Mean +/- stdev of
2022: 66.2 +/- 36.6 ug/m³   

Mean +/- stdev (from yearly means)
1998 to 2022: 43.1 +/- 9.3 ug/m³
2002 to 2022: 43.1 +/- 10.1

Trends 1998 - 2022: 35.39+0.60*x (be careful: API400 values may be too low!)
             2018 - 2022: Cairsens sensors; no trend calculated as 2022 value seems too high.

Please note the succession of 3 different instruments
2002 - 2004: O341M (Environnement SA)
2005- 2014: API400 (Teledyne)
2015-2017: O341M
2018 - 2022: Cairsens O3&NO2 (Environnement SA). The sensor is replaced every year by a new one.
As NO2 values are below the minimum of this instrument, readings can be taken as O3 only (in ambient air: no correction for temperature and pressure!).
The official Beckerich  station data are used for calibrating the Cairsens readings (from time to time).

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

The overall trend is positive, but the trends from 2002 to 2022 (~2 decades) and that from 2013 to 2022 (last decade) are negative.
The slopes of all these trends are very small, so don't be fooled by the plots!

Uccle DS readings, MKIII Brewer (or MKII when MKIII unavailable): 328.9 +/- 35.4 (291 days)
minimum : 249.7 (27 Oct )
maximum: 444.0 (14 Mar)

164 common day direct sun readings for 2022 at Uccle and Diekirch (see second plot, Diekirch measurements are excellent!):
Diekirch                    : 322.2 +/- 32.9
Uccle                         : 331.5 +/- 32.2


Uccle  has a slight positive trend of +3.6 DU/decade for the 1998-2019 period, and a similar of +3.9 DU/decade from 2010 to 2019.(see also [16])

Calibration multiplier to apply to the Diekirch DU data [55] and [56] if Uccle Brewer(s) are the reference: 1.02755 (R² =0.87)

Once more, this year measurements show how good the Microtops II instrument is compared to the enormously more expensive Brewers!




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].

Attention: The instrument for measuring CO2 (API Teledyne E600) has been replaced by a Vaisala GMP343 sensor the 27 Jun 2017. The jump from 2017 to 2018 seems implausible high, so a zero bias should be considered possible!

Mean and stdev of the year 2022: 441.95 +/- 8.76 ppmV (yearly average of the Airvisual Pro CO2 sensor = 430.5 ppmV)

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

Trends :
2002 to 2020: 0.5 ppmV*y^-1
2018 to 2022: 5.5 ppmV*y^-1


The sharp plunge in 2013 should be taken with caution; there also was a change in the calibration gas the 21 Jan. 2014.
 

The second picture zooms on the last 4 years, and gives the readings of Diekirch (DIK), Mauna Loa (MLO)  from 2018 to 2021; and Hohenpeissenberg (HPB) from 2018 to 2021 as 2022 data are not yet available for HPB. Note the very different elevations! Mauna Loa has no vegetation at all, Diekirch and HPB similar grass and forests.

The yearly trends are for this period are

Be careful with the Vaisala readings, as the Vaisala GPM343 might not give the same accuracy as the former API! These readings also are given for local atm. pressure and non-dried air!

The CO2 data (monthly averages) show the summer-time lows, which reflect the impact of variable seasonal photo-synthesis (see here). A simple 12 month periodic sinus pattern was also found in 2014, 2015, 2021. 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 and 2017.

This year 2022 the yearly amplitude of the sinus fit is 8.6 ppmV (a total swing of ~17.2 ppmV, to be compared to about 12.4 ppmV at the HPB station for 2019 [48]).
The R2 is not exceptional high, but the summer minimum clearly stands out.

Note the large difference between the maximum October and minimum August readings: 472.6 - 435.4 = 37.2ppmV
 

Asymptotic CO2 mixing ratio (Massen-Beck model)

Addendum 3  describes our model to calculate an asymptotic CO2 mixing ratio. The plot shows how these values vary since 2018 (Vaisala sensor), 
suggesting a yearly increase of 5.4 ppmV since 2018 (practically the same as given by the reading data).

_.

Attention: the change of temperature Pt100 sensor introduced a bias of +1.61, apparent since the 2017 series, and
visible when comparing the airtemp with dry bulb temperature readings.
The yearly average airtemp readings (as given in the data files like 2022_only.xls) have been corrected by
subtracting this bias starting 2017!

Mean of the year 2022 (from monthly averages):
Diekirch:  11.08   (corrected for bias)
Findel:      11.18

Mean Diekirch temperatures (+/- stdev) from yearly averages:

1998 to 2022 :  10.39 +/- 0.50 °C      (corrected for bias)          
2002 to 2022 :  10.44 +/- 0.22  °C     (corrected for bias)
 

The sensor location has not been moved since 2002! Sensor is a PT100 (see comments in 2015_only.xls); new 4-20mA amplifier (with calibration) installed the 4th May 2016.

Trends  from 2002 to 2022 (be aware that 2018 was a very strong El Nino year!), see 2nd plot:
meteoLCD:    +0.015 °C/year (0.15 °C/decade) (corrected for bias)
Findel:            +0.046 °C/year  (0.46 °C/decade)

Note the sharp cooling in 2021 and the warming in 2022.         

Latest Global temperature anomaly trends for same period 2002-2022 (base:1991 - 2020):
UAH (satellite, LTT):          + 0.14°C/decade (Global Land)   [62]
RSS (satellite, LTT)   :    
CRU (Hadcrut4krig v2):  

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

DTR = daily max - daily min temperature

Mean and stdev of the year 2022 (from monthly averages):
Diekirch: 9.84 +/- 3.56
Findel:    8.58 +/- 2.93

Mean DTR at Diekirch:

1998 to 2022:  8.71
2002 to 2022:  8.32
 

For 1998 to 2022: all trends are positive, the 24hmin trend is lower than the 24hmax trend.

A fingerprint of anthropogenic climate warming is that daily minima increase more rapidly than daily maxima
so that the DTR trend should become negative. This fingerprint does not exist here (and neither at the Findel station, see 2nd plot).

 

The BEST observational data set for Luxembourg [29] stops at 2013. For our latitude of 50° North, BEST shows a positive DTR trend for the period 1988 to 2011, whereas theCMIP5 multi-model mean gives a similar but negative trend... so much for the concordance between climate models and observations!

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

Trends  from 2002 to 2022:
(2016 was a very strong El Nino year!):
Diekirch:    +0.13 °C/year
Findel:       +0.11
Germany:  +0.10   [46]
NAO:         +0.03

The plot shows the mean temperatures from December (of previous year) to February. It also shows in magenta the NAO index for the months Dec to Feb (right y-axis)

The North Atlantic Oscillation clearly influences our winters (but note the exception for 2015 and 2019! [51]).

Mean moist enthalpy of 2022: 32.00 +/- 13.28 kJ/kg (corrected for Air_temp bias of 1.6°C)

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 mostly 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 from 2002 to 2022:  28.35 +/- 1.34 kJ/kg

Trend is positive from 2002 to 2022; the 2016 "monster" El Nino extended into 2017 . Note the sharp rise in 2022!

1998 - 2022 mean +/- stdev: 680.6 +/- 130.8 mm 
2002 - 2022 mean +/-stdev:  646.4 +/-  104.0 mm
 

The negative trend from 1998 to 2018 seems spectacular: -85 mm/decade, but it is caused by the very high values of 2000 and 2001.
The 2002-2021 period has a much more small trend of -33 mm/decade.

Note that the very dry year 2022 is similar to 2005 !

Clearly precipitation shows an oscillation pattern, so linear trends should be taken with precaution (or simply seen as nonsense).

 A good model for the Diekirch data is a sinus function: the calculation (Levenberg-Marquart algorithm) suggests for the interval 2002 - 2022 a 5.55 years period (~66 months, R² = 0.38); in the model x = 0  corresponds to 2002), with a mean value of 648 mm and an amplitude of 87 mm; the phase shift of 1.5 rad is close to 1/2 period. All these values are similar to those of the preceding  year. All 4 parameters are significant at the alpha = 0.95 level!
[6] gives short term periods of 6 to 7 years for the Western European region.

The oscillatory rainfall pattern is a good example how foolish it is to apply linear regressions to data when these are harmonic, something the media, activist groups and many politicians often do without much thinking.

Values of total solar energy of the year 2021:
Diekirch: 1266.8 KWh/m²
 (was 1113.5 in 2021)
 

1998 to 2022 mean +/- stdev: 1125.2 +/- 57.1 kWh*m^-2*y^-1
2002 to 2021 mean +/- stdev: 1126.9 +/- 61.4 kWh*m^-2*y^-1


Trends from 1998 to 2021 is small, and relative important (~7.2 kWh*m^-2*y^-1) for last 20 years. [52]

(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]

Values of sunshine hours of the year 2022:

Diekirch:      2098 hours (215m asl) (from pyranometer)
Findel:          2234 hours (365m asl, (from Campbell- Stokes?, known to measure in excess)
Trier:            2119 hours (279m asl) [40] [53] (Petrisberg)
Maastricht: 2139 hours (114m asl) [53]

 Trends:
1998 to 2022:   +45.3 hours/decade
2002 to 2022:   +6.4 hours/decade !

The decline from 2015 to 2017 is clearly visible in the German PV electricity production, but the negative trend reverses for the very sunny year 2018 [58].

Note the sharp decline in 2021.

See paper [23] by F. Massen comparing 4 different methods to compute sunshine duration from pyranometer
 

The 2nd 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.

All 4 stations give totals that practically always vary in the same manner (synchronous increase and decrease).

The trends of all 4 stations are positive since 1998 and  similar, except Diekirch being lower

All stations show distinct decline in sunshine hours in 2021, and a 2022 total close to that of 2003.

These positive trends probably suffice to explain the warming since 1998:

The correlations between mean temperature are yearly sunshine hours are positive for the 4 stations, and these correlations are statistically significant at the alpha = 0.95 level for all stations:

Diekirch: 0.45, Findel 0.60, Trier 0.65, Maastricht 0.48

See the last multi-graph figure for the temp-versus-sunshine relationship at the 4 stations meteoLCD, Findel airport, Trier-Petrisberg and Maastricht airport.

The trend over 2002 - 2022 is slightly positive, in concordance with solar irradiance and sunshine hours.
 

.

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.

 

mean +/- stdev:
1998 to 2022: 55.00 +/- 4.63 kWh*m^-2*y^-1
2002 to 2022: 55.70 +/- 4.10



 

^{The 3 independent measurements of  solar energy, sunshine hours, eff.UVB and UVA doses
all point to an increase since 1998. All are of similar magnitude than those of the heatwave year 2003.}

Attention: only 78% of possible measurements available due to sensor downtime!
Comparison between yearly averages at Diekirch, Luxembourg-Liberté and Vianden (rural) [39]; Luxembourg and Vianden values derived by inspection from graphs):
 

The NOx/NO measurements by the AC31M instruments from Environnement SA have been stopped the 30 December 2017. The AC31M has reached its end of life.



 

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

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 0.73 and is significant at the p = 0.05 level, whereas the correlation between mean solar irradiance and temperature is 0.42 (not significant).

A change of 1 Wm^-2 of mean solar irradiance would cause a (big!) average heating of 0.5 °C per decade and a change of 0.9 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.

Our temperature measurements give a heating of 0.7°C/decade for the same period (Findel shows 0.5°/decade), which is close to the correlation given if the solar irradiance was the unique warming influence!

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.

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.

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!

The Mauna Loa average CO2 mixing ratio for 2017 is 406.6, which would suggest that our asymptotic value of 392.3 is too low. If we use only the measurements by the new Vaisala GMP343 sensor, the asymptotic value becomes 395.7.

The Mauna Loa average CO2 mixing ratio for 2018 is 408.5, so our asymptotic value of 406 is quite close. The R² of the model (the goodness of the fit) is also quite acceptable: R² = 0.50. All parameters are significant at the 5% level (alpha = 0.95).

The Mauna Loa average CO2 mixing ratio for 2020 is 414, so our asymptotic value of 417 is very close, keeping in mind that CO2 levels increase slightly with latitude!
The R² of the model (the goodness of the fit) is also quite acceptable: R² = 0.56. All parameters are significant at the 5% level (alpha = 0.95).

The Mauna Loa average CO2 mixing ratio for 2021 is 416.5, so our asymptotic value of 422.6 is close, keeping in mind that CO2 levels increase slightly with latitude!
(possibly ~2 ppm should be added to the MLO readings for the difference in latitudes from 20° to 50°N).

The December 2020 CO2 readings at the Hohenpeissenberg station near Munich were 420.9 ppmV
The R² of the model (the goodness of the fit) is also quite acceptable: R² = 0.49. All parameters are significant at the 5% level (alpha = 0.95).

The Mauna Loa average CO2 mixing ratio for 2022 is 418.6, so our asymptotic value of 427.3 is close, keeping in mind that CO2 levels increase slightly with latitude!
(possibly ~2 ppm should be added to the MLO readings for the difference in latitudes from 20° to 50°N).

The R² of the model (the goodness of the fit) is also quite acceptable: R² = 0.50. All parameters are significant at the 5% level (alpha = 0.95).