The CCREST campaign

Characterising CirRus and icE cloud acrosS thespecTrum
Anthony Baran, Stuart Fox + many others
2nd ESA EarthCARE Validation Workshop,27 May 2021
Contact:
anthony.baran@metoffice.gov.uk
stuart.fox@metoffice.gov.uk

www.metoffice.gov.uk© Crown Copyright 2020, Met OfficeCampaign motivation
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Ice clouds play an important role in the earthatmosphere radiation balance for both weather
forecasting and climate modelling
Significant uncertainties in understanding of ice cloudradiative impact:• Diversity of ice crystal size and shape• Mass-dimension and area-dimension
relationships• Shape and extent of size distribution (particularlysmall ice)
Retrieval of ice microphysics from remote sensing
requires realistic ice optical models across thespectrum
Also needed for all-sky assimilation in NWP models
Existing scattering databases are not fully consistent
with observations

The long-term averaged Met Office ES model (GA 7)
predictions of (a) short-wave and (b) long-wave TOA
irradiances minus the CERES EBAF product fromWalters et al. gmd-12-1909-2019

Radar/lidar/SW radiative closure studyfrom Ewald et al. amt-2020-448

Mid- and far-infrared closure
study from Bantges et al.
acp-20-12889-2020

Objectives (wider project, airborne campaign is one component)•Constrain the shape of the small ice and large ice modes in the PSD•

Determine which shapes of ice crystals and their aggregations mostly contribute to the observed mass– andarea–dimension power laws
Determine whether it is possible to obtain consistent representations of cirrus and ice cloud throughgeneralisations of mass– and area–dimension relationships and their single-scattering properties. To apply
optimal representations to improve all-sky data assimilation of cloudy radiances
Reduce uncertainty in the globally-averaged short-wave and long-wave irradiances at the TOA to within current
observational uncertainties of ±10 W m-2
Reduce uncertainty in solar and infrared heating rate profiles of cirrus and ice cloud to within several K d-1
Reduce modelled zonally-averaged temperature biases through improved ice cloud representation
Understand and quantify the contributions of cirrus and ice cloud to uncertainties in global cloud feedbacks andclimate sensitivity

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Comprehensive in-situ
microphysics observations

Observation requirements•••

Simple scenes••

Single-layer cirrus
Well-characterised surface

Simultaneous in-situ
and remote sensing
observations

Passive and active remotesensing••

Multiple aircraft required••

Simultaneous in-situ/remote
Instrument payloads

Radiometer, radar, lidar
Fully-characterised cloudscenesFull size distributions
Reliable small ice measurements
Bulk liquid/ice water content

EarthCARE
FORUM

Spectrally-resolved
observations across theelectromagnetic spectrum•

microwave/sub-mm, far-ir, mid-ir, SW

Planning status• Campaign proposal approved by internal Met Office advisory groupMay 2020

September
2020

April 2021

• First CCREST workshop held to bring together interested parties, introduce the campaign and discuss next steps• Following the workshop, a campaign White Paper was produced• Interested parties to explore options for funding participation• Second CCREST workshop held
• Campaign timing/locations discussed• Prepare funding/grant proposals, confirm participation of partners• Choose campaign location
2021-2022 • Ongoing instrumentation development• Detailed campaign planning2023• Preferred time for CCREST
March 2024••••

Aircraft availability
Occurrence of single-layer cirrus
Low cloud-top height
Sufficient solar zenith angle

EarthCARE co-ordination/synergy
Definite• Co-ordinate with EarthCARE track when it coincides with CCREST scene of interest
Possible• Perform additional cloud observations coincident with EarthCARE where they are of relevanceto CCREST goals e.g.:• In-situ cloud microphysical measurements to constrain mass-area-dimension relationships
Unlikely• Dedicated EarthCARE flights observing scenes with no CCREST interest, e.g. clear sky/aerosol
Questions• What cloud scenes are of most interest for EarthCARE cal/val?
• What observations types (e.g. in-situ or remote sensing) are most useful? Which are preferred tohave the closest co-incidence to the satellite overpass?