understanding formation and maintenance of...

Understanding formation and maintenance of mixed-phase Arctic stratus through long-

term observation at two Arctic locations

Gijs de BoerE.W. Eloranta, G.J. Tripoli

The University of Wisconsin - Madison

AGU San Francisco, 14 December, 2007

Introduction


IntroductionThese cloud structures are extremely prevalent in the Arctic:

- SHEBA: 48% occurrence in May (Rogers et al., 2001)- Low altitude stratus frequency of up to 70% during transitional seasons (Curry et al., 1996; Herman and Goody, 1976)- From Eureka: over 1700 30 minute cases for September 2005-December 2006.- From M-PACE: over 500 30 minute cases for mid September-mid November, 2004.

2004 (Barrow) 2005 (Eureka) 2006 (Eureka)0

500

1000

1500October Single Layer Stratus

Month

Num

ber o

f Cas

es


Introduction

From ARM Model intercomparison (Klein et al.)

Introduction

- Ice Formation (Pruppacher and Klett, 1997)


•Homogeneous nucleation

•Heterogeneous nucleation•Deposition freezing•Contact freezing•Condensation freezing•Immersion freezing

•Some Multiplication Processes•Drop shattering•Ice-ice collisions•Splinter ejection during riming


Observations

• UW Arctic High Spectral Resolution Lidar• NOAA ETL Millimeter Cloud Radar• 12-hr. Radiosonde Frequency• In-situ from M-PACE

• Microwave Radiometer• U. Idaho Polar AERI• CALIPSO• CloudSAT

Instruments

Observations


Where does the ice come from?

Low IN, but substantial ice...

Example from M-PACE: CFDC Average out of cloud IN concentration for 9 and 10 October 2004: 0.16 1/LIce particle concentrations: ~10 1/L

So nucleation not by:-Deposition freezing-Condensation freezing -Contact freezingalone

Time (UT)

Altit

ude

(km

)

Lidar backscatter cross section (Masked values shown in black and white)

13 14 15 16 17 18 19 20 21 22 23

1.0

2.0

3.0

4.0

1/(m str)1e!8

1e!7

1e!6

1e!5

1e!4

1e!3

Time (UT)

Altit

ude

(km

)

Radar backscatter cross section (Masked values shown in black and white)

13 14 15 16 17 18 19 20 21 22 23

1.0

2.0

3.0

4.0

1/(m str)1e!14

1e!13

1e!12

1e!11

1e!10

1e!9

1e!8

1e!7


Observations


Observations

Time (UT)

Altit

ude

(km

)

Cloud Mask (Masked values shown in black and white)

13 14 15 16 17 18 19 20 21 22 23

1.0

2.0

3.0

4.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1


Observations

230 240 250 260 270 2800

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Temperature (K)

Norm

alize

d #

Probability Density Function

Cloud Min. Temp.Cloud Max. Temp.


Observations

230 240 250 260 270 2800

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Temperature (K)

Norm

alize

d #



Hom

ogen

eous

Fre

ezin

g (<

-35

°C)

(Hag

en e

t al

., 19

81; J

ense

n et

al.,

1998

)


Observations

230 240 250 260 270 2800

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Temperature (K)

Norm

alize

d #



Hom

ogen

eous

Fre

ezin

g (<

-35

°C)

(Hag

en e

t al

., 19

81; J

ense

n et

al.,

1998

)

Splin

ter

Ejec

tion

(> -

8°C

)(H

eym

sfiel

d an

d M

osso

p, 1

984)

230 235 240 245 250 255 260 265 270!10

!5

0

5

10

15

20

)*c. Tem1erature (7)

(Tcb!T

s*c)/!

< (7

/km

)


Observations


Observations

Why the horizontal variability in ice production?


Observations

Figures courtesy of M. Shupe (NOAA)

Why the horizontal variability in ice production?

Summary


Ice production likely not due to:- Homogeneous Nucleation (too warm)- Condensation, deposition or contact freezing alone (too few IN)- Drop splinter ejection during riming (too cold)

Summary



Key to understanding ice production:- Likely lies with understanding controlling mechanisms for horizontal variability in observed precipitation

Summary



Key to understanding ice production:- Likely lies with understanding controlling mechanisms for horizontal variability in observed precipitation

Future investigation- Numerical sensitivity experiments to look at individual processes.- Evaluate role of vertical velocity in cloud layer

understanding formation and maintenance of...

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