….A good attempt to try and see through the fog of the ‘climate wars.’

Originally posted on Climate Etc.:

by Judith Curry

This past week, there have been several essays and one debate that provide some good perspectives on what we don’t know about climate change, and whether we should be alarmed.

View original 1,043 more words

On UCLA’s main website there is a ‘space missions’ page. On it there is a section for the Diviner mission, which mapped the Moon’s surface temperature. We covered it in a series of posts a while back, as it is crucial to our understanding of Earth’s climate:

divops_lroflybyDiviner: The Diviner Lunar Radiometer is one of seven instruments aboard NASA’s Lunar Reconnaissance Orbiter spacecraft, which was launched on June 18, 2009. It is the first instrument to create detailed, global maps of surface temperature over the lunar day and year. Diviner’s measurements are also used to map compositional variations, derive subsurface temperatures, assess the stability of potential polar ice deposits, and infer landing hazards such as roughness and rock abundance. Read more here.

But the links to the diviner subdomain are broken, and although references to other pages about the mission such as press releases and news articles are found by searching the UCLA site, the science has gone. OK, so websites get changed, links get broken, servers crash and don’t get rebooted for a while. So what?  Why does this matter?


While giggling about the botched “Death blow” dealt by Anthony Watts and other members of team wassup to our solar-planetary theory yesterday, it occurred to me that the rather thin rolled-up paper they tried to bludgeon Nicola Scafetta with only considered the all too brief thermometer record. No wonder Sverre Holm found his windows too narrow to see the big picture through, as Nicola Scafetta pointed out in a comment deleted by Anthony Watts. When considering climate swings on the timescale of interest, in this case, around 60 years, we need to look at longer records.

A paper we discussed a few days ago used a paleoproxy to compare millennial scale changes in terrestrial climatic indicators with Steinhilber et al’s 2009 10Be proxy reconstruction of TSI (Total Solar Irradiance). Their work is sufficiently detailed to be able to discern sub-centennial swings in these climatic and solar indicators. Here’s panel ‘d’ of their figure 2, which I’ve annotated with vertical lines marking peaks in the curves.



Announcement on the SORCE Status page:

TSI-stpsat3Total Irradiance Monitor Status

(updated 24 Feb. 2014)

TIM daily solar measurements have resumed in a new operations mode.

The TIM, along with all other SORCE instruments, ceased collecting solar measurements after a battery cell failure on 30 July 2013. The LASP SORCE spacecraft operations team has implemented a new means of operating the instrument to acquire continued TSI measurements in the present limited-power mode. These measurements are expected to be more intermittent and of lower quality than those during the primary mission phase due to thermal and pointing issues, and this will be reflected in the time-dependent uncertainties given in the released data files.


A 0.6-Million Year Record of Millennial-Scale Climate Variability in the Tropics†

Kelly Ann Gibson2,*, Larry C. Peterson1DOI: 10.1002/2013GL058846©2014. American Geophysical Union


[1] A ~600-kyr long scanning X-ray fluorescence (XRF) record of redox variability from the Cariaco Basin, Venezuela, provides insight into rapid climate change in the tropics over the past five glacial-interglacial cycles. Variations in the sediment accumulation of the redox-sensitive element molybdenum (Mo) can be linked to changes in Intertropical Convergence Zone migration and reveal that millennial-scale variability is a persistent feature of tropical climate over the past 600 kyr, including during periods of interglacial warmth.


Guest Post By Doug Proctor.

What sparked my post is  Bob Tisdale’s graphs of global temperature anomalies AND a graph that split the anomalies into Northern and Southern Hemispheres. A clear example of a computational result that misleads: the Northern Hemisphere has been warming while the Southern Hemisphere has been cooling. Not global, regional.

Plot by Bob Tisdale

What does it tell us about, in this case, “global” warming when the temperatures of inland areas correlate well to cloud cover while the coast does not, with a mentioned “protection” from sea winds? It tells us the “global” (in this case the inland + coastal area) will have a temperature rise in its combined data while only the inland area did. And it also tells us that there is no “global” cause: it is the regional cloud cover and lack of cooling seawind that is responsible. Computational, yes, representational, no.



A conclusion and its implication in the summary paper was: because our scientific investigation leads us to the prediction that the Sun is headed into a protracted minimum, the warming forecast by the IPCC might not happen.

This has led to the journal being axed by the parent Publishing house Copernicus. The papers are still available at this link
Please download and disseminate them widely.

Heres the letter sent to Coordinating editor Nils Axel Mörner and chief editor Sid Ali Ouadfeul:


Guest post from Roger Andrews, who says: ” This is a review that extends Euan Mearns’ article on sunshine hours, cloud cover and SAT in the UK over mainland Europe and the North Atlantic. It reveals some interesting features that I make no attempt to explain – basically because I can’t – but someone else may have some ideas.” Apologies to Roger A for the delay in getting this article posted.

by Roger Andrews

The recent “UK temperatures since 1933” post discussed the relationships between sunshine hours, which were assumed to be an inverse cloud cover proxy, on surface air temperatures (hereafter SAT) at 23 UK stations. Here I summarize the relationships between sunshine hours, cloud cover and SAT over  Europe using observations from ~30 stations selected from the European Climate Assessment (ECA) data set (acknowledgement as requested to Klein Tank, A.M.G. and Coauthors, 2002. Daily dataset of 20th-century surface air temperature and precipitation series for the European Climate Assessment. Int. J. of Climatol., 22, 1441-1453.) Station locations are shown in Figure 1:



This is a guest post by Jerry Lundry

Two plots are presented for annual average temperature in the United States Historical Climate Network (USHCN). This data set is highly regarded by some in climate science and is sometimes used as a surrogate for world-wide temperatures. Among its attributes are its coverage of a large land mass (the forty-eight contiguous United States), dense coverage of that land mass (1218 stations), and records that are complete to 1912 and missing only about eighty stations back to 1895. Temperatures for all stations are also provided for 1908.

In 2012, the author downloaded and produced annual average temperatures for this data set. The first figure below provides average annual temperatures for 1908 and 1912-2011. The curve faired through the data is a standard Excel sixth-order polynomial. This curve shows minima in years 1914 and 1970, and maxima in years 1940 and 2004, give or take a year or two.


Figure 1


IPCC neglected to account for coastal waters absorbing far more co2 than they emit since the industrial revolution, according to research published in Nature today. This from Science Daily:

Coastal portions of the world’s oceans, once believed to be a source of carbon dioxide (CO2) to the atmosphere, are now thought to absorb as much as two-thirds more carbon than they emitted in the preindustrial age, researchers estimate.

“The evidence suggests that human activities in coastal zones will continue to have an important impact on global carbon cycling,” Bauer said. “It’s a tricky area of study, but omitting the coastal ocean from the overall carbon budget leaves a gap in projections for future atmospheric CO2 levels.”

Prior to the industrial age, decomposing plant materials in coastal waters and sediments likely led to the release of carbon dioxide. The Nature paper suggests that microscopic plant growth in coastal areas, fueled by fertilizer runoff, is now leading to greater uptake of CO2. It also suggests that the atmospheric buildup of carbon dioxide caused by the burning of fossil fuels is further contributing to this uptake of CO2 by coastal waters.


Having been down a similar route with my own simple model which replicates HADsstV3 to a Pearson R^2 of 0.9 for monthly data, I’m happy to put up this model which achieves an accuracy of R^2=0.95 for smoothed data, using a slightly different technique. Sunspot numbers are a major component in this model by Andrew McRae, although so far as I can tell there is no integration to simulate ocean heat retention as there is with my own effort. Hopefully, he’ll make the spreadsheet available for sharing to interested parties:

Andrew writes:

I was inspired by the work of Dan Pangburn and decided to try to create a simple climate model using the external solar magnetic forcing and internal 60yr ocean cycle as the main factors, with a bit of CO2 thrown in just so it doesn’t feel left out.
The results were quite… interesting.

Here is a screen shot of the model output compared to measurements, plus a few background details in the caption of which I’m sure all of you are already aware but I wanted to write the caption for a potentially wider audience.



Trebuchet war engines utilise a similar principle to the slingshot effect

H/T to Ian WIlson for this article which reveals a decades old mysterious anomaly with the slingshot effect: The technique used to accelerate deep space probes towards their destination using Earth’s gravity. Unexplained variations have puzzled the experts. This from Science daily:

Oct. 9, 2013 — A mystery that has stumped scientists for decades might be one step closer to solution after ESA tracking stations carefully record signals from NASA’s Juno spacecraft as it swings by Earth today.

NASA’s deep-space probe will zip past to within 561 km at 19:21 GMT as it picks up a gravitational speed boost to help it reach Jupiter in 2016.

Engineers hope that the new measurements will unravel the decades-old ‘flyby anomaly’ — an unexplained variation in spacecraft speeds detected during some swingbys.



Latest output from R.J. Salvador’s solar variation model, now up to a 91% correlation with the sunspot record since 1749.

My thanks to R.J. Salvador for this guest posting of his solar variation model based on planetary periods. It’s forecast is in good agreement with that made by Tim Channon back in Feb 2011 using a different technique and different data (Judith Lean’s TSI reconstruction). R.J.’s model is available to interested parties known to the talkshop, make a request in comments for a copy (7meg .xls). R.J. asked me to include Sparks plots of Uranus orientation to the Sun which is included into the model as the 1/4 period of its orbit. Click for full size.




A Mathematical Model of the Sunspot Cycle for the past 1000 Years
By R.J. Salvador


Using many features of Ian Wilson’s Tidal Torque theory, a mathematical model of the sunspot cycle has been created that reproduces changing sunspot cycle lengths and has an 85% correlation to the sunspot numbers from 1749 to 2013. The model makes a reasonable representation of the sunspot cycle for the past 1000 years, placing all the solar minimums in their time periods. More importantly, I believe the model can be used to forecast future solar cycles out quantitatively for 30 years and directionally for 100 years.  The forecast is for a solar minimum and quiet sun for the next 30 to 100 years. The model is a slowly changing chaotic system with patterns that are never exactly the same, much like a model of the weather. Inferences as to the causes of the sunspot cycle patterns can be made by looking at the models terms and relating them to aspects of the Tidal Torque theory and possibly Jovian magnetic field interactions.

The Model

The Tidal Torque theory proposed by Ian Wilson provides a system of interrelated consistent frequencies and now I believe a unique set within a narrow error range.

This model is simply four interacting waves but they are modulated to create an infinite possibility for sunspot formation.


This is the second post in a series attempting to unlock the door to the secret life of our solar system. In part one we presented some observations demonstrating a selection of the relationships between the motion of the planets, cyclic climatic and solar periods found in palaeo-proxy records, and ratios in the Fibonacci series, including many which are very close to the ‘Golden Section’ or phi. In this post we’ll take a closer look at the ‘gas giant’ Jovian planets; Jupiter, Saturn, Uranus and Neptune.



Oldbrew and Tallbloke: Why Phi? – Part 1

Posted: September 1, 2013 by Rog Tallbloke in Cycles, data, Phi, solar system dynamics

This post lays the groundwork for a series we will publish over the coming weeks and months. It consists of some of the observations gathered since February when I published my discovery that the Fibonacci series and the Golden Ratio – Phi connect the planetary orbits, the synodic conjunction periods they form with their neighbours, solar cycle periods and cycles found in terrestrial climatic proxy time series. Stuart has done the bulk of the calculator heating work here, with interjected observations, conversations and deliberations with myself.




Reposted for discussion from Ian Wilson’s blog Astro-Climate Connection


Direct instrumental observations of the Sun since 1610 have shown that the level of sunspot activity on the Sun has a mean periodicity of 22.3 years, known as the Hale cycle. In addition, these observations of the Sun have shown that there are longer-term periodicities present in the level of solar activity.

One of the most prominent long-term cycles that have been identified is the ~210 year de Vries (Suess) cycle. However, because of the limited time over which instrumental observations have been available, the confirmation of the de Vries cycle [1] has required the use of proxies such as de-trended δC14 from tree rings [2,3], Be10 levels in the GRIP ice cores [4,5,6], and dust profiles in GISP2 ice cores [7].  These proxy observations have indicated that:

a) the de Vries cycle amplitude varies with a period of about 2200 years [6]. In other words, its appearance is intermittent in nature.

b)  the largest amplitude of the de Vries cycle are found near Hallstatt cycle minima centered at 8,200, 5,500, 2,500 and 800 B.P .[6]

c) grand solar minima occur preferentially at minima of the Hallstatt cycle that are characterized by large de Vries cycle amplitudes [6].

d) the cycle length is somewhere in the range 205 – 210 years, with the more precise estimates being in the range 207-208 years.