Cloud top pressure/altezza 1.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 slicing 8.MLEV (minimum local emissivity radiance) 9.WV intercept method 10.Molecolar scattering (Raman scattering) 11.A-band assorbimento. Photon path length, solo giorno 12.Lidar 13.Cloud radar

OMBRA

Stereoscopia

Hasler, BAMS 1981

IR-WV Curva precalcolata Misura clear sky Misura broken cloudy Stima Tb fully cloudy

MLEV

CO 2 Slicing Input Temperature and Water Vapor profiles (representative of the FOV under consideration) Observations for, at least, two channels in the CO 2 absorption band

CO 2 Slicing: Theory Solving Equation: I ob ( )-I clear ( ) I cloud (,p c )-I clear ( ) I cloud ( p c )-I clear ( ) = The solution is given by the value of p c that minimizes the difference between the right and left side

Pair Selection Broad Band Spectrometer: Interferometer:

Example spectra

CO 2 Slicing: weighting function space MODIS CO 2 channels Interferometer CO 2 channels

CO 2 Slicing Results Cloud top height differences from lidar (CLS) (1 km intervals).

IR Retrieval Scheme for Clouds Temperature and water vapor retrievals in clear sky FOVs Calibrated data Cloud mask Determination of cloud altitude, thickness and temperature Determination of cloud emissivity Retrieval of microphysical properties (optical thickness, ice water path, particle size and shape) Validation of Products

Cloud Emissivity

Minimum Local Emissivity Variance (MLEV) Observations between 750 and 900 cm -1

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

CO 2 Slicing and MLEV Results Cloud top height differences from lidar (CLS) (1 km intervals). Cloud top height differences from lidar (CLS). CO2 Slicing MLEV

Cloud Top Retrieval Conclusions The high-spectral CO 2 Slicing seems to be more accurate than the broadband version MLEV can be used to compliment the CO 2 Slicing. The different approaches seem to agree better in presence of optically thick clouds Use images to assist in analysis

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/Height Stereoscopia Analisi dellombra Assorbimento differenziale: O 2 A-band Molecular scattering Raman Scattering (UV) Limb Sounding Temperatura CO2 15 micron slicing MLEV

Cloud top pressure, temperature, effective emissivity Retrieved for every 5x5 box of 1 km FOVs, when at least 5 FOVs are cloudy, day & night CO 2 Slicing technique (5 bands, µm) – retrieve p c ; T c 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 CO 2 slicing at high spatial resolution (P. Menzel, R. Frey, K. Strabala, L. Gumley, et al. – NOAA NESDIS, U. Wisc./CIMSS) Cloud top properties (P. Menzel, R. Frey, K. Strabala, L. Gumley, et al. – NOAA NESDIS, U. Wisc./CIMSS) S. Platnick, ISSAOS 02

CO 2 slicing: theory Solving Equation: I ob ( )-I clear ( ) I cloud (,p c )-I clear ( ) I cloud ( p c )-I clear ( ) = solution given by the value of p c that minimizes the difference between the right and left side

CO 2 slicing: weighting functions Bands w/greater CO 2 absorption have weighting functions more sensitive to high clouds S. Platnick, ISSAOS 02 Example spectra (~ µm) MODIS CO 2 band weighting functions

BT in and out of clouds for MODIS CO 2 bands - demonstrate weighting functions and cloud top algorithm S. Platnick, ISSAOS 02