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:
1998 to 2014: 39.0 +/- 6.8 ug/m3
2004 to 2014: 36.0 +/- 6.1
2005 to 2014: 35.6 +/- 6.2
  
Attention: there are about 15% missing data in 2013 due to frequent sensor failures, so the 2013 data point and the 2004-2014 trend line could be lower.
Watch the left scale to note that all trends are very small!

 

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

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 2007: * 0.95
2008 to 2010: * 1.00
2011              : * 1.06

2012              : * 1.04
2013              : * 1.06 (provisional)

2
013 common days measurements results:
Diekirch   = 321.6 DU
Uccle DS = 342.0 DU
Uccle data are from WOUDC (stat.53, Brewer#16, provisional as Dec. data not yet available)
2014 common measurements update asap!

1998 to 2012 mean +/- stdev:
Diekirch:
323.9 +/- 14.60
   Uccle.:  328.8 +/- 3.5
(Uccle without 2009/10/11
)
                                   

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 
 

The 1998-2001 data are too unreliable to be retained for the trend analysis.

2002 to 2014
mean +/- stdev:: 407.7 +/- 5.1 ppmV
trend = +0.54 ppmV per year

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!

The measurements of the German stations of Hohenpeissenberg (HPB) and Ochsenkopf.(OXK) and of Mauna Loa (MLO) are not yet available for comparison.[34]
                                       

This paragraph and figure not yet updated as the MLOand other data are not yet available!
The right 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 asymptotic mixing ratios are reasonably close to those of Mauna Loa (adjusted) up to 2012; the yearly trends calculated from the mean and asymptotic values at Diekirch are noticeably lower (0.83 and 0.88 ppmV*y-1) than the MLO trend of 2.05.
Compared trends from 2006 to 2012 for EU sites:
Ochsenkopf (OXK): 0.68
Hohenpeissenberg (HPB): 1.68
Diekirch: 1.14.  See also [25]

End of not updated paragraph

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.

 

 

 

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                
2002 to 2014 : 10.39 +/- 0.51 °C
2005 to 2014 : 10.41 +/- 0.56 °C

The sensor location has not been moved since 2002! There were 2 sensors replacements during 2014 (see comments in 2014_only.xls).

Trends  from 2002 to 2014 are practically flat at Diekirch and Findel:
meteoLCD:      +0.03°C/decade
Findel:              - 0.03°C/decade


Latest Global temperature anomaly trends:
UAH (satellite)   : + 0.028°C/decade   [45] (update)
RSS (satellite)   : -  0.065°C/decade
CRU (Hadcrut4): -  0.02°C/decade  .  [18]

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

Diurnal Temperature             
Range (DTR)  [°C]

DTR = daily max - daily min temperature

For 2004 to 2014: all trends close to flat.
Small positive DTR trend: +0.026 °C per year
.
Findel DTR trend is   -0.013 °C per year.

mean +/- stdev::
1998 to 2014:
 8.51 +/- 0.57 °C      
2004 to 2014: 8.55 +/-  0.45
2005 to 2014:  8.58 +/- 0.46

A fingerprint of global warming is that daily minima increase more than daily maxima so that the DTR trend should become negative. Clearly the data do show the contrary at Diekirch, and the Findel DTR trend is practically flat.

The BEST data [29] from 2013 and 2014 are not yet available.

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

.
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
Findel:       +0.15 °C/decade
Germany:  -0.36  °C/decade [46] (1988-2014)
NOA:         +0.26 °C/decade

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)

The North Atlantic Oscillation clearly influences our winters; the correlations between the 3 different DJF series and DJFM_NAO are 0.81, 0.81 and 0.82, all significant at the 5% level. The NAO trend is practically equal to the Diekirch trend.

Total Yearly Rainfall [mm]
 

1998 to 2014 mean +/- stdev:
706.9 +/- 143.5 mm .

Trends (which are pretty meaningless here!):
1998 to 2014: - 11.9 mm*y-1
2004 to 2014: + 9.8
2005 to 2014: + 15.4
                            

Rainfall in Diekirch may be very different from that at the Findel airport ! Totals for 2014:
Diekirch = 725, Findel = 858, Trier = 780 mm.

Acceptable simple model: Sinus function of 7 years period (R2 = 0.33). Model more or less correctly reflects rising and falling precipitation.

[6]
gives medium term periods of 10 to12 years for the  region from England to eastern Germany.

Solar energy on a horizontal plane

1998 to 2014 mean +/ std:
1109.3 +/-41.1
kWhm-2y-1

Visible negative trends:
1998 to 2014: -2.5 kWhm-2y-1
2004 to 2014: -1.7 kWhm-2y-1
2005 to 2014: -0.8 kWhm-2y-1
(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 duration
(derived from pyranometer data by Olivieri's method)

Totals for 2014:
meteoLCD: 1550 hours (215m asl)
Findel:         1796 hours (365m asl, Campbell- St.)
Trier:            1571 hours (279m asl) [40]

Negative trends:
1998 to 2014: - 4.3 hours*y-1
2004 to 2014: -16.2
2005 to 2014: -18.6

Mean +/- stdev:
1998 to 2014:  1647 +/- 168 hours
2004 to 2014:  1629 +/- 114
2005 to 2014:  1624 +/- 119

Note important negative trend from 2004 to 2014: - 16.2 hours per year = 162 hours/decade!

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:
1998 to 2013: 0.130 +/- 0.009 eff. kWh*m-2y-1
2004 to 2013: 0.129 +/- 0.005

All trends are essentially flat:
1998 to 2014: + 0.0001 kWh*m-2y-1
2004 to 2014:  - 0.00005
2005 to 2014:  - 0.00006

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 flat trend in biologically effective UVB is  consistent with the ???? of the total ozone column [28] ) to be verified!
 

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.

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.
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 2014  27.92 +/- 0.85 kJ/kg
2004 to 2014: 27.75 +/- 0.81

                       
Trend is clearly negative: -0.15 KJ/kg per year (or even -0.22 KJ/kg for the last  decade) which is consistent with the trends in temperature and solar energy during the last decade.

 

   
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, 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
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:
 
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
(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.

 

 

 

 


file: meteolcd_trends.html

francis.massen@education.lu
last revision: 01 Mar 2015