CPR L2, cloud & precipitation
algorithm developer needs
27 May 2021
2nd EarthCARE calibration/validation
workshop
ESA UNCLASSIFIED – For ESA Official Use Only1

Cloud-top, vertically integrated and layerwise
Quantity
Macrophysics

Cloud-top height
Cloud-top phase & type
Optical thickness

Effective radius

Ice cloud& snow

Water path
Surface snow rate*

Optical thickness

Liquid cloud Effective radiusRain

At nadir
M-COP, A-CTH,A-TC, C-TC, AC-TC
M-CM, A-TC, C-TC,AC-TC
M-COP, A-EBD,ACM-CAP

M-COP, A-ICE,ACM-CAP
M-COP, A-ICE, C-CLD,ACM-CAP
C-CLD, ACM-CAP

M-COP, A-EBD,ACM-CAP
M-COP, ACM-CAP

Across-track
M-COP, AM-CTH
M-CM, AM-CTH
M-COP

Vertical profiles
Quantity
Cloud/precipitation
fraction
Cloud/precipitation
classification

At nadirA-TC, C-TC, AC-TC
A-TC, C-TC, AC-TC

Extinction

A-EBD, ACM-COM,ACM-CAP

Extinction-to-backscatter
ratio

A-EBD, ACM-CAP

M-COP

Effective radius

M-COP

Water content
Snow rate

A-ICE, ACM-COM,ACM-CAP
A-ICE, ACM-COM,ACM-CAP
C-CLD, ACM-CAP

Median diameter
Normalized numberconcentration

C-CLD, ACM-CAP

Density factor (riming)

ACM-CAP

M-COP

Extinction

M-COP

Effective radius

M-COP

Water content

Water path

M-COP, ACM-CAP

Surface rain rate*

C-CLD, ACM-CAP

Rain rate

Rain water path

C-CLD, ACM-CAP

Rain water content
Median drop size
Normalized number
concentration

C-CLD, ACM-CAP

A-EBD, ACM-COM,ACM-CAP
ACM-COM, ACM-CAP
C-CLD, ACM-COM,ACM-CAP
C-CLD, ACM-CAP
C-CLD, ACM-CAP
C-CLD, ACM-CAP
C-CLD, ACM-CAP

2Uncertainty
CPR
L2aAntenna pointing correction
Doppler decomposition:
sedimentation + air motion

Macrophysics

Aerosol/cloud discrimination
Cloud layer detection andstructure
Cloud spatial scales
Liquid clouds not fully
resolved by radar/lidar
synergy

Locations/scenes/regimes• Ice clouds at all latitudes• Range of surface types

Snow microphysics (e.g.
PSDs, microwave scattering,density & fallspeed)• Stratiform vs convective• Rimed snow
• Cloud-tops across range of temperatures, locations &cloud types

Surface snow rate

• Range of meteorological conditions

How to account for• Deep ice clouds: embedded mixed-phase layers

Relation between rain rateand drop size distribution• Warm rain (maritime)• Convective/stratiform rain
• Dependence on snow properties aloft• Continuity of mass flux & size distributions acrossmelting layer

Liquid radiatively-important liquid• Layered cloud scenes
cloud clouds not detected by ATLID • Warm liquid clouds within cold rain
Rain

Melting layer structure &radar attenuation

Products• CFADs of reflectivity and Doppler velocity
from ground-based radars

C-APC, C-CD

• Unrimed/rimed snow
• Multiple-frequency Doppler radars• Drizzle/rain• Convective/stratiform; other sources of vertical motion • In-situ measurements• Ground-based lidars• Cloud embedded in aerosol layers• Collocated in-situ aerosol sampling• Multiple cloud layers• Ground-based (& scanning?) lidars &• Cirrus over liquid cloudradiometers• Non-precipitating liquid clouds• Cumulus & stratocumulus clouds• High-resolution satellite imagery• Land/sea, day/night, boundary layer conditions, etc.
• Physical depth of liquid clouds (i.e. cloud base height) • Ground-based ceilometers/lidars• Mixed-phase layers embedded in ice• Multiple-frequency radars to constrain W• Liquid (& liquid-topped mixed-phase) clouds below
band attenuation
optically thick ice clouds• Microwave radiometers for LWP• Warm liquid clouds within cold rain
• Aircraft profiles of LWC

CPR surface clutter removal

Ice
cloud Ice microphysics (e.g. PSDs,& snow ice optics, mass-size rel’n)Measurements needed

C-CD
A-ALD,
AM-ACD, A-TC
M-CLD,AM-CTH, A-TC,
C-TC, AC-TC
M-CM
A-TC, C-TC,
AC-TC• Ground-based radars• Bulk precipitation and particle imaging
measurements at surface• Profiles of in-situ particle properties in iceclouds• In situ aircraft measurements• Visible & IR radiances

C-TC, C-FMR• Ground-based multiple-frequency radars• Dual-pol weather radars over ocean

C-CLD,
ACM-CAP• Ground-based & airborne multiplefrequency radar

C-CLD,
ACM-CAP

C-CLD,
ACM-CAP

A-ICE,
ACM-CAP
C-CLD,• Ground-based radars and in-situ at surface
ACM-CAP• Microwave radiometer for LWP
ACM-CAP• Profiles of liquid water content

3RADAR OBSERVATIONSESA L2a Products: C-FMR & C-CD

Validation of Doppler variables:•

Validation/calibration of antenna pointing correction (C-APC)•Sedimentation velocity & Doppler spectral width products

Statistical validation: CFADs & joint histograms•

Isolating physical processes:• cloud/precipitation regimes• zonal, land/sea, atmospheric conditions

Ground-based and aircraft measurements:•Attenuation of ground-based W-band radars a challenge fordirect comparison (esp. in rain and mixed-phase scenes)•Aircraft measurements over oceans
4

MACROPHYSICSESA L2b products: C-TC & AC-TC

Uncertainties in target classification•••

Due to ATLID extinction:•Liquid cloud base•Complex & layered scenes

Melting layer•

Diagnosed from ECMWF wet-bulb temperature•Complex vertical structure (& microphysics not
represented in retrievals)

Freezing rain & supercooled drizzle•

Not currently diagnosed, but presumably contribute toradar attenuation

Validation of ground clutter removal•

near-surface CFADs from ground-based radars
5

MICROPHYSICSESA L2b products: C-CLD, ACM-CAP

In-situ ice microphysics:••

Ice particle properties are inherently variable, andneed characterizing across different regimes.
•Particle size distributions (Field et al. 2005)•For consistency across synergistic
measurements, need consistent
representations of particle area and volume,
mass, reflectivity, and terminal velocity.

Density
Fallspeed v = f (D, A, m)

Microwave scattering model: Self-Similar
Rayleigh Gans Approximation (SSRGA; Hogan etal. 2017)•How best to represent rimed snowflakes?
(Mason et al. 2018, 2019)
6

MICROPHYSICSESA L2b products: C-CLD, ACM-CAP
Precipitation microphysics•How to validate rain retrievals over ocean?
•Polarimetric weather radar networks for insights into
precipitation microphysics•

because of wider spatial coverage, possible to build up
direct validation datasets•••

Limited to coastal sites: sufficientlyrepresentative?

Ship-based precipitation gauges anddisdrometers (e.g. OceanRAIN; Klepp et al. 2018)

Snow retrievals do not rely on PIA, so can be morerobustly evaluated over land•Weather radar networks•

Ground stations: in situ & multiple-frequency
radarBAECC 2014
Hyytiälä, Finland (ARM)

7

MICROPHYSICSESA L2b products: C-CLD & ACM-CAP
Statistical validation of cloud & precipitation:••

CFADs of retrieved quantities resolve processes•

Aggregation/riming in snow•

Collision & coalescence, evaporation in rain

Joint histograms (retrieved & in-situ)•Correlations between physical quantities(e.g. parameters of the size distribution)8