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 Tinel KNMI, 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 No instrument noise No multiple scattering (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: Variable k: Both Donovan and Tinel (after modification) algorithms produce highly accurate extinction Variable k: Error in extinction varies with k, but not unstable

Blind Test 1: Results 2 Effective radius: Ice water content: 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

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) Extinction coefficient Effective radius Francis et al. relationship Radar only retrieval Mitchell relationship

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 Clear sky profile Error 20-40 W m-2 depending on habit and k Cloudy profile Shortwave up

Heating rates Radar/lidar: very accurate Radar alone: almost as good

Case from First Blind Test Excellent extinction (both Donovan and Tinel) re depends on mass-size relationship, but can still be too low Extinction poor from radar only Extinction coefficient Effective radius Poor radar-only retrieval, particularly at cloud top Mitchell relationship Francis et al. relationship Effective radius underestimate

Radiation (Edwards-Slingo code) Excellent longwave, good shortwave Slight effect of habit and k; better than radar alone Effective radius not very important? Clear sky profile Error 20-30 Wm-2 depending on habit and k Cloudy profile Longwave up Shortwave up

Error due to higher Z here Heating rates Radar/lidar: reasonably accurate Radar alone: OK but some biases Error due to higher Z here

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 Radar Five new profiles from EUCREX dataset This is what they would look like without instrument noise or multiple scattering Note strong lidar attenuation Lidar

Instrument noise Radar 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! Lidar

Donovan retrieval: with multiple scattering

Tinel retrieval: no multiple scattering

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 Mitchell and 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 Mass-size relationship: Error~10 Wm-2 Underestimate radiative effect if multiple scattering neglected Shortwave up

Typical case: radar/lidar retrievals No retrieval in lower part of cloud Important to include multiple-scattering in retrieval Extinction coefficient Effective radius Donovan: good retrieval at cloud top Difference between Mitchell and Francis et al. mass-size relation Tinel: no multiple scattering Wild retrieval where lidar runs out of signal

Typical case: radiative fluxes At top-of-atmosphere, lower part of cloud important for shortwave but not for longwave Underestimate radiative effect if multiple scattering neglected Albedo too low (80 W m-2): lower part of cloud is important but mass-size less so (10 W m-2) OLR excellent:lower part not important Longwave up Shortwave up

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

Simple solution: blend profiles Where lidar runs out of steam, scale radar-only retrieval for seamless join Much better result than pure radar/lidar or radar only Lidar becomes unreliable here Radar/lidar only Radar only Scale radar-only retrieval to match Blended Extinction coefficient Shortwave up

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 Lidar becomes unreliable here Blended Radar only Radar/lidar only Scale radar-only retrieval to match here Extinction coefficient Shortwave up

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?

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

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