1. the mpi max-doas inversion scheme 2. cloud classification 3. results: aerosol od: correlation...
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1. The MPI MAX-DOAS inversion scheme2. Cloud classification3. Results: • Aerosol
• OD: Correlation with AERONET• Surface extinction: Correlation with Nephelometer• Mixing Layer Height: Correlation with Ceilometer
• NO2 • Surface mixing ratio: Correlation with EMPA • Mixing Layer Height: Correlation with Ceilometer• Inversion of synthetic NO2 SCDs
4. Conclusions
Results of the profile inversion from MPI MiniMAX-DOAS measurements during CINDI
Thomas Wagner, Reza Shaigan, Steffen Beirle
MPI Mainz, Germany
Aerosol profiles are parametrised by 3 parameters:following the ideas of
Li, X., Brauers, T., Shao, M., Garland, R. M., Wagner, T., Deutschmann, T., and Wahner, A.: MAX-DOAS measurements in southern China: retrieval of aerosol extinctions and validation using ground-based in-situ data, Atmos. Chem. Phys., 10, 2079-2089, 2010.
A) vertical optical depth OD(related to total aerosol amount)
B) mixing layer height MLH (important atmospheric parameter)
C) fraction of total optical depth in boundary layer (allows to adjust vertical profile, depending e.g. on vertical mixing into free troposphere) f = 0.9
90%Constant extinction in ML, exponential decrease above
1. The MPI MAX-DOAS inversion scheme
f = 1.5
New (since Nov. 2009):
f > 1:
Profiles with elevated layers
Aerosol profiles are parametrised by 3 parameters:following the ideas of
Li, X., Brauers, T., Shao, M., Garland, R. M., Wagner, T., Deutschmann, T., and Wahner, A.: MAX-DOAS measurements in southern China: retrieval of aerosol extinctions and validation using ground-based in-situ data, Atmos. Chem. Phys., 10, 2079-2089, 2010.
1. The MPI MAX-DOAS inversion scheme
f = 1.1
New (since Nov. 2009):
f > 1:
Profiles with elevated layers
Aerosol profiles are parametrised by 3 parameters:following the ideas of
Li, X., Brauers, T., Shao, M., Garland, R. M., Wagner, T., Deutschmann, T., and Wahner, A.: MAX-DOAS measurements in southern China: retrieval of aerosol extinctions and validation using ground-based in-situ data, Atmos. Chem. Phys., 10, 2079-2089, 2010.
1. The MPI MAX-DOAS inversion scheme
Multi-layer aerosols can not
be described by this parametrisation
Modelling of O4 AMFs:
•Radiative transfer modelling:• Backward Monte-Carlo RTM McArTim (Deutschmann, 2009)
• Surface albedo: 5%
• Surface altitude of measurement site
• Pressure and temperature profiles from US standard atmosphere
• Greenblatt et al. O4 cross section (corrected by +15% to +25%)
• Single scattering albedo: 0.95
• Asymmetry parameter: 0.68
• Number of aerosol scenarios: 172480
MLH (14): 20, 100, 200, 300, 500, 700, 1000, 1200, 1500, 1750, 2000, 2500, 3000, 5000m
OD (10): 0.05, 0.1, 0.2, 0.3, 0.5, 0.7, 1.0, 1.5, 2.0, 3.0
f (11): 0.1, 0.2, 0.3, 0.4, 0.5, 0.7, 1.0, 1.1, 1.2, 1.5, 1.8
for 8 elevation angles and 14 SZA / rel. Azimuth angles
1. The MPI MAX-DOAS inversion scheme
Parametrisation of NO2 profiles in a similar way:
A) mixing layer height MLH (important atmospheric parameter)
B) fraction f of total VCD in boundary layer (allows to adjust vertical profile, depending e.g. on vertical mixing into free troposphere)
However, no absolute tropospheric VCD is varied, because NO2 AMF depends only on relative profile
1. The MPI MAX-DOAS inversion scheme
Aerosol inversion:
Modelled AMFs are fitted to the measured data in the following way:
Measurements:
-Subtraction of O4 DSCD at 90° for each elevation sequence
-Division by O4 VCD => O4 DAMF
Model results:
-Subtraction of O4 AMF at 90° for each elevation sequence => O4 DAMF
Least squares fit: OD, ML (f: fixed)
1. The MPI MAX-DOAS inversion scheme
Result of aerosol fit, Cabauw, 26.6. Sequence 6
Min: 0.0054 for layer height 0.5km, optical depth: 0.23
1. The MPI MAX-DOAS inversion scheme
NO2 inversion:
Modelled AMFs are fitted to the measured data in the following way:
Measurements:
- Subtraction of NO2 DSCD at 90° for each elevation sequence
- Division by (shifted) DSCD at 10°
Model results (calculated for specific aerosol scenario):
- Subtraction of NO2 AMF at 90° for each elevation sequence => NO2 DAMF
- Division by DAMFs at 10°
Least squares fit: ML (f: fixed)
Aerosol parameter from O4 inversion
1. The MPI MAX-DOAS inversion scheme
Result of NO2 fit, Cabauw
30.6. sequence 5930.6. sequence 62
Chi2 = 0.05Chi2 = 0.004
1. The MPI MAX-DOAS inversion scheme
Classification of the cloud cover
using radiance and O4 observations at 90° elevation angle
Temporal variation of radiance smooth?yes => Temporal variation of O4 smooth?
yes => clear dayno => cloudy day
no => cloudy day
O4 absorption largely increased and/or varying rapidly compared to clear day?
yes => thick cloud
no => thin cloud
2. Cloud classification
Day with clear sky
24.6.2009
6/24/09 04:48 6/24/09 09:36 6/24/09 14:24 6/24/09 19:12
Tim e
1E+5
1E+6
1E+7
Rad
ianc
e [c
ount
s/se
c]
0.0
0.2
0.4
0.6
CI
(rat
io 3
20/4
40)
0.0E+0
1.0E+3
2.0E+3
3.0E+3
O
4 D
SC
D
[1e4
0]
Cabauw
Bruxelles
2. Cloud classification
6/26/09 04:48 6/26/09 09:36 6/26/09 14:24 6/26/09 19:12
Tim e
1E+5
1E+6
1E+7
Rad
ianc
e [c
ount
s/se
c]
0.0
0.2
0.4
0.6
C
I (r
atio
320
/440
)
0.0E+0
1.0E+3
2.0E+3
3.0E+3
O
4 D
SC
D
[1e4
0]
Day with 'thin' clouds
26.06.2009
Cabauw
Bruxelles
2. Cloud classification
Day with 'thick' clouds
1.7.2009
7/12/09 04:48 7/12/09 09:36 7/12/09 14:24 7/12/09 19:12
Tim e
1E+5
1E+6
1E+7
Rad
ianc
e [c
ount
s/se
c]
0.0
0.2
0.4
0.6
CI
(rat
io 3
20/4
40)
0.0E+0
1.0E+3
2.0E+3
3.0E+3
O
4 D
SC
D
[1e4
0]
Cabauw
Bruxelles
2. Cloud classification
Classification of the cloud cover using radiance and O4 observations at 90° elevation angle
-1
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
22.6 26.6 30.6 4.7 8.7 12.7
Time
Diff
eren
ce o
f O4
AM
F
Clear skyThick cloudsThin clouds
O4 AMF – O4 AMFcloudfree
2. Cloud classification
A) Typical diurnal cycles
B) Aerosol OD: Correlation with AERONET data
C) Surface extinction: Correlation with WetNephelometer data
D) Mixing Layer Height: Correlation with Ceilometer data
3.1 Results: Aerosols
0
0.2
0.4
0.6
0.8
1
1.2
1.4
24.Jun00:00
24.Jun02:24
24.Jun04:48
24.Jun07:12
24.Jun09:36
24.Jun12:00
24.Jun14:24
24.Jun16:48
24.Jun19:12
24.Jun21:36
25.Jun00:00
Time
Aer
osol
OD
360
nm
OD_f0.5
OD_f0.9
OD_f1.1
OD_f1.5
AOT_360
f: 0.5f: 0.9f: 1.1f:1.5AERONET
Clear sky
cloudy
3.1 Results: Aerosols A) Typical diurnal cycles
0
0.2
0.4
0.6
0.8
1
1.2
1.4
03.Jul02:24
03.Jul04:48
03.Jul07:12
03.Jul09:36
03.Jul12:00
03.Jul14:24
03.Jul16:48
03.Jul19:12
03.Jul21:36
Time
Aer
osol
OD
360
nm
OD_f0.5
OD_f0.9
OD_f1.1
OD_f1.5
AOT_360
f: 0.5f: 0.9f: 1.1f:1.5AERONET
mostly cloudy
Clear sky
3.1 Results: Aerosols A) Typical diurnal cycles
y = 0.8383x + 0.1987
R2 = 0.1992
0
0.5
1
1.5
2
2.5
3
0 0.2 0.4 0.6 0.8 1 1.2 1.4
AERONET OD 360nm
MA
X-D
OA
S O
D 3
60nm
All coincidences (half hour averages)
3.1 Results: Aerosols B) Correlation with AERONET OD
O4 scaling factor = 1.2f=0.9
y = 0.7003x + 0.1374
R2 = 0.2092
0
0.5
1
1.5
2
2.5
3
0 0.2 0.4 0.6 0.8 1 1.2 1.4
AERONET OD 360nm
MA
X-D
OA
S O
D 3
60nm
Data with layer heigth >= 3km removed
3.1 Results: Aerosols B) Correlation with AERONET OD
y = 0.6805x + 0.1331
R2 = 0.2517
0
0.5
1
1.5
2
2.5
3
0 0.2 0.4 0.6 0.8 1 1.2 1.4
AERONET OD 360nm
MA
X-D
OA
S O
D 3
60nm
Also data with chi2 >= 0.04 removed
3.1 Results: Aerosols B) Correlation with AERONET OD
0
0.5
1
1.5
2
2.5
3
3.5
29.0602:24
29.0607:12
29.0612:00
29.0616:48
29.0621:36
30.0602:24
30.0607:12
30.0612:00
30.0616:48
30.0621:36
Time
MA
X-D
OA
S O
D 3
60nm
Days with (unrealistic) rapid variation of the aerosol OD:
3.1 Results: Aerosols B) Correlation with AERONET OD
y = 0.7022x + 0.0401
R2 = 0.6364
0
0.5
1
1.5
2
2.5
3
0 0.2 0.4 0.6 0.8 1 1.2 1.4
AERONET OD 360nm
MA
X-D
OA
S O
D 3
60nm
Data with rapid variation of OD (> 0.5) removed
3.1 Results: Aerosols B) Correlation with AERONET OD
y = 0.7467x + 0.0337
R2 = 0.5037
0
0.5
1
1.5
2
2.5
3
0 0.2 0.4 0.6 0.8 1 1.2 1.4
AERONET OD 360nm
MA
X-D
OA
S O
D 3
60nm
Only data for thin clouds
3.1 Results: Aerosols B) Correlation with AERONET OD
y = 0.5497x + 0.0578
R2 = 0.9011
0
0.5
1
1.5
2
2.5
3
0 0.2 0.4 0.6 0.8 1 1.2 1.4
AERONET OD 360nm
MA
X-D
OA
S O
D 3
60nm
Only data for clear sky
Coincidences only in the morning!(with systematically low MAX-DOAS results)
3.1 Results: Aerosols B) Correlation with AERONET OD
y = 0.521x + 0.5985
R2 = 0.0657
0
0.5
1
1.5
2
2.5
3
0 0.2 0.4 0.6 0.8 1 1.2 1.4
AERONET OD 360nm
MA
X-D
OA
S O
D 3
60nm
Only data for thick clouds
3.1 Results: Aerosols B) Correlation with AERONET OD
Correlation with WetNephelometer data from Paul Zieger
3.1 Results: Aerosols C) Correlation with in-situ extinction
Correlation with WetNephelometer data from Paul Zieger for different layer heights
>1500m:Slope 2
<1500m Slope 1
0
500
1000
1500
2000
2500
0:00 4:48 9:36 14:24 19:12 0:00Time
Laye
r he
ight
[m]
MAX-DOAS aerosol layer height
F-value: 0.9
F-value: 1.1
3.1 Results: Aerosols D) Correlation with Ceilometer MLH
y = 0.2371x + 2210.9
R2 = 0.0077
y = -0.0422x + 1457.5
R2 = 0.00030
1000
2000
3000
4000
5000
6000
0 200 400 600 800 1000 1200 1400 1600 1800 2000Ceilmeter_MLH1 [m]
MA
X-D
OA
S L
ayer
hei
ght [
m]
MAX-DOAS_F09MAX-DOAS_F11Linear (MAX-DOAS_F09)Linear (MAX-DOAS_F11)
all data
3.1 Results: Aerosols D) Correlation with Ceilometer MLH
only clear sky observations and chi2 < 0.04
y = 1.242x + 686.27
R2 = 0.2589
y = 1.7872x + 1126.9
R2 = 0.1675
0
1000
2000
3000
4000
0 200 400 600 800 1000 1200 1400 1600 1800 2000
Ceilometer MLH1 [m]
MA
X-D
OA
S a
eros
ol la
yer
heig
ht [m
]
MAX-DOAS_F09MAX-DOAS_F11Linear (MAX-DOAS_F11)Linear (MAX-DOAS_F09)
3.1 Results: Aerosols D) Correlation with Ceilometer MLH
3.2 Results: NO2
A) Typical diurnal cycles
B) Mixing ratio: Correlation with EMPA data
C) Mixing Layer Height: Correlation with Ceilometer data
D) Inversion of synthetic NO2 DSCDs
0
2
4
6
8
10
12
14
16
18
20
25.Jun02:24
25.Jun04:48
25.Jun07:12
25.Jun09:36
25.Jun12:00
25.Jun14:24
25.Jun16:48
25.Jun19:12
25.Jun21:36
Time
NO
2 M
ixin
g ra
tio [
ppb]
EMPA in-situ
NO2 mixing ratio for different aerosol f-values
thin clouds
3.2 Results: NO2 A) Typical diurnal cycles
0
2
4
6
8
10
12
14
16
18
20
25.Jun02:24
25.Jun04:48
25.Jun07:12
25.Jun09:36
25.Jun12:00
25.Jun14:24
25.Jun16:48
25.Jun19:12
25.Jun21:36
Time
NO
2 M
ixin
g ra
tio [p
pb]
NO2_mix_NO2_0.2NO2_mix_NO2_0.5NO2_mix_NO2_0.8NO2_mix_NO2_0.9NO2_mix_NO2_1.0NO2 in-situ
thin clouds
NO2 mixing ratio for different NO2 f-values
3.2 Results: NO2 A) Typical diurnal cycles
y = 0.7159x + 2.1508
R2 = 0.2153
0
5
10
15
20
25
30
35
40
0 2 4 6 8 10 12 14 16 18 20
NO2 mixing ratio EMPA [ppb]
MA
X-D
OA
SN
O2
mix
ing
ratio
[ppb
]
All coincidences (half hour averages, f-value: 0.9)
3.2 Results: NO2 B) Correlation with EMPA mixing ratio
y = 0.7449x + 1.2219
R2 = 0.3507
0
5
10
15
20
25
30
35
40
0 2 4 6 8 10 12 14 16 18 20
NO2 mixing ratio EMPA [ppb]
MA
X-D
OA
S m
ixin
g ra
tio [p
pb]
All coincidences (half hour averages, f-value: 0.9)
Chi2 < 0.04
3.2 Results: NO2 B) Correlation with EMPA mixing ratio
y = 0.9381x + 0.2634
R2 = 0.7211
0
5
10
15
20
25
30
35
40
0 2 4 6 8 10 12 14 16 18 20
NO2 mixing ratio EMPA [ppb]
MA
X-D
OA
S m
ixin
g ra
tio N
O2
[ppb
]
Only thin clouds
3.2 Results: NO2 B) Correlation with EMPA mixing ratio
y = 0.4506x + 0.949
R2 = 0.5023
0
5
10
15
20
25
30
35
40
0 2 4 6 8 10 12 14 16 18 20
NO2 mixing ratio EMPA [ppb]
MA
X-D
OA
S N
O2
mix
ing
ratio
[ppb
]
clear sky
(only early morning data)
3.2 Results: NO2 B) Correlation with EMPA mixing ratio
y = 2.3134x - 2.8438
R2 = 0.556
0
5
10
15
20
25
30
35
40
0 2 4 6 8 10 12 14 16 18 20
NO2 mixing ratio EMPA [ppb]
MA
X-D
OA
S N
O2
mix
ing
ratio
[ppb
]
Only thick clouds
3.2 Results: NO2 B) Correlation with EMPA mixing ratio
3.2 Results: NO2 B) Correlation with EMPA mixing ratio
Slope of fit R2
All data 0.72 0.22
chi2<0.04 0.74 0.35
thin clouds 0.94 0.72
clear sky 0.45 0.50
thick clouds 2.31 0.56
On some days the NO2 mixing ratios depend strongly on the assumed (relative) aerosol profile.
The mixing ratios derived for an elevated aerosol layer (f>1) agree better with the in-situ data.
For these observations also the lowest chi2 is found in the aerosol fit (O4 data) for an assumed elevated aerosol layer
3.2 Results: NO2 B) Correlation with EMPA mixing ratio
0
2
4
6
8
10
12
14
16
18
20
26.Jun02:24
26.Jun04:48
26.Jun07:12
26.Jun09:36
26.Jun12:00
26.Jun14:24
26.Jun16:48
26.Jun19:12
26.Jun21:36
Time
NO
2 M
ixin
g r
atio [
ppb]
NO2_mix_Aerosol_0.9NO2_mix_Aerosol_1.0NO2_mix_Aerosol_1.1NO2 in-situ
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
26.Jun02:24
26.Jun04:48
26.Jun07:12
26.Jun09:36
26.Jun12:00
26.Jun14:24
26.Jun16:48
26.Jun19:12
26.Jun21:36
Time
Chi^
2Chi2_0.9Chi2_1.0Chi2_1.1
Lowest chi2 for elevated aerosol layer
Better agreement of NO2 mixing ratio for elevated aerosol layer
3.2 Results: NO2 B) Correlation with EMPA mixing ratio
3.2 Results: NO2 C) Correlation with Ceilometer MLH
Slope of fit R2
All data 0.48 0.79 0.13 0.23
chi2<0.04 0.52 0.90 0.32 0.39
thin clouds 0.56 0.91 0.34 0.37
clear sky 0.80 1.15 0.52 0.55
thick clouds 0.32 0.35 0.11 0.07
Aerosol fit: f=0.9 f=1.1
Fit results for all daily profiles (UV profile 03)
F-value
Layer height
NO2 VCD
Chi2
3.2 Results: NO2 D) Inversion of synthetic NO2 DSCDs
(UV profile 03, all daily profiles)
3.2 Results: NO2 D) Inversion of synthetic NO2 DSCDs
Results for all UV profiles
3.2 Results: NO2 D) Inversion of synthetic NO2 DSCDs
-simple MAX-DOAS inversion scheme for UV measurements, based on MC-RTM LUT and least squares fit of simple profile parametrisation
-discrimination scheme for clear sky / thin clouds / thick clouds
Aerosol inversion:
-aerosol OD is reasonable for aerosol f-value of 0.9, clear sky and thin cloud observations; MAX-DOAS aerosol OD about 25% smaller than AERONET
-aerosol extinction agrees well with wetnepelometer data for layer heights <1500m
-aerosol layer height shows (weak) correlation with ceilometer data only for clear sky
4. Conclusions
NO2 inversion:
-NO2 mixing ratio agrees well with in-situ observations for clear sky and thin cloud observations; only weak dependence on aerosol f-value; almost no dependence on NO2 f-value
-NO2 layer height shows reasonable correlation with ceilometer data for clear sky and thin cloud data
Inversion of synthetic NO2 SCDs
-good agreement found for NO2 profiles for low and high aerosol load
-for some profiles rather large deviations during the day
4. Conclusions
y = 0.6884x + 0.021R2 = 0.5416
y = 0.7467x + 0.0337R2 = 0.5037
y = 0.6606x + 0.1803R2 = 0.3198
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
0 0.2 0.4 0.6 0.8 1 1.2 1.4AERONET OD 360nm
MA
X-D
OA
S O
D 3
60nm
Factor_10_f09
Factor_095_f09
Factor_09_f09
Linear(Factor_10_f09)Linear(Factor_095_f09)Linear(Factor_09_f09)
different scaling factors for the O4 cross section
(observations for thin clouds)
+20 % seems to be the best choice
3.1 Results: Aerosols B) Correlation with AERONET OD
+15 %
+20 %
+25 %
y = 0.7467x + 0.0337
R2 = 0.5037
y = 1.0305x + 0.1673
R2 = 0.3008
y = 0.2296x + 0.0949
R2 = 0.50550
0.5
1
1.5
2
2.5
0 0.2 0.4 0.6 0.8 1 1.2 1.4
AERONET OD 360nm
MA
X-D
OA
S O
D 3
60nm
Factor_095_f02Factor_095_f05Factor_095_f08Factor_095_f09Factor_095_f10Factor_095_f11Factor_095_f12Factor_095_f15Factor_095_f18Linear (Factor_095_f09)Linear (Factor_095_f02)Linear (Factor_095_f18)
Correlations for different f-.values
(observations for thin clouds)
0.9 seems to be a good choice
3.1 Results: Aerosols B) Correlation with AERONET OD
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
25.Jun03:36
25.Jun06:00
25.Jun08:24
25.Jun10:48
25.Jun13:12
25.Jun15:36
25.Jun18:00
Time
Ae
roso
l Ext
inct
ion
[1
/km
]
ext_f0.2ext_f0.5ext_f0.8ext_f0.9ext_f1.0ext_f1.1ext_f1.2ext_f1.5
Aerosol extinction for different aerosol f-values
thin clouds
3.1 Results: Aerosols
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
03.Jul03:36
03.Jul06:00
03.Jul08:24
03.Jul10:48
03.Jul13:12
03.Jul15:36
03.Jul18:00
03.Jul20:24
Time
Ae
roso
l Ext
inct
ion
[1
/km
]
ext_f0.2ext_f0.5ext_f0.8ext_f0.9ext_f1.0ext_f1.1ext_f1.2ext_f1.5
clear skycloudy sky
3.1 Results: AerosolsAerosol extinction for different aerosol f-values
0
5
10
15
20
25
30
35
40
0 5 10 15 20
NO2 mixing ratio EMPA [ppb]
MA
X-D
OA
S N
O2
mix
ing
ratio
[ppb
]
NO2f09_aer02NO2f09_aer05NO2f09_aer08NO2f09_aer09NO2f09_aer10NO2f09_aer11NO2f09_aer12NO2f09_aer15NO2f09_aer18Linear (NO2f09_aer02)Linear (NO2f09_aer08)Linear (NO2f09_aer10)Linear (NO2f09_aer12)Linear (NO2f09_aer18)
y = 1.0632x + 0.2259, R2 = 0.678
y = 0.9407x + 0.3009, R2 = 0.7168
y = 0.9338x + 0.2464, R2 = 0.721
y = 0.6263x + 0.8643, R2 = 0.6754
y = 0.6142x + 0.9857, R2 = 0.6386
for different aerosol f-values (thin cloud data)
3.2 Results: NO2 B) Correlation with EMPA mixing ratio
0
5
10
15
20
25
30
35
40
0 2 4 6 8 10 12 14 16 18 20
NO2 mixing ratio EMPA [ppb]
MA
X-D
OA
S N
O2
mix
ing
ratio
[pp
b]
NO2f02_aer05NO2f05_aer05NO2f08_aer05NO2f09_aer05NO2f10_aer05
y = 0.9717x + 0.3211, R2 = 0.7096y = 1.0283x + 0.135, R2 = 0.7167y = 0.9981x + 0.207, R2 = 0.6989y = 0.9981x + 0.207, R2 = 0.6989y = 0.9816x + 0.2562, R2 = 0.6929
for different NO2 f-values (thin cloud data)
Almost no dependence on NO2 f-value
3.2 Results: NO2 B) Correlation with EMPA mixing ratio
0
2
4
6
8
10
12
14
16
18
20
26.Jun02:24
26.Jun04:48
26.Jun07:12
26.Jun09:36
26.Jun12:00
26.Jun14:24
26.Jun16:48
26.Jun19:12
26.Jun21:36
Time
NO
2 M
ixin
g r
atio [
ppb]
NO2_mix_Aerosol_0.9NO2_mix_Aerosol_1.0NO2_mix_Aerosol_1.1NO2 in-situ
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
26.Jun02:24
26.Jun04:48
26.Jun07:12
26.Jun09:36
26.Jun12:00
26.Jun14:24
26.Jun16:48
26.Jun19:12
26.Jun21:36
Time
Chi^
2Chi2_0.9Chi2_1.0Chi2_1.1
Day with better agreement for elevated layer
(some periods)
Lowest chi2 for elevated aerosol layer
Better agreement of NO2 mixing ratio for elevated aerosol layer
3.2 Results: NO2 B) Correlation with EMPA mixing ratio
y = 0.7945x + 400.99
R2 = 0.2293
y = 0.4812x + 390.21
R2 = 0.133
0
500
1000
1500
2000
2500
3000
0 500 1000 1500 2000Ceilometer MLH1 [m]
MA
X-D
OA
S N
O2
laye
r he
ight
[m]
Reihe1Reihe2Linear (Reihe2)Linear (Reihe1)
aerosol f-value: 0.9aerosol f-value: 1.1
(all data, NO2 f-value: 0.9)
3.2 Results: NO2 C) Correlation with Ceilometer MLH
y = 0.8992x + 343.95
R2 = 0.393
y = 0.5188x + 354.32
R2 = 0.31910
500
1000
1500
2000
2500
3000
0 200 400 600 800 1000 1200 1400 1600 1800 2000
Ceilometer MLH1 [m]
MA
X-D
OA
S N
O2
laqy
er h
eigh
t [m
]
Reihe1Reihe2Linear (Reihe2)Linear (Reihe1)
aerosol f-value: 0.9aerosol f-value: 1.1
NO2 Chi2 <0.04
3.2 Results: NO2 C) Correlation with Ceilometer MLH
y = 0.9146x + 321.42
R2 = 0.3747
y = 0.555x + 300.26
R2 = 0.34080
500
1000
1500
2000
2500
3000
0 200 400 600 800 1000 1200 1400 1600 1800 2000
Ceilometer MLH1 [m]
MA
X-D
OA
S N
O2
laqy
er h
eigh
t [m
]
Reihe1Reihe2Linear (Reihe2)Linear (Reihe1)
aerosol f-value: 0.9aerosol f-value: 1.1
Only thin clouds
3.2 Results: NO2 C) Correlation with Ceilometer MLH
y = 1.1512x + 224.52
R2 = 0.5465
y = 0.8048x + 304.4
R2 = 0.51640
500
1000
1500
2000
2500
3000
0 200 400 600 800 1000 1200 1400 1600 1800 2000
Ceilometer MLH1 [m]
MA
X-D
OA
S N
O2
laqy
er h
eigh
t [m
]
Reihe1Reihe2Linear (Reihe2)Linear (Reihe1)
aerosol f-value: 0.9aerosol f-value: 1.1
Only clear sky
3.2 Results: NO2 C) Correlation with Ceilometer MLH
y = 0.3484x + 761.79
R2 = 0.0728
y = 0.3162x + 467.65
R2 = 0.10550
500
1000
1500
2000
2500
3000
0 200 400 600 800 1000 1200 1400 1600 1800 2000
Ceilometer MLH1 [m]
MA
X-D
OA
S N
O2
laqy
er h
eigh
t [m
]
Reihe1Reihe2Linear (Reihe2)Linear (Reihe1)
aerosol f-value: 0.9aerosol f-value: 1.1
Only thick clouds
3.2 Results: NO2 C) Correlation with Ceilometer MLH
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