4c5_L.Lavanant

ITSC
-
12

Cloud processing in IASI
context



Lydie Lavanant

Météo
-
France, Centre de Météorologie Spatiale, BP 147, 22300

Lannion Cedex France


Purpose:

Retrieval of
cloud

information and atmospheric profiles in cloudy
conditions

Steps
:

»
Test case description

»
CO
2
-
slicing method

»
Avhrr cloud description in IASI fov

»
IASI channel selection in cloudy conditions

»
Preliminary results of profile retrieval in cloudy conditions



01/03/02

Test Case

Global IASI orbit simulation. Feb. 1996

13000 situations with:

•

simulated IASI cloudy and noisy spectra 0.25 cm
-
1 (R. Rizzi model)

•

Colocated atmospheric profiles:


NWP analyses in T, Q, O on RTIASI levels


Cloud description (cover, CLWV, CIWV) on 31 NWP levels

Dataset provided by Eumetsat (ISSWG)

CO
2

slicing method


Ref: Menzel and Stewart 1983, Smith and Frey 1990


[(
Rclr
–

Rmeas
)
k

/ (
Rclr
–

Rmeas
)
ref
]
–

[N
e
k

(
Rclr
-

Rcld
)
k

/ N
e
ref
(
Rclr
-

Rcld
)
ref
]

= f
pc


Rmeas: measured radiance

Rclr: clear radiance computed from the colocated forecast

Rcld: black
-
body radiance at the cloud level n

k= channel from 690 cm
-
1
to 810 cm
-
1

Ref= reference channel = 899.75 cm
-
1


For each channel k: cloud pressure

= pressure which minimises equation

P_co2 =
S

(p_co2(k) w
2
(k)) / Sw
2

W =
d
f
pc

/
d
lnp

N
e

= (
Rclr
–

Rmeas
)
ref

/ (
Rclr
-

Rcld
)
ref


Assumption: one thin cloud layer

Rejections: (
Rclr
–

Rmeas
) < sqrt(2)*radiometric noise


N
e

< 0

Preliminary results of CO2 method using CDS cloudy
spectra

100
-
200

23

158.4

102.4

200
-
300

358

47.1

103.3

300
-
400

396

-
9.7

132.7

400
-
500

658

-
31.8

131.7

500
-
600

802

-
51.3

120.2

600
-
700

913

-
97.2

112.3

700
-
800

1057

-
126.6

125.9

800
-
900

793

-
147.6

135.8

900
-
1000

1534

-
129.9

164.0

1000
-
1050

72

-
51.4

71.4


Method:


•
Adapt RTIASI for implementing RTTOV7 cloudy routines
developed by F. Chevallier and al. (2001)

•
Simulate cloudy noisy IASI spectra
Rmeas

for all CDS situations
using:

»
NPW profiles (T,H2O,.., CC, CLWV, CIWV)

»
radiometric noise

•
Compute clear noisy radiances
Rclr for the same fov
using:

»
RTIASI clear

»
noisy NWP profiles (apply forecast errors)

•
Apply CO2
-
slicing method




Examples of IASI
cloudy spectra





Variation with the number of channels





1 cloud layer

N
e

> 0.3

1 cloud layer

RTIASI cloudy + noise

Profile= analysis

24 channels. r
e
solution:5cm
-
1

Variation with emissivity

Variation with
emissivity

Several cloud layers

RTIASI cloudy + noise

Profile= analysis

Variation with
emissivity

1 cloud layer

RTIASI cloudy

Profile=forecast

P_Co2,
e
_Co2

1 cloud layer

RTIASI cloudy + noise

Profile=forecast

s

= 0.2
-

0.25

Cloud top pressure

CDS dataset cloud pressure

CO2 retrieved cloud pressure

AVHRR Cloud mask in IASI fov

Operational routine for HIRS fov

(inside AAPP)

»

Based on a threshold technique
applied

.

every AVHRR pixel in sounder fov

. to various combinations of channels




»
Combinations of channels depend on:

. geographical location of the pixel

. solar illumination and viewing geometry


»
Thresholds computed in
-
line with:


. constant values from experience

. tabulated functions defined off
-
line


through RTTOV simulations on


climatological data
-
set

. TWVC retrieved from colocated AMSU
-
A

Current products:

»

percentage

clear

AVHRR

in

FOV

»

surface

temperature

from

AVHRR



split
-
window

»

black

body

cloud

coverage

in

FOV

»

cloud

top

temperature

for

the

black



body

layer

»

clear/cloudy

flag

for

each

AVHRR



pixel


Next

version
:

»
Ts,

Tcld,

Cloud

type

for

each

Avhrr



pixel

»
-
>

number

of

clouds

AVHRR Cloud mask in IASI fov


AVHRR Cloud mask in IASI fov


Validation over Europe

correctly detected

Cloudy targets

Cloud free targets

sea ; day


1774 (99.8%)

584 (87.8%)

sea ; glint

269 (98.8%)

72 (89%)

sea ; twilight

59 ( 98.3%)

12 (90%)

land ; day

995 (99.5%)

638 (80.9%)

land ; twilight

27 (100%)

11 (67.4%)


7007 targets of 5x5 AVHRR
pixels


Noaa12
,

14
,

15


for
3 years


38
cloud
types


Mask comparison with visual
analysis of satellite imagery by
CMS nephanalysts

March
2001

Clear land


Clear sea

Cloudy
land Cv>50

Cloudy sea
Cv>50

N

937

103

136

55

Bias (K)

0.02

0.64

0.49

0.15

Std (K)

0.99

0.39

0.98

0.65

Comparison of satellite obs.
and Hirs 8 RTTOV6 Tbs using:

* NWP profile,

* AVHRR clear cover +Ts,

* AVHRR black
-
body cloud
cover +Tn

Channels selection and retrieval in clear conditions on CDS

•

Rodgers DFS selection

•

Guess error matrix = forecast

•

Use a mean profile for mid
-
latitude
conditions

the 300 most informative channels

Clear situations

nbsit= 187 (1/10)

Channels selection above the cloud

Select channels from the 300 most informative channels in clear conditions

Ex: for p_cloud=850 hPa

. uncontaminated channels above the cloud top level: about 65% channels selected

. cloud contaminated
channels

with

(
Tbobs
–

Tbgucld
)

<
0.
3
K

:

about

85%

channels
selected

Profile retrieval in cloudy conditions. CDS dataset

un
-
contaminated channels above the cloud

600
<
p_cloud
<
700

Nbsit= 132 (1/3)

700
<
p_cloud
<
800

Nbsit= 146 (1/4)

800
<
p_cloud
<
900

Nbsit= 138 (1/7)

900
<
p_cloud
<
1000

Nbsit= 166 (1/5)

w
ith

un
-
contaminated
channels above
cloud
:

1DVar in clear
conditions


Profile retrieval in cloudy conditions

with cloud
information as control variable

all P_cld

>

800hPa

1807 situations

(15% of situations)

P_cld

e
_cld

Cloud c
ontrol variables: ln(p_cld),
e_
cld

Cloud g
uess: CO2 p_cld and
e_
cld

selected channels: Tbobs
–

Tbgucld
<
0.
3
K

-
>

more than
8
0% channels selected

before
1d_var

after

1d_var

a
ll selected
channels
: 1DVar
cloudy


forecast

as
background

Summary:

•
Create IASI cloudy spectra using NWP analyses (T,H2o,.., CC, CLWV,
CIWV)

•
Use CO2 method to determine the cloud top pressure and emissivity

•
Retrieve temperature profile in cloudy condition with CO2 cloud
parameters as guess

•
validate on CDS dataset


Future:

•
Consolidate the results on recent NWP data (with cloud profile
information on 60 levels)
-
> package

»
add the water vapor profile

»
Combine IASI, AVHRR and AMSU information

•
Validate on AIRS observations

•
Adapt the method to the IASI stand
-
alone package

•
Test a cloud
-
clearing method (J. Joiner)