Data trends at meteoLCD: 1998 to 2014
Trends computed from yearly averages at meteoLCD,
Diekirch, Luxembourg.
Graphs may be freely copied and used, under the condition to cite:
MASSEN, Francis: Data trends at meteoLCD, 1998 to 2013. http://meteo.lcd.lu
Older trends are here!
Most important conclusions for the last decade (from 2005 to 2014 linear trends); percentages are (yearly trend)/(start-value)*100
1. Solar dimming is -17 kWh*m-2*decade-1
[- 0.15 %], sunshine duration -186
hours*decade-1
[-1%]
2. Local temperatures are practically flat (-0.057 °C*decade-1) [
-0.6%]
3. There is a small positive trend in DTR (daily max.
increase more than daily min.)
4. The winter cooling trend has reversed from last year and shows now a slight warming of +0.7 °C*decade-1
5. Ground O3 increases by 10 ug*m-3*decade-1
[+ 3%], thickness of ozone layer decreases by
5.4 DU*decade-1 [-0.16%]
6. Local CO2 mixing ratio decreases by 0.8 ppmV*decade-1
(suspicious!), increases by +5.4 ppmV*decade-1
from 2002 to 2014
7. The biologically effective UVB dose remains
constant.
8. The UVA dose declines by 0.42 kWh*m-2*y-1
[-0.7%]
9. Precipitation (rainfall) increases by 154 mm*decade-1
(rainfall seems periodic!)
10. Energy content of moist air (enthalpy) declines by -2.2 KJ*Kg-1*decade-1
[-0.8%]
NO/NO2 measurements are discontinued in 2014. No more updates to the
1998-2013 series.!
Ground
Ozone [ug/m3] ("bad ozone") From 1998 to 2014: negative trend: -0.5 ug/m3 per year Mean
+/- stdev:
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Total
Ozone Column [DU] ("good ozone") Mean +/_std of 2014: 328.2 +/- 40.3 DU (Uccle gives +0.95 for the 1998-2010 period) (see also [16]) Trendlines (start year is x = 0): 1998 to 2014: 312.12 +1.47*x 2002 to 2014: 330.25 - 0.14*x 2005 to 2014: 332.18 - 0.54*x (Uccle gives +0.95DU*y-1 for the 1998-2010 period) (see also [16])
Calibration
multiplier to apply if Uccle Brewer #16 is the reference: 1998 to 2012 mean
+/- stdev: |
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CO2
mixing ratio in ppmV The 1998-2001 data are too unreliable to be retained
for the trend analysis. The sharp plunge in 201 should be taken with caution;
there was a change in the calibration gas the 21 Jan. and the primary
standard used (600 ppmV) has an accuracy of 1%. The trends from 2009 to 2011
and 2013 to 2014 are relatively close: 2.3 and 1.7 ppmVy-1 , so
the down to the 2013 value or the higher preceding values could be a
artifact (a bias problem). The blue line shows the slight negative trend (
-0.08) of the last decade; use this with care! This paragraph and figure not
yet updated as the MLOand other data are not yet available!
The 2013 CO2 data clearly showed the summer-time lows and
winter highs, which are assumed showing the impact of increased
photo-synthesis (see here). This simple 12
month periodic sinus pattern does not hold for 2014, but a 6 month period
sinus is an acceptable model (the figure shows the monthly averages).
Actually, as shown in addendum 3, the intensity of wind speed seems
to be an important driver of this pattern (as visible from the low CO2
values during the winter months) masking the effect of photosynthesis.
If we omit the Jan, Feb and Dec months, we find again the "classic" sine wave, now with an amplitude of 11 ppmV (or a total swing of 22 ppmV, the double of 2013), which is close to the 20 ppmV found at the stations Hohenpeissenberg (HPB) and Ochsenkopf (OXK) in 2013. |
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Air
temperature [°C]
Trend from 1998 to 2014: +0.0045 °C per year, practically flat! Mean temperatures (+/- stdev):
1998 to 2014 :
10.33 +/- 0.47 °C The sensor
location has
not been moved since 2002! There were 2 sensors replacements during 2014
(see comments in 2014_only.xls). |
|
Diurnal
Temperature Range (DTR) [°C]
DTR = daily max - daily min temperature |
. |
Winter
temperatures [°C] 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. Diekirch: +0.30 °C/decade since
2002 The plot shows the mean temperatures of
December (from previous year), January and February. It also shows in
brown (right Y-axis) the NAO index for the months Dec to Mar [32] (2014
only DJF) |
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Total
Yearly Rainfall [mm]
1998 to 2014 mean +/- stdev: |
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Solar
energy on a horizontal plane
1998 to 2014 mean
+/ std: |
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Sunshine
duration (derived from pyranometer data by Olivieri's method)
Totals for 2014: The decline from 2012 to 2013 is -10.8%, to be compared to the data from the Fraunhofer Institut which give a decline of -10.6 % of the German PV "Volllasttunden" [37]
See paper
[23] by F. Massen
comparing 4 different methods to compute sunshine duration from pyranometer |
|
Biologically
eff. UVB dose on a horizontal plane in kWh/m2
Practically flat trend line for the whole period.
mean +/- stdev: All trends are essentially flat: See
[10]
and [22] (poster finds slight
positive trend in June (+2%) and negative trend in August (-1%), no trend
for other months, for period 1991 to 2008) |
|
UVA
dose on a horizontal plane in kWh/m2 mean +/- stdev: 1998 to 2013 54.3 +/- 4.8 kWh*m-2*y-1 2004 to 2013: 54.7 +/- 4.1 Trends: 1998 to 2014: + 0.07 kWh*m-2*y-1 2004 to 2014: - 0.28 2005 to 2014: - 0.42 The 2 independent measures of Solar energy, and UVA dose all point to a solar dimming since 2004. |
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Enthalpy of moist air in kJ/kg See [24] on how the energy content of moist air is
calculated. Several authors, as 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. |
|
NO
concentration in ug/m3 (end of measurements in 2014. This part will not be updated anymore!) The 1998-1999 data are too unreliable to be retained. 2000 to 2013: trend: - 0.3 ug*m-3*y-1 see [11] which gives ~30% reduction from 1990 to 2005 for the EU-15 countries. |
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NO2
concentration in ug/m3
(end of measurements in 2014. This part will not be updated anymore!) The 1998-1999 data are too unreliable to be retained. 2000 to 2013: trend: + 0.3 ug*m-3*y-1 Many missing data from 2011 to 2013 ( 25%, 21% , 8%) so be careful! All these concentrations are low! Luxembourg-City has a background of 58 and rural Vianden (Niklausberg) one of 9.4 (average since 1988) [38]
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References:
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 |
3 |
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) |
21 |
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
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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 |
28 |
UNEP, Scientific Assessment: Stratospheric Ozone and
Surface Ultraviolet Radiation http://ozone.unep.org/Assessment_Panels/SAP/Scientific_Assessment_2010/04-Chapter_2.pdf |
29 | http://berkeleyearth.lbl.gov/regions/luxembourg |
30 | K. Makowski: The daily temperature amplitude and surface solar radiation. Dissertation ETH Zürich #18319, 2009 |
31 | http://de.wikipedia.org/wiki/Zeitreihe_der_Lufttemperatur_in_Deutschland#Winter |
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 |
34 | http://www.esrl.noaa.gov/gmd/ |
35 | http://www.atmos.ucla.edu/~qli/publications/Jiang_2011_GBC.pdf |
36 | Fung: A Hyperventilationg Biosphere (Sep. 2013) |
37 |
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 |
40 | Wetterkontor: http://www.wetterkontor.de/de/monatswerte-station.asp |
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 ? |
Addendum
1 2014 update! |
Lindzen & Choi [19] 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 [20] 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:
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Addendum
2 2014 update! |
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.
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Addendum (new for 2014) |
A short
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 [21]. There is some debate about the (global) changes of the seasonal CO2 amplitude, which seems to increase due to global greening [41], agricultural green revolution [43], changing air trans-continental circulation [42] and possibly other unknown factors. Look also at the presentation [44]. 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. |
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file: meteolcd_trends.html
francis.massen@education.lu
last revision: 01 Mar 2015