Blind tests of radar/lidar retrievals in ice clouds: Assessment in terms of

radiative fluxes

Robin Hogan, Malcolm Brooks, Anthony Illingworth

University of Reading, UK

David Donovan Claire TinelKNMI, The Netherlands CETP, France

Ice cloud retrievals: the problem

• Radar only– Not well

related to radiative properties

• Lidar only– Difficult to

correct for attenuation

Combined radar and lidar

• Current plan for CloudSat and Calipso…– Combine Calipso Level 2 extinction profile with CloudSat

reflectivity product to get IWC and effective radius (size is related to ratio of Z and extinction coefficient)

– But the large errors in the extinction will feed through to very inaccurate retrievals, particularly at cloud base

• Alternative: use radar to constrain lidar inversion– Donovan et al. (2000): find lidar ratio that minimizes the

variation in implied effective radius in furthest few gates– Tinel et al. (2000): find lidar ratio that minimizes the

implied variation in number concentration in the profile– CloudSat must ingest Calipso Level 1 backscatter product

Blind Tests

• At last CloudSat science meeting a “Blind Test” of these algorithms was reported:– I used aircraft spectra to simulate radar/lidar profiles– Dave Donovan and Claire Tinel ran their algorithms to

derive profiles of extinction, IWC and effective radius

• What we found:– Both algorithms retrieved extinction very accurately,

even for 1-way optical depths of up to 7 (lidar reduced by 10-6)

– Stable to uncertain lidar extinction-to-backscatter ratio

– However, re and IWC retrievals sensitive to mass-size relation

Blind Test 1

(From aggregation study)

• No instrument noise• No multiple scattering• No molecular scattering• High lidar sensitivity• Two versions of each

profile provided, with variable or constant extinction/backscatter ratio “k”, which was not known by the algorithms

Blind Test 1:Results 1

• Constant k:– Both Donovan and Tinel

(after modification) algorithms produce highly accurate extinction

• Variable k:– Error in extinction varies

with k, but not unstable

In this talk…• Ultimate test: are these retrievals accurate enough to

constrain the radiation budget?– Perform radiation calculations on true & measured profiles– Assess errors in terms of fluxes and heating rates– What are the most sensitive of the retrieved parameters?

• But in the Blind Test, the “measured” profiles were noise-free and almost infinitely sensitive!

• Second Blind Test simulates instrumental limitations that will be faced by EarthCARE for:– 10-km dwell (1.4 seconds), 400-km altitude, 355-nm lidar– Conclusions similar for CloudSat/Calipso

• Radar/lidar combination better than radar alone?– Also test Z-IWC, Z-, Z-re relationships (from EUCREX)

Case from First Blind Test• Excellent extinction (both Donovan and Tinel)

• Good re if same mass-size relationship used (otherwise 40% too low)

Mitchell relationship

Francis et al. relationship

Radar only retrieval

Extinction coefficient Effective radius

ie

IWCr

23

What about radiative fluxes?• Edwards-Slingo 1-D plane-parallel calculations

– Excellent longwave, good shortwave, slight effect of habit and extinction-backscatter ratio, better than radar alone – Effective radius not very important?

Longwave up

Shortwave up

Clear sky profile

Cloudy profile

Error 20-40 W m-

2 depending on habit and k

Heating rates

• Radar/lidar: very accurate

• Radar alone: almost as good

Second Blind Test: more realistic

• Ice size distributions from EUCREX aircraft data– Correction for 2D-C undercounting of small ice crystals

• Radar– Simulate 100-m oversampling of 400-m Gaussian pulse– Noise added based on signal-to-noise and number of pulses

• Lidar– Add molecular scattering appropriate for 355 nm– Instrument noise: photon counting - Poisson statistics– True lidar sensitivity: incomplete penetration of cloud– Multiple scattering: Eloranta model with 20-m footprint– Extinction-to-backscatter unknown but constant with height– Night-time operation, negligible dark current

Accounting for small ice crystals

– 2D-C probe undercounts small crystals

– Assume gamma distribution for crystals < 100 m diameter

– Mode at 6 m– Same conc. at

100 m– Conc. 2.5 times

higher at 25 m

Instrument noise

• Five new profiles from EUCREX dataset

• This is what they would look like without instrument noise or multiple scattering– Note strong lidar

attenuation

Radar

Lidar

Instrument noise

• Five new profiles…• With instrument noise &

multiple scattering– Radar virtually unchanged

except finite sensitivity– Lidar noise noticeable– Lidar multiple scattering

increases return

• Note: “radar-only” relationships derived using same EUCREX dataset so not independent!

Radar

Lidar

Good case: lidar sees full profile

• Extinction and effective radius reasonable when use same habit and include multiple scattering

Extinction coefficient Effective radius

Donovan: includes multiple scattering

Difference between Mitchelland Francis et al. mass-size

Tinel: no multiple

scattering

Good case: radiation calculations

• OLR and albedo good for both radar/lidar and radar-only (but radar-only not independent)

Longwave up

Shortwave up

Mass-size relationship:

Error~10 Wm-2Underestimate

radiative effect if multiple

scattering neglected

Typical case: radar/lidar retrievals

• No retrieval in lower part of cloud– Important to include multiple-scattering in retrieval

Extinction coefficient Effective radius

Wild retrieval where lidar runs out of

signal

Donovan: good retrieval at cloud

top

Difference between Mitchelland Francis et al.

mass-size relation

Tinel: no multiple

scattering

Typical case: radiative fluxes

• At top-of-atmosphere, lower part of cloud important for shortwave but not for longwave

Longwave up Shortwave up

OLR excellent

:lower part not importan

t

Albedo too low (80 W m-2): lower part

of cloud is important but

mass-size less so (10 W m-2)

Underestimate radiative

effect if multiple

scattering neglected

Typical profile: Heating rates

• Heating profile would be reasonable if full profile was retrieved

• What do we do when the lidar runs out of signal?

Erroneous 80 K/day heating

No cloud observed so no heating by cloud

here

Possible solution: blend profiles

• Where lidar runs out of steam, scale radar-only retrieval for seamless join– Better result than pure radar/lidar or radar only

Extinction coefficient Shortwave up

Lidar becomes unreliable here

BlendedRadar

only

Radar/lidar only

Scale radar-only retrieval to match here

Sensitivity of radiation to retrievals

• Longwave: Easy! (for plane-parallel clouds…)– Sensitive to extinction coefficient– Insensitive to effective radius, habit or extinction/backscatter– OLR insensitive to lower half of cloud undetected by lidar– “Blending” usually gets in-cloud fluxes to better than 5 W m-2

• Shortwave: More difficult– Most sensitive to extinction coefficient– Need full cloud profile: blending enables TOA shortwave to be

retrieved to ~10 W m-2, in-cloud fluxes less accurate– Some sensitivity to habit and therefore effective radius– Slight sensitivity to extinction/backscatter ratio

Conclusions• Extinction much the most important parameter:

– Good news: this can be retrieved accurately independent of assumption of crystal type

– So lidar can provide the extra accuracy at cloud top necessary if retrievals are to be consistent with measured TOA fluxes

– But need to include multiple scattering in retrieval– Must avoid erroneous spikes where lidar loses signal!

• What is the best way to blend profiles?– Scale radar-only retrieval? Or switch straight to radar-only?– Need to analyze aircraft spiral descents through ice cloud

• How could radiances from passive instruments be used to refine the retrievals?– E.g. do SW radiances provide multiple-scattering information?

An invitation!

• Try your algorithm on profiles of radar reflectivity and attenuated lidar backscatter from the first blind test (variable lidar ratio, no instrument noise):– http://www.met.rdg.ac.uk/radar/esa/blind_test.html

• If it passes the test, try profiles from the second blind test (multiple scattering, instrument noise):– http://www.met.rdg.ac.uk/radar/esa/blind_test2.html