Jun Li 1, W. Paul Menzel 2, Xuebao Wu 1, Chian-Yi Liu 1, Timothy J. Schmit 2, and Allen Huang 11Cooperative Institute for Meteorological Satellite Studies (CIMSS), University of Wisconsin - Madison 2 NOAA/NESDIS/STAR, Madison, Wisconsin

USING MODIS and AIRS for Cloud Property characterization

Figure 7. AIRS window (11 µm) BT (left) and retrieved cloud-top height (m) (right) during MPACE.

4. Conclusions(1) MODIS can help AIRS in sub-pixel cloud detection, classification and characterization.(2) MODIS can help AIRS cloud-clearing on the single FOV basis.(3) MODIS can be used together with AIRS for cloud property retrievals during both daytime and nighttime.ACKNOLEDGEMENT: This program is supported by NOAA ABI/HES program NA07EC0676, and NASA MODIS science team program.

REFERENCES Li, J., W. P. Menzel, Z. Yang, R. A. Frey, and S. A. Ackerman, 2003: High-spatial-resolution surface and cloud-type classification from MODIS multispectral band measurements, J. Appl. Meteorol., 42, 204 - 226Li, J., W. P. Menzel, F. Sun, T. J. Schmit, and J. Gurka, 2004a: AIRS sub-pixel cloud characterization using MODIS cloud products, J. Appl. Meteorol. 43, 1083 – 1094.Li, J., W. P. Menzel, W. Zhang, F. Sun, T. J. Schmit, J. Gurka, and E. Weisz, 2004b: Synergistic use of MODIS and AIRS in a variational retrieval of cloud parameters, J. Appl. Meteorol. 43, 1619 – 1634.Li, J., C.-Y. Liu, H.-L. Huang, T. J. Schmit, X. Wu, W. P. Menzel, and J. J. Gurka, 2005a: Optimal cloud-clearing for AIRS radiances using MODIS, IEEE Trans. on Geoscience and Remote Sensing, 43, 1266 –1278.Li, J., A. Huang, C.-Y. Liu, et al., 2005b: Retrieval of cloud microphysical properties from MODIS and AIRS, J. Appl. Meteorol., 44, 1526 – 1543.

3. MODIS/AIRS synergism for cloud property retrievalWith help of MODIS cloud mask and cloud phase mask, products such as cloud-top pressure (CTP), cloud particle size (CPS) in radius, cloud optical thickness (COT) can be retrieved from AIRS data with 1DVAR or minimum residual (MR) algorithms (Li et al. 2004b; 2005b). Note: there is no AIRS single footprint operational cloud property products.

1. AIRS sub-pixel cloud characterization using MODIS data

AIRS sub-pixel cloud characterization (Li et al. 2004a) with MODIS:

(a) collocated MODIS 1 km cloud mask is used to derive an AIRS single footprint cloud mask;

(b) collocated MODIS 1 km cloud phase mask is used to derive an AIRS single footprint cloud phase mask;

(c) collocated MODIS 1 km surface and cloud type classification mask (Li et al. 2003) is used to derive an AIRS single footprintsurface and cloud type classification mask.

BT (K)

A1

A2

A3

Clear Water Cld Ice Cld Mixed phase Undecided

2. AIRS cloud-clearing with MODIS

Figure 6. Temperature RMS difference between AIRS retrievals and the ECMWF analysis, ~ 250 thin cloudy footprints are included in the statistics.

Cloud contaminated

Cloud-cleared

Clear Neighbor

Figure 2a. 1km MODIS 11µm BT superimposed to the small area A2 indicated by Figure 1.

Figure 1. BT of an AIRS window channel (901.69 cm-1) on 06 September 2002

Figure 2b. 1km MODIS phase mask superimposed to the small area A1 indicated by Figure 1.

AIRS BTMODIS cloud mask (1 km)

AIRS cloud mask (13.5 km)

MODIS cloud phase mask (1 km)

Figure 4. An AIRS window (12 µm) brightness temperature (upper left), MODIS 1 km cloud mask (upper right), AIRS cloud mask derived from the MODIS cloud mask (lower left), and MODIS 1 km cloud phase mask used for AIRS cloud phase mask (lower right).

Figure 3. MODIS Spectral Response Functions (SRFs) overlap with an AIRS brightness temperature spectrum.

Optimal imager/sounder cloud-clearing Methodology

(Li et al. 2005; IEEE Trans. On Geoscience and Remote sensing, June issue).

2)]([(1

*)( cci

clrM

i i

RfRNJi νσ−=∑

N* is solved by minimizing J(N*) !9 MODIS band (22, 24, 25, 28, 30, 31, 32, 33, 34) are used

*

*21

1 N

NRRRcc

−−

= ννν

Optimal imager/sounder cloud-clearing Methodology

(Li et al. 2005; IEEE trans. On Geoscience and Remote sensing, June issue).

N* then can be analytically solved from minimizing the cost function

0)(

*

*

=∂

∂N

NJ

∑

∑

−−

−−=

iii

clrMi

i

iii

clrMi

i

RfRfRRf

RfRfRRf

N

i

i

)]()(][)([1

)]()(][)([1

2122

2112

*

ννν

ννν

σ

σ

An extension of single band N*

method (Smith et al. 1968, 2004) !

30.75%

22.60%20.30%

26.35%

Clear CC-S CC-F Full Cloud

AIRS clear(13.5 km)

AIRS clear + CC-S(13.5 km)

MODIS clear(1 km)

AIRS alone MODIS+AIRS

MODIS alone

6.7um

Figure 5. The BT images of MODIS band 28 (7.3 µm) convoluted from the AIRS clear footprints (upper left), the AIRS clear plus successful cloud-cleared footprints (upper right), and the MODIS clear BT observations with 1 km spatial resolution (lower right).

AIRS CTH (m)

Barrow

Box A

MPACE: Mixed Phase Artic Cloud ExperimentGranule 223, 17 October 2004

CTP comparison with LidarAIRS time is 22:17:32

MODIS CTH=5.5 km; AIRS CTH=7.6 km

Vertical Layers

AIRS Effective Radius=38.6 um

AIRS time = 22:17:32 UTC

AIRS OD=1.44

Figure 8. AIRS BT spectra from clear calculation, observation, and calculation with retrieved CTP, ECA, CPS and COT at ARM Barrow site.

Figure 9. Comparisons between AIRS cloud-top height (CTH), optical depth (OD), and effective radius with lidar observations at ARM Barrow site.

Thick ice clouds

BT(K)

Figure 2c. 1km MODIS classification mask superimposed to the small area A3 indicated by Figure 1.

Aqua MODIS IR SRF Overlay on AIRS Spectrum

Direct spectral relationship between IR MODIS and AIRS provides unique application of MODIS in AIRS cloud_clearing !

AIRS window BT image AIRS cloud optical thickness retrieval

(With MODIS cloud mask and cloud phase mask)