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 7.8.2018

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 7.8.2018

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 7.8.2018

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 70 -80 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 7.8.2018

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 2004 -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 7.8.2018

Results 305nm OMI +30% 324nm OMI +17% OMI – GB UV comparison – statistics Results Results Y axsis Brewer full circles cloudless cases 305nm OMI +30% 324nm OMI +17% Stelios Kazadzis, OMI science team meeting Helsinki, June 2008 7.8.2018

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 7.8.2018

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 7.8.2018

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 7.8.2018

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 7.8.2018

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 7.8.2018

Post correction : method 1 Post correction methods Post correction : method 1 Ta (λ) = AOD(λ) * [1 - SSA(440nm)] Aerosol absorption CF(λ) = 1.1 + 1.5 * Ta(λ) no sza dependence SSA @ 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 7.8.2018

Post correction: method 2 Post correction methods Post correction: method 2 Tas =Ta / cos(sza) Aerosol absorption CF(λ) = 1.07 + 1.8 * Tas(λ) SSA @ UV ? need of GB data Improve sza dependence Normalized Tabs – new slope Stelios Kazadzis, OMI science team meeting Helsinki, June 2008 7.8.2018

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 SSA@440 = const S3: AOD= const and SSA@340 = const Stelios Kazadzis, OMI science team meeting Helsinki, June 2008 7.8.2018

Overview of post corrections Post correction methods Overview of post corrections 6th Approach: CF(λ) = 1 + 3 * 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 7.8.2018

Overview of post corrections Post correction methods Overview of post corrections 6th Approach: CF = 1 + 3 * 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 – 1.11-1.17 small improvement of sigma Stelios Kazadzis, OMI science team meeting Helsinki, June 2008 7.8.2018

Overview of post corrections Post correction methods Overview of post corrections 6th Approach: CF = 1 + 3 * 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 1.15.. 1.02-1.07 Stelios Kazadzis, OMI science team meeting Helsinki, June 2008 7.8.2018

Overview of post corrections Post correction methods Overview of post corrections 6th Approach: CF = 1 + 3 * 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…0.98-1.05 Stelios Kazadzis, OMI science team meeting Helsinki, June 2008 7.8.2018

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 7.8.2018

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 7.8.2018

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 7.8.2018

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 7.8.2018

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 7.8.2018

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 7.8.2018

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 1 - 60 minutes 10- 18 % second period statistics 90% within 18% Just the selection of the station for the comparison Stelios Kazadzis, OMI science team meeting Helsinki, June 2008 7.8.2018

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 7.8.2018

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 7.8.2018

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 7.8.2018

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 7.8.2018

Back up air masses 4 day back traj Stelios Kazadzis, OMI science team meeting Helsinki, June 2008 7.8.2018

Back up – Lidar 2 days Stelios Kazadzis, OMI science team meeting Helsinki, June 2008 7.8.2018

Back up TOMS and UVA correction Stelios Kazadzis, OMI science team meeting Helsinki, June 2008 7.8.2018

Back up Brewer –MODIS (2000-2007) Stelios Kazadzis, OMI science team meeting Helsinki, June 2008 7.8.2018

Back up Brewer AOD (1996-2007) 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 7.8.2018

Back up SSA Thessaloniki (1998-2005) Stelios Kazadzis, OMI science team meeting Helsinki, June 2008 7.8.2018

Back up SSA scout Stelios Kazadzis, OMI science team meeting Helsinki, June 2008 7.8.2018

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 7.8.2018