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

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

Sodankyläcloud-free

rMB = 0.08

Sodankyläovercast

rMB = 0.29

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)

Matching OMI and MODIS CODsOMI 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

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

COD1 COD2

CMF1 CMF2• exponential relation R vs COD• logarithmic average of COD has been

found to be useful

• from MODIS cmp/w OMI COD

R2

R1

Figure from Zinner and Mayer (JGR, 2006)

MODIS

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

COD1 COD2

• exponential relation R vs COD• logarithmic average of COD has been

found to be useful

• from MODIS cmp/w OMI COD

R1,2

Figure from Zinner and Mayer (JGR, 2006)

OMI

CMF1,2

CMF = Cloud Modification Factor• CMF = Fall-sky / Fcloudfree

• CMF can be averaged (assuming independent pixel radiative transfer):

CMF1,2 = (CMF1 + CMF2)/2

CMFMODIS = CMF1,2,…,N

CMFMODIS cmp/w CMFOMI

• radiative transfer model used to calculate CMFMODIS and CMFOMI

OMI Science Team 2014, Anders Lindfors / FMI

COD1 COD2

CMF1,2 = ( CMF1 + CMF2 ) / 2

OMI vs. MODIS (#1): nr of colocated pixels

OMI Science Team 2014, Anders Lindfors / FMI

• 10 days: 10—19 July 2006

• 1.4 x 106 colocated pixels in total

• Only OMI footprints fully cloudy as seen by MODIS were included

• Finland is sunny !

OMI vs. MODIS (#2): COD vs. exponent of log-averaged COD

OMI Science Team 2014, Anders Lindfors / FMI

• All cases included

• 1.4 x 106

colocations• good agreement• OMI somewhat

lower than MODIS for COD>10

OMI vs. MODIS (#3): COD vs. exponent of log-averaged COD

OMI Science Team 2014, Anders Lindfors / FMI

• MODIS ice clouds• 500 x 103

colocations• OMI COD

somewhat higher than MODIS

OMI vs. MODIS (#4): COD vs. exponent of log-averaged COD

OMI Science Team 2014, Anders Lindfors / FMI

• MODIS water clouds

• 450 x 103

colocations• OMI COD clearly

lower than MODIS

Undestanding difference between ice and water clouds

OMI Science Team 2014, Anders Lindfors / FMI

ICE WATER

OMIOMI

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

OMI vs. MODIS (#5): CMF vs. latitude

OMI Science Team 2014, Anders Lindfors / FMI

• All cloud types• 10th/90th 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

OMI vs. MODIS (#6): CMF vs. latitude

OMI Science Team 2014, Anders Lindfors / FMI

• Ice clouds• 10th/90th percentile

limits: COD 1—80 • OMI CMF lower than

MODIS CMF difference 0.02

OMI vs. MODIS (#7): CMF vs. latitude

OMI Science Team 2014, Anders Lindfors / FMI

• Water clouds• 10th/90th percentile

limits: COD 1—80 • OMI CMF clearly

higher than MODIS• Finnish latitudes

(60N): CMF difference 0.06

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?

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