This blog started 28th September 2008 as a quick communication tool for exchanging information, comments, thoughts, admonitions, compliments etc… related to http://meteo.lcd.lu , the Global Warming Sceptic pages and environmental policy subjects.
The EU wants to spend 20% of its budget to avoid “dangerous global warming” (now called “climate change”), but it seems unaware that winters in the EU zone are steadily cooling since quite a long time. I pointed to our meteoLCD data showing this trend for a couple of years, and our latest trend graph for the period 1992 to 2012 showed this:
The overall trend for Diekirch is -0.42 °C/decade (that of our national meteo station at Findel airport even -0.67 °/dec). Ed Caryl has a comment at the Notrickszone blog of Pierre Gosselin, where he examines winter trends from the GISS data. The global figure shows this:
Luxembourg belongs to the light-blue region, which means that the trend for the 1995-2012 period of 18 years is between -0.5 and -1.0 °C, which gives a decadal trend of -0.28 to -0.56 °C/dec (with a mean value of -0.42 °C/decade, really close to the meteoLCD trend).
The analysis of the Diekirch data shows that the winter temperatures correlate very well with the NAO index of the December to March months. The coming years will tell us if this not so surprising correlation remains stable.
I wonder that absolutely NONE of our climate anxious politicians and NGO’s seems to recognize this situation, which is an observable fact and not a prediction of some climate models ensemble. Colder winter will be problematic, as they stress the energy needs for heating, and collide with the ambition to continuously lower energy usage.
The Austrian meteorologist Dominik Jung found the same winter cooling throughout the Alps, which should comfort the managers of the various sky resorts who have been continuously told by the climate alarmists that sky resorts have no future due to climate warming.
The 44/3 edition of europhysicsnews, the journal of the European Physical Society, contains an interesting comment by its former president Fritz Wagner titled “The pitfalls of time derivatives”. You may read it here (highlights by me).
The author writes that last year (2012) the total subsidies for the Energiewende were 17 billion Euros (17*10**9, billion always used in the US tradition), to be compared to the 13.7 billion of the federal science and education budget!
The Bundesministerium f. Umwelt, Naturschutz und Reaktorsicherheit gives more recent and higher numbers in his latest brochure: the total EEG costs are about 20.4 billion Euros in 2013 and will rise to 23.6 billion in 2014 !
Being a fusion researcher, F. Wagner belongs to a category of German scientists I wish good courage to stem the tide of the hysterical “anti-atomism” embraced by the large majority of the German media and politicians. The last sentence of his opinion-paper reminds us that the electricity production of Norway, Sweden and France is essentially CO2 free, a fact not welcome in his country!
Read also on this subject an interview (in German) with Dr. Günther Keil, president of the “Deutscher Arbeitsgeberverband”: “Nur Dilettanten beschließen Maßnahmen, deren logische negative Auswirkungen sie nicht sehen können.”
In the preceeding comment I showed using the IWES report that the decadal decline in potential wind power was about 14% per decade during the 1992-2012 time period in Germany (coastal and land locations). Such an important decline of the available wind resource should be show up in the electricity produced by the wind turbines. The easiest metric to use is the capacity factor (CF) or the equivalent parameter “Volllaststunden”. (VLh) prefered in German reports. The relation between both parameters is CF = VLh/8760.
1. The ThinkAero data
It is not easy to find reliable data,so I will start with the data found at the ThinkAero blog. Here we have a table which gives the average VLh of all German wind turbines and also those located in the Land Baden-Würtemberg.
The upper red data points represent the German average, the lower blue squares the numbers for in-land Baden-Würtemberg. Trend lines have been computed with Excel. Clearly both groups show declining VLh’s (or CF’s).
As in the previous comment, we clearly find that the year 2007 was an exceptional good one, both for the whole country as well as for Baden-Würtemberg.
For the whole country, the decline given by the trend line would be 62.5 hours per decade, or about -4%/decade (percentages calculated w.r. to the trend line). The same calculation made for Baden-Würtemberg gives -181 hours per decade or -14.8%/decade.
The situation in Baden-Würtemberg becomes dramatic during the last 4 years 2008 to 2011:
Here we see a decline of -32% during that short period. Needless to say that such a slump will make all economic predictions a laughing-stock!
2. The BMU data
The website of the BMU (Bundesministerium f. Umwelt…) has a data table with values from 2000 to 2012. To be able to compare to the ThinkAero data let us just use the results from 2004 to 2012:
If we use the ThinkAero data and add the BMU value of 1530 for the year 2012, the same calculation gives a decadal decline of -3.5%, close to the BMU result.
3. The BWE data
The Bundesverband WindEnergie gives a table with the “Windjahr” percents (actually these are anomalies of probably the wind resource (not the produced wind electricity) over an unspecified period, probably a decade):
Here again we find a decline of -12.2% per decade (computed from the trend line), a number close to those found in the preceding comment. And as is the case for Baden-Würtemberg, the last 4 years are especially worrying.
1. Both the wind resource data and the capacity factor (or Volllaststunden) data show a (long-term) decline
The 2 series we have studied give the following decadal declines in percent for the period 2004 to 2012:
ThinkAero (Volllaststunden): – 3.5%
BMU (Volllaststunden) : – 4.5%
The declines in wind resource given by the IWES report (preceeding comment) and by the BWE are comparable (-14% and -12.2%)
2. Especially instructive is the comment given in “Energiewirtschaftliche Tagesfragen” from September 2013: “Bisher ist ein Trend zu steigenden VLS trotz stetiger technischer Weiterentwicklung durch Serienproduktion und rapide gestiegene Anlagenkapazitäten und Nabenhöhen nicht erkennbar.”
Approximate translation: “Up until now a rising trend in CF’s can not be detected, despite technical progress and fast rising power capacities and wind turbine heights”.
It would be more correct to acknowledge that an uncomfortable declining trend is clearly detectable!
In two previous comments (here and here) I wrote about declining wind power and declining capacity factors of installed wind turbines in Europe and especially in Germany and Ireland. The German Fraunhofer “Institut für Windenenergie und Energiesystemtechnik IWES” has published a very interesting report “Windenergie Report Deutschland 2012” which I recommend for reading to everyone interested in wind energy, be he a 100% fan or a more skeptic individual. Sure, the IWES must be on the side of the wind power pushers, but this report has serious scientific reflections and, if you read it carefully, they do not refrain to put the finger on spots that hurt (click here for an English version).
I intend to write a couple of comments on this report; this first one will exclusively document the dramatic decline in available wind power over Europe during the last 21 years.
1. The potential wind velocities over Europe.
This picture taking from a EEA report shows the mean wind speed over sea and land (I do not know if this a an average over a certain period neither at what height above ground it is measured, so let us take it simply as a rough indicator). Wind power in W/m2 is proportional to the cube of wind speed and to the air density (P = 1/2*density*speed**3), so to convert to W/m2 multiply the cube by 1.25 as the density of air is about 2.5). This gives approx. 1.25*1000 = 1250 W/m2 for offshore locations , and this number must be approximately divided by 3. The main unsurprising result is that offshore potential is much higher that onshore. Onshore potential at 5 m/s is only 5**3/10**3 = 0.5**3 = 1/8 of offshore potential.
2. The year 2012 with respect to the long time mean over 20 years
This picture from the report clearly shows that at most locations the 2012 wind potential is considerably lower than the 20 year mean: onshore locations in Germany are about 20% lower than this mean. The blue color describing lower potential is dominant if we neglect the offshore locations at great distances from shorelines.
3. The trend over 21 years for German locations.
The IWES report has another figure, that documents the real dramatic decline for various German wind power locations. I have digitized the curves relative to the coastal (“Küste”) and northern plain regions (“Norddeutsche Tiefebene”) using the wonderful UNSCAN-IT software, and calculated the linear trends:
This figure (modified fig.34 of the report) shows an eye-opening decline from 1992 to 2012, with the 2007 peak being a real exception. The trend lines have approximately the same slopes: at coastal and plain locations, potential wind power decreased by ~100 W/m2 (-29%), which gives a decrease of roughly -14% per decade (percentages calculated w.r. to the start point of the trend line) !
This is a very worrying trend for wind power, and one wonders why this trend is mostly ignored in the media and political discussions. The extreme increase in yearly added wind turbines masks this decline of the available resource. But if the installation of new turbines comes to a halt due to saturation, the negative trend (if it continues…) could well spell disaster for wind energy production and investors.
PS: The ZHAO et al. paper I referred to in a previous post finds a decline of -2.9% for wind velocity per decade (from 1978 to 2008). This results in approx. -24%/3 = -8% per decade in wind power (the divisor 3 represents very roughly the usual efficiency of wind turbines).
IWES: Windenergie Report Deutschland 2012. (link)
MASSEN F., 2013: Bad wind, lower wind power, exploding costs. (link)
MASSEN F,. 2011: Wind Power (link)
MASSEN F., 2011: Réflexions sur les éoliennes (link)
ZHAO et al: Is Global Strong Wind declining? Advances in Climate Change, 2011.
There is a lot of discussion in the blogosphere on the paper Cleaner air: Brightening the pollution perspective?” by O’Dowd et al. (paywalled!) which suggests that European warming of the last decade(s) is (also) caused by a sky brightening: the good results of air-pollution control lead to a rise in the negative radiative forcing of the aerosols (i.e. the negative forcing becomes less negative), and as a consequence solar irradiance at ground level increases. This increase is at least partially responsible for the observed warming.
Colin O’Dowd and co-authors have published a similar free-access article in issue 11 of the bulletin of Royal Irish Academy’s Climate Change Sciences Committee (here). Wang et al published in 2012 a paper “Atmospheric impacts on climatic variability of surface incident solar radiation” which essentially follows the same path.
What makes me uncomfortable, is that both authors clearly affirm that we have an ongoing solar brightening in Europe (brightening and dimming is a seen as a decadal change in solar irradiance). Here is a figure from Wang’s paper showing the situation in Europe:
The green line shows the anomaly (5 years smoothing applied) of solar irradiance, the blue of the inverted atmospheric optical depth (-AOT) and the red of the free (= cloudless) sky fraction. Clearly AOT declines after 2000, and solar irradiance increases.
O’Dowd et al conclude their investigation with “…the trends of reducing anthropogenic aerosol emissions and concentrations, at the interface between the North-East Atlantic and western-Europe, lead(ing) to a staggering increase in surface solar radiation of the order of ∼20% over the last decade.”
These are strong words, and paint a situation that is the contrary of what I have been measuring since about 15 years. Actually, in Diekirch (Luxembourg) we have an ongoing solar dimming since 1998, which has even become stronger after 2003 (the heat-wave year I would not dare to take as a starting point for a regression line!)
There also is no warming here, but we even measure a slightly cooling since 2002 (see here). What gives me some comfort that our measurements are not picked out of the blue, are the satellite data from Helioclim for Luxembourg (which alas stop at 2005):
Martin Wild from ETH (Zürich, Switzerland) is one of the world specialists in global dimming/brightening, and co-author of the Wang and Norris papers. He asserts that there was a dimming in Europe from 1950 to 1980, followed by two brightening periods of different magnitude from 1980 to 2000 and after 2000 (see here). So he is in consensus with the two other authors.
Assuming these authors correct, global European trends may clearly be very different from those of smaller specific regions. So one should be cautious to generalize a broad picture to regional scale, where the exact opposite might go on.
Let us conclude with another paper by Norris et al. “Trends in aerosol radiative effects over Europe inferred from observed cloud cover, solar ‘‘dimming,’’ and solar ‘‘brightening’’” which use the GEBA archive (Global Energy Balance Archive) and which give this picture:
The blue dots correspond to decreasing, the red to increasing irradiance. Now watch the right part and the legends: all crossed circles correspond to statistically not significant trends, and clear circles to a situation where 25% or more data are missing. If we leave out these measurements, not much remains in the 1987-2002 part which allows to conclude to a brightening. Here the right part magnified:
If you keep only the statistically significant points and those with enough data you have 3 cooling points (Germany, France, Bulgaria) and three brightening (2 in northern Italy and one in Finland), see the arrows. Not so impressive!
- Colin O’Dowd, Darius Ceburnis, Aditya Vaishya, S. Gerard Jennings, Eoin Moran : Cleaner air: Brightening the pollution perspective? AIP Conf. Proc. 1527, pp. 579-582; doi:http://dx.doi.org/10.1063/1.4803337 (4 pages)
- K. C. Wang, R. E. Dickinson, M. Wild, S. Liang: Atmospheric impacts on climatic variability of surface incident solar radiation. Atmos. Chem. Phys., 12, 9581–9592, 2012. http://www.atmos-chem-phys.net/12/9581/2012/ doi:10.5194/acp-12-9581-2012 (link)
- Joel R. Norris, Martin Wild: Trends in aerosol radiative effects over Europe inferred from observed cloud cover, solar ‘‘dimming,’’ and solar ‘‘brightening’’. JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 112, D08214, doi:10.1029/2006JD007794, 2007 (link)
The last 7 days from 01 to 07 August 2013 give a nice example of the increase of ambient air radioactivity with precipitation. During these days we had at Diekirch 3 very short precipitation events, which leave a visible fingerprint in the data series of the gamma Geiger counter:
We see that the short precipitation events (in blue on the top plot) correlate perfectly with activity peaks (in red on the bottom plot). The first event in the night of the 03 August has 3.4mm precipitation and an increase of radioactivity by about 19 nSv/h, to be compared to the “normal” increase for this period of the day of 3 nSv/h. So this rainfall event produced approx. a 500% higher radioactivity level. The 3 events are too few to look for a relationship; but obviously the greatest precipitation event also produced the highest radioactivity rise.
This phenomenon is well-known and usually attributed to radon washout, with radon daughters like the gamma emitter Pb214 gathering on the instrument in the wet rainwater film. After evaporation has removed this wet cover, levels return to normal.
I found some discussions on this effect here:
If you have more to say on this, thank you for a comment.
08 Aug 13: corrected units typing error: activity is nanoSv/h (nSv/h), not microSv/h (uSv/h)
10 Aug 13: Two readers sent me interesting comments (thank you!), and I will summarize these here with their tacit authorization:
Antoine KIES is a friend, emeritus professor of physics of the University of Luxembourg (Laboratoire Physique des Radiations), and a well known radon and ambient radioactivity specialist. He says this (translated from Luxembourgish): “This is a normal and well-known situation, as a short rain fall deposits the daughter products (as polonium, lead, bismuth) of radon which are attached to aerosols. As the periods of these radioactive daughters are short, the increase in measured gamma activity is a short peak. Precipitation can block the out gassing of radon from the soil, so usually one observes a minimum of activity when the soil is wet. The diurnal variation of ambient air activity is mostly caused by radon.”
Marcel Severijnen is a former head of the Environmental Monitoring Department of the Province of Limburg in the Netherlands and also has a climate blog. He writes (translated from German): “Twenty years ago I had in my room a terminal from the BMNI (Binnenlandse Zaken Meetnet Nucleaire Incendenten) which is a network with over 300 measuring stations (now integrated into the LMR (Landelijk Meetnet Radioactiviteit, see http://www.rivm.nl/Onderwerpen/N/Nationaal_Meetnet_Radioactiviteit/Resultaten). The peaks during heavy rain showers were always very visible, and represented something like a precipitation radar. Today values below 200 nSv/h are considered normal. Above this limit the RVIM makes an analysis of the situation and when 2000 nSv/h is reached, the local fire brigades are set on alert…”
The link to the Dutch network is very interesting. Luxembourg also has many “official” measuring stations (see here) but no website with real-time data (except our “unofficial” meteoLCD). Nevertheless monthly reports are available here.
The EEA has released a new report (#6/2013) “EU bioenergy potential from a resource-efficiency perspective“.
It makes for an interesting reading, as much of the hype found in earlier reports has quietly vanished and now makes place to more sober thinking.
The following figure shows the dramatic return to reality from the 2006 report and this one:
The report also shows quite clearly the problem of “carbon debt” when using forestry resources : when wood is burned, all the stored carbon is released in one CO2 pulse into the atmosphere, and this “debt” will be repaid only during the coming years when a mass equivalent to the burned one will have regrown. The authors concede that “… as a consequence, this report probably over-estimates the GHG mitigation from using forest biomass to generate energy“. This realism has to be applauded!
One of the most important aspects ILUC (indirect land use change) is now discussed quite heavily, and its importance made apparent. The authors also write ” Conversely, where biomass is derived from energy cropping, some bioenergy pathways lead to additional GHG emissions and other environmental impacts.”
Read this report, even if you are no great fan of bioenergy!
In this post I will reflect on the relationship between observed CO2 increase in the atmosphere and its relation to global temperature increase. Here I really can not quite see eye into eye with Prof. Salby.
First a note on terminology, which is regrettably imprecise: when Salby speaks of temperature, he means temperature anomaly dT; net CO2 emission is taken as the atmospheric mixing ratio in ppmV and the rate r as ppmV/year
1. Time series CO2 and global temperature anomaly.
In a first graph, Salby shows (and says so) that CO2 annual variations are proportional to the annual variations of dT:
In this graph, dT (Anomalous Temp) effectively seems to follow the pattern of the CO2 emission rate ( = yearly mixing ratio variation) EXCEPT during the last period from 2001 where clearly the relation-ship has changed. It is regrettable that Salby has not insisted on this departure from the usual pattern.
Let us check this graph using as in the previous post the MLO CO2 data from 1979 to 2012 and the NCDC land+ocean global temperature anomalies for the same period. A moving average of 13 months is applied before plotting.
There is quite a difference between the two figures; it seems that the CO2 data have been heavily smoothed in Salby’s plot; probably he also used yearly data only, and not monthly ones.
2. The proportionality of CO2 rate to the integral of temperature anomaly.
Salby says that the CO2 molecules emitted into the atmosphere (by both natural and human sources) will stay there for a very long time. In that case the net emission rate per year is equal to the delta(CO2) derived from atmospheric measurements. As he says that global temp. anomalies are (linearly) correlated to delta(CO2), this assumption gives the following relations (where the second is simply the mathematical conclusion from the first):
The oral explanations that Salby gives of the last (rather trivial) relation are a bit confusing; I listed carefully several times, but do not quite get the point when he explains the integral with the notion of “sum”.
To check this last relation, I will assume that the initial rate r is zero. Here are the steps of my calculations:
- the available monthly data series are divided into chunks of 12 months.
- from the CO2 data, compute the annual mean, and then the yearly delta (which reduces the 34 years period to 32 years, 1980-2011; this reduction comes from the use of the DADiSP delay function).
- from the temperature anomaly chunks, compute the sum for each year, which is the integral over that year
- now divide the delta(CO2) data by the sums, which should give the “constant” temperature sensitivity gamma.
Here is the figure with the results:
If we look at the full period, clearly the first 10 years (1980-1989) fall out. But restricting the computation to the last part (years 1990 to 2011) gives a “reasonable” constant sensitivity varying between 0.2 and 0.4 (unit is (ppmV/y)/(K).
The assumption about the linear correlation between deltaCO2 and temp. anomaly should be taken with a grain of salt (better with quite a lot of grains!). As a consequence temperature sensitivity does not seem a constant over longer periods, and this parameter should be handled like a hot potato. As many authors have speculated, the atmosphere is too complicated to be content with proportionalities i.e. linear relationships!
26 June 2013: some minor housekeeping in the text.
Prof. Murray SALBY presented his conference “Relationship between Greenhouse Gases and Global Temperature” the 18 April 2013 at the University of Hamburg (see Youtube version here and MP4 version here). His presentation was similar, but not identical to that I discussed in a previous post. It was quite technical in several parts (the video shows a very silent public, but this could simply show that German academics are well-mannered), but not overwhelming for someone who is familiar with the usual tools used in signal or time series processing. Nevertheless, it is good idea to go several times through this great presentation (the Quicktime player is handy for making precise stops at a certain slide), and to make some musings on several aspects.
1. The lag between observed CO2 and temperature changes.
In this first comment, I will compare some findings concerning the time lag between the observed measurements between CO2 and some of the global temperatures. I made several calculations myself, using the exceptional DADiSP software (which remains my favorite tool since many, many years).
Here is what Prof. Salby shows concerning the cross-correlation between CO2 and global temperature (colored elements added by me): CO2 levels lag temperature by about 8.5 months (temperature rises first, CO2 follows).
I made the same calculations using various monthly CO2 and temperature data for the 1979 to 2012 period: the seasonal detrended Mauna Loa CO2 data , the NCDC series of various monthly global temperature anomalies (ocean, land and ocean, land) and the RSS satellite data of lower troposphere temperature anomalies.
The next figure shows the cross-correlation between CO2 and the NCDC ocean temperature (SST anomaly):
The lag between SST and CO2 is 13 months: temperature first rises, and 13 month after its (statistical) maximum, CO2 reaches its next peak value.
Prof. Ole Humlum (from the climate4you blog) and co-authors published in “Global and Planetary Change 100 (2013) 51–69″ a paper “The phase relation between atmospheric carbon dioxide and global temperature” (pay-walled, see abstract here). Using a different calculation method, they too find CO2 levels lagging temperature.
The following table summaries the different findings:
The RSS cross-correlation in the last row has a first miniscule peak at 12 months lag, and a next one at 15 months.
Normalizing the correlations (using the XCORR function of DADiSP) gives the following cross-correlation maxima for the NDC and RSS series: NCDC land: 0.64, NCDC ocean: 0.77, NCDC land + ocean: 0.77 , RSS lower troposphere: 0.59
These numbers (to be compared to the Salby 0.5 maximum) show that one should use either SST alone, or the global land plus ocean series. The satellite derived lower troposphere anomalies seem to be less influential in documenting the CO2 changes.
All these lags are of the same sign, i.e. all point to an observed temperature rise preceding the CO2 rise. This would invalidate the essential IPCC “consensus” that atmospheric CO2 levels are the primary drivers of global temperature change. The lags found above are a hint that temperature change is the (or at least one of others) cause, and CO2 change the effect, and not the other way around.
2. First conclusion
The Salby, Humlum and my own calculations all show that global temperature change is not driven by atmospheric CO2 mixing ratio, but that statistically speaking, it is the inverse: if temperature rises, CO2 follows. This lag has been found for instance in the Vostok ice core series, albeit with much longer delays (about 800 years). Our short term observations simply document the well known physical effect that a warmer ocean will absorb less CO2 than a colder one. Hardly surprising!
What can not be deduced from these correlations is that the CO2 increase in the atmosphere has a predominant natural origin. More on this in a next comment.
PS: The Humlum paper has not been well received by different researchers. M. Richardson has a comment in print (pay-walled, see abstract here) that seems to show that Humlum’s method violates conservation of mass. A second critique is that it can not be shown that the natural contribution to atmospheric CO2 levels is distinguishable from zero. More on this in a next comment.