Deep convection defined by Split WindowToshiro Inoue

 CCSR/ The University of Tokyo, Kashiwanoha Chiba, 277-8568, JapanMRI/JMA, Tsukuba Ibaraki, 305-0052, Japan

1. Cloud type classified by Split Window

4. Mehr Licht on Split Window for GOES-R

Figure 1 Pt. Reyes California

2. Life Cycle of Deep Convection in terms of cloud type

Inoue (1987) developed a cloud type classification method using the Split Window (11 and m) based on the characteristics of brightness temperature difference between the Split Window (BTD=TBB11-TBB12) for ice cloud found by Inoue (1985). Six cloud types (cumulonimbus type, dense cirrus type, thick cirrus type, thin cirrus type, N-type and cumulus/stratocumulus type) are classified by the TBB and BTD. Cloud type classification by the Split Window was validated using the collocated and coincident observation of Earth Radiation Budget Experiment (ERBE) (Inoue and Ackerman, 2002). They showed reasonable agreement between cloud type and long-wave, shortwave radiation by ERBE. Correspondence between cloud type by Split Window and ISCCP cloud type is shown in Fig. 1 (Luo et al, 2002). Most cloud types are reasonably agree with each other. Figure 2 shows cloud type map constructed from Split Window data of Meteosat-8, with the sub-satellite point of CALIPSO. As seen in Fig.3, cirrus type cloud by the Split Window corresponds to high cloud in CALIPSO observations

Figure 1 Correspondence between cloud type by Split Window (green) and ISCCP cloud type (black)

IRIS effect proposed by Lindzen et al. (2002) was studied using the cloud type classified by the Split Window and coincident TRMM PR and TMI observation. Three day mean SST and TPW derived from the TMI are used to study the relation ship between PR rainfall and DC defined by the Split Window. Figure 9 shows the number of Cb and Ci in relation to SST (top), and rainfall rate by PR (blue) and TMI (green) in relation to SST. Figure 10 shows same as Fig.9 except for Total Precipitable Water (TPW). The tendency of Ci number and rainfall rate is not monotonous with SST or TPW.Now, we use the TBB threshold of 273K and BTD of 1K to classify anvil including thinner Ci. We select the anvil which includes Cb within the new threshold area. Figure 11 shows the case of July 2001, while Fig. 12 shows the January 2001 case. There seems a tendency of smaller number of Ci with the increase of SST.

Figure 6 Life cycle of deep convection

Figure 3 CALIPSO observation over 5S-20N

Figure 4 Definition of deep convection with core part (Cb) and anvil (Ci)

Figure 4 shows the definition of deep convection (DC). DC was defined as cloud colder than 253K. The 253K corresponds to about 8km (400hPa) altitude in US tropical standard atmosphere. Using BTD, we can classify Ci within DC. Figure 5 shows hourly change of cloud type. DC starts from cu/cb and decays with full of Ci.

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1 2 3 4 5 6 7 8 9 10 11

Time from DC Initiation

% of Ci within 253K (DC)

3HR 4HR 5HR 6HR 7HR 8HR 9HR10HR11HR

3. IRIS Effect ?

The GOES-W Split Window data were used to study life cycle of DC for 11 months in 2001. The DC with longer duration indicates larger size at mature stage. Life cycle of DC is summarized as Figures 6 and 7. Regardless of size of DC, the Ci % within the DC increases with time goes on. Comparison with PR shows that smaller % of Ci corresponds to larger rainfall rate (Fig.8).

Figure 2 Cloud Type Map with sub-satellite points of CALIPSO

Figure 5 Hourly loud type map (Cb (red/blue), Ci (green))

Figure 7 Temporal variation of Ci % Figure 8 Ci % within DC and PR rainfall rate

Ci Cb

Alto-Cu

Cu Sc St

3.6

680hPa

440hPa

Optical Thickness

Cloud H

eight

Cb

Cu

Thin Ci

Thick Ci

N-

Ty

pe

BTD=2.5K BTD=1K

TBB=253K

Dense Ci

23

Alto-St

Ciro-St

Nimbo-St

253K

Ci

BTD>1CbBTD<1

Using the Split Window, we can classify cloud type and can retrieve SST and TPW over cloud free ocean area. We can also retrieve cloud properties of ice cloud and optically thin water cloud. Further low-level wind can be retrieved using the TPW pattern over cloud free ocean. The MORPF technique can be improved over jet cirrus prevailing region.

Proper selection of filter range and calibration especially for colder temperature is essential, since accurate BTD=TBB11-TBB12 is a key for Split Window analysis.

Ushio, T., D. Katagami, K. Okamoto, T. Inoue, 2007: On the use of split window data in deriving the cloud motion vector for filling the gap of passive microwave rainfall estimation. SOLA, 3, 1-4.Kawamoto, K. , T. Inoue, H. Lutz and J. Schmetz, 2006: Retrieval of optical thickness and effective radius of thin low-level water clouds using the split window of Meteosat-8. SOLA, 2, 144-147. Inoue, T. and H. Kamahori, 2003: 　 Comparison of water vapor field between GANAL and satellite retrieval, Tenki ( Japanese), 50, 335-339. Inoue, T. and S. Ackerman, 2002: Radiative effect of various cloud types as classified by the split window technique over the eastern sub-tropical Pacific derived from collocated ERBE and AVHRR data. J. Meteor. Soc. Japan, J. Meteor. Soc. Japan, 80, 1383-1394.Luo, Z., W. B. Rossow, T. Inoue, and C. J. Stubenrauch, 2002: Did the Eruption of the Mt. Pinatubo Volcano Affect Cirrus Properties? J. Climate, 15, 2806 - 2820 Inoue, T. and K. Aonashi, 2000: A comparison of cloud and rainfall information from instantaneous VIRS and PR observations over a frontal zone in east Asia during June 1998, J. Appl. Meteor., 2292-2301Inoue, T. and W. L. Smith, 1994: The feasibility of extracting low level wind by tracing low level moisture observed with GOES-7. J. Appl. Meteor., 33, 594-604Inoue, T. , 1990: The relationship of sea surface temperature and water vapor amount to convection over the western tropical Pacific revealed from split window measurements. J Meteor. Soc. Japan, 68, 589-606Inoue, T. , 1987a: A cloud type classification with NOAA 7 Split-Window measurements. J. Geophys, Res., 92, 3991-4000Inoue, T. , 1985:On the temperature and effective emissivity determination of semi-transparent cirrus clouds by bi-spectral measurements in the 10 m window region, J. Meteor. Soc. Japan, 63, 88-99 .

Figure 9 No. of Cb (blue) and Ci (green) and rainfall rate by PR and TMI in reation to SST

Figure 10 Same as Fig.9 except for TPW

Figure 11 Mean Ci size with SST for 273Kthreshold during Jul, 2001

Figure 12 Same as Fig. 11 except for Jan, 2001

P1.97

TPW retrieval by TMI (left) and Split Window (right)

Relative Humidity Profile from Split Window

Retrieval cloud parameter from Split Window

IR image and larger BTD area for above retrieval case

Absorption characteristics of water and ice for 3-16 m