Journal of the Meteorological Society of Japan, Vol. 75, No. 1, pp , Day-to-Night Cloudiness Change of Cloud Types Inferred from

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1 Journal of the Meteorological Society of Japan, Vol. 75, No. 1, pp , Day-to-Night Cloudiness Change of Cloud Types Inferred from Split Window Measurements aboard NOAA Polar-Orbiting Satellites By Toshiro Inoue Meteorological Research Institute, 1-1 Nagamine, Tsukuba, Ibaraki 305, Japan (Manuscript received 25 June 1996, in revised form 2 December 1996) Abstract Split window measurements aboard the NOAA polar orbiting satellites have been used to study cloud cover change between day and night over the western Pacific. The split window technique can discriminate optically thin cirrus type clouds (ice clouds) from optically thick cumulus type clouds. In this study, cirrus and cumulus type clouds are each divided into two classes depending on cloud brightness temperatures (TBB). Cirrus are classified as either warm or cold type, while cumulus type are divided into cumulonimbus type and low-level cumulus/stratocumulus type. From the comparison with ISCCP analysis, mean optical thickness of warm cirrus, cold cirrus, cumulus/stratocumulus and cumulonimbus type clouds were found to be 2.2, 7.4, 15.3 and 33.7, respectively. The diurnal change in cloud cover of the above cloud types is studied for typhoon cases as individual convective systems and for an area of 20 degrees latitude by 30 degrees longitude over the western tropical Pacific. Cumulonimbus type clouds, warm cirrus type clouds and low-level cumulus/stratocumulus type clouds show tendencies toward higher cloud cover at night (about 2:30 local time). Cold cirrus type clouds show a tendency toward more cloud cover during the day (about 14:30 local time). 1. Introduction Cloudiness is involved in several physical processes such as radiative exchange, precipitation and small- and large-scale dynamics in the atmosphere. Increased knowledge of diurnal cloud variability should lead to a better understanding of the complex mechanisms involved in clouds (Minnis and Harrison, 1984). Past estimates of the variation of cloudiness have been derived primarily from infrared window radiances observed from polar-orbiting and geostationary satellites (Rossow and Lacis, 1990). The occurrence of semi-transparent cirrus clouds was hard to detect in these single-channel approaches. The number of algorithms which detect cirrus clouds is very small and most of them utilize visible or 3.7 gm data, which limits their usefulness during nighttime or daytime. Recently, multi-spectral techniques have been used to better detect cirrus clouds in the large scale using low spatial resolution data of roughly 20km by 20km (Wu and Susskind, 1990; Wylie and Menzel, 1989). In these methods, broken opaque cloud, overcast transmissive cloud and broken transmissive cloud were all labeled as "cirrus" (Wylie and Menzel, 1989). (C) 1997, Meteorological Society of Japan Four basic cloud types (arbitrarily named as warm cirrus, cold cirrus, cumulonimbus and low-level cumulus/stratocumulus clouds) are classified based on the split window technique (Inoue, 1987). In this study, we use the split window data (11um and 12um observations) to study day-to-night change in cloud cover over the western Pacific. Since the split window consists of longwave infrared data, the cloud detection algorithm works equally well during day and night. The problem of partial cloudiness within fields of view is reduced by use of high spatial resolution AVHRR data. 2. Data This study utilizes high spatial resolution Advanced Very High Resolution Radiometer (AVHRR) Global Area Coverage (GAG) data. The GAG data is sampled every 3 lines and averaged for four pixels. We compiled NOAA-9 data for January, 1987 and NOAA-11 for 1-28 September, 1990 (no data on 8th and 9th) over the western Pacific from 40S 40N and 120E-180E with 0.1 degree latitude/longitude grids. Both NOAA-9 and NOAA-11 cross the equator at approximately 2:30 and 14:30 local time. The split window data of channel 4 and channel 5 of the AVHRR are calibrated orbit by orbit. Over the area of 40S 40N and 120E-180E,

2 60 Journal of the Meteorological Society of Japan Vol. 75, No. 1 Table 1. Mean optical thickness by ISCCP analysis for the cloud types classified by the split window method. Fig. 1. Cloud type classification diagram (after Inoue, 1989). both day and night cloud maps were constructed using channel 4 TBBs and brightness temperature differences (BTD) of the split window. One cloud map (day or night) over the area contains data from several orbits but observations are all close to the 2:30 or 14:30 local time. 3. Cloud type classification by split Window Inoue (1987) developed the split window technique to classify cloud types objectively. Using observations from the AVHRR aboard NOAA-7, Inoue (1985) found differences of absorption characteristics by cirrus clouds between the 11um and 12um channels. The cloud type classification technique utilizes this differential absorption by ice crystals between 11um and 12um. Optically thin cirrus clouds consisting of ice crystals are characterized as those observations whose BTD (=TBB(11um)- TBB (12um)) are larger than that of cloud-free areas, where BTD depends on atmospheric water vapor abundance. Optically thick clouds are characterized by smaller BTDs. These characteristics are seen in model calculations (e. g., Prabhakara et al., 1987; Parol et al., 1991). Using a diagram of TBB versus BTD (Fig. 1), after Inoue, 1989), we classify cloud types over the tropical ocean area for cloudy pixels. In this study, we define I-1 and I-2 cloud types in Fig. 1 as cold cirrus type clouds (ice clouds with cold TBB), and I-3 cloud type as warm cirrus type clouds (ice clouds with warm TBB). Therefore, four cloud types (warm cirrus type, cold cirrus type, cumulonimbus type (Btype in Fig. 1) and cumulus/stratocumulus type (Utype in Fig. 1)) are studied to see the cloud cover change between day and night. N-type clouds are generally seen at the edge of thin cirrus clouds and thin cirrus clouds over the low-level optically thick clouds. Further study is required for the multi-layer cloud case, since it is very important in radiation budget studies. Although the overlap cloud case might affect the estimation of cloud cover, we studied for the above four cloud types based on Fig. 1 in this study. Ackerman and Inoue (1994) studied the shortwave and longwave cloud radiative forcing at the top of the atmosphere as a function of cloud type, classified by the split window technique, using collocated AVHRR and Earth Radiation Budget Experiment (ERBE) observations. Collocated AVHRR data were used for the purpose of finding ERBE footprints covered uniformly by a single cloud type. Cumulonimbus type clouds show very large values of cloud forcing in both shortwave and longwave. Cirrus type clouds and optically thick cumulus/stratocumulus type clouds, which are warmer than -20C, show similar values of longwave cloud forcing but significantly different values of shortwave cloud forcing. These results are consistent with our knowledge of these cloud types and demonstrates the effectiveness of split window data in classifying cloud types. 4. Comparison between split window and IS- CCP analysis. To validate the spit window algorithm, cloud types by the split window technique are compared with analysis by the International Satellite Cloud Climatology Project (ISCCP) over the western tropical Pacific. ISCCP DX data for daytime orbits were used in this comparison. The ISCCP analysis retrieves visible optical thickness and cloud altitude for every cloudy pixel. Therefore, for each cloud pixel classified by the split window algorithm, corresponding ISCCP data were available for comparison. Table 1 shows the mean optical thickness from ISCCP analysis for the corresponding split window cloud type. Cirrus clouds show smaller values of optical thickness than optically thick cumulus clouds.

3 February 1997 T. Inoue 61 Fig. 2. Scatter plots of cloud temperature and optical thickness by ISCCP algorithm for cumulonimbus type clouds classified by the split window method. Fig. 4. Histogram of day and night cloud cover of cumulonimbus type clouds for the typhoon cases during September in Fig. 3. Same as Fig. 1, except for cirrus type clouds classified by the split window method. Also, optical thickness of cold cirrus is larger than for warm cirrus. These statistics are results from only 4 orbits of data over the western tropical Pacific but it shows the effectiveness of the split window method. Figure 2 shows a scatter plot of cloud temperature and optical thickness from the ISCCP analysis for cumulonimbus clouds as identified by the split window algorithm. The figure shows many clouds are classified as thick enough to be classified as cumulonimbus but ISCCP analysis indicates 40% of this cloud as cirrostratus whose optical thicknesses is smaller than 23. This plot suggests that the split window technique sometimes assigns optically thick clouds like cumulonimbus in place of optically thin clouds. Figure 3 shows cloud temperatures and optical thicknesses for the cirrus type clouds classified by the split window technique. Optical thicknesses for these clouds were less than 20. This indicates the effectiveness of the split window technique in detecting optically thin cirrus clouds. However, there are many clouds whose retrieved cloud altitudes are lower than cirrus level in the ISCCP analysis. Precise analysis would be required to improve the algorithm and the point of this comparison is to show the characteristics of the split window cloud type classification technique. Since the ISCCP analysis requires visible data, it has a crucial deficiency during the nighttime hours, while the split window technique can be applied both day and night. The split window algorithm could add valuable information to the study of diurnal variation of cloud systems from a cloud type perspective. 5. Results 5.1 Cloud cover for typhoon cases We selected eight typhoon cases from 26 days of observations in September, These eight cases were chosen because the typhoon eye was located near the sub-satellite track for both day and nighttime orbits. Cloud amounts were computed within a 12 degree latitude/longitude area centered at the typhoon eye. Figure 4 shows cloud cover of cumulonimbus type clouds for both day and night. Generally, the nighttime orbits show larger cloud amounts. Figure 5 shows cloud amounts of warm cirrus type clouds. These also show larger values of cloud cover at night. Contrary to these results, cold cirrus clouds show larger cloud cover during the day (Fig. 6). Muramatsu (1983) studied diurnal variations of

4 62 Journal of the Meteorological Society of Japan Vol. 75, No. 1 Table day mean cloud cover for the cloud types over the area of 0-20N and E during January in Fig. 5. Same as Fig. 3, except for warm cirrus type clouds. Fig. 6. Same as Fig. 3, except for cold cirrus type clouds. connective activity associated with mature typhoons using GMS infrared data. He found that convective cloud cover over the central part of typhoons, defined by cloud TBBs of -70C or colder, showed sharp maxima at 6-7 local time and minima at local time. On the other hand, cloud cover defined by -30C<TBB<0C showed maxima at about 21 local time and minima at 6 local time. He explained this temperature dependent diurnal variation of cloud cover as a result of outward expansion of cirrus clouds following an early morning convective peak in the eye wall and spiral bands. Our results are consistent with this study. 5.2 Cloud cover over the tropical oceans Table 2 shows the 15-day mean of cloud cover for each cloud type over the western tropical Pacific from 0-20N and 140E-170E in January, Total cloud amounts and cloud amounts of cold clouds (TBB<-50C) show larger values at night. However, cloud cover of warmer clouds (TBB<-20C) show a larger value during the day. These results are also consistent with Muramatsu (1983). Cumulonimbus clouds, warm cirrus clouds and low level cumulus/stratocumulus clouds show larger cloud cover values at night. But cold cirrus clouds, defined as clouds with TBBs colder than -20C and 1C<BTD<3C, indicate larger values during the daytime. These results are the same as for the typhoon cases. Figures 7-10 show day-to-day cloud cover for each cloud type in September, 1990 over the area from 0-20N and E. We selected a relatively large area to minimize cloud contamination from outside the border of the area where the cloud cover was computed. Cumulonimbus cloud cover generally shows larger values at night (six exceptions in 26 cases). Warm cirrus cloud cover also shows larger values at night (one exception in 26 cases), on the other hand, cold cirrus cloud cover indicates larger values during the day (four exceptions in 26 cases). These day-to-night cloud cover change for cloud types are seen more clearly over the tropical ocean than in typhoon cases. This tendency agrees with the analysis by Muramatsu (1983) for mature typhoons. He found early morning enhancement of convective activity and gradual expansion of cirrus anvils due to active convection near the center of typhoons. Menzel et al. (1992) studied the diurnal change of cirrus cloud cover over the United States using the CO2 slicing technique. They found that overall, cirrus cloud cover showed some diurnal variation in the summer months, with an increase subsequent to afternoon convection. Kubota and Nitta (personal communication) studied diurnal variation of convective activity over the western Pacific during TOGA-CORE period using GMS IR data. They found the local time of convective activ-

5 February 1997 T. Inoue 63 Fig. 7. Histogram of day and night cloud cover of cumulonimbus type clouds over the 0-20N and E during September in Fig. 8. Same as FIg. 7, except for warm cirrus type clouds. ity peak shifts from morning to afternoon depending on the TBB, which is used to define convective activity, from210 K to 240K. Since the single infrared technique cannot tell cloud type, the result might be affected by cold cirrus in this study. Further, preliminary results from GOES-9 split window data indicate the time lag between local time for maximum cloud cover of cumulonimbus type clouds and cold cirrus type clouds (Inoue, 1996). Therefore, we conclude, at this time, that cold cirrus cloud cover increases during the day (14:30 local time) in our analysis due to cirrus anvil expansion with a time lag following the early morning convective maximum. Low-level cumulus/stratocumulus cloud cover shows larger values at night than during the daytime (two exceptions in 26 cases). Minnis and Harrison (1984) studied the diurnal variation of stratocumulus over the eastern tropical Pacific in that area off the west coast of South America where it is well known that stratocumulus clouds prevail. There-

6 64 Journal of the Meteorological Society of Japan Vol. 75, No. 1 Fig. 9. Same as Fig. 7, except for cold cirrus type clouds. FIg. 10. Same as Fig. 7, except for cumulus/stratocumulus type clouds. fore, single-channel infrared data can detect the diurnal features of stratocumulus clouds for this specific case. Over the tropical ocean, both cirrus and low level stratocumulus clouds generally coexist. It is difficult to discriminate between cirrus and stratocumulus using single-channel infrared data, since both cloud types exhibit similar TBBs. Minnis and Harrison (1984) demonstrated the night time maximum of stratocumulus cloud cover over the area. Our finding, by use of the split window technique, is consistent with that study. 6. Concluding remarks In this paper, we report cloud cover change between day and night as a first step in studying the diurnal changes of clouds. Split window data are very effective in detecting cirrus clouds which are difficult to classify objectively in visible/infrared satellite algorithms. So far, NOAA polar orbiting satellites are the only carrier of the split window channels, although split window data on GOES-8, 9 and GMS-5 are now in operational use. We studied the changes of cloud cover between day and night for the individ-

7 February 1997 T. Inoue 65 ual convective systems near the centers of typhoons, and over a wide area of the western tropical Pacific using NOAA polar orbiting satellite data. Cumulonimbus clouds, warm cirrus (TBB> -20C) clouds and low level cumulus/stratocumulus clouds show tendencies toward larger cloud cover at night (2:30 local time). These findings are consistent with previous works (Muramatsu, 1983; Minnis and Harrison, 1984). Cold cirrus (TBB<-20C) clouds show a tendency toward larger cloud cover during the day (14:30 local time). These day and night cloud cover change for cloud types are seen more clearly over the tropical Pacific than in typhoon cases. It is known that convective activity over the ocean increases early in the morning (e. g., Murakami, 1983). This implies that cirrus anvil from centers of convection spread gradually outward to make the cold cirrus cloud cover larger in the afternoon. Muramatsu (1983) discussed these features in his study of mature typhoons. We compared the split window cloud type classification and ISCCP cloud type analysis over the tropical ocean. Optical thickness of warm cirrus, cold cirrus, cumulus/stratocumulus and cumulonimbus type clouds were found to be 2.2, 7.4, 15.3 and 33.7, respectively. Cirrus clouds identified by the split window algorithm indicate that the optical thicknesses were smaller than 20. However, 30% of these clouds are assigned as mid-level in the ISCCP analysis, since the cloud temperatures are warmer than the 440 hpa level. The optical thickness of cumulonimbus clouds classified by the split window method were larger than 10 according to the corresponding ISCCP data. However, in the cloud type definition of ISCCP, the optical thicknesses of deep convective clouds is greater than 23. Therefore, 40% of the cumulonimbus clouds identified by the split window would be classified as cirrostratus clouds by the IS- CPP algorithm. This implies that the BTD has a limitation in classifying optically thick clouds. Currently the split window technique does not retrieve optical thickness nor cloud temperature. It classifies cloud types qualitatively. We have developed a technique to retrieve two of the following parameter, given the remaining one: optical thickness, cloud temperature and effective radius of cirrus clouds. This will be reported in a separate paper. Acknowledgments The author would like to thank Prof. Steven Ackerman and Mr. Richard Frey at Space Science and Engineering Center at the University of Wisconsin-Madison for comments and correction for English. References Ackerman, S. A. and T. Inoue, 1994: Radiation energy budget studies using collocated AVHRR and ERBE observations. J. Appl. Meteor., 33, Inoue, T., 1985: On the temperature and effective emissivity determination of semi-transparent cirrus clouds by bi-spectral measurements in the 10um window region. J. Meteor. Soc. Japan, 63, Inoue, T., 1987: A cloud type classification with NOAA- 7 Split Window measurements. J. Geophys. Res., 92, Inoue, T., 1989: Features of clouds over the tropical Pacific during northern hemispheric winter derived from split window measurements. J. Meteor. Soc. Japan, 67, Inoue, T., 1996: Diurnal variation of cloudiness for cloud types inferred from GOES-9 split window: Preliminary results. Proceedings of 1996 Meteorological satellite users' conference, Menzel, W. P., D. P. Wylie and K. I. Strabala, 1992: Seasonal and diurnal changes in cirrus clouds as seen in four years of observations with the VAS. J. Appl. Meteor., 31, Minnis, P. and E. F. Harrison, 1984: Diurnal variability of regional cloud and clear-sky radiative parameters derived from GOES data. Part II: November 1978 cloud distributions. J. Climate Appl. Meteor., 23, Murakami, M., 1983: Analysis of the deep convective activity over the western Pacific and Southeast Asia. Part I: Dirunal variation. J. Meteor. Soc. Japan, 61, Muramatsu, T., 1983: Diurnal variations of satellitemeasured TBB areal distribution and eye diameter of mature typhoons. J. Meteor. Soc. Japan, 61, Parol, F., J. C. Buriez, G. Brogniez and Y. Fouquart, 1991: Information content of AVHRR channels 4 and 5 with respect to the effective radius of cirrus cloud particles. J. Appl. Meteor., 30, Prabhakara, C., R. S. Fraser, G. Dalu, M. L. C. We, R. J. Curran and T. Styles, 1988: Thin cirrus clouds: seasonal distribution over oceans deduced from Nimbus- 4 IRIS. J. Appl. Meteor., 27, Rossow, W. B. and A. A. Lacis, 1990: Global, seasonal cloud variations from satellite radiance measurements. Part II: Cloud properties and radiative effects. J. Climate, 3, Wu, M. L. and J. Susskind, 1990: Outgoing longwave radiation computed from HIRS2/MSU soundings. J. Geophys. Res., 95D, Wylie, D. P. and W. P. Menzel, 1989: Two years of cloud cover statistics using VAS. J. Climate Appl. Meteor., 2,

8 66 Journal of the Meteorological Society of Japan Vol. 75, No. 1