1 a first look at mid-level clouds using cloudsat, calipso, and modis data stanley q. kidder, j....

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1 A First Look at Mid-Level Clouds Using CloudSat, CALIPSO, and MODIS Data Stanley Q. Kidder, J. Adam Kankiewicz, Thomas H. Vonder Haar Cooperative Institute for Research in the Atmosphere Colorado State University Vincent E. Larson Department of Mathematical Sciences University of Wisconsin–Milwaukee Lawrence D. Carey Department of Atmospheric Sciences Texas A&M University Denise E. Hagan Northrop Grumman Space Technology Redondo Beach, CA

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Page 1: 1 A First Look at Mid-Level Clouds Using CloudSat, CALIPSO, and MODIS Data Stanley Q. Kidder, J. Adam Kankiewicz, Thomas H. Vonder Haar Cooperative Institute

1

A First Look at Mid-Level Clouds Using

CloudSat, CALIPSO, and MODIS Data

Stanley Q. Kidder, J. Adam Kankiewicz, Thomas H. Vonder Haar Cooperative Institute for Research in the Atmosphere

Colorado State University

Vincent E. LarsonDepartment of Mathematical Sciences

University of Wisconsin–Milwaukee

Lawrence D. Carey Department of Atmospheric Sciences

Texas A&M University

Denise E. HaganNorthrop Grumman Space Technology

Redondo Beach, CA

Page 2: 1 A First Look at Mid-Level Clouds Using CloudSat, CALIPSO, and MODIS Data Stanley Q. Kidder, J. Adam Kankiewicz, Thomas H. Vonder Haar Cooperative Institute

2

Why We Care about Mid-Level Clouds

• They obstruct visibility• Supercooled water clouds pose an icing

hazard for aircraft, particularly unpiloted aircraft

• They are poorly forecast by NWP models• They provide a simple laboratory with

which to study the interaction of latent heating, microphysics, radiation, and turbulence

Page 3: 1 A First Look at Mid-Level Clouds Using CloudSat, CALIPSO, and MODIS Data Stanley Q. Kidder, J. Adam Kankiewicz, Thomas H. Vonder Haar Cooperative Institute

3

Motivation: Current NWP

models do a poor job of mid-level cloud prediction

Mid-level Cloud Modeling Studies Goal: To help identify (and improve) forecast model

deficiencies that inhibit reliable mid-level cloud forecasts

Need increased vertical resolution in

NWP models to resolve mid-level

clouds

Page 4: 1 A First Look at Mid-Level Clouds Using CloudSat, CALIPSO, and MODIS Data Stanley Q. Kidder, J. Adam Kankiewicz, Thomas H. Vonder Haar Cooperative Institute

4

Cloud Layer Experiments (CLEX)Ten experiments since 1995

Optically Opaque Mixed-Phase

Region (~300-500 m deep)

Precipitating Ice Region

(~.2-2.5 km deep)

Generating Cells ~ 1-1.5 km in Length

Typical Particle Concentrations: 100-200 cm-3 (Liquid)20-150 L-1 (Ice)

SupercooledLiquid

Ice

=

=

What we have learned:

Page 5: 1 A First Look at Mid-Level Clouds Using CloudSat, CALIPSO, and MODIS Data Stanley Q. Kidder, J. Adam Kankiewicz, Thomas H. Vonder Haar Cooperative Institute

5

6

5

4

3

2

Hei

gh

t (k

m)

Typical Mixed-Phase Cloud Structure

The vertical profile of LWC (red diamonds) and IWC (blue diamonds) during the 14 October 2001 straight-line ascent from 1440 to 1510 UTC.

Liquid Water on Top

5

4

3

Hei

gh

t (k

m)

Tem

per

atu

re (

C)

o

-5

-10

-15

-20

124-4-12-20-28-36

Reflectivity (dBZ)

0.00 0.05 0.10 0.15 0.20 0.25(g m )-3

Water Content1440 1455 1510

Time (UTC)

Cloud Radar Reflectivity Profile (14 Oct 2001)

LWCIWC

Ice Below

Page 6: 1 A First Look at Mid-Level Clouds Using CloudSat, CALIPSO, and MODIS Data Stanley Q. Kidder, J. Adam Kankiewicz, Thomas H. Vonder Haar Cooperative Institute

6

Canadian CloudSat/CALIPSO Validation Project (C3VP)

Funded by CSA, C3VP will strive to provide an intensive evaluation of the CloudSat standard data products. Validation will occur over four twelve-day IOPs (Nov-Mar 2006-07) and involve ~ 100 hours of aircraft flight time. This is the only cold-season CloudSat validation effort planned during the mission!

CIRA’s CLEX-10 participation in C3VP will include: CIRA’s CLEX-10 participation in C3VP will include: ~23 hours of Convair-580 ~23 hours of Convair-580 flight time devoted exclusively to the study of mixed-phase clouds and icing flight time devoted exclusively to the study of mixed-phase clouds and icing conditionsconditions

NRC Convair−580

Page 7: 1 A First Look at Mid-Level Clouds Using CloudSat, CALIPSO, and MODIS Data Stanley Q. Kidder, J. Adam Kankiewicz, Thomas H. Vonder Haar Cooperative Institute

7

Page 8: 1 A First Look at Mid-Level Clouds Using CloudSat, CALIPSO, and MODIS Data Stanley Q. Kidder, J. Adam Kankiewicz, Thomas H. Vonder Haar Cooperative Institute

8

9 Nov 2006 18:00 UTC

MODIS 12 um

A

B

AB

C3VP Target Region

Page 9: 1 A First Look at Mid-Level Clouds Using CloudSat, CALIPSO, and MODIS Data Stanley Q. Kidder, J. Adam Kankiewicz, Thomas H. Vonder Haar Cooperative Institute

9

Supercooled Liquid Layers

Ice Virga

Early Results from C3VP/CLEX (31 Oct 2006)

532 nm backscatter (up & down) minutes before 532 nm backscatter (up & down) minutes before the A-train overpass the A-train overpass

(Courtesy of Kevin Strawbridge/Environment Canada)(Courtesy of Kevin Strawbridge/Environment Canada)

Page 10: 1 A First Look at Mid-Level Clouds Using CloudSat, CALIPSO, and MODIS Data Stanley Q. Kidder, J. Adam Kankiewicz, Thomas H. Vonder Haar Cooperative Institute

10

B

A

Mixed-Phase Clouds Viewed By MODIS/CloudSat/CALIPSO

7/21/06 22:55 UTCMODIS 11 µm

−166− 168− 170− 172− 174− 176− 178

− 22

− 24

− 26

− 28

Page 11: 1 A First Look at Mid-Level Clouds Using CloudSat, CALIPSO, and MODIS Data Stanley Q. Kidder, J. Adam Kankiewicz, Thomas H. Vonder Haar Cooperative Institute

11

Hei

gh

t (k

m)

0

5

10 CloudSat Radar Reflectivity (dBZ)

CloudSat Cloud Mask

BA

Hei

gh

t (k

m)

0

5

10

Hei

gh

t (k

m)

0

5

10 CALIPSO 532 nm Backscatter

-40

-30

-20

-10

0

Page 12: 1 A First Look at Mid-Level Clouds Using CloudSat, CALIPSO, and MODIS Data Stanley Q. Kidder, J. Adam Kankiewicz, Thomas H. Vonder Haar Cooperative Institute

12

CloudSat Reflectivity

Page 13: 1 A First Look at Mid-Level Clouds Using CloudSat, CALIPSO, and MODIS Data Stanley Q. Kidder, J. Adam Kankiewicz, Thomas H. Vonder Haar Cooperative Institute

13

CALIPSO 532 nm Backscatter

Page 14: 1 A First Look at Mid-Level Clouds Using CloudSat, CALIPSO, and MODIS Data Stanley Q. Kidder, J. Adam Kankiewicz, Thomas H. Vonder Haar Cooperative Institute

14

VIIRS Cloud Phase

Algorithm B

A

Mixed-Phase Clouds Viewed By MODIS/CloudSat/CALIPSO

Page 15: 1 A First Look at Mid-Level Clouds Using CloudSat, CALIPSO, and MODIS Data Stanley Q. Kidder, J. Adam Kankiewicz, Thomas H. Vonder Haar Cooperative Institute

15

Preliminary CloudSat Data AnalysisJuly 2006

• Cloud — a range bin with Cloud_Mask >= 20

• Cloud Top — a cloudy range bin with a non-cloudy range bin immediately above it

• Cloud-Top Temperature — the temperature in the ECMWF analysis at the same height as the cloud top

Definitions:

Page 16: 1 A First Look at Mid-Level Clouds Using CloudSat, CALIPSO, and MODIS Data Stanley Q. Kidder, J. Adam Kankiewicz, Thomas H. Vonder Haar Cooperative Institute

16

Latitudinal Distribution

• Mixed-phase defined as cloud tops with temps between 0°C and -45°C from ECMWF fields

• Few mixed-phase clouds in tropics and subtropics; many in the mid- and high latitudes

CloudSat July 2006

0% 20% 40% 60% 80%

-90 to -75

-60 to -45

-30 to -15

0 to 15

30 to 45

60 to 75

Lat

itu

de

Zo

ne

Fraction of Rays

Possibly Mixed-Phase

Other Cloud

Page 17: 1 A First Look at Mid-Level Clouds Using CloudSat, CALIPSO, and MODIS Data Stanley Q. Kidder, J. Adam Kankiewicz, Thomas H. Vonder Haar Cooperative Institute

17

Cloud-Top Height Distribution

• All latitudes• Fairly uniform

distribution in the troposphere

CloudSat July 2006

0 200000 400000 600000 800000

0

2

4

6

8

10

12

14

16

18

Hei

gh

t o

f C

lou

d T

op

(km

)

Number of Clouds

Page 18: 1 A First Look at Mid-Level Clouds Using CloudSat, CALIPSO, and MODIS Data Stanley Q. Kidder, J. Adam Kankiewicz, Thomas H. Vonder Haar Cooperative Institute

18

Cloud-Top Temperature

• Quite a uniform distribution with perhaps a few more at very cold and very warm temperatures

CloudSat July 2006

0 200000 400000 600000 800000

-5 to 0

-10 to -5

-15 to -10

-20 to -15

-25 to -20

-30 to -25

-35 to -30

-40 to -35

-45 to -40

Tem

per

atu

re B

in (

°C)

Number of Clouds

Page 19: 1 A First Look at Mid-Level Clouds Using CloudSat, CALIPSO, and MODIS Data Stanley Q. Kidder, J. Adam Kankiewicz, Thomas H. Vonder Haar Cooperative Institute

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Cloud Thickness

• Most mixed-phase clouds are thin

• The long tail is puzzling, perhaps an artifact of the analysis

CloudSat July 2006

0 100000 200000 300000 400000 500000

39

36

33

30

27

24

21

18

15

12

9

6

3

Clo

ud

Th

ickn

ess

(pix

els)

Number of Clouds

Page 20: 1 A First Look at Mid-Level Clouds Using CloudSat, CALIPSO, and MODIS Data Stanley Q. Kidder, J. Adam Kankiewicz, Thomas H. Vonder Haar Cooperative Institute

20

Day/Night Distribution

• Slightly fewer mixed-phase clouds at night (0130 LT) than in the daytime (1330 LT)

CloudSat Jul 2006

0 500000 1000000 1500000 2000000 2500000 3000000

Day

Night

No. of Clouds

Page 21: 1 A First Look at Mid-Level Clouds Using CloudSat, CALIPSO, and MODIS Data Stanley Q. Kidder, J. Adam Kankiewicz, Thomas H. Vonder Haar Cooperative Institute

21

Contoured Frequency by Altitude Diagram (CFAD)

• Cloud = CloudSat Cloud Mask >= 20

• Cloud-Top Temp between -5°C and -40°C

• All latitudes, day and night

• Probably shows ice crystal growth below cloud top

Page 22: 1 A First Look at Mid-Level Clouds Using CloudSat, CALIPSO, and MODIS Data Stanley Q. Kidder, J. Adam Kankiewicz, Thomas H. Vonder Haar Cooperative Institute

22

Conclusions and Future Plans

• We should be able to get a near global picture of mid-level, mixed-phase clouds using CloudSat, CALIPSO, and MODIS data

• We will be analyzing CALIPSO data soon (They were released on Monday, Dec. 11)

• A detailed study of CLEX-10/C3VP cases will take place

• We hope to use these data to improve modeling of mid-level, mixed-phase clouds