Retrieval of vertical cloud properties of deepconvective clouds by spectral radiance measurements

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1 Faculty of Physics and Earth Sciences Retrieval of vertical cloud properties of deepconvective clouds by spectral radiance measurements Tobias Zinner Evi Jäkel, Sandra Kanter, Florian Ewald, Tobias Kölling Manfred Wendisch, Ulrich Pöschl, Bernhard Mayer Munich University, Leipzig University, MPI Mainz

2 Aerosol and Clouds Rosenfeld et al., 2008 Aerosol CCN, type mixing/ entrainment Cloud particle phase, habit r eff, LWC 3D structure # 2

3 Aerosol and Clouds Rosenfeld et al., 2008 Aerosol CCN, type mixing/ entrainment Cloud particle phase, habit r eff, LWC 3D structure Following ideas of Rosenfeld et al Martins et al Marshak et al Cloud side remote sensing # 3

4 Goals Evaluate differences in r eff (z) and phase(z) for pristine vs. polluted situations Test theories on CCN derivation from remote sensing of r eff (z) Validation for cloud side remote sensing of r eff (z) and phase(z) evaluation of technique proposed for satellite missions (e.g. CHASER, CLAIM-3D) validation of phase and r eff retrieval influence of missing (?) geometry information r eff vs. DSD depending on penetration depth into cloud

5 1. Identification of illuminated cloud parts Use signature of surface albedo in cloud spectra to identify shadowed cloud parts RGB image blue: clear, red: illuminated Normalized simulated spectra of cloud sides for (a) grass surface albedo Vertical scans of cumulus cloud

6 2. Identification of thermodynamic phase Jäkel et al Measured spectral radiance of cloud edges. phase index Phase index derived from water and ice clouds based on 3D simulations

7 2. Identification of thermodynamic phase negative phase index liquid water phase index

8 spatial line airmacs FOV 3. Statistical retrieval of effective droplet radius VZA 120 Monte Carlo RT simulated CAR RGB (flight height 10km) Ewald flight direction

9 3. Statistical retrieval of effective droplet radius water (11.75 µm) Main challenges: high spatial resolution (~ m) 3D geometry 3D illumination effects Statistical lookup-table solution Zinner et al Ewald et al r eff

10 spatial line 3. Statistical retrieval of effective droplet radius VZA 120 Monte Carlo RT simulated CAR RGB (flight height 10km) Ewald flight direction

11 spatial line 3. Statistical retrieval of effective droplet radius Ewald 2012 VZA flight direction

12 Instrument airmacs aka Eagle/Hawk Acquisition of one spectral and one spatial dimension Prism-Grating-Prism Entrance Slit 2D CMOS Sensor (1 x spatial, 1 x spectral) Aikio, 2001 SPECIM

13 1 st spatial dimension Instrument airmacs aka Eagle/Hawk Acquisition of one spectral and one spatial dimension Slit FOV nm 2500 nm Spectral dimension Flight direction (2nd spatial dimension)

14 Position on HALO aircraft

15 Rack and side view port

16 Quarz glass windows mounted in SVP Loss due to reflection Herasil quarz glas additional loss due to OH contamination

17 Best flight patterns straight legs Flight patterns? optimum sun illumination ( aircraft shadow on the cloud ) high spatial resolution reff(z) statistics from cloud ensembles

18 Best flight patterns straight legs Flight patterns? optimum sun illumination ( aircraft shadow on the cloud ) lower spatial resolution reff(z) from single cloud

19 Summary Evaluate differences in r eff (z) and phase(z) for pristine vs. polluted situations Test theories on CCN derivation from remote sensing of r eff (z) Validation for cloud side remote sensing: evaluation of technique proposed for use on satellite missions (e.g. CHASER, CLAIM-3D) validation of phase and r eff retrieval influence of missing geometry information r eff vs. DSD depending on penetration depth into cloud Best flight pattern for cloud side remote sensing straight legs optimum sun illumination ( aircraft shadow on the cloud ) Come to Sandra Kanters Poster outside!

20 Hopefully!

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