Lessons learned from the validation of Aeolus
L2A product with EARLINETNikos Siomos (NOA)
Holger Baars (TROPOS)
Contribution from the EARLINET consortium
ESA UNCLASSIFIED – For ESA Official Use Only

2nd ESA EarthCARE Validation Workshop
25-28 May 2021 (online)
1

EARLINET Cal/Val
Evaluate the AEOLUS satellite L2A product with the retrievals of the ground-based lidar systems
of EARLINET (European Aerosol Research Lidar Network)
StationNo. of Overpasses

Antikythera

8Andoya1AthensUnder Processing

Barcelona

20

Bucharest

2

Granada14

Evora25

Lecce

2

Leipzig

Under ProcessingLille

3Potenza

6Thessaloniki

9Warsaw

196 Overpasses






AEOLUS Baseline 10files (06/2019 - 10/2020)
AEOLUS Baseline 11 files(10/2020 – 05/2021)
Analysis focused on theAEOLUS Backscatter
Conversion to AEOLUS
like co-polar backscatter
when possible

Backscatter profiles from 13 stations were analysed –more will be added soon
4 stations included depolarization ratio profiles at 355m –used for conversion to AEOLUS like BackscatterMethodology
Collocation Criteria
Spatial collocation → 100km

Temporal collocation → ±3 hoursHandling multiple profiles in a single overpass●Closest overpass: The closest satellite profile in time to
the ground-based measurement is selected●Average overpass: The satellite profiles (up to 3 for100km radius) are averaged

Methodology
Basic Cloud Screening on AEOLUS profiles
Using the profile optical depth → less than 1.5

Using bin-to-bin backscatter difference → less than 7.5 Mm-1 sr-1

Methodology
Basic Cloud Screening on AEOLUS profiles
Using the profile optical depth → less than 1.5

Using bin-to-bin backscatter difference → less than 7.5 Mm-1 sr-1

More sophisticated approaches in the future (not implemented here)Use satellite cloud data (e.g. MSG) for automated cloud screeningAeolus-like products: backscatter coefficient
Simulation for a typical dust aerosol layer witha linear particle depolarization ratio ~30%

AEOLUS detects the co-polar component from circularly
polarized radiation at 355nm → underestimation whencomparing to the total backscatter

Some EARLINET stations perform linear particle
depolarization measurements

The total backscatter can be converted to AEOLUS like:●●by converting the particle linear to particle circulardepolarization ratio first
Then use the particle circular depolarization ratio toconvert the total to co-polar backscatter (AEOLUS likebackscatter)

It is important to identify thedust cases!

Dust mask
EARLINET based flags
Thresholds applied on depolarization profiles (355 or 532nm)
Particle Dep. Ratio between 0.1 and 0.4 in a vertical region larger than 500m in the profile
Not all stations have depolarization channels!
Antikythera Sample Profiles

PDR at 355nmPDR at 355nm

Dust
Altitude [km]Dust
Altitude [km]No dustAltitude [km]Altitude [km]No dustPDR at 355nm

PDR at 355nm

Dust mask
AERONET based flags (Version 3 – Level 1.5 files)
Using the Fine Mode Fraction 550nm and the Single Scattering Albedo 440nm

FMF usually available for daytime direct sun measurements

Lee et al. 2010
Siomos et al. 2020

Some examples
Cloud Mask off

Cloud Mask onHere at least 1 satellite profile within the overpass was cloud free.

Removing the cloudy ones leaves the best to be selected as overpass for the Average profile

Some examples
Cloud Mask off

Cloud Mask on

The ground spike is common. It is not clear if it due to cloud contamination

The bin-to-bin backscatter threshold leads to better profiles

EARLINET vertical profiles to AEOLUS vertical levels
The conversion is performed casewise
Each overpass corresponds toslightly different altitude verticallevels due to orography• Rescaling of ground profiles to AEOLUS vertical bins
• Modification on the profile shape and optical properties
magnitude• Necessary in order to quantify the differences!

Correlation – cloud mask off

AEOLUS Backscatter [Mm-1 sr-1]

AEOLUS Backscatter [Mm-1 sr-1]

Altitude [km]Altitude [km]

Altitude [km]Altitude [km]EARLINET Backscatter [Mm-1 sr-1]

EARLINET Backscatter [Mm-1 sr-1]

Larger AEOLUS backscatter values due to clouds --> low correlation

Correlation – cloud mask on

AEOLUS Backscatter [Mm-1 sr-1]

Altitude [km]Altitude [km]

AEOLUS Backscatter [Mm-1 sr-1]

Altitude [km]Altitude [km]EARLINET Backscatter [Mm-1 sr-1]

EARLINET Backscatter [Mm-1 sr-1]

Most large values are removed and the correlation improvesHigher correlation values for the Middle Bin algorithm – closest profile better correlated for the co-polarBiases below 2km – cloud mask on

AEOLUS tendency to overestimate below 2km in the Middle bin algorithm
Reason --> Ground spike! It mainly occurs to Middle Bin

Biases above 2km – cloud mask on

Better statistics above 2km! Both the mean bias and the spread are reduced
Using the co-polar backscatter doesn’t seem to improve the bias BUT the number of co-polar data is limited
Applying the dust flags will show if there is a clear negative AEOLUS total backscatter bias

SummaryA basic cloud mask can be achieved from AEOLUS data – awaiting for the Baseline 12
products that include scene homogeneity flagging
AEOLUS vs EARLINET backscatter correlation increase from approx. 0.2 - 0.3 to 0.5 - 0.7 bythrowing out the cloud contaminated data
Better correlation for the Middle Bin than the Rayleigh Bin
The ground spike issue is more pronounced in the Middle Bin algorithm leading to positive
biases below 2km
Better statistics (mean absolute bias and spread) above 2km: MAB 1.25 → 0.35 Mm-1sr-1
Spread: 2.5 → 0.5 Mm-1sr-1
The dust flags will be applied soon → check if dust cases are associated with more negative
total backscatter mean biases

Thank you for your attention!
2nd ESA EarthCARE Validation Workshop
25-28 May 2021 (online)
ESA UNCLASSIFIED – For ESA Official Use Only17