1. OMI UV spectral irradiance: comparison with ground based measurements in an urban environment
Stelios Kazadzis
A. Bais, A. Arola
OMI science team meeting
Helsinki, June 2008
Finnish Meteorological Institute
Laboratory of Atmospheric Physics, Thessaloniki, Greece
Name, fmi, present resukts

2. Outline
OMI – ground based UV spectral irradiance comparison – statistics
Aerosol absorption – post correction approaches
Campaign: Spacial and temporal UV variability within an OMI grid
Outline
I will present a comparison of 3.5 years of OMI and GB spectral UV irradiance measurements
Reffering to aerosol absorption problem neglected by the OMI UV retrieval algorithm. Introduce some possible post correction procedures
Results of a experimental campaign with UV and aerosol spectrla measurements within an OMI viewing grid
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

3. The problem - absorbing aerosols
OMI – GB UV comparison – statistics
The problem - absorbing aerosols
Current OMI UV algorithm does not account for absorbing aerosols
(e.g. organic carbon, smoke, dust )
Motivation: current OMI UV algorithm does not account for absorbing aerosols
Previous work by Tanskannen showed that OMI comparison with pristine sites as Lauder provide good results but Omi overestimates UV irradiance at urban areas.
Comparison for the first year of OMI life and for Daily erythemal irradiance
Tokyo: +32%
Tanskannen et al., JGR 2007
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

4. OMI – GB UV comparison – statistics
Thessaloniki Area
High aerosol load - Aerosol transport Sahara dust intrusions Biomass burning from NE - Very high PM10 conc.
Sahara - Dream model
Thessaloniki: Eastern Mediterranean city with 1.2 mil.
Highest AOD in European level
Both local sources and also aerosol transport (saharan dust, aerosol from biomass burning activities from NE)
PM10 concentration exceeding daily limit of 50mg/cm3 more than 200 days per year (mean of mg/cm3)
The site is facing the Aegean Sea to the south and west and is situated along expected pathways through which pollution from central and Eastern Europe influences aerosol loading over the
Eastern Mediterranean (Amiridis et al., 2005). Aerosol optical depth (AOD) measurement records (Kazadzis et al., 2007) show that AOD values at Thessaloniki area are among the highest in a European level.
The color indicates the dominant land cover where the detection occurred. Land cover classes were combined into five final categories which are Forest,….
We observe that the main source of smoke from the region of Black Sea is mainly attributed to agricultural burning activities. The type of burning land is critical for the determination of the source emission properties of the smoke.
Fire hot spots - summer
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

5. Instrumentation - comparison
OMI – GB UV comparison – statistics
Instrumentation - comparison
Thessaloniki September 2004-December 2007
Brewer instrument (spectral-calibrated, wavelength shift corrected) UV irradiance at 305, 324, 380 nm and CIE Total column ozone spectral AOD at UV wavelengths CIMEL AOD (340nm) , SSA(440nm), .. NILU-UV 305nm, 324nm, 340nm, 380nm Cloud – cloudless case separation Pyranometer, observations, sky camera pix Daily OMI overpass time (mean over ±15 minutes)
Intercomparison exercise spetember december 2007
Measurements that were conducted
Brewer, cimel, nilu, cloud separation
OMI
Rooftop of the School of Natural Sciences
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

6. Results 305nm OMI +30% 324nm OMI +17%
OMI – GB UV comparison – statistics
Results
Results
Y axsis Brewer full circles cloudless cases
305nm OMI +30% nm OMI +17%
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

7. Results 380nm OMI +11% CIED OMI +20%
OMI – GB UV comparison – statistics
Results
Similar comparison
Distributions of the ratio OMI vs GB
380nm OMI +11% CIED OMI +20%
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

8. Results - statistics All data cloudless Wavel. (nm) 305 324 380 CIED m
OMI – GB UV comparison – statistics
Results - statistics
Wavel.
(nm)
All data
cloudless m R2
W10
W20
305
1.30
0.94
43.3
68.2
1.27
0.95
64.8
87.6
324
1.17
0.89
51.3
73.1
1.15
0.91
76.9
92.4
380
1.13
47.2
70.7
1.11
71.8
89.7
CIED
1.20
0.93
51.5
75.4
1.19
75.0
91.9
All results wavelength dependence on the ratio
Cloudless , cloud free results
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

9. Results - statistics All data cloudless Wavel. (nm) 305 324 380 CIED m
OMI – GB UV comparison – statistics
Results - statistics
Wavel.
(nm)
All data
cloudless m R2
W10
W20
305
1.30
0.94
43.3
68.2
1.27
0.95
64.8
87.6
324
1.17
0.89
51.3
73.1
1.15
0.91
76.9
92.4
380
1.13
47.2
70.7
1.11
71.8
89.7
CIED
1.20
0.93
51.5
75.4
1.19
75.0
91.9
Explain 20% more in 10 or 20 agreement for cloudy cloudless
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

10. Cloudless cases: Ta(λ) = AOD(λ) * [1 - SSA(λ)]
Post correction methods
Post correction methods - TOMS experience
Krotkov et al., OE 2004
Cloudless cases: Ta(λ) = AOD(λ) * [1 - SSA(λ)]
Arola et al., JGR 2005
As OMI inherits basic TOMS UV algorithm
Corrections proposed in the past
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

11. UV attenuation – Thessaloniki, cloudless cases
Post correction methods
UV attenuation – Thessaloniki, cloudless cases
Thessaloniki cloudles sky cases
Model calculations to se what is the aerosol effect compared with OMI differences on a monthly basis
+10% from extrapolation
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

12. Post correction : method 1
Post correction methods
Post correction : method 1
Ta (λ) = AOD(λ) * [1 - SSA(440nm)]
Aerosol absorption CF(λ) = * Ta(λ)
no sza dependence
UV ?
need of GB data
First approach by arola et al using actual measurements GB and Omi differences to find the dependence of the Ratio to Tabs
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

13. Post correction: method 2
Post correction methods
Post correction: method 2
Tas =Ta / cos(sza)
Aerosol absorption CF(λ) = * Tas(λ)
UV ?
need of GB data
Improve sza dependence
Normalized Tabs – new slope
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

14. Post correction: use of RT model
Post correction methods
Post correction: use of RT model
Abs + scat
scat
Another approach use of RTM
Correct for all effect
Three scenarios a. measurements of aod and ssa
b. Measured aod , ssa is const as measured by the cimel instrument at 440nm
c. Aod constant ( mean) SSA= 0.88 ( Bais et al, Arola et al.)
S1: AOD and SSA synchronous measurements S2: AOD and = const S3: AOD= const and = const
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

15. Overview of post corrections
Post correction methods
Overview of post corrections
6th Approach: CF(λ) = * Ta(λ)
Table with all the results of the 6 approaches:
OMI/Brewer ratio [R]
Method
305 nm
Mean (1σ)
324 nm
380 nm
Obs
Original
No correction
1.27 (0.15)
1.15 (0.10)
1.11 (0.12)
267 S1
Apply Ta slope
1.17 (0.13)
1.07 (0.09)
1.05 (0.13)
135 S2
Apply Tas slope
1.18 (0.13)
1.09 (0.10) M1
Model
1.13 (0.12)
1.04 (0.08)
1.01 (0.11) M2
Model constant SSA
1.14 (0.13)
1.03 (0.09)
0.99 (0.10) M3
Model const. SSA-AOD
1.12 (0.13)
1.02 (0.09)
0.98 (0.10) S3
1 + 3 * Ta (λ)
1.11 (0.13)
1.03 (0.10)
6th approach Nasa
Original and standard deviation
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

16. Overview of post corrections
Post correction methods
Overview of post corrections
6th Approach: CF = * Ta(λ)
Table with all the results of the 6 approaches:
OMI/Brewer ratio [R]
Method
305 nm
Mean (1σ)
324 nm
380 nm
Obs
Original
No correction
1.27 (0.15)
1.15 (0.10)
1.11 (0.12)
267 S1
Apply Ta slope
1.17 (0.13)
1.07 (0.09)
1.05 (0.13)
135 S2
Apply Tas slope
1.18 (0.13)
1.09 (0.10) M1
Model
1.13 (0.12)
1.04 (0.08)
1.01 (0.11) M2
Model constant SSA
1.14 (0.13)
1.03 (0.09)
0.99 (0.10) M3
Model const. SSA-AOD
1.12 (0.13)
1.02 (0.09)
0.98 (0.10) S3
1 + 3 * Ta (λ)
1.11 (0.13)
1.03 (0.10)
305nm
1.27 – small improvement of sigma
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

17. Overview of post corrections
Post correction methods
Overview of post corrections
6th Approach: CF = * Ta(λ)
Table with all the results of the 6 approaches:
OMI/Brewer ratio [R]
Method
305 nm
Mean (1σ)
324 nm
380 nm
Obs
Original
No correction
1.27 (0.15)
1.15 (0.10)
1.11 (0.12)
267 S1
Apply Ta slope
1.17 (0.13)
1.07 (0.09)
1.05 (0.13)
135 S2
Apply Tas slope
1.18 (0.13)
1.09 (0.10) M1
Model
1.13 (0.12)
1.04 (0.08)
1.01 (0.11) M2
Model constant SSA
1.14 (0.13)
1.03 (0.09)
0.99 (0.10) M3
Model const. SSA-AOD
1.12 (0.13)
1.02 (0.09)
0.98 (0.10) S3
1 + 3 * Ta (λ)
1.11 (0.13)
1.03 (0.10)
324 nm
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

18. Overview of post corrections
Post correction methods
Overview of post corrections
6th Approach: CF = * Ta(λ)
Table with all the results of the 6 approaches:
OMI/Brewer ratio [R]
Method
305 nm
Mean (1σ)
324 nm
380 nm
Obs
Original
No correction
1.27 (0.15)
1.15 (0.10)
1.11 (0.12)
267 S1
Apply Ta slope
1.17 (0.13)
1.07 (0.09)
1.05 (0.13)
135 S2
Apply Tas slope
1.18 (0.13)
1.09 (0.10) M1
Model
1.13 (0.12)
1.04 (0.08)
1.01 (0.11) M2
Model constant SSA
1.14 (0.13)
1.03 (0.09)
0.99 (0.10) M3
Model const. SSA-AOD
1.12 (0.13)
1.02 (0.09)
0.98 (0.10) S3
1 + 3 * Ta (λ)
1.11 (0.13)
1.03 (0.10)
380 nm 1.11…
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

19. Correction results 305nm +11% 324nm +2% 380nm +0%
Post correction methods
Correction results
305nm +11%
324nm +2%
Overview off all corrections.
380nm +0%
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

20. Effects of sza, AOD, SSA, ozone, time on ratios
Post correction methods
Effects of sza, AOD, SSA, ozone, time on ratios
Investigate possible dependance of the ratios and the ocrrections(sza, AOD, Tabs, ozone, time
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

21. Spatial and temporal UV variability within an OMI grid
Campaign: 1 to 30 October, 2007
3 sites Each: NILU UV at 305, 324, 380nm CIMEL (AOD, SSA, ..) Pyranometer, sky camera Main site + Brewers Spectral UV, ozone CCD (spectral AOD) 2 Lidars (City – Rural)
Last part includes
Red line city, yellow industrial area, green rural area, Epanomi
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

22. UV Measurements at the three sites
Spatial and temporal UV variability within an OMI grid
UV Measurements at the three sites
Results of Irradiance at 324nm and OMI
Mean deviations same levels (included)
AUTH +15, Epanomi +21, Sindos +18 sd(16, 50 , 31) mean +16
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

23. AOD variability in an OMI grid
Spatial and temporal UV variability within an OMI grid
AOD variability in an OMI grid
Patterns saharan dust event
Second period very low aerosols with aerosol building up especially at the city area
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

24. UV differences in an OMI grid
Spatial and temporal UV variability within an OMI grid
UV differences in an OMI grid
+20%
-20%
5 clear days of the second period
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

25. Spatial UV variability at 3 stations (2 * sigma / mean)*100
Spatial and temporal UV variability within an OMI grid
Spatial UV variability at 3 stations (2 * sigma / mean)*100
Variability calculate mean and st deviation to get rid of the absolute differences divide with mean
Colors NILU minutes
% second period statistics 90% within 18%
Just the selection of the station for the comparison
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

26. Temporal UV variability
Spatial and temporal UV variability within an OMI grid
Temporal UV variability
Tenporal : variability for the whole month including cloudy and cloudless
(2 * sigma / mean)*100
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

27. Conclusions
3.5 years of OMI and ground based at Thessaloniki, Greece: measurement comparison showed an OMI overestimation of UV irradiances.
Cloudless cases: Main reason is the aerosol absorption. Higher deviations at lower wavelengths
Possible methods to correct this effect: AOD and SSA measurements or/and an aerosol absorption climatology needed in a global scale
SSA in the UV: while mean SSA at 440 nm is 0.90 (Thessaloniki) an SSA of 0.82 is needed for eliminating GB and OMI UV differences at 305nm. SSA at UV-B wavelengths needs further investigation.
Simple public information (e.g. UVINDEX) retrieved from OMI at such populated-urban areas are affected from this bias. +20% on cloudless day.
Aerosol variation within an OMI satellite pixel can cause UV differences equal to a percentage (~18%) that 90% of cloudless comparison cases lie within. Statistical analysis limitations ?
Spatial and temporal UV variability has to be taken into account when comparing GB and satellite UV, especially at city areas.
Comparison under cloudy conditions requires more investigation as absolute differences are large and spatial and temporal UV variability plays a very important role on single station – satellite, comparison.
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

28. Thank you Campaign acknowledgments: D. Balis, N. Kouremeti, V
Thank you Campaign acknowledgments: D. Balis, N. Kouremeti, V. Amiridis, M. Zebila, E. Giannakaki, J. Herman, AERONET
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

29. OMI – GB normalized biases 3 stations
Spatial and temporal UV variability within an OMI grid
OMI – GB normalized biases 3 stations
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

30. Back up air masses 4 day back traj
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

31. Back up – Lidar 2 days
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

32. Back up TOMS and UVA correction
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

33. Back up Brewer –MODIS (2000-2007)
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

34. Back up Brewer AOD ( )
Aerosol optical depth, origin and transport:
Mean monthly aerosol optical depth derived from 9 years of Brewer direct sun measurements. Mean values from each cluster is presented. Clusters represent the location of the origin of the air masses arriving after 48 hours at Thessaloniki for the height of 1500m.North east cluster and especially on summer months represents air masses with biomass burning aerosol loading.
Kazadzis 2007 ACP

35. Back up SSA Thessaloniki (1998-2005)
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

36. Back up SSA scout
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008

37. Spatial and temporal UV variability within an OMI grid
Spectral measurements of direct and global UV irradiance at the surface were made with two Brewer spectroradiometers. In addition, global (diffuse plus direct) UV irradiance and photosynthetically active radiation (PAR) were measured, on a minute basis, at each of the three sites with three NILU-UV multi-channel radiometers.
In-situ measurements of aerosol vertical profiles were derived from two Lidar systems operating at (AUTH) and the site of Epanomi.
Total ozone column was derived from the Brewers and cloud observations and sky images at the AUTH site. Cloud observations were performed at all sites at a half hour basis.
Sun and sky radiance measurements were conducted with three CIMEL automatic sun tracking photometers, each installed at one of the three sites. These data were used to derive aerosol optical properties such as the aerosol optical depth (AOD), the Angstrom exponent a (AEa) and the single scattering albedo (SSA).
Stelios Kazadzis, OMI science team meeting Helsinki, June 2008