Incorporating EarthCARE observations into a multi-lidar cloud climate record: the ATLID (Atmospheric Lidar) cloud climate product
Authors: Feofilov Artem G. , Chepfer Hélène , Noël Vincent , Szczap Frederic 
Published: July 2023

Abstract. Despite significant advances in atmospheric measurements and modeling,
clouds' response to human-induced climate warming remains the largest source
of uncertainty in model predictions of climate. The launch of the Cloud-Aerosol
Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite in 2006
started the era of long-term spaceborne optical active sounding of
Earth's atmosphere, which continued with the CATS (Cloud-Aerosol Transport
System) lidar on board the International Space Station (ISS) in 2015 and the Atmospheric Laser Doppler
Instrument (ALADIN) lidar on board Aeolus in 2018. The next important step
is the Atmospheric Lidar (ATLID) instrument from the EarthCARE (Earth Clouds, Aerosols and Radiation Explorer) mission,
expected to launch in 2024. In this article, we define the ATLID Climate Product, Short-Term (CLIMP-ST)
and ATLID Climate Product, Long-Term (CLIMP-LT). The purpose of CLIMP-ST is
to help evaluate the description of cloud processes in climate models,
beyond what is already done with existing space lidar observations, thanks
to ATLID's new capabilities. The CLIMP-LT product will merge the ATLID cloud
observations with previous space lidar observations to build a long-term
cloud lidar record useful to evaluate the cloud climate variability
predicted by climate models. We start with comparing the cloud detection capabilities of ATLID and CALIOP
(Cloud-Aerosol Lidar with Orthogonal Polarization) in day- and nighttime, on
a profile-to-profile basis in analyzing virtual ATLID (355 nm) and CALIOP
(532 nm) measurements over synthetic cirrus and stratocumulus cloud scenes.
We show that solar background noise affects the cloud detectability in
daytime conditions differently for ATLID and CALIPSO. We found that the simulated daytime ATLID measurements have lower noise than
the simulated daytime CALIOP measurements. This allows for lowering the cloud
detection thresholds for ATLID compared to CALIOP and enables ATLID to
better detect optically thinner clouds than CALIOP in daytime at high horizontal
resolution without false cloud detection. These lower threshold values will
be used to build the CLIMP-ST (Short-Term, related only to the ATLID
observational period) product. This product should provide the ability to evaluate
optically thin clouds like cirrus in climate models compared to the current
existing capability. We also found that ATLID and CALIPSO may detect similar clouds if we convert
ATLID 355 nm profiles to 532 nm profiles and apply the same cloud detection
thresholds as the ones used in GOCCP (GCM-Oriented CALIPSO Cloud Product; general circulation model).
Therefore, this approach will be used to build the CLIMP-LT product. The CLIMP-LT
data will be merged with the GOCCP data to get a long-term (2006–2030s)
cloud climate record. Finally, we investigate the detectability of cloud
changes induced by human-caused climate warming within a virtual long-term
cloud monthly gridded lidar dataset over the 2008–2034 period that we
obtained from two ocean–atmosphere coupled climate models coupled with a
lidar simulator. We found that a long-term trend of opaque cloud cover
should emerge from short-term natural climate variability after 4 years
(possible lifetime) to 7 years (best-case scenario) for ATLID merged with
CALIPSO measurements according to predictions from the considered climate
models. We conclude that a long-term lidar cloud record built from the merging
of the actual ATLID-LT data with CALIPSO-GOCCP data will be a useful tool for
monitoring cloud changes and evaluating the realism of the cloud changes
predicted by climate models.