Cloud top pressure/altezza1. Temperatura Necessita il profilo, giorno/notte, emissivita’2. Temperatura corretta Necessita il profilo, stima optical thickness,

relazione optical thickness emissivita’3. A partire dal tipo (soggettiva e storica)4. Ombra (illuminazione, cloud detection, shadow detection, calcolo). Solo di

giorno, sole allo zenith, solo bordi, no calibrazione, si risoluzione spaziale (OK per VIS), complessita’ nel riconoscimento di forme, solo su superfici riflettenti, nubi fine e senza contorni definiti (cirri)

5. Stereoscopia. >1 osservazione contemporanee (vento) (geostazionari: perfettamente in fase, multiviewing: (A)ATSR (2), MISR (9), POLDER (14)), geometria (no calibrazione), cloud detection, navigazione, cloud recognition (difficile, limitato ai bordi), risoluzione spaziale, nubi fini e senza contorni

6. Limb sounding + vede nubi fine, no calibrazione, problemi a scendere (<7 km), possibilie ambiguità con aerosols, numero di misure per orbita, risoluzione spaziale (cirri sono estesi)

7. CO2 slicing8. MLEV (minimum local emissivity radiance)9. WV intercept method10. Molecolar scattering (Raman scattering)11. A-band assorbimento. Photon path length, solo giorno12. Lidar13. Cloud radar

OMBRA

http://www-research.ge.ucl.ac.uk/cloudmap/reports/firstreport.pdf

Stereoscopia

Stereoscopia

Hasler, BAMS 1981

Hasler, BAMS 1981

Hasler, BAMS 1981

IR-WVCurva precalcolataMisura clear skyMisura broken cloudyStima Tb fully cloudy

MLEV

CO2Slicing

InputTemperature and Water Vapor profiles

(representative of the FOV under consideration)

Observations for, at least, two channels in the CO

2 absorption band

CO2Slicing: Theory

Solving Equation:

Iob()-Iclear()

Iob()-Iclear()

Icloud(,pc)-Iclear()

Icloud(pc)-Iclear()

=

The solution is given by the value of pc that minimizes the difference

between the right and left side

Pair Selection

Broad Band Spectrometer:Interferometer:

Example spectra

CO2Slicing: weighting function

spaceMODIS

CO2 channels

Interferometer CO

2 channels

IR Retrieval Scheme for Clouds

Temperature andwater vapor

retrievalsin clear sky

FOVs

Calibrateddata

Cloud mask

Determinationof cloud altitude,

thickness and temperature

Determinationof cloud

emissivityRetrieval of

microphysical properties (optical

thickness, ice water path,

particle size and shape)

Validation of Products

Cloud Emissivity

observed clear

cloud clear

I IN

I I

I

I I

I I

I I I II

I

I Iclear

cloud

clear cloud clearclear

cloud

clear cloud( ) ( )( ) ( )

I

I I

I I

I I I II

I

I Iclear

cloud

clear cloud clearclear

cloud

clear cloud( ) ( )( ) ( )

Minimum Local Emissivity Variance (MLEV)

Observations between 750 and 900 cm-1

2'' min

observed clear

cloud clear

I I

I I

Retrieved cloud at 9.5 km, lidar indicates single layer cloud between 7.5 and 9.8 km.

lidar

The fact that the depth of solar Fraunhofer lines in scattered light is less than those observed in direct sunlight, was discovered by Shefov [1959] [17] and Grainger and Ring [1962] [6] and is known as the ”Ring Effect” or ”Filling-in”. Several publications analysed this effect and its origins, showing that rotational Raman scattering provides the dominant contribution to the Ring Effect [1, 10, 4, 5, 8, 3, 18]. The majority of these studies however concentrated on cloud-free conditions.

Cloud radar

• INIZIO VECCHIE: VERIFICARE

Cloud top pressure, temperature, effective emissivity Retrieved for every 5x5 box of 1 km FOV’s, when at least 5

FOV’s are cloudy, day & night CO2 Slicing technique (5 bands, 12.0-14.2 µm)

– retrieve pc; Tc from temperature profile

– ratio of cloud forcing in 2 nearby bands– most accurate for high and mid-level clouds

Previously applied to HIRS (NOAA POES, 20 km), GOES sounder (~ 30 km)

Accuracy of technique ~ 50 mb

MODIS 1st satellite sensor capable of CO2 slicingat high spatial resolution

Cloud top properties ((P. Menzel, R. Frey, K. Strabala, L. Gumley, et al. – P. Menzel, R. Frey, K. Strabala, L. Gumley, et al. –

NOAA NESDIS, U. Wisc./CIMSSNOAA NESDIS, U. Wisc./CIMSS))

S. Platnick, ISSAOS ‘02

CO2 slicing: theory

Solving Equation:

Iob()-Iclear()

Iob()-Iclear()

Icloud(,pc)-Iclear()

Icloud(pc)-Iclear()

=

solution given by the value of pc that minimizes the difference

between the right and left side

CO2slicing: weighting functions

Bands w/greater CO2 absorptionhave weighting functions more

sensitive to high clouds

S. Platnick, ISSAOS ‘02Example spectra (~ 12.65-14 µm)

MODIS CO2 band weighting functions

1000

100

10

0.0 0.2 0.4 0.6 0.8 1.0

Pre

ssu

re (

mb

)

Weighting Function dt(,p)/d ln p

Channel 32 33 34 35 36

Central Wavelength (µm)

12.020 13.335 13.635 13.935 14.235

36

1.2

35

34

33

321000

100

10

0.0 0.2 0.4 0.6 0.8 1.0

Pre

ssu

re (

mb

)

Weighting Function dt(,p)/d ln p

Channel 32 33 34 35 36

Central Wavelength (µm)

12.020 13.335 13.635 13.935 14.235

36

1.2

35

34

33

32

BT in and out of clouds for MODIS CO2 bands

- demonstrate weighting functions and cloud top algorithm

S. Platnick, ISSAOS ‘02