Archive for the ‘Dataset’ Category

My thanks to Tony Thomas for giving the talkshop the exclusive of his take on this breaking news item:

Gergis findings re-surface – the Hockey Stick lives!

By Tony Thomas 31-03-2014

josh-gergisHello again Hockey Stick, goodbye global Medieval Warming Period.

These are the conclusions of a multi-proxy 1000-year climate reconstruction published today (March 31) in Nature Climate Change, by Dr Raphael Neukom of the Oeschger Centre at the University of Bern, and Dr Joelle Gergis of the University of Melbourne.

Dr  Neukom   summed up for a University of Melbourne press release:

The study showed the ‘Medieval Warm Period’, as identified in some European chronicles, was a regional phenomenon. 

During the same period, temperatures in the Southern Hemisphere were only average. Our study revealed it was not a common climate event that many people have previously assumed.

The paper claims that in 99.7 percent of the results, the warmest decade of the millennium occurred after 1970.

The press release says,“And surprisingly, only twice over the entire past millennium have both hemispheres simultaneously shown extreme temperatures.

One of these occasions was a global cold period in the 17th century; the other was the current warming phase”.”[1]


H/T to Gerry Pease for alerting me to this paper from last year by Steinhilber and Beer which lays out a solar prediction from their analysis of their reconstruction of solar activity from proxy data.

Prediction of solar activity for the next 500 years
Friedhelm Steinhilber1 and Jürg Beer1
Received 18 May 2012; revised 18 February 2013; accepted 2 March 2013.

Recently, a new low-noise record of solar activity has been reconstructed for the past 9400 years by combining two 10Be records from Greenland and Antarctica with 14C fromtree rings [Steinhilber et al., 2012]. This record confirms earlier results, namely, that the Sun has varied with distinct periodicities in the past. We present a prediction of mean solar magnetic activity averaged over 22 years for the next 500 years mainly based on the spectral information derived from the solar activity record of the past. Assuming that the Sun will continue to vary with the same periodicities for the next centuries, we extract the spectral information from the past and apply it to two different methods to predict the future of solar magnetic activity.


This’ll keep Oldbrew and me busy with the calculators  for a while. :)


The artist concept depicts multiple-transiting planet systems, which are stars with more than one planet. The planets eclipse or transit their host star from the vantage point of the observer. This angle is called edge-on.
Image Credit: NASA

NASA’s Kepler mission announced Wednesday the discovery of 715 new planets. These newly-verified worlds orbit 305 stars, revealing multiple-planet systems much like our own solar system.

Nearly 95 percent of these planets are smaller than Neptune, which is almost four times the size of Earth. This discovery marks a significant increase in the number of known small-sized planets more akin to Earth than previously identified exoplanets, which are planets outside our solar system.

The Kepler team continues to amaze and excite us with their planet hunting results. That these new planets and solar systems look somewhat like our own, portends a great future when we have the James Webb Space Telescope in space to characterize the new worlds.


Nicola Scafetta and Richard Willson have a new paper in press which contains the most thorough analysis yet of the intercomparison of the empirical ACRIM and modeled PMOD TSI series. It’s a comprehensive yet readable paper of high interest to all diligent climate researchers interested in determining the relative strengths of various climate drivers. It is also an important historical document for philosophers of science investigating the shift from observation based empirical solar science to model based  dogma underpinning preconceptions of the power of trace gases to control Earth’s surface temperature. The IPCC and Team Wassup’s Leif Svalgaard are not going to like it, and will therefore try to ignore it, thus further underminng their credibility.


ACRIM total solar irradiance satellite composite validation versus TSI proxy models
Nicola Scafetta & Richard C. Willson

From the paper:

PMOD TSI composite (Fröhlich and Lean 1998; Fröhlich 2004, 2006, 2012) is essentially a theoretical model originally designed to agree with Lean’s TSI proxy model (Fröhlich and Lean 1998). It relies on postulated but experimentally unverified drifts in the ERB record during the ACRIM Gap,and other alterations of the published ERB and ACRIM results, that are not recognized by their original experimental teams and have not been verified by the PMOD by original computations using ERB or ACRIM1 data.


Brilliant Czech researcher P.A. Semi has sent us the fruits of some considerable labour, which he has asked us to share with the Solar-planetary community. Since the venue at Pattern Recognition in Physics was axed by Copernicus (The Innovative Science un-PublisherTM), he says he is not sure where to get this published, so the Talkshop it is for now. I will also add it to the repository I am building at ‘Solar System Science’, a new venture I’m setting up in collaboration with other researchers. Tim Channon will be interested in working with the dataset which can be generated from the resources Semi has provided, and I’m sure others will be too. Here’s a sample of the output:


Semi Writes:

Hello Tallbloke and others.

I’ve produced the Synoptic map of Sunspots 1874-2012 and Interpolated Sunspot Area, that allows to investigate sunspot record without smoothing, while removing the 27-day false signal of single-face problem another way – by interpolating individual Sunspot groups: if they can be matched on the next rotation, they are linearly interpolated to the new position and size, if they are not matched, they are interpolated in 17 days linearly to zero. This way, the far-side Sunspots are interpolated and the record does not need the usual monthly smoothing, that wipes away precise timings. (There still exists some single-face problem – the Sunspots, appearing on the far side first, are delayed until they get to the front side, and the 17-day fade-out makes a typical fade-out curves in the chart, but still better than if the group disappeared abruptly on the limb…)

Congratulations to Nicola Scafetta  and Richard Willson on the publication of their new paper, made freely available by high impact journal Pattern Recognition in Physics :

Multiscale comparative spectral analysis of satellite total solar irradiance measurements from 2003 to 2013 reveals a planetary modulation of solar activity and its nonlinear dependence on the 11 yr solar cycle.



From the ‘Not as bad as we theorised’ department, a paper which finds that models of water cycling in rainforest over-estimated the effect of drought by a big factor. The paper is paywalled, but there’s a write up here which summarises. Worth noting that the paper emphasises this natural resilience operates best in undisturbed forest.

Journal of Climate 2013 ; e-View

Impact of evapotranspiration on dry season climate in the Amazon forest
Anna Harper*

College of Engineering, Mathematics, and Physical Sciences, University of Exeter, Exeter, Devon, UK, Department of Atmospheric Science, Colorado State University, Fort Collins, CO, USA
Ian T. Baker, A. Scott Denning, David A. Randall, Donald Dazlich, and Mark Branson

Department of Atmospheric Science, Colorado State University, Fort Collins, CO, USA


Moisture recycling can be an important source of rainfall over the Amazon forest, but this process relies heavily upon the ability of plants to access soil moisture. Evapotranspiration (ET) in the Amazon is often maintained or even enhanced during the dry season, when net radiation is high. However, ecosystem models often over predict the dry season water stress. We removed unrealistic water stress in an ecosystem model (the Simple Biosphere model, SiB3), and examined impacts of enhanced ET on the dry season climate when coupled to a GCM. The “Stressed” model experiences dry season water stress and limitations on ET, while the “Unstressed” model has enhanced root water access and exhibits strong drought tolerance.


Repost of a repost by Clive best, shamelessly stolen because it’s so good. This adds to the several posts already here at th talkshop comparing sunshine hours to temperature regionally and globally. How long can the mainstream climate scintists ignore this growing body of evidence which demonstrates a link between solar activty levels, albedo cloud amount levels and surface temperature? H/T to A.C. Osborn

This is a repost written by Euan Mearns and is an introduction to the work we consequently did this summer concerning cloud and CO2 radiative effects on UK temperatures. Two more posts will follow describing the radiative model in more detail.


  • Terrestrial sunshine records provide an inverse proxy for cloud cover. Sunshine at surface means cloud free line of sight between the point on the surface and the Sun.
  • We present concordant sunshine and temperature records for 23 UK Met Office weather stations. Data is available for a handful of stations from 1908 but it is only from 1933 that there are a sufficient number of stations to provide representative cover of the UK.
  • Data from 1933 to 1956 is believed to be affected by air pollution from burning coal for home heat and power generation, therefore our main analysis focusses on the time interval 1956 to 2012.
  • Both temperature (Tmax) and sunshine hours show cyclic variation, both showing a tendency to rise in the period 1980 to 2000 in keeping with global warming that has been documented in many studies.
  • In the UK there is a high degree of covariance between sunshine and Tmax, sunny years tend to be warmer. The correlation coefficient (R2) between sunshine hours and Tmax is 0.8 whilst R2 for CO2 and Tmax is 0.66 (calculated on 5 year means). A significant portion of warming observed in the UK may be attributed to temporal variations in sunshine and cloud cover.
  • This post presents a summary of the raw data in 14 charts. Next week we will present a combined net cloud forcing and radiative forcing model with the aim of quantifying the relative contributions of dCloud and dCO2.

Figure 1 Maximum daily temperature (Tmax, red, LH scale) and minimum daily temperature (Tmin, blue, RH scale) from the Leuchars weather station. The red and blue lines are annual averages. The black lines are centred 5y moving averages. Note high degree of co-variation between Tmax and Tmin. Also note how temperatures drifted higher during the 1990s and 2000s but recently are drifting down again, in keeping with the global temperature trend.


Here’s a new paper which looks at the group and Wolff sunspot numbers in the mid C19th. The authors find the Wolff sunspot numbers (WSN) prior to 1848 are too high, and need reducing 20%. This brings the Wolff sunspot number more into line with Group Sunspot Number (GSN). The full paper is available (for a short time) directly from A&A here (free signup required).

Inconsistency of the Wolf sunspot number series around 1848

Raisa Leussu1,2, Ilya G. Usoskin1,2, Rainer Arlt3 and Kalevi Mursula1

1 Department of Physics, PO Box 3000, University of Oulu, 90014 Oulu, Finland
2 Sodankylä Geophysical Observatory (Oulu unit), University of Oulu, 90014 Oulu, Finland
3 Leibniz Institute for Astrophysics Potsdam, An der Sternwarte 16, 14482 Potsdam, Germany

Received: 26 July 2013
Accepted: 23 September 2013


Aims. Sunspot numbers form a benchmark series in many studies, but may still contain inhomogeneities and inconsistencies. In particular, an essential discrepancy exists between the two main sunspot number series, Wolf and group sunspot numbers (WSN and GSN, respectively), before 1848. The source of this discrepancy has remained unresolved so far. However, the recently digitized series of solar observations in 1825–1867 by Samuel Heinrich Schwabe, who was the primary observer of the WSN before 1848, makes such an assessment possible.



I haven’t time to edit this properly, so I hope Roger Andrews will forgive me for just pasting his email into this guest post and lobbing in the images. Somewhere in the archives there’s a post From RA in which he used my cumulative solar technique to get some good fits too. I’ll link it  if anyone finds it. You’ve all seen data before, and know what to do…

Here are the results of the empirical models I ran five or so year ago, plotted on the three sets of figures linked to below and accompanied by a writeup, sort of.  The first set of figures allows for both anthropogenic and natural forcings. Results are presented for the 60-90N, 30-60N, 0-30N, 0-30S and 30-60S latitude bands and for the area-weighted global average of these bands. (There weren’t enough data to put together a comparison for 60-90S.)