Data trends at meteoLCD: 1998 to 2016 (update finished)
Trends computed from yearly averages at meteoLCD,
Graphs may be freely copied and used, under the condition to cite:
MASSEN, Francis: Data trends at meteoLCD, 1998 to 2016. http://meteo.lcd.lu
Older trends are here!
Attention: in all trend equations (y = a+b*x) the variable x represents the year, with x = 1 for the first year in the trend period.
Most important conclusions from 1998 (2002, 2004) to 2016 linear trends:
1. Noticeable solar dimming since 2004, sunshine
duration decreases by -126
2. Local temperatures show slight warming of 0.017°C/y since 2002
3. DTR trends since 2002 and for last decade remain flat
4. The winter trend since 2002 shows a warming of +0.7 °C*decade-1
5. Since 2002 ground O3 trend is flat, thickness of ozone layer slightly decreases by 5 DU*decade-1
6. Local CO2 mixing ratio increases by approx. +2 ppmV*year-1 from 2013 to 2016
7. The biologically effective UVB dose is very slightly increasing since 2004 (and since 1998)
8. The UVA dose is slightly decreasing since 2004
9. Precipitation (rainfall) shows a sinusoidal pattern; over the last 2 full periods 2005-2016 the trend is +5.2 mm/y
10. Energy content of moist air (enthalpy) declines by -0.7 kJ*kg-1*decade-1
NO/NOx measurements are discontinued in 2014 and 2015; reintroduced in 2016 (30% missing hours).
Mean and stdev of the year 2016: 39.9 +/- 31.2
Ozone Column [DU]
Mean and stdev of the year 2016: 317.9 +/- 45.4
minimum : 219.0 (12 Nov)
maximum: 422.0 (24 Apr)
Uccle (Brewer 16&178, DS only): 331.1 +/- 41.4
Trendlines (start year is x =
multiplier to apply to the Diekirch DU data :
mixing ratio in ppmV
Mean and stdev of the year 2015: 407.6 +/- 4.9
The 1998-2001 data are too unreliable to be retained
for the trend analysis.
The second picture zooms on the last 4 years, and
gives the readings of Diekirch, Mauna Loa (MLO) and Hohenpeissenberg (HPB,
only from 2013 to 2015, 2016 data not yet available). Note the very
different elevations! Mauna Loa has no vegetation at all, Diekirch and HPB
similar grass and forests.
The CO2 data (monthly averages) often show the summer-time lows and
winter highs, which reflect the impact of variable seasonal photo-synthesis (see here).
A simple 12
month periodic sinus pattern was found in 2014 and 2015.
Actually, as shown in addendum 3, the CO2 lowering intensity of wind
speed seems to be an important modifier of this pattern, possibly masking the effect (or
better: the non-effect) of photosynthesis. This happened in 2016, as the
seasonal swing is much less sinusoidal, and only a sharp minimum in August
can be seen.
Mean and stdev of the year 2016
(from monthly averages):
1998 to 2016 :
10.37 +/- 0.48 °C
sensor location has not been moved since 2002! The old thermistor sensor has
been replaced by a PT100
(see comments in 2015_only.xls); new 4-20mA
amplifier (with calibration) installed the 4th May 2016.
Range (DTR) [°C]
DTR = daily max - daily min temperature
Mean DTR (
For 2002 to 2016: all trends are practically flat (DTR
would diminish by 0.17°C/century, which is insignificant)
Values of DJF temperature of the year 2016:
Contrary to what is often suggested in the media, winters were cooling since 2002 to 2013. The cooling trend (about -0.5 °C/decade) has now reversed into a slight warming.
Trends from 2002 to 2016 (2016 was a very strong El Nino year!):
The plot shows the mean temperatures of
December (from previous year), January and February. It also shows in
brown the NAO index for the months Dec to Feb 
Enthalpy of moist air in kJ/kg
Mean moist enthalpy of 2016: 30.72 +/- 14.41 kJ/kg
See  on how the energy content of moist air is
calculated. Several authors, (e.g. Prof. Roger Pielke Sr.) insist that air
temperature is a poor metric for global warming/cooling, and that the energy
content of the moist air and/or the Ocean Heat Content (OHC) are better
Yearly Rainfall [mm]
Values of rainfall (precipitation) of the year 2016:
1998 to 2016 mean +/- stdev: 695.5 +/- 136.5 mm
The negative trend from 1998 to 2015 seems spectacular:
-120 mm/decade, which comes from the very high values of 2000 and 2001.
Clearly precipitation shows an oscillation pattern, so linear trends should be taken with precaution. A good model for the Diekirch data is a sinus function of 5.35 years period (~64 months, R2 = 0.62; see lower graph). If we take the period 2005 - 2016 corresponding to 2 full periods, the linear trend becomes positive with +5.2 mm/y !
The same model suggests a similar period of 5.73
years for the Findel precipitation pattern (R2 = 0.52)
The third plot shows both the Findel and Diekirch annual precipitation, with the averages as dotted lines. Clearly the Findel readings are always higher, which seems normal considering the exposed situation at Findel airport versus Diekirch situated at the bottom of a valley (the elevation at Findel is also higher by 156 m ).
energy on a horizontal plane
Values of total solar energy
of the year 2016:
1998 to 2016 mean +/- stdev: 1107.1 +/- 44.9 kWh/m2
(meteoLCD values derived from pyranometer data by Olivieri's method)
Values of sunshine hours
of the year 2016:
The decline from 2012 to 2013 is -10.8%, to be compared to the data from the Fraunhofer Institut which gives a decline of -10.6 % of the German PV "Volllasttunden" . For a graph on the evolution of the German PV capacity factors click here.
 by F. Massen
comparing 4 different methods to compute sunshine duration from pyranometer
This graph shows the plots of the four above-mentioned stations. It should be noted that meteoLCD (Diekirch) is located in a valley, Findel, Trier and Maastricht airport on top of a plateau. The Findel totals are much higher than those of the other stations, which certainly is also partially caused by the use of the Campbell-Stokes instrument known to give too high readings (in July and August the excess of Findel readings was highest).
All 4 stations give totals that practically always vary in the same manner (synchronous increase and decrease).
eff. UVB dose on a horizontal plane in kWh/m2
Erythemal UVB dose of the year 2016: 0.132 KWh/m2
mean +/- stdev:
1998 to 2016: 0.130 +/- 0.008 eff. kWh*m-2y-1
2004 to 2016: 0.130 +/- 0.005
Trends over 1998-2016 and 2004-2016 are the same, are practically flat!
From 2002 to 2016, the trend is slightly negative (-0.0002 eff. kWh*m-2y-1); this is compatible with the small decrease in TOC (total ozone column). Several comments  have shown that the RAF (radiation amplification factor) at Diekirch is about 1.0. If we apply the RAF formula to the start and end-points of the 2002-2016 trendlines of UVBdose and TOC we get 1.006 = ~1
dose on a horizontal plane in kWh/m2
UVA dose of the year 2016: 52.7 KWh/m2
(some problems with internal temperature stabilization of the sensor)
mean +/- stdev:
The 2 independent measures of solar energy and UVA doses all point to a slight solar dimming since 2004.
NO and NO2
concentration in ug/m3
(End of measurements useable for trends in 2013. No trends will be calculated for this year!)
70% of possible measurements available due to sensor downtime!
see  which gives ~30% reduction from 1990 to 2005 for the EU-15 countries.
|1||Europe's Environment 4th AR (2007) Fig. 2.2.3 http://reports.eea.europa.eu/state_of_environment_report_2007_1/en/Belgrade_EN_all_chapters_incl_cover.pdf|
|2||EPA: Ozone trends. http://www.epa.gov/airtrends/ozone.html|
Jonson et al: Can we explain the trends in European ozone levels? Atmos. Chem. Phys. Discuss., 5, 5957–5985, 2005. http://www.atmos-chem-phys-discuss.net/5/5957/2005/acpd-5-5957-2005.pdf
|4||Ozone trends at Uccle http://ozone.meteo.be/ozone/trends.php|
|5||Rebetez, Beniston: Analyses of the elevation dependency of correlations between sunshine duration and diurnal temperature range this century in the Swiss Alps. 1998.|
|6||R.G. Vines, CSIRO: European rainfall patterns. International Journal of Climatology, vol.5, issue 6, p. 607-616.|
|7||http://global-warming.accuweather.com (15 Jan 2009).|
|8||J.W. Krzyscin, J.L.Borkowski: Total ozone trend over Europe: 1950 - 2004. ACPD, 8, 47-69, 2008.|
|9||NASA: Solar Physics: The Sunspot Cycle.|
|10||de Backer et al: ftp://ftp.kmi.be/dist/meteo/hugo/posters/20080630tromso_hdb.pdf (temporarly unavailable)|
|11||EEA: Emission trends of NOx 1990 - 2005|
|12||L. Motl: http://motls.blogspot.com/2009/12/uah-msu-temperatures-for-2009-and.html . Dec.2009|
|13||K. Makovski: The daily temperature amplitude and surface solar radiation..Dissertation for the degree of doctor of sciences. ETHZ 2009.|
|14||A. Ohmura: Observed long-term variations of solar irradiance at the earth's surface. Space Science Reviews (2006) 125: 111-128|
|15||J. van Oldenvorgh: Western Europe is warming much faster than expected. Clim.Past. 16Jan.2009|
|16||Van Malderen, De Backer, Delcloo: Revision of 40 years of ozone measurements in Uccle, Belgium. Poster, EGU2009, Vienna.|
|17||EEA: Air pollution by ozone across Europe during summer 2009|
|18||Climate4 you: Global temperature trends|
|19||Lindzen & Choi: On the determination of climate feedback from ERBE data (GRL, 2009)|
|20||Scafetta, N.: Empirical analysis of the solar contribution to global mean air surface temperature change. Journal of Atmospheric and Solar-Terrestrial Physics, 2009 (doi:10.1016/j.jastp.2009.07.007)|
Massen, F., Beck, E. :Accurate
estimation of CO2 background level from near ground
measurements at non-mixed environments
in: Leal, W., editor: The Economic, Social and Political Elements of Climate Change
Climate Change Management, 2011, Part 4, 509-522. Springer. DOI: 10.1007/978-3-642-14776-0_31
|22||De Backer & Van Malderen: Time series of daily erythemal UVB doses at Uccle Belgium. Poster, July 2009.|
|23||Massen, F.: Sunshine duration from pyranometer readings, 2011|
|24||Massen F., Calculating moist enthalpy from usual meteorological measurements (July 2010) and Calculating moist enthalpy revisited (Sep. 2010)|
|25||CDIAC: Online Trends|
|26||UAH MSU data: http://vortex.nsstc.uah.edu/public/msu/|
|27||Vigouroux et al: Evaluation of ozone trends from g-b FTIR observations. Atmos. Chem. Phys., 8, 6865–6886, 2008|
UNEP, Scientific Assessment: Stratospheric Ozone and
Surface Ultraviolet Radiation
|30||K. Makowski: The daily temperature amplitude and surface solar radiation. Dissertation ETH Zürich #18319, 2009|
|32||Tim Osborne: NAO data (http://www.cru.uea.ac.uk/~timo/datapages/naoi.htm)|
|33||Helioclim satellite measurements of solar irradiation at http://www.soda-is.com/eng/services/services_radiation_free_eng.php|
|36||Fung: A Hyperventilationg Biosphere (Sep. 2013)|
Fraunhofer Institut Stromproduktion : http://www.ise.fraunhofer.de/de/downloads/pdf-files/aktuelles/stromproduktion-aus-solar-und-windenergie-2013.pdf
|38||EEA interacive map. http://www.eea.europa.eu/themes/air/interactive/no2|
|39||Portail de l'Evironnement: http://www.environnement.public.lu/air_bruit/dossiers/PA-reseaux_mesure_air/reseau_automatique/resultats_mesures_live/index.html|
|41||Amplitude of the atmosphere's seasonal CO2 cycle . CO2science|
|42||Fung et al. : The changing carbon cycle at Mauna Loa observatory|
|43||Zeng et al.: Agricultural green revolution as a driver of increasing atmospheric CO2 seasonal amplitude (2014)|
|44||Zeng: The changing CO2 seasonal cycle (presentation, 2014)|
|45||Sceptical Science Trend Calculator : https://www.skepticalscience.com/trend.php|
|46||Kämpfe, Kowatsch: Winter 2014/15 in Deutschland: Erneut zu mikd - warum ?|
|47||NOAA Climate Prediction Center: http://www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/nao.shtml|
|48||Hohenpeissenberg Klimagase: http://www.dwd.de/DE/forschung/atmosphaerenbeob/zusammensetzung_atmosphaere/spurengase/inh_nav/klimagase_node.html|
|49||meteo.be: solar irradiance Uccle: http://www.meteo.be/meteo/view/fr/23023844-2015.html|
|50||Francis Massen: Ozone, change is the norm! https://meteolcd.wordpress.com/2015/10/26/the-total-ozone-column-change-is-the-norm/|
|51||El Nino's and La Nina's years and intensities: http://ggweather.com/enso/oni.htm|
|52||Solar cycle progression : http://services.swpc.noaa.gov/images/solar-cycle-sunspot-number.gif|
|53||Meteo data from all DE and NL stations: http://wetterzentrale.de (click on Archiv)|
|54||Massen, F. : First Radiation Amplification factor for 2016|
|55||Massen.F, Zimmer M.: Comparing the year 2016 Total Ozone Column measurements at Uccle and Diekirch (pdf)|
|Lindzen & Choi  define the non-feedback
climate sensitivity as ΔT0 = G0*ΔF, where G0
= 0.25 Wm-2 and ΔF is the change in radiative forcing.
A change in solar irradiance of -0.82 kWh*m-2y-1 (decade 2005 to
2014) corresponds to ΔF
= - 820/8760 = -0.09 Wm-2 and should yield a cooling of ΔT0
= -0.25*0.09 = -0.02 K (or °C).per year. The meteoLCD measurements
give a cooling of 0.0057 Ky-1, about 3 times less.
Scafetta  defines a climate sensitivity in respect to changes in solar radiation by k1s = ΔT/ΔF and finds k1s = 0.053. Our data for the decade 2005 to 2014 give ΔT/ΔF= - 0.0057/(-0.09) = 0.06, a value close to that of Scafetta!.
Summary for the 2005 to 2014 decade:
|It makes for an interesting exercise to compare
the influence of mean yearly solar forcing on moist enthalpy and air
temperature for the decade 2005 to 2014.
analysis of the seasonal CO2 pattern in 2014.
The mean monthly CO2 data show an oscillatory pattern which can be modeled by a 6 month period sine wave. This is not consistent with the commonly admitted explication that the summer lows and winter highs are a fingerprint of changing photosynthesis, which should lead to a single annual sinus wave (as in 2013).
The 6 month period is essentially caused by the low Jan, Feb and Dec values, and is replaced by the usual 12 period if these months are omitted.
The right figure shows the monthly mean CO2 and monthly mean wind speeds. Clearly low wind goes with high CO2, independent of the seasons (significant correlation R = -0.86 !)
The next figure gives the CO2 mixing ratios versus the monthly mean wind speed; the usual exponential model beautifully describes this pattern. The horizontal asymptote of 395.5 ppmV should correspond to the background CO2 level, as shown in .
There is some debate about the (global) changes of the seasonal CO2 amplitude, which seems to increase due to global greening , agricultural green revolution , changing air trans-continental circulation  and possibly other unknown factors. Look also at the presentation .
Locally it seems that the effects of higher/lower wind speeds and photosynthesis are difficult to untangle. If we restrict our data to those days where the mean wind speed is less than 1, the correlation between CO2 and wind speed is lower (-0.76) but still significant.
Curiously all the papers studying this seasonal amplitude problem seem to ignore the influence of changing wind speeds.
analysis for 2015
Here again higher wind speeds usually go together with lower CO2 levels (notice the exception on March!), but the monthly mean values do not follow the usual model well.
If we take all 17520 individual measurements, the picture becomes clearer, and we find that our "bumerang" model follows reasonably well the overall pattern. The horizontal asymptote suggest a background CO2 level of about 389 ppmV, which seems a bit low.
analysis for 2016 (wind speed from cup anemometer)
The high wind speeds lower the January , February (and December) values which normally should be higher; so the "usual" sinus pattern with a trough during the summer months is mostly absent.
Using all CO2 measurements of the year, we find again our boomerang pattern; the usual model has a better R2 than in 2015, but the asymptotic value of 383 is definitively too low!
02 Jan 2017: Start of update to include 2016 data.