A comparison between observed and simulated hydrometeor size distributions in MCS using the AMMA 2006 microphysical data set

V. Giraud, C. Duroure and W. Wobrock

Laboratoire de Météorologie Physique (LaMP)/OPGC, Université Blaise Pascal/CNRS, Clermont-Ferrand, France

The model

Detailed (bin) microphysics in the 3D non-hydrostatic dynamics of Clark et al (2002)

= DESCAM 3D (Leroy et al., 2009)

Model results

References:Leroy D., W. Wobrock and A. I. Flossmann, 2009: The role of boundary layer aerosol particles for the development of deep convective clouds: a high resolved 3D model with detailed (bin) microphysics applied to CRYSTAL-FACE. Atmos. Res., DOI: 10.1016/j.atmosres.2008.06.001

Observations

Modeled vs. observed cloud spectra

convective systems on 10 sept. 2006

Cloud radar reflectivity

Objective

Warm microphysical processes : aerosol particle growth and activation, droplet de-activation, growth of drops by condensation and collision-coalescence, break up.

Cold microphysical processes : homogeneous and heterogeneous nucleation, growth by vapor deposition, riming and melting.

fd : drop numberfi : ice crystal numberfAP : wet aerosol particle numbergAP,d : aerosol mass inside drops gAP,i : aerosol mass inside ice crystals

AcknowledgementsThe calculations for this study have been done on computer facilities of the « Institut du Développement et des Ressources en Informatique Scientifique » (IDRIS, CNRS) in Orsay (France) and the « Centre Informatique National de l’Enseignement Supérieur » (CINES in Montpellier (France).

• a significant mode occurs between 100 – 400 µm: the model results explain this effect by presence of numerous ice crystals

Objective : improving our understanding of the cloud particle spectra in deep convective clouds and their effect

on cloud radar reflectivity

Can detailed cloud modeling in a highly resolved 3D dynamical frame reproduce the observed features of a convective tropical MCS?

In this model study special emphasis is put on :

•Observed and modeled spectra of hydrometeors and their effect on radar reflectivity•The role of the crystal shape for the observed size distributions and for the simulated reflectivity as observed by a cloud radar

Observed and simulated hydrometeor spectra

• Observed hydrometeor numbers > 500 µm decrease with altitude,the simulated spectra,however, show only a very weak decrease with height.• the mean spectra pre-sented for the simula-tions also represent 700 individual samples.

Aircraft measurements of 1 Hz for hydrometeors > 25 µm were observed on horizontal flight tracks at 7.5 and 10 km – each observation took 11 -12 min. • the dashed lines show the mean spectra over all 700 indi-vidual samples• in the solid (weighed) spectrathe statistical underestimation for large particles was corrected

•Observed particle numbers for sizes < 300 µm do not differ between 7.5 and 10 km !Simulations, however, show in the range from 80 – 300 µma strong variability with height.The number increase in this range results from the increas- ing ice crystal concentration due to the decrease in tempe-rature.

flight track from 8 to 9 h

Reflectivity of the airborne Cloud Radar (Rasta) at 2 different altitudes

flight track at 10 kmflight track at 7.5 km

Hydrometeor spectra observed by PMS 2D-C and 2D-P

at 7.5 km

1 min. mean

at 10 km

10/09/2006 - 08TU

0° 10°

10°

0 5 0 1 0 0 1 5 0 2 0 0 2 5 0 3 0 0 3 5 0 4 0 0 4 5 0 5 0 0

X in k m

re l.h u m . (% ) Z = 1 3 k m t = 3 6 7 .5 m in

0

5 0

1 0 0

1 5 0

2 0 0

2 5 0

3 0 0

3 5 0

4 0 0

4 5 0

5 0 0

Y in

km

2 0

2 5

3 0

3 5

4 0

4 5

5 0

5 5

6 0

6 5

7 0

7 5

8 0

8 5

Total IWCIWC and Total LWCLWC after 6 h of integration cloud top extension after 6h simulated spectrum at 7.5 km

10 100 1000 10000

d iam eter (µm )

1E-008

1E-006

0.0001

0.01

1

100

dN

/dD

(lit

er-1

µm

-1)

water dropsice crysta ls (spheres)water + ice

water + ice, butice m ass = 0.02 D 2.2 (aggregates)

effect of non-sphericity on ice

• ice crystals sizes increase significantly if mass-diameterrelations are considered

10 100 1000size (µm )

1E-008

1E-007

1E-006

1E-005

0.0001

0.001

0.01

0.1

1

10

1E+002

2D-C+P in 7.5 km2D-C+P in 10 kmsim ulation in 10 kmsim ulation in 7.5 km

10 100 1000size (µm )

1E-008

1E-007

1E-006

1E-005

1E-004

1E-003

1E-002

1E-001

1E+000

dN /d

D (

l-1 µ

m-1

)

7.5 km (weighed)7.5 km (m ean)10 km (weighed)10 km (m ean)

10 100 1000size (µm )

1E-008

1E-007

1E-006

1E-005

0.0001

0.001

0.01

0.1

1

10

1E+002

m odeling resu lts10000 m9000 m7500 m

* Initialization: sounding of Niamey on 9 sept. 2006, 17 h* aerosol spectra from aircraft observations in July ’06 during AMMA SOP2B

model

0 5 0 1 0 0 1 5 0 2 0 0 2 5 0 3 0 0 3 5 0 4 0 0 4 5 0 5 0 0x (k m )

d iffe ren ce in re flec tiv ity d B Z ( 0 .0 2 d -2 .2 - sp h e rica l)

-3 5

-3 0

-2 5

-2 0

-1 5

-1 0

-5

0

5

1 0

0 5 0 1 0 0 1 5 0 2 0 0 2 5 0 3 0 0 3 5 0 4 0 0 4 5 0 5 0 0x (k m )

c lo u d rad a r re flec tiv ity (d B Z )

0

5

1 0

1 5

Z in

km

-3 0

-2 5

-2 0

-1 5

-1 0

-5

0

5

1 0

1 5

2 0

2 5

Simulated radar reflectivity (wavelength 3.1 mm, attenuation included ):

•The left figure gives the reflectivity based on calculations for sphericalhydrometeors (ice crystals and drops are optically well distinguished)

•The right figure gives the difference between calculations for ZR that considers all ice crystals > 200 µm following a mass-diameter relation m = 0.02d2.2 and ZR that uses a spherical shape for all ice crystals (as illustrated in the right figure)

using a mass diameter relation for large ice crystals already causes an increase of more than +10 dBZ in the major parts of the deep convective clouds

More sophisticated measurements are needed in order to understand the microphysical structure, the ice/water partitioning and the

morphology of the ice particles in deep convective clouds

observation modelingmodeling /observation