Lessons for EarthCARE from the assimilationof cloud-affected Aeolus backscatter
Mark Fielding
Marta Janisková, Karen Henry,Will McLean, Angela BenedettiPre-launch EarthCARE science andvalidation workshop, ESA-ESRINNovember 15th 2023

© ECMWF December 6, 2023

ATLID and ALADIN are on the same side!
• Previously, all cloud lidar assimilation experiments at ECMWF haveused CALIPSO observations as a proxy for EarthCARE data.
• Aeolus ALADIN lidar is technically much closer related to EarthCARE’sATLID than the CALIPSO lidar, despite its primary goal of measuringline-of-sight winds.

• Several activities investigating the benefit of Aeolus aerosol backscatter(e.g., AEOLUS DISC), but, so far, cloud has mainly been seen as noisethat must be removed.
➢ Can Aeolus observations be used to prepare for ATLID assimilation?
➢ How useful is Aeolus cloud backscatter for NWP?
➢ Can Rayleigh backscatter be assimilated?

Vertical resolution and pointing angle are the major differences
between ATLID and ALADIN
CharacteristicEarthCARE ATLID

Aeolus ALADIN

Specification

3° off-Nadir
355 nm0.62 m diameter telescope
35 μrad receiver field of view

37.5° off-Nadir
355 nm1.50 m diameter telescope
19 μrad receiver field of view

Altitude

400 km

400 kmResolution

103 m vertical
0.285 km horizontal
0.03 km footprint

500 m - 1000 m vertical~5 km horizontal
0.009 km footprint

Misc.

High-spectral-resolution
receiver with Rayleigh and Mie
co-polar and total cross-polar
channels

High-spectral-resolution receiverwith Rayleigh and Mie copolar
channels only

…requires some adaptations to observation operator

Observation-side
Data products and pre-processing

Observation screening

Initially L2A total attenuatedbackscatter. Capability for
individual HSRL channels

ATLID

Mie attenuated backscatter
ALADIN

Rayleigh attenuated backscatter

Observation errors

Comprehensive, based upon
CALIPSO studies and L2A
cloud mask.

Error inventory approach,combining representativity error*,
instrument error and forward
model error

Basic screening on FG
departures and minimum
backscatter values

Fixed value of 10 dB*see Fielding and Stiller 2019, JGR

Model-side

4D-VarMicrophysical assumptions

Observation operator

PSD: Field et al., 2007

Triple column approachaccounting for sub-gridcondensate variability
and cloud overlap. Plattapproximation for multiple
scattering. + adaptations
for ALADINATLIDJOINTALADINSingle scattering
properties: Baran?? 2010
mixture with fixed lidar
ratio (consistent withCAPTIVATE retrievals)

See Fielding and Janisková 2020, QJRMS

Bias correction
Initially none, thenclimatological based upon
temperature and region.

NoneAdapting the observation operator for ALADIN
Optical depth due
to clouds
Platt coefficient

Apparent
backscatter𝛽′ 𝑟Optical depth
due to gases−2 (𝜂𝜏𝑐𝑙𝑜𝑢𝑑 +𝜏𝑔𝑎𝑠 )cos 𝜃= (1 − 𝛿)𝛽(𝑟)𝑒Slant angle

Depolorization ratio

Unattenuatedbackscatter

Modifications for ALADIN

Determining the depolarization ratio

Theoretical (355 nm)• Unlike spherical particles, such as water droplets, ice particles are
generally strongly depolarizing.
• Depolorization ratio can be measured empirically or computed
numerically from assumed ice particle shapes.
Observed using CALIPSO (532 nm)
Okamoto et al., 2019

Choose a constant𝛿=0.4 for initial testing
Courtesy NASA (CALIPSO user guide)Hu, 2007

Choosing test period --- ECMWF monitoring of Aeolus HLOS winds
Mid-mission: lower errors, relatively high laser energy

Rennie and Isaksen, 2023

12-hourly monitoring of Aeolus L2A Mie attenuated backscatter+ 3 s.d.
mean (FG dep)(dB)
- 3 s.d.

s.d. (FG dep)(dB)

Number ofobservations

2020-06-01

Monitoring shows stable observations during period
2020-09-01

Aeolus orbit– 1st June 2020
Mie attenuated backscatter
PSCs

Aerosol?

ObsModelGenerally good agreement withobservations

Latitude (degN)

Brighter ice cloud topsAeolus orbit– 1st June 2020
Rayleigh attenuated backscatter
PSCs

Signal too noisy to provide
information on air density

Aerosol?

Obs

Model

Generally good agreement withobservations

Latitude (degN)

Rayleigh signal not affected by depolarization

Climatology of observed and simulated cloud fraction – June 2020

PSCs

Aeolus Mie cloud fraction

Simulated Mie cloud fraction

Artefact?

Surface returns

Model deficiency?
Aerosols?

Comparison of Aeolus and CALIPSO observed cloud amountMore noise inAeolus
backscatter?

Aeolus Mie cloud fraction

Simulated Mie cloud fraction

June 2020
PSCsbrighter at355 nm

CALIPSO cloud fraction

Simulated CALIPSO cloud fraction

June 2010

More screening
in CALIPSOobs?

See Feofilov et al., 2022 AMT for more detailed analysis

4D-Var experiment setup• CY48R1 4D-Var experimentation using a horizontal resolution of TCo639 spectral
truncation (corresponding to ~ 18 km on a cubic octahedral grid) and 137 levels:o 3-month period: 1 June 2020 – 31 August 2020

• Measurements of L2A Mie and Rayleigh attenuated backscatter (at 355 nm, ALADIN)
superobbed to (O160-> ~72 km) and 1 km vertical heights.

• Performed experiments:o Control – reference run, run with all regularly assimilated observations except
Aeolus winds
o +winds – operational configuration including Aeolus HLOS winds – see Rennie etal., 2021
o +clouds – experimental run including attenuated Mie and Rayleigh attenuatedbackscatter lidar observations on top of other regularly assimilated observations
o +winds+clouds - experimental runs including attenuated Mie and Rayleighattenuated backscatter lidar observations and HLOS winds
Rennie, et al., 2021: The impact of Aeolus wind retrievals on ECMWF global weather forecasts. QJRMS

Assimilating Aeolus cloud obs. broadly neutral on forecasts of large-scale variables+clouds+winds+clouds+winds

0.02

0.0

Wind-0.02

Difference in RMS error normalised by RMS
error of control

Temperature

0.04 REDworse-0.04
BLUEbetter

3-month period: 1 June 2020 – 31 August 2020

Assimilating Aeolus cloud Mie and Rayleigh backscatter has slight positive benefit
on microwave all-sky obs!
MWRIATMSHumidity andtemperature

Humidity

Temperature

More careful bias correction
and observation error tuning
should increase impact
Time period: 03-06-2020 to 31-08-2020

Summary• Aeolus cloud backscatter observations have been assimilated into a global model forthe first time!
• Initial results show impact is broadly neutral, but slight additional positive benefit whensimultaneously assimilating winds and cloud information.
• Cloud observations from Aeolus could be useful for model evaluation – Aeolus sees
clouds at different point in diurnal cycle. PSCs are clearly visible!

• More careful cloud/aerosol screening required for comparison with CALIPSO➢ Can Aeolus observations be used to prepare for ATLIDassimilation?
➢ How useful is Aeolus cloud backscatter for NWP?
➢ Can Rayleigh backscatter be assimilated?

EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS

YES

YES

YES (but more analysis required)☺

October 29, 201416