retrieval of cloud parameters from the new sensor generation satellite multispectral measurement

Retrieval of cloud parameters from the new sensor generation satellite multispectral measurement

F. ROMANO and V. CUOMO F. ROMANO and V. CUOMO

ITSC-XII Lorne, Victoria, Australia

Main Object:

Improvement using AMSU data and high spectral resolution data (IASI and IMG)

in

•cloud detection

•cloud clearing

•cloud forcing radiative

•retrieval of cloud parameters


TOP CLOUD HEIGHTOP CLOUD HEIGH

The cloud radiative forcing the simple difference between cloud and cleared radiances can be useful in the estimation of top cloud height.

Accurate cloud clearing and cloud detection packages are necessary to estimate cloud radiative forcing.


IASI Cloud Clearing SchemeIASI Cloud Clearing SchemeIASI Cloud Clearing SchemeIASI Cloud Clearing Scheme

AMSU Data IASI DataIASI/AMSUREG. COEF.

Synthetic IASI Data

Variogram

Clear IASI FOV in the Box

Kriging interpolation

Cleared IASI data and errors

Cloud Mask


IASI Cloud Clearing TestIASI Cloud Clearing Test

DATASETDATASET

•R. Rizzi’s Cloudy Dataset (CDS)

•M. Madricardi’s AMSU Brightness Temperature Data set


CLOUD CLEARING RESULTS CLOUD CLEARING RESULTS

Results, on the basis of IASI simulated data and ATOVS data,

show that

the root mean square error of the Kriging clear brightness temperatures estimates is

well below 1°K for any IASI or HIRS channels.


IASI/AMSU CLOUD DETECTIONIASI/AMSU CLOUD DETECTION

AMSU data have been used in order to have some information about the clear radiance field.

The test based on AMSU data allow to detect all the overcast FOVs and high cloud.

Low clouds, thin cirrus clouds and partially FOVs cloudy is detected using some tests based on IASI or IMG signatures.


IASI/AMSU CLOUD DETECTION VALIDATION

IASI/AMSU CLOUD DETECTION VALIDATION

•R. Rizzi’s Cloudy Dataset (CDS)

•M. Madricardi’s AMSU Dataset

Data usedFOVsnumber

Clear FOVSdetected cloud

Cloud FOVSdetected Clear

FOVS detectedExactly

91200 2418 ( 2.6 % ) 2485 ( 2.7 % ) 86297 ( 94.6 % )


IMG/AMSU CLOUD DETECTION VALIDATION

IMG/AMSU CLOUD DETECTION VALIDATION

•MEASURED IMG DATA•COLLOCATED AMSU/MSU DATA

Data usedFOVsnumber

Clear FOVsdetected cloud

Cloud FOVsdetected Clear

FOVs detectedExactly

580 12 (2.06%) 26 (4.48%) 542 (93.45%)


CO2 slicing has been extensively used to retrieve cloud top pressure and cloud effective emissivity. The radiance from a partially cloudy air column region can be written as:

Using Radiative Transfer Equation and after simple operation we obtain:

RRRclearcloud

)1(

c

s

p

p

cleardBpRR )(


CO2 slicing method CO2 slicing method

CLOUD TOP HEIGHT : Single Cloud LevelCLOUD TOP HEIGHT : Single Cloud Level

For two close spectral channels and viewing the same FOV can be written as:

222

111

22

11

)(

)(

dBp

dBp

c

s

c

s

p

p

p

p

clear

clear

RRRR


In order to apply the CO2 slicing technique to IASI data, it is necessary to select the best pairs of frequency to be use in the cloud top retrieval.

The method used, select all the channel in the (700 – 753 cm-1) absorption band whose weighting functions peak between 200 mb and 900 mb.

It use all the possible combinations of those channels, with the first channel in the pair always associated with the lower wavenumber.


Then apply the CO2 slicing technique to retrieve the cloud top heights, using all the selected channel pairs.

Finally selected the number of pairs that best satisfy the radiative transfer equation for all the spectral channels.

For each FOV the pairs number of different solutions found are used to evaluate a cost function:

N

i1

2

c

siiiii

p

pi

cleardBpRR )(


The solution associated to the smallest values of cost function are averaged to determine the cloud top height.

Increasing the number of channel pairs used in average causes a improvement in the accuracy of the top cloud height retrieval.

At the end the algorithm select 36 pairs of channels.


When the cloud height is known, the cloud effective emissivity has been estimate using the infrared window channel data (893 cm-1) by means from the follow relation:

RBRR

clear

wcw

clear

ww

pT

))((


To examine the performance of the top cloud height and effective emissivity algorithm, the numerical simulations of clear and cloudy radiances were carried out using synthetic data from LBLRTM.

Additional instrumental noise were simulated according to IASI specification noise level.


Radiances are simulated for ten cloud-top pressure (900 mb, 850 mb, 830 mb, 800 mb, 730 mb, 750 mb, 730 mb, 700 mb, 650 mb, 600 mb)

for four cloud amounts (0.1, 0.5, 0.7, 1)

and for the U.S. Standard climatological profile, for all the frequency used in the algorithm measured


CLOUD TOP HEIGHT : Two Cloud LevelCLOUD TOP HEIGHT : Two Cloud Level

The cloud forcing when you consider two level cloud (upper and lower cloud) can be expressed as:

dBpdBpch

sh

cl

s

p

ph

p

phhll

clear

RR )()()1(

From all the solutions we select these best satisfies the radiative transfer equation for all spectral channels.


In the same way we defined a cost function and the solutions associated to the smallest values are averaged to determine the upper and lower cloud top height.

Increasing the channel pairs number used in average causes a improvement in the accuracy of the top cloud height retrieval.

At the end the algorithm select 44 pairs of channels


Cloud Top height Package ValidationCloud Top height Package Validation

The top cloud height package has been apply at the simulated CDS-IASI cloud data.

Between the 91200 FOVs 1010 FOVs with a single cloud layer and 605 FOVs with two cloud levels have been selected.

The temperature profile and the profiles of atmospheric transmittance for the spectral frequency have been calculated as a function of top cloud top pressure.

The cloud top altitude is assumed to vary according to the 43 pressure discrete layering.


Single Cloud Level Single Cloud Level

0 200 400 600 800 1000

0

200

400

600

800

1000

a=4.70 b=0.99 r=0.99 sd=1.61

Clo

ud to

p pr

essu

re (m

b)

Retrieved Cloud Top Pressure (mb)


Two Cloud Levels Two Cloud Levels

0 100 200 300 400

0

100

200

300

400

a=-0.78 b=0.99 r=0.99 sd=1.56

Clo

ud to

p pr

essu

re (m

b)

Retrieved cloud top pressure (mb)


Two Cloud Levels Two Cloud Levels

650 700 750 800 850 900 950650

700

750

800

850

900

950

1000

a=6.03 b=0.99 r=0.99 sd=1.77

Clo

ud to

p pr

essu

re (m

b)

Retrieved cloud top pressure (mb)


Conclusions and Future WorkConclusions and Future Work

AMSU data and high spectral resolution IASI and IMG sounders data can greatly be improved retrieval cloud parameters.

The cloud top pressure and the effective emissivity retrieval are in good agreement with the true theoretical values.

The cloud top pressure retrieved packages will be extend to multiple cloud levels.

Validation, based on radiosonde and meteorological radar, will be extend to IMG and AIRS measured data.


retrieval of cloud parameters from the new sensor generation satellite multispectral measurement

Documents

high cloud

accurate cloud

cloud radiative forcing

cloud detection packages

single cloud levelfor

cloud effective emissivity

fovs numberclear fovs

fovs cloudy