blind tests of radar/lidar retrievals: assessment of errors in terms of radiative flux profiles

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Blind tests of radar/lidar retrievals: Assessment of errors in terms of radiative flux profiles Malcolm Brooks Robin Hogan and Anthony Illingworth David Donovan and Claire Tinel

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Blind tests of radar/lidar retrievals: Assessment of errors in terms of radiative flux profiles. Malcolm Brooks Robin Hogan and Anthony Illingworth David Donovan and Claire Tinel. Introduction. First blind test showed that - PowerPoint PPT Presentation

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Page 1: Blind tests of radar/lidar retrievals: Assessment of errors in terms of radiative flux profiles

Blind tests of radar/lidar retrievals: Assessment of

errors in terms of radiative flux profiles

Malcolm BrooksRobin Hogan and Anthony Illingworth

David Donovan and Claire Tinel

Page 2: Blind tests of radar/lidar retrievals: Assessment of errors in terms of radiative flux profiles

Introduction• First blind test showed that

– Both Donovan and Tinel algorithms could retrieve extinction coefficient very accurately

– Effective radius and IWC depend on assumption of habit (i.e. “density” or the mass-size relationship)

• Second blind test included multiple scattering, molecular scattering and instrument noise:– Reasonable extinction profiles were generally obtained if multiple

scattering was included in the retrieval, otherwise extinction was underestimated

– Retrieval only possible where lidar still has good signal• What are the radiative implications?• How do these retrievals compare to radar-only?

Page 3: Blind tests of radar/lidar retrievals: Assessment of errors in terms of radiative flux profiles

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

Page 4: Blind tests of radar/lidar retrievals: Assessment of errors in terms of radiative flux profiles

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

Page 5: Blind tests of radar/lidar retrievals: Assessment of errors in terms of radiative flux profiles

Blind test 1:Results 2

• Effective radius:– Good, but difficult if re >

80 microns because of radar Mie scattering

– Sensitive to particle habit • Ice water content:

– Extinction ~ IWC/re

– Hence if extinction is correct then the % error in effective radius is equal to the % error in IWC

Page 6: Blind tests of radar/lidar retrievals: Assessment of errors in terms of radiative flux profiles

Best case: radar/lidar retrieval

• Excellent extinction, good re if same mass-size relationship is used (otherwise 40% too low)

Mitchell relationship

Francis et al. relationship

Radar only retrieval

Extinction coefficient Effective radius

Page 7: Blind tests of radar/lidar retrievals: Assessment of errors in terms of radiative flux profiles

Best case: radiation calculations• Used Edwards-Slingo radiation code

• Excellent longwave, good shortwave but slight effect of habit and k; better than radar alone

Longwave up

Shortwave up

Clear sky profile

Cloudy profile

Error 20-40 W m-2 depending on

habit and k

Page 8: Blind tests of radar/lidar retrievals: Assessment of errors in terms of radiative flux profiles

Worst case: radar/lidar retrieval

• Radar/lidar extinction excellent, re underestimated• Extinction poor from radar only

Extinction coefficient Effective radius

Effective radius underestimate

Poor radar-only

retrieval, particularly at cloud top

Page 9: Blind tests of radar/lidar retrievals: Assessment of errors in terms of radiative flux profiles

Worst case: radiation calculations

• Excellent longwave, still good shortwave!• Effective radius not very important?

Longwave up Shortwave up

Error 20-30 W m-2

Page 10: Blind tests of radar/lidar retrievals: Assessment of errors in terms of radiative flux profiles

Blind test 1: Heating rates• Radar/lidar: very accurate• Radar alone: OK but some biases

Best case Worst case

Error due to higher Z here

Page 11: Blind tests of radar/lidar retrievals: Assessment of errors in terms of radiative flux profiles

Blind test 2(From EUCREX)

• Instrument noise• Multiple scattering• Molecular scattering• True lidar sensitivity• Constant extinction to

backscatter ratio• Note: radar-only

relationships derived using this dataset so not independent!

Page 12: Blind tests of radar/lidar retrievals: Assessment of errors in terms of radiative flux profiles

Donovan retrieval: with multiple scattering

Page 13: Blind tests of radar/lidar retrievals: Assessment of errors in terms of radiative flux profiles

Tinel retrieval: no multiple scattering

Page 14: Blind tests of radar/lidar retrievals: Assessment of errors in terms of radiative flux profiles

Good case: radar/lidar retrieval

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

Extinction coefficient Effective radius

Full profile retrieved

Difference between Mitchelland Francis et al.

Page 15: Blind tests of radar/lidar retrievals: Assessment of errors in terms of radiative flux profiles

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 has modest

effect:Error<10

Wm-2

Underestimate radiative effect if

multiple scattering neglected

Page 16: Blind tests of radar/lidar retrievals: Assessment of errors in terms of radiative flux profiles

Poor case: radar/lidar retrievals

• No retrieval in lower part of cloud

Extinction coefficient Effective radius

Wild retrieval where lidar runs

out of signal

Good retrieval at cloud top

Page 17: Blind tests of radar/lidar retrievals: Assessment of errors in terms of radiative flux profiles

Poor case: radiation calculations

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

Longwave up Shortwave up

OLR excellent despite lower

part not retrieved Albedo

underestimated (90 W m-2):

lower part of cloud is

important

Page 18: Blind tests of radar/lidar retrievals: Assessment of errors in terms of radiative flux profiles

Blind test 2: Heating rates• Heating profile reasonable if full profile retrieved

Best case Worst case

Erroneous 80 K/day heating

No cloud observed so no heating by cloud

here

Page 19: Blind tests of radar/lidar retrievals: Assessment of errors in terms of radiative flux profiles

Sensitivity of radiation to retrievals

• Longwave: easy!– Sensitive to extinction coefficient– Insensitive to effective radius, habit or extinction/backscatter– OLR insensitive to lower half of cloud undetected by lidar

• Shortwave: difficult to get to better than 20 W m-2

– Most sensitive to extinction coefficient– Need full cloud profile to get correct albedo– Some sensitivity to habit and therefore effective radius– Slight sensitivity to extinction/backscatter ratio– Note: not included habit dependence of asymmetry

parameter or single-scattering albedo

Page 20: Blind tests of radar/lidar retrievals: Assessment of errors in terms of radiative flux profiles

Conclusions• Extinction much the most important parameter:

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

– But need to include multiple scattering in retrieval• Need to retrieve something when no more lidar:

– Switch to radar-only retrieval?– Assign error to both radar/lidar and radar-only retrievals and

produce a consensus value, weighted accordingly?– Must avoid erroneous spikes where lidar loses signal!– Use imager (VIS & IR) synergy to give top-of-atmosphere

radiances and provide a constraint for the retrieval: how would this be incorporated into the algorithms?

– Do SW radiances provide multiple-scattering information?

Page 21: Blind tests of radar/lidar retrievals: Assessment of errors in terms of radiative flux profiles

Scaling the radar-only retrieval

• Where radar/lidar retrieval fails, can we scale the radar-only retrieval to get a seamless join?– Dubious: the profiles are not real but simulated!

Good fit Partial fit