Satellite retrieval of cloud condensation nuclei (CCN) concentrations for convective clouds

Transcription

1 Satellite retrieval of cloud condensation nuclei (CCN) concentrations for convective clouds Youtong Zheng 1, Daniel Rosenfeld 2, Zhanqing Li 1 1 Department of Atmospheric and Oceanic Science, University of Maryland, College Park, Maryland, 20742, USA. 2 Institute of Earth Sciences, The Hebrew University of Jerusalem, Jerusalem, 91904, Israel. 1

2 Acknowledgement Hebrew University of Jerusalem: Eyal Hashimshoni, David Giguzin, Tom Goren, Baruch Fischman Meteorological Institute of Shaanxi Province: Yu Xing, Yannian Zhu, Guihua Liu, Zhiguo Yue Max Planck Institute for Chemistry: Mira L. Pöhlker, Christopher Pöhlke, Ulrich Pöschl and Meinrat O. Andreae NOAA ESRL: Anne Jefferson University of Sao Paulo: Paulo Artaxo, Henrique Barbosa 2

3 Aerosol-monsoon interactions Lau et al.,

4 Aerosol-monsoon interactions Aerosol-radiation interactions Lau et al.,

5 Aerosol-monsoon interactions Aerosol-radiation interactions Aerosol-cloud interactions Lau et al.,

6 Aerosol-monsoon interactions Aerosol-radiation interactions Aerosol-cloud interactions Lau et al.,

7 Aerosol-cloud interactions 7

8 Aerosol-cloud interactions 8

9 Aerosol-cloud interactions Only CCN matters! 9

10 Key Gaps in understanding aerosol-cloud interactions CCN measurements are scant: o In-situ and ground-based remote sensing o No space-based measurements! 10

11 How about AOD? Satellite-retrieved AOD is inherently not suitable for studying aerosol-cloud interactions: o AOD not representing aerosol concentration near cloud base o Cloud contamination o AOD retrieval is an ill-posed technique (The number of known variables is less than what is required) o Lack of accurate AOD signal for the pristine boundary layer, where accuracy is most critical 11

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13 The retrieval concept 3/4 1/2 b d s CW N max S max : maximum super saturation W b : cloud base updrafts N d: adiabatic cloud droplets number concentration Pinsky et al.,

14 The retrieval concept 3/4 1/2 b d s CW N max S max : maximum super saturation W b : cloud base updrafts N d: adiabatic cloud droplets number concentration Pinsky et al.,

15 The retrieval concept 3/4 1/2 b d s CW N max S max : maximum super saturation W b : cloud base updrafts N d: adiabatic cloud droplets number concentration Pinsky et al.,

16 The retrieval concept How can we retrieve W b and N d from satellite? 3/4 1/2 b d s CW N max S max : maximum super saturation W b : cloud base updrafts N d: adiabatic cloud droplets number concentration Pinsky et al.,

17 Launched on 26/10/2011 Suomi/NPP VIIRS Imager 375 m thermal resolution

18 Solar radiation High spatial resolution is required to resolve the vertical structure of convective clouds. Lower resolution misses all but largest and deepest clouds. Satellite Coarse Fine R1 R2 Measurement concept for T-r e based CCN retrievals

19 Measurement concept for T-r e based CCN retrievals

20 Temperature Effective radius(re) Measurement concept for T-r e based CCN retrievals

21 T ct Temperature T cb Effective radius(re) Measurement concept for T-r e based CCN retrievals

22 T cb, T ct -> adiabatic LWC T ct Temperature T cb Effective radius(re) Measurement concept for T-r e based CCN retrievals

23 T cb, T ct -> adiabatic LWC R e T ct Temperature T cb Effective radius(re) Measurement concept for T-r e based CCN retrievals

24 T cb, T ct -> adiabatic LWC R e -> adiabatic R e T ct Temperature T cb Effective radius(re) Measurement concept for T-r e based CCN retrievals

25 T cb, T ct -> adiabatic LWC R e -> adiabatic R e -> adiabatic M a T ct Temperature T cb Effective radius(re) Measurement concept for T-r e based CCN retrievals

26 T cb, T ct -> adiabatic LWC R e -> adiabatic R e -> adiabatic M a N d T ct Temperature T cb Effective radius(re) Measurement concept for T-r e based CCN retrievals

27 Satellite retrieval of W b W max = 0.94H b W b = 0.59H b [m/s] [m/s] Zheng and Rosenfeld, GRL,

28 LES simulations Large Eddy Simulation (LES): Resolution: 100m Region: Southern Great Plains Time: 6~24 hrs (local time) for five dates 28

29 Validation against ground-based Doppler Radar/lidar W max = 0.94H b [m/s] W b = 0.59H b [m/s] Red: SGP Blue: MAGIC Green: GOAmazon Zheng and Rosenfeld,

30 The retrieval concept 3/4 1/2 b d s CW N max S max : maximum super saturation W b : cloud base updrafts N d: adiabatic cloud droplets number concentration Pinsky et al.,

31 The retrieval concept 3/4 1/2 b d s CW N max S max : maximum super saturation W b : cloud base updrafts N d: adiabatic cloud droplets number concentration Pinsky et al.,

32 The retrieval concept 3/4 1/2 b d s CW N max S max : maximum super saturation W b : cloud base updrafts N d: adiabatic cloud droplets number concentration Pinsky et al.,

33 The retrieval concept CCN 3/4 1/2 b d s CW N max S max : maximum super saturation W b : cloud base updrafts N d: adiabatic cloud droplets number concentration Pinsky et al.,

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35 Application to Houston region D Rosenfeld, YZheng et al., 2016 The numbers in each area are, top: CCN (cm -3 ); middle: S (%), bottom: cloud base temperature ( C). Unstable clean tropical air mass flows northward (upward in the image) from the Gulf of Mexico. The Houston urban effect is clearly visible by more than tripling the CCN concentrations over Houston 35

36 Summary 1. Aerosols, which serve as CCN, can affect cloud properties, which alter the heating gradients, convections and circulations, thus affecting the hydrological cycle of the monsoon climate. 2. Measuring cloud-aerosol interactions requires disentangling CCN from updraft effects, both of which were not measurable until very recently. 3. Existing satellite data is an under-exploited resource, which can still provide new fundamental insights. 4. More investigations (extensive validations and modeling study) are needed before the algorithms can be applied operationally. 36

37 THANK YOU! 37