Data trends at meteoLCD: 1998 to 2015 (update done)


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 2015. 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 year 1998

 

Most important conclusions from 1998 (2002, 2004) to 2015 linear trends: (black lines not yet updated!)

1. Only small Solar dimming since 2004, sunshine duration decrease is -35 hours*decade-1
2. Local temperatures are practically flat since 2002
3. DTR trends since 2002 remains flat since 2002
4. The winter trend since 2002 shows a warming of +0.5 C*decade-1
5. Since 2002 ground O3 trend is flat,
 thickness of ozone layer slightly decreases by 2.6 DU*decade-1
6. Local CO2 mixing ratio increases by approx. +19 ppmV*decade-1 from 2009 to 2015
7. The biologically effective UVB dose is slightly decreasing since 2004
8. The UVA dose is slightly decreasing since 2004
9. Precipitation (rainfall) decreases by 29 mm*decade-1 since 1998 (rainfall seems periodic, so this trend could be meaningless!)
10. Energy content of moist air (enthalpy) declines by -2.2 kJ*kg-1*decade-1
 
NO/NO2 measurements are discontinued in 2014 and 2015. No more updates to the 1998-2013 series.!

Ground Ozone [ug/m3]
("bad ozone")

Mean and stdev of the year 2015: 46.9 +/- 34.4   

Mean +/- stdev:
1998 to 2015: 39.0 +/- 6.8 ug/m3
2002 to 2015: 36.0 +/- 6.1

Trends 1998 - 2015: -2.8 per decade
             2002 - 2015:  0.1 per decade (flat trend line)  

Watch the left scale to note that trends are very small!

 

See [1] [2] [3] [17]

Total Ozone Column [DU]
("good ozone")

Mean and stdev of the year 2015: 324.2 +/- 42.7
minimum : 220.6 (5 Nov)
maximum: 445.6 (18 Apr)

Trendlines (start year is x = 1):
1998 to 2014:
312.08 +1.24*x  (+12.4 DU/decade)
2002 to 2014: 332.04 - 0.26*x  (- 2.6 DU/decade  )

(Uccle
 gives +0.95DU*y-1  for the 1998-2010 period) (see also [16])

Calibration multiplier to apply if Uccle Brewer #178 is the reference:
2015              : * 1.033 (provisional, many Uccle data not yet available)

2
015 common 107 days measurements results:
Diekirch   = 326.2 DU
Uccle DS = 337.6 DU (update when all Uccle data are available)


See [4] [8] ([8] shows strong positive trend starting 1990 for latitudes 45-75 North, Europe): [27] give +1.32 DU/y at the Jungfraujoch for 1995-2004.
See also recent EGU2009 poster [16].

CO2 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.

Trendlines (1998 is x = 1):
2002 to 2015:
403.0 + 0.40*x    (+   4.0 ppmV/decade)
2002 to 2012: 394.9 + 1.35*x   (+ 13.5 ppmV/decade)
2013 to 2015: 372.9 + 1.87*x    (+ 18.7 ppmV/decade)
 

The sharp plunge in 2013 should be taken with caution; there also was a change in the calibration gas the 21 Jan. 2014
The Mauna Loa 2015 average is 400.83 ppmV, the trend for the 2013 to 2015 period is about 15 ppmV/decade [34]
The German Hohenpeissenberg trend for the 2010 to 2015 period is 17 ppmV/decade, very close to the 2013-2015 meteoLCD trend of 18.7[48]
                                       

The second picture shows the asymptotic CO2 values (CO2wind) derived from the model published in [21] .
The blue upper curve shows the yearly mean values at Diekirch; the middle red curve the asymptotic CO2 values that would exist if wind velocity was infinite, and the lower green curve the yearly averages at Mauna Loa, augmented by +1.8 ppmV to respect the latitudinal gradient of approx. 0.06 ppm per degree.
The yearly trends calculated from the yearly mean and the asymptotic values at Diekirch are very similar to the MLO trend of 2.08 for the last 3 years:

MLO:                    +2.08 ppmV/year
Diekirch CO2:        +1.87 ppmV/year
Diekirch CO2wind: +1.90 ppmV/year

Trends are also similar for the period 2009 to 2012 (see the thin trend lines).
 

The CO2 data (monthly averages) clearly show the summer-time lows and winter highs, which reflect the impact of variable seasonal photo-synthesis (see here). This simple 12 month periodic sinus pattern was also found in 2014. Actually, as shown in addendum 3, the CO2 lowering intensity of wind speed seems to be an important modifier of this pattern  (as visible from the low CO2 values during the Jan and Feb months), possibly masking the effect (or better: the non-effect) of photosynthesis.
 

If we omit the Jan and Feb months, we find the "classic" sine wave, with an amplitude of 11 ppmV (or a total swing of 22 ppmV), which is close to the 20 ppmV found at the stations Hohenpeissenberg (HPB) and Ochsenkopf (OXK) in 2013. The 12 month periodic sinus model is rather good, with an R2=0.66.

.

 

 

 

 

 

 

Air temperature [C]

Mean and stdev of the year 2015 (from monthly averages):
Diekirch: 10.15 +/- 5.72 
(10.20 from all half-hour readings)
Findel:     10.36 +/- 6.48


Mean temperatures (+/- stdev):

1998 to 2015 : 10.33 +/- 0.46 C                
2002 to 2015 : 10.37 +/- 0.49 C
2006 to 2015 : 10.40 +/- 0.56 C (last decade)

The sensor location has not been moved since 2002! The old thermistor sensor has been replaced by a PT100 (see comments in 2015_only.xls).

Trends  from 2002 to 2015:
meteoLCD:      -0.03C/decade
Findel:              +0.11C/decade


Latest Global temperature anomaly trends for same period:
UAH (satellite)   : + 0.05C/decade   [45]
RSS (satellite)   : - 0.062C/decade
CRU (Hadcrut4): + 0.013C/decade

Highest decadal Central England warming trend from 1691 to 2009: +1.86C/decade for 1694-1703!
See also [15] (which may be obsolete)

Diurnal Temperature 
Range (DTR)  [C]

DTR = daily max - daily min temperature

Mean and stdev of the year 2015 (from monthly averages):
Diekirch: 8.76 +/- 3.36 
(8.79 from all half-hour readings)
Findel:     7.75 +/- 2.81

Mean DTR ( +/- stdev):
1998 to 2015:
 8.53 +/- 0.55
2002 to 2015:  8.65 +/- 0.57
2006 to 2015:  8.59 +/- 0.47 (last decade)

For 2002 to 2015: all trends are practically flat.
Findel DTR trend is  flat from 2004 to 2015.


A fingerprint of climate warming is that daily minima increase more rapidly than daily maxima so that the DTR trend should become negative. Clearly the data do not show this neither at Diekirch nor at the Findel.

The BEST data set for Luxembourg [29] stops at 2013.

See [5], [13] and [30]

.
Winter temperatures [C]

Values of DJF temperature of the year 2015:
Diekirch: 3.63
Findel:     1.73

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:   +0.5 C/decade since 2002
Findel:       +0.1 C/decade
Germany:  +0.3  C/decade [46]
NOA:         +0.5 C/decade (NOA normalized index)

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 [47]

The North Atlantic Oscillation clearly influences our winters (but note the 2014 year exception!); the correlations between the 3 different DJF temperature series and NAO normalized index are 0.54, 0.40 and 0.60, all except the second (Findel) significant at the 5% level. The NAO index trend is equal to the Diekirch trend.

Total Yearly Rainfall [mm]

Values of rainfall (precipitation) of the year 2015:
Diekirch: 575.6
Findel:     630.4

1998 to 2015 mean +/- stdev: 700.7 +/- 138.4 mm 
2002 to 2015 mean +/-stdev:  655.1 +/_108.9 mm
 

The negative trend from 1998 to 2015 seems spectacular: -123.5 mm/decade, which comes from the very high values of 2000 and 2001.
The 2002-2015 period suggests a more constant pattern and shows a much lower trend of -28.5 mm/decade
.

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 5.38 years period (R2 = 0.54) (see lower graph).

The same model  suggests a similar period of 5.78 years for the Findel precipitation pattern (R2 = 0.43)

[6]
gives short term periods of 6 to 7 years for the Western European region.

 

Solar energy on a horizontal plane

Values of total solar energy of the year 2015:
Diekirch: 1127.3 KWh/m2
Uccle:      1111.7    [49]

1998 to 2015 mean: 123.92 W/m2 = 1085.5 kWh/m2
2002 to 2015 mean: 124.02 W/m2 = 1086.4 kWh/m2


Visible negative trend: 1998 to 2015: -17.6 kWhm-2/decade
(not surprising with exceptional 2003 peak!)
Nearly flat trend from 2004 to 2015   : -1.8 kWhm-2/decade
(actual solar cycle #24 begins Jan. 2009).

(see Addendum 1 for calculations of radiative forcing and solar sensitivity, addendum 2 for detecting a solar influence on temperature and moist enthalpy)

Helioclim satellite measurements show ongoing solar dimming over Luxembourg for 1985 to 2005  [33] (see graph)
[14] finds 0.7 Wm-2y-1 for West-Europe 1994-2003 , meteoLCD +1 Wm-2y-1 for 1998-2003.See also [9]

Sunshine hours  
(meteoLCD values derived from pyranometer data by Olivieri's method)

Values of sunshine hours of the year 2015:
Diekirch:     1550 hours (215m asl)
Findel:         1796 hours (365m asl, Campbell- Stokes)
Trier:            1652 hours (279m asl)
[40] (Diekirch total used for missing May data)
Uccle:          1734 hours (100m asl)


Negative trends:
1998 to 2015: - 116 hours/decade
2004 to 2015: -   35 hours/decade

Note that negative trend has diminished (nearly flat since 2004).

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
 

 

The next graph shows the plots of the four above-mentioned stations. It should be noted that meteoLCD (Diekirch) is located in a valley, Findel and Trier 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). The 2006 and 2007 Uccle values should be taken with caution!

From 2007 on all 4 stations give totals that vary in the same manner (synchronous increase and decrease)

Biologically eff. UVB dose on a horizontal plane in kWh/m2  

Erythemal UVB dose of the year 2015: 0.140 KWh/m2

mean +/- stdev:
1998 to 2015: 0.130 +/- 0.009 eff. kWh*m-2y-1
2002 to 2015: 0.132 +/- 0.009

All trends are practically 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)

(The slight negative trend in biologically effective UVB is not consistent with the slight negative trend of the total ozone column [28], [50] , but consistent with the small  decrease of solar irradiance
since 2004).

UVA dose on a horizontal plane in kWh/m2 

UVA dose of the year 2015: 50.54 KWh/m2
 

mean +/- stdev:
1998 to 2015  53.8 +/- 4.6 kWh*m-2*y-1
2004 to 2015: 53.9 +/- 4.2

Overall trend is flat, from 2004 to 2015 slightly negative.
 

The 3 independent measures of solar energy, UVB and UVA doses all point to a slight solar dimming since 2004.

Enthalpy of moist air in kJ/kg
 

Mean moist enthalpy of 2015: 26.01+/- 11.32 kJ/kg

See [24] 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 metrics
Mean yearly moist enthalpy values are very close, but they may change from zero up to 60 KJ/kg during a year. Moist enthalpy can not be calculated for temperatures <= 0 C.

mean +/- stdev:
2002 to 2015  27.78 +/- 0.96 kJ/kg
2004 to 2015: 27.60 +/- 0.92

                       
Both trends are clearly negative which is consistent with the trends in temperature and solar energy. during the 14 years.

 

   
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
2004 to 2013 rend:   idem

mean +/- stdev:
2000 to 2013: 9.2 +/- 1.8 ug/m3
2004 to 2014: 8.5 +/- 1.5

Many missing data from 2011 to 2013 ( 25%, 21% , 8%) so be careful! All these concentrations are very low! Luxembourg-City has a background of 25-30 and rural Vianden (Niklausberg) one of 2.5 (approx. 2013 values from [39])

see [11] which gives ~30% reduction from 1990 to 2005 for the EU-15 countries.

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
2004 to 2013 rend:   + 0.6

mean +/- stdev:
2000 to 2013: 22.5 +/- 3.9 ug/m3
2004 to 2014: 22.7 +/- 4.5

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]

 

   

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, 59575985, 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
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, 68656886, 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 Zrich #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/ccgg/trends/index.html
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 Kmpfe, 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/

          

 


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:
 
meteoLCD (observations) ΔT/ΔF = 0.06 K/(Wm-2y-1) ΔT       = - 0.0057 Ky-1
ΔF       = - 0.09 Wm-2y-1
ΔT/ΔF =   0.06
Lindzen & Choi G0 = 0.25 ΔT = - 0.0200 Ky-1 (computed)
Scafetta k1s  = 0.053 ΔT = -0.0050 Ky-1 (computed)

 

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.

Both air temperature and moist enthalpy are positively correlated to changes in solar forcing ( = mean solar irradiance). The Pearson correlation between mean solar irradiance and moist enthalpy is 0.11 and is not significant at the p = 0.05 level, whereas the correlation between mean solar irradiance and temperature is 0.69 and significant.

A change of 1 Wm-2 of mean solar irradiance would cause a (big!) average heating of 1.2 C per decade and a change of 0.3 kJ/kg of moist enthalpy per decade.

Possibly taking into account some lag (as for instance 4 months for temperature lagging solar forcing) would change these numbers.

 

Addendum 3
 
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.

 

 

 

 

 

 

 

 

 

 

 

The same 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.

 

 

 

 


file: meteolcd_trends.html

francis.massen@education.lu
 

History:

01 Mar 2016. Errors in the equations of the CO2 regression lines corrected; edited.