1. OMI Science Team 2014, Anders Lindfors / FMI OMI cloud optical depth contributes to the observed positive bias in surface UV Anders V. Lindfors, T. Mielonen, M.R.A. Pitkänen, A. Arola, J. Tamminen Finnish Meteorological Institute

2. What is known about OMUVB performance? OMUVB is known to overestimate the surface UV Discussion has concentrated on aerosols as the reason for overestimation Mikko Pitkänen (MSc, 2013)  comparison in Jokioinen and Sodankylä, matching the overpass time  cloud classification using sunshine duration, cloud amount, surface solar radiation  OMUVB performance depends on clouds  overcast conditions: stronger overestimation  similar results also in other studies: Weihs et al. (ACP, 2008) OMI Science Team 2014, Anders Lindfors / FMI Sodankylä cloud-free rMB = 0.08 Sodankylä overcast rMB = 0.29

3. OMUVB under overcast clouds? Interest in understanding why there is a systematic, cloud-related overestimation in OMUVB No proper validation of OMI cloud optical depth (COD) has been done COD is a primary input to OMUVB calculations Idea: to compare OMI COD (Aura) with MODIS COD (Aqua) Aim: to understand more about why OMUVB overestimates in overcast conditions OMI Science Team 2014, Anders Lindfors / FMI http://en.wikipedia.org/wiki/A-train_(satellite_constellation)

4. Matching OMI and MODIS CODs OMI 24 x 13 km (nadir) selected footprint in white MODIS zoom-in: same area 16 min before selected OMI pixel in white 200—400 MODIS pixels

5. OMI cloud optical depth  how compare with MODIS? how to compare CODs from two different instruments? MODIS 1 x 1 km OMI 13 x 24 km COD 1 COD 2 CMF 1 CMF 2 exponential relation R vs COD logarithmic average of COD has been found to be useful from MODIS cmp/w OMI COD R2R2 R1R1 Figure from Zinner and Mayer (JGR, 2006) MODIS

6. OMI cloud optical depth  how compare with MODIS? how to compare CODs from two different instruments? MODIS 1 x 1 km OMI 13 x 24 km COD 1 COD 2 exponential relation R vs COD logarithmic average of COD has been found to be useful from MODIS cmp/w OMI COD R 1,2 Figure from Zinner and Mayer (JGR, 2006) OMI CMF 1,2

7. CMF = Cloud Modification Factor CMF = F all-sky / F cloudfree CMF can be averaged (assuming independent pixel radiative transfer):  CMF 1,2 = (CMF 1 + CMF 2 )/2  CMF MODIS = CMF 1,2,…,N  CMF MODIS cmp/w CMF OMI radiative transfer model used to calculate CMF MODIS and CMF OMI OMI Science Team 2014, Anders Lindfors / FMI COD 1 COD 2 CMF 1,2 = ( CMF 1 + CMF 2 ) / 2

8. OMI vs. MODIS (#1): nr of colocated pixels OMI Science Team 2014, Anders Lindfors / FMI 10 days: 10—19 July 2006 1.4 x 10 6 colocated pixels in total Only OMI footprints fully cloudy as seen by MODIS were included Finland is sunny !

9. OMI vs. MODIS (#2): COD vs. exponent of log-averaged COD OMI Science Team 2014, Anders Lindfors / FMI All cases included 1.4 x 10 6 colocations good agreement OMI somewhat lower than MODIS for COD>10

10. OMI vs. MODIS (#3): COD vs. exponent of log-averaged COD OMI Science Team 2014, Anders Lindfors / FMI MODIS ice clouds 500 x 10 3 colocations OMI COD somewhat higher than MODIS

11. OMI vs. MODIS (#4): COD vs. exponent of log-averaged COD OMI Science Team 2014, Anders Lindfors / FMI MODIS water clouds 450 x 10 3 colocations OMI COD clearly lower than MODIS

12. Undestanding difference between ice and water clouds OMI Science Team 2014, Anders Lindfors / FMI ICE WATE R OMI More backscatter for same optical depth OMI cloud model always assumes water clouds Scattering phase function of ice: more backscatter  OMI sees ice clouds as thicker!  This explains relative difference between water / ice cloud performance

13. OMI vs. MODIS (#5): CMF vs. latitude OMI Science Team 2014, Anders Lindfors / FMI All cloud types 10 th /90 th percentile limits: COD 1—80 OMI CMF higher or at same level as MODIS Finnish latitudes (60 N):  small CMF difference of 0.02—0.03

14. OMI vs. MODIS (#6): CMF vs. latitude OMI Science Team 2014, Anders Lindfors / FMI Ice clouds 10 th /90 th percentile limits: COD 1—80 OMI CMF lower than MODIS  CMF difference 0.02

15. OMI vs. MODIS (#7): CMF vs. latitude OMI Science Team 2014, Anders Lindfors / FMI Water clouds 10 th /90 th percentile limits: COD 1—80 OMI CMF clearly higher than MODIS Finnish latitudes (60N):  CMF difference 0.06

16. OMI Science Team 2014, Anders Lindfors / FMI To Conclude Results are preliminary, more analysis needed:  categorize by SZA, VZA, etc.  regional aspects OMI underestimates water cloud COD as compared to MODIS OMI overestimates ice cloud COD as compared to MODIS Overall: overestimation somewhat dominates  can only explain 5—10% of systematic difference between cloud-free and overcast surface UV  At FMI’s stations observed difference is ~20 % How good is MODIS?

17. COD as function of wavelength OMI COD is representative for UV wavelengths, based on radiance at ca 360 nm MODIS is representative for mid- visible, based on visible and IR radiances (what precisely?) Figure shows the COD of libRadtran following Hu & Stamnes – minimum tau=7.44 (360nm) – maximum tau=7.65 (660nm) This means MODIS and OMI CODs are comparable although there is a different in wavelength