'&

$%

CLOUD - RADIATION INTERACTIONS

Laura Rontu

Finnish Meteorological Institute

laura.rontu@fmi.�

March 1, 1999

1

'&

$%

CONTENTS:

In uence of clouds on radiation

� Cloud condensate amount

� Size distribution of cloud droplets

� Ice crystals and water droplets

In uence of radiation on clouds

Interaction of cloud and radiation parametrizations in HIRLAM

� Connections of the parametrization schemes

� Predicted and diagnosed variables

Parametrizing e�ective radius

� Definition of re

� Short-wave radiation

� Long-wave radiation

2

'&

$%

Validation

� Problems of validation of radiation parametrizations in

cloudy cases

� IRCCM comparisons

� A sensitivity example

� JASIN case

� Jokioinen comparisons

� Influence of radiation on a forecast

Conclusions

3

'&

$%

INFLUENCE OF CLOUDS ON RADIATION

4

Table 1: Global annual mean energy bugdets Wm�2

[Kiehl et al(1998)]

Field Observation CCM3

TOA

OLR 234:8 236:97

Clear sky OLR 264:0 266:22

Solar absorbed 238:1 236:88

Clear solar absorbed 286:3 286:42

LWCF 29:2 29:25

SWCF �48:2 �49:54

Net TOA 3:3 �0:09

Cloud fraction % 52:2� 62:5 58:83

Surface

Solar absorbed 142� 168 171:05

Clear solar absorbed 217:2 220:83

Net longwave 45:8� 66 60:68

Clear net longwave 70:7 92:39

Latent heat 78 89:97

Sensible heat 24 20:47

Net surface 0:00 �0:07

5

'&

$%

Figure 1: Observed and modelled by NCAR CCM3 cloud forcing

6

'&

$%

INFLUENCE OF CLOUD DROPLET SIZE ON

RADIATION

More pollution ! more CCN ! more drops ! brighter clouds

� � 2�Nr2�z

or

LWC � 43�r3N ! � � 3LWC�z

2r

More pollution ! more CCN ! smaller drops ! brighter clouds

Twomey, 1977

But:

LWC � precipitation release

More pollution ! more CCN! more smaller drops ! less

precipitation ! more LWC ! brighter clouds Liou and Ou, 1989

7

Figure 2: Interactions including cloud particle size

([Liou and Ou (1989)])8

'&

$%

INFLUENCE OF RADIATION ON CLOUDS

� Radiative heating/cooling of the surface

! shallow and deep convection

! development of fog and stratus

� Radiative cooling of the cloud top

Radiative heating of the cloud bottom

! dynamics of stratiform and convective clouds

9

'&

$%

RADIATION

SURFACETURBULENCE

CONDENSATION

TqCCC

∆∆

PBL clouds

F F

F

T qCCC C f

TqCCCuv

∆∆∆

T

TW

∆

∆

s

∆∆

ice

sS sL

sM∆

∆

T q Fs s sR

Figure 3: Interactions between the HIRLAM parametrization schemes

10

'&

$%

Predicted and diagnosed variables

Prognostic equation only for grid volume total cloud water content

Needed also:

Fractional cloud cover

� related to grid size/cloud structure

� diagnosed from humidity separately for convective/stratiform

clouds

Rain water

� given by Gp (precipitation release)

11

'&

$%

Cloud/precipitation ice content

� phase of cloud water diagnosed as f(T)

e.g. Matvejev (1984)

� used also for precipitation

� melting included

Drop size information

� none

12

'&

$%

EFFECTIVE RADIUS FOR WATER CLOUDS:

r3e;water = kr3v (1)

The parameter k is di�erent for marine and continental clouds.

The cloud condensate content (CCC = liquid + ice water content, in

kgm�3) in the cloud is connected to rv by

CCC =4�

3�`Nr3v (2)

where �`=1000 kgm�3 is the density of liquid water and N the number

concentration of the cloud droplets.

Combining (1) and (2) yields

re;water =�

3CCC

4��`kN�1=3

(3)

13

'&

$%

0 0.5 1 1.52

4

6

8

10

12

14

16

18

CCC [g/m3]

r e,w

ater

[µ

m]

Figure 4: re;water as a function of CCC for continental (solid) and

marine (dashed) clouds ([Wyser et al(1999)])

14

'&

$%

EFFECTIVE RADIUS FOR ICE CLOUDS:

� sparse observational data about the sizes and shapes of ice

crystals

� non-spherical particles

De = 326:3 + 12:42Tc + 0:197T 2c + 0:0012T 3c ; (4)

where Tc is inÆC and De in �m. The e�ective radius is obtained by

simply assuming re;ice = De=2.

15

'&

$%

USING OF EFFECTIVE RADIUS FOR SHORT-WAVE

RADIATION PARAMETRIZATION:

b10 = b10are;SW + b10b

b13 = b13are;SW + b13b;

(5)

where re;SW is the e�ective radius for short-wave calculations. Values

for all the b-parameters are found by adjusting the HIRLAM

radiation scheme to a more sophisticated radiative transfer model.

16

'&

$%

WATER CLOUDS

1 10 100 10000

0.2

0.4

0.6

0.8

1

M [g m−2]

Tra

nsm

issi

vity

2.5

15

1 10 100 10000

0.02

0.04

0.06

0.08

0.1

0.12

M [g m−2]

Abs

orpt

ivity

2.5

15

Figure 5: Transmissivity and absorptivity of water clouds as a function of in-

tegrated cloud condensate amount M for various re;water at a zenith angle of

60o.([Wyser et al(1999)])

17

'&

$%

ICE CLOUDS

Ice clouds are included in the SW parametrization through an

equivalent radius, req. An ice cloud with particles of size re;ice has

the same optical properties as a water cloud with re;water=req.

An assumption is made for the relation between re;ice and req,

req = a1re;ice + a2 cos � + a3 (6)

The transmissivity ^T for a number of ice clouds is calculated with the 5-band

radiative transfer model with ice optics. The a-parameters are found by matching

the HIRLAM transmissivity with the new values for b and re = req to the result

from the radiative transfer model.

18

'&

$%

PROBLEM: VERTICAL INTEGRATION

The e�ective radius for the SW calculations, re;SW, is determined from

re;water and req. re;SW should be representative not only of the level under

consideration, but also of all the cloud water and cloud ice above.

re;SW(j) =Pj

i=1 [re;water(i)(1� fice(i)) + req(i)fice(i)]C(i)CCC(i)�z(i)Pji=1CCC(i)C(i)�z(i)

;(7)

where C(i) is the cloud cover and �z(i) the thickness of the layer i.

19

'&

$%

Using e�ective radius for long-wave radiation

parametrization:

ka;x = c1 + c2 exp(�c3re;x) (8)

where the index x stands for either water or ice. Expression (8) is

taken from ECHAM 4 (Roeckner et al. 1996). The total mass

absorption coeÆcient is composed of water and ice contributions.

The e�ective emissivity � of a cloudy layer now becomes

� = Cf1� exp [�(ka;watermw + ka;icemi)]g; (9)

where mw = (1� fice)CCC�z and mi = ficeCCC�z are the cloud

water and cloud ice amounts (in gm�2) of the layer.

20

'&

$%

HOW TO VALIDATE A RADIATION SCHEME?

Possibilities and problems

� standard veri�cation

� comparison with line-by-line calculations

� model intercomparisons (ICRCCM)

� comparison with special observations

� uxes at the top of the atmosphere from satellite data

21

'&

$%

� surface radiation uxes + aerological sounding data

clear sky: quite possible (but - point value/grid average -

e.g. albedo in winter forest)

cloudy sky: where to take the cloud water

(adiabatic/diagnostic/model integration)

In uence of radiation parametrizations in forecast

� one-dimensional model runs

� three-dimensional experiments and parallel runs

22

Table 2: ICRCCM comparisons

SW down (Wm�2) low thin low thick high thin high thick

ICRCCM CS 782�31 - 779�31 -

ICRCCM CL 921�18 537�48 920�18 536�54

H2 old 814 251 853 241

H2 new CS 767 153 760 149

H2 new CL 892 525 930 529

LW down (Wm�2)

ICRCCM CS 399�8 - 360�7 -

ICRCCM CL 389�11 413�3 358�7 363�7

H2 old 409 416 356 371

H2 new CS 408 416 368 371

H2 new CL 378 416 358 371

23

Hei

ght

SWdown/So=0.17re,SW=5.8 m

SWdown/So=0.19re,SW=6.9 m

SWdown/So=0.22re,SW=9.8 m

Cloud condensate content in grid volume

a b cH

eigh

t

SWdown/So=0.27re,SW=11.9 m

SWdown/So=0.27re,SW=11.9 m

SWdown/So=0.22re,SW=9.8 m

0 1

Cloud condensate content in grid volume Fraction of ice

a b c d

Figure 6: Sensitivity examples

24

Table 3: Net radiation uxes in the JASIN case

SW net (Wm�2) Above cloud In cloud Below cloud

H2 old 275 205:::270 205

H2 new/diagnosed re� 305 230:::300 230

H2 new/observed re� 270 200:::265 200

Obs* 260�50 210:::275�40 200�40

Schmetz* 280 235:::255

LW net (Wm�2)

H2 old �85 �7:::� 10 �18

H2 new/diagnosed re� �85 �8:::� 10 �18

H2 new/observed re� �85 �7:::� 10 �18

Obs** �70�4 �10:::� 20�4 �20�4

Schmetz and Raschke** �90 0 �20

25

1000 1100 1200 1300 1400 1500 1600 1700 1800

Time (day+hour, LST)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Liq

uid

wat

erpa

th(k

g/m

-2)

1

2

3

4

5

6

7

8

Tl

ldi

(18)

cobserved cloudinessmodel LWPmodel cloudiness

1000 1100 1200 1300 1400 1500 1600 1700 1800

Time (day+hour, LST)

180

210

240

270

300

330

360

390

420

450

Dow

nwar

dLW

radi

atio

n(W

/m2 ) b

observationH2 newH2 old

1000 1100 1200 1300 1400 1500 1600 1700 1800

Time (day+hour, LST)

-100

0

100

200

300

400

500

600

700

800

Dow

nwar

dSW

radi

atio

n(W

/m2 ) a

observationH2 newH2 old

Figure 7: Downward short-wave (a)

and long-wave (b) radiation fluxes at

Jokioinen from 12 UTC 9 July to 12 UTC 19

July, 1989.26

H

H

H

L

L

L

L

and cloud condensate amount (g/m2)Predicted 96070900+12h surface pressure (hPa)

Figure 8: The reference HIRLAM forecast at 00 UTC 9

July 1996 +12h.

27

13

13

14

1413

13

1311

14

14

13

1718

20

14

19

20

19

13

13

21

15

19

17

14

18

11

15

17

15

14

14

13

16

18

16

12

10

0809

1211

12

21

19

09

12

09

11

16 20

17

11

18

23

23

23

22

2218

15

14

15

19

17

15 18

18

12

08

18

19

18

15

19

20

17

20

19

14

17

20 13

18 12

12

13

18 15

2517

29

26

32

27

33

16 23

1917

32

32

23

22

28

16

16

15 13

12

15

12

19

12 12

11

11

7

12

18

13 17

11

13

14

16

15

12

12

12

21

19

21

20

20

27

2727

29

31

21

14

15

20

20

16

12

13

13

19

8

17

13

08

13

17

07

13

two-metre temperatures (C)Predicted 96070900+12h and observed at 96070912

Figure 9: Two-metre temperature and cloud

cover at 12 UTC 9 July

28

'&

$%

CONCLUSIONS

Importance of consistent cloud and radiation schemes

� cloud condensate content

� cloud ice de�nition

� fractional cloud cover

� cloud droplet/crystal size

The most important thing in the cloud-radiation

interactions is to obtain good cloud condensate

content/cloud cover forecasts.

Surface radiation ux observations as a tool for model

validation (also in cloudy cases).29

'&

$%

References

[Kiehl et al(1998)] Kiehl, J.T., J.J. Hack and J.W. Hurrell, 1998:

The energy budget of the NCAR Community Climate Model

CCM3. J.Climate, 11, 1151-1178.

[Liou and Ou (1989)] Liou, K.-N. and S.-C.Ou, 1989: Role of cloud

microphysical processes in climate: an assessment from a

one-dimensional perspective. J.Geoph.Res., 94(D6), 8599-8607

[Twomey(1977)] Twomey, S., 1977. The in uence of pollution on the

shortwave albedo of clouds. J.Atmos.Sci, 34,1149-1152. Liou,

[Wyser et al(1999)] Wyser, K., L. Rontu and H. Savij�arvi, 1999:

Introducing the e�ective radius into a fast radiation scheme of a

mesoscale model. Accepted for publication in Contr. Atm. Phys.

30