Adv. Space Res. Vol. 9, No. 7, pp. (7)161-(7)165, 1989 0273 1177/89 $0.00 +.50 Printed in Great Britain. All rights reserved. Copyright © 1989 COSPAR

T H E G L O B A L D I S T R I B U T I O N OF O B S E R V E D C L O U D I N E S S - - A C O N T R I B U T I O N TO T H E ISCCP

Jul ius L o n d o n , * S t e p h e n G. W a r r e n * * a nd Ca ro l e J. H a h n * * *

*Department of Astrophysical, Planetary' and Atmospheric Sciences, University of Colorado, Boulder, CO 80309, U.S.A. **Department of Atmospheric Sciences, University of Washington, Seattle, WA 98195, U.S.A. ***CIRES, University of Colorado, Boulder, CO 80309, U.S.A.

ABSTRACT Satellite-inferred overall global cloud patterns generally corroborate those derived from ground-based observations. Both show significant differences of cloudiness between the two hemispheres and over extended land as compared with ocean areas. However, the averaged latitudinal values of surface-based observed cloud amounts are about 10 percent higher than those derived from Nimbus-7 observations. The largest difference (10-20 percent) is in the subtropics of each hemisphere and at subpolar and polar latitudes during the summer. The difference in reported average global total cloud amounts is about 10 percent.

INTRODUCTION

The distribution of cloudiness over the globe is one of the basic characteristics of the atmosphere that determines the distribution of radiative energy sources and sinks in the earth-atmosphere system. The three-dimensional pattern of net radiative input (or deficit) helps to drive the general circulation while the net radiative gain (or loss) at the surface is significant in regulating the energy exchange between the surface and atmosphere and is an important component affecting atmosphere-biosphere interac- tions. (e.g. , /1/ ; /2/) . Reliable cloud observations are thus fundamental to a description of the earth- atmosphere system and to an understanding of the basic physical processes that affect that system. This realization was brought into focus with the formation of the International Satellite Cloud Climatology Project (ISCCP) about ten years ago, which project subsequently became a part of the World Climate Research Programme (WCRP). An important component of the ISCCP has been, from the outset, the development of a so-called "ground-truth" time and space distribution of observed total cloudiness and dominant cloud types.

Surface cloud information is available from the international network of ground-based observations and from individual observational programs using ground-based all-sky camera techniques and Lidar techniques. Limited cloud observations are also available using aircraft platforms. Since the mid- 1960s, different satellite systems have provided extensive information on global cloud patterns. Of these various observational methods, surface-based and satellite inferred observations currently provide the most appropriate documentation for the development of improved global cloud climatologies.

Ground based "observations" of clouds are distinct from satellite based "observations" in at least 2 ways. The former reports "sky cover" while the latter, for nadir observations, reports "earth cover." In general, this projection difference can result in slightly higher cloud amounts reported by ground observers. Of perhaps more serious concern are the differences that result from the subjective cloud identification and cloud amount estimates by human observers, and the interpretation of proxy information derived from satellite measurements of visible spectral albedo and/or infrared irradiance to infer total cloud amount and, in some cases, broadly classified cloud types (e.g., /3/; /4/) . These differences, which can lead to an important discrepancy in describing the "observed distribution" of clouds, stem from the lack of a precise common definition of the cloud. The first method (synoptic observations) is based on an agreed upon recognition pattern (/5/). The second (satellite observations) is the agreed upon equivalence of measured radiative characteristics of clouds involving also specific measurement techniques and retrieval approximations (i.e., observed spectral resolution, threshold assumptions, etc.). It should be noted, however, that despite these various differences, when averaged over suitable intervals of space and time, the results of the two methods are in general agreement. One of the objectives of ISCCP is to evaluate how the remaining differences can be resolved.

GROUND-BASED TOTAL CLOUD OBSERVATIONS

Total cloud observations made by ground observers over different parts of the globe have been variously archived (see, for instance, /6/) . Two of the more complete sets of individual observations currently available are the Comprehensive Ocean-Atmosphere Data Set (COADS) (/7/) for the oceans and syn- optic reports from the "SPOT" archive of the Fleet Numerical Oceanography Center (FNOC) for the land. We have used these data sets to analyze the global distribution of various characteristics of clouds (total amount, amount by cloud type, etc.) over land (/8/) and ocean (/9/).

(7)161

(7)162 J. London et al.

For reasons described in the above references, we have chosen for the period of our analyses (1971-1981) for land and (1952-1981) for ocean. For the results discussed below we have combined the land and ocean analyses for the period 1971-1981. The results are limited to the global distribution of total cloud amount averaged for the four seasons (DJF, MAM, JJA, and SON) based on a 5 ° x 5 ° lat/lon grid. Details of the averaging procedures and treatment of the various biases, both obserwtional and statistical, that axe part of this study are discussed in detail by Warren et al., ( / 8 / ; / 9 / ) . A brief review of that discussion is contained in Warren et al. (/4/). The axchived binned data set is discussed by Hahn et al. (/10/). Some of our preliminary results are discussed in London et al. (/11/).

DISTRIBUTION OF TOTAL CLOUD AMOUNT

The average global distribution of total cloud amount for the period 1971-1981 is shown in Figs. la. (DJF) and lb. (JJA).

During DJF the highest total cloud amounts (over 80 percent) axe located over tropical land areas of the Southern Hemisphere and at subpolax ocean areas. In the Southern Hemisphere summer (DJF) clouds cover more than 80 percent of the entire ocean area south of about 50°S. A large portion of the Antarctic Ocean between about 55 and 65 degrees has over 90 percent cloud cover, predominantly stratus type clouds. The subpolax ocean maxima result from advection of moist air over the cold polar ocean waters. In the tropical land areas, the cloud maxima are associated with deep convection in the ITCZ. Cloudiness minima, less than 40 percent, are located chiefly over subtropical latitudes of north Africa, India, southwestern U.S. and central Australia. Over the oceans, the cloudiness minima are mostly in the eastern equatorial and subtropical north and south Pacific.

There is a general northward shift of total cloud patterns from DJF to JJA. During JJA the land tropical maxima, greater than 80 percent, are now located over Western Africa north of the equator, NW South America and SE Asia. The minimum cloudiness over land in the Southern Hemisphere during these months (Southern Hemisphere winter) is less than 10 percent over SW Africa, less than 30 percent over Brazil and less than 20 percent over Central Australia. In the Northern Hemisphere, the cloudiness over Southern Europe, N. Africa, and the Near East is almost everywhere less than 20 percent.

Comparison of the surface-based global cloud distributions, as discussed above, with the Nimbus-7 bi- spectral total cloud analysis for the single months July (1979) and January (1980) as discussed by Stowe et al. (/12/) show very similar geographic patterns but with the ground based data generally giving 10- 20 percent higher cloud amounts. The differences tend to be largest in subtropic regions over the oceans and at polar latitudes during the summer. For instance, there is almost no area where the Nimbus-7 observations show total cloud amount, for either Jan or Jul, of over 90 percent. The satellite-inferred cloud amounts axe seriously underestimated in the presence of low clouds over cold snow surfaces.

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Fig. 1. (a) D J F

The g loba l d i s t r i b u t i o n of t o t a l c loud a m o u n t (%) f rom s u r f a c e - b a s e d obse rva t i ons (1971-81)

Global Distribution of Observed Cloudiness (7)163

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f rom su r f ace -ba sed obse rva t ions (1971-81)

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The average latitudinal variation as determined from ground-based observations for each of the four seasons is shown in Fig. 2. Maximum cloudiness (75-90 percent) is found at latitudes 50°S-70°S where there is the least average zonal land area and in the summer and autumn (75-80 percent) at high latitudes of the Northern Hemisphere. Secondary maxima are at northern hemisphere subpolar latitudes and in the North Equatorial zone. The average cloud cover minima are in the subtropics of each hemisphere associated with the poleward (descending branch) of the Hadley circulation. Note that in the subtropics and at subpolar latitudes the Southern Hemisphere cloud amounts are always greater than those in the Northern Hemisphere. This is clearly the result of the larger ocean surface area in the Southern Hemisphere. Also, southward of 3O°S there is almost no interseason variation in total cloud cover. The relatively large interseasonal variations occur between + 30 ° with latitudinal shifts of the equatorial and tropical circulation patterns, and poleward of 60°N, where land area influences dominate the annual cloud variation.

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The average zonal d i s t r i b u t i o n of to ta l c loud a m o u n t (%)

land + ocean (1971-81) for each season

(7)164 J. London et al.

COMPARISON WITH OTHER TOTAL CLOUD ANALYSES

Additional analyses of the global distribution of total cloud cover have been discussed by Berlyand et al. (/13/) based primarily on surface observations, and Rossow (/14)) and Stows et al. (/12/) derived from satellite observations. The Berlyand et al. (/13/) data set combines various information sources including some satellite data and atlases based on cloud observations that, in some cases, date back to the early 1909s. The satellite data (Nimbus-7) cover the global distribution for single months (Jan 1980; Jul 1979). Our studies (see references above) have shown that interannual differences of latitudinal averages are generally small.

Comparison of the latitude variation of total cloud amount as derived from the present study, that of Berlyand et al. ( /13/) and that derived from Nimbus-7 observations, (/12/), are shown in Fig. 3(a) for January and Fig. 3(b) for July. As can be seen, the two different analyses from surface observations track each other quite well during both months. This is not at all surprising since there is strong overlap of the cloud data sets. The slightly lower cloud amounts, given by Berlyand et al. ( /13/) , are partly due to their inclusion of cloud data prior to 1950.

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C o m p a r i s o n of t he ave rage o b s e r v e d zona l d i s t r i b u t i o n o f t o t a l

c loud a m o u n t (%) , l and Jr Ocean , f rom di f fe ren t sources (see t e x t )

The total cloud distribution given by the Nimbus-7 data set infers a lower cloud amount than reported from surface observations at almost all latitudes. This difference is largest in the subtropics of each hemisphere (10-25%) and in polar regions in the summer. The large differences in the subtropics are probably due to the satellite underestimate of the presence of trade cumuli in those regions. As mentioned earlier, the differences during summer at polar latitudes probably reflect the satellite inability to discriminate adequately between low level clouds and clear skies in the presence of a cold underlying ocean surface and/or a surface of snow or sea ice. Values derived from the ISCCP retrievals do not show these large differences and, indeed, are reasonably close to those given by surface-based observations

~ ee, for instance,/12/). Note that at equatorial latitudes and subpolar latitudes of the winter Southern emisphere, the differences between surface-based and satellite derived cloud amounts are small.

The global total cloud cover (%) as derived from each of the data sets is:

J a n J u l y

Present study 62 61 Berlyand et al. (1980) 61 60

Stows et al. (1988) 51 52

Global Distribution of Observed Cloudiness (7)165

During each equivalent season (summer/winter), each study also shows that there is more cloud cover in the Southern Hemisphere as compared with the Northern Hemisphere.

Continued intercomparison among the different cloud observation techniques is obviously required to develop an improved global cloud climatology. However, it should be recognized that a part of the current differences stems from the different definition of clouds. It may be that somewhat different climatologies are needed in response to the different application requirements.

ACKNOWLEDGEMENTS

The work reported here was supported by the National Climate Program Office (NOAA) and the Carbon Dioxide Assessment Program of DOE under NOAA grant NA 80 AA-D-00030 and by NASA grant 2206- CL-229.

No te : The grid box cloud data that were used for the analyses published in the land and ocean atlases referred to in Warren et a l . ( / 8 / ; / 9 / ) are available on magnetic tape from the Data Support Section at NCAR, Boulder, CO 80307 and from the Carbon Dioxide Information Center (Department of Energy, Oak Ridge National Laboratory, Oak Ridge, TN 37831).

REFERENCES

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2. R. E. Dickinson, Land surface processes and climate--surface albedos and energy balance, Adv. in Geophys., 25, 305-353 (1983).

3. W. B. Rossow, F. Mosher, E. Kinsella, A. Arking, M. Desbois, E. Harrison, P. Minnis, E. Ruprecht, G. Seze, C. Simmer, and E. Smith, ISCCP cloud algorithm intercomparison, J. Clim. and Appl. Meteor., 24,877-903 (1985).

4. S. G. Warren, C. J. Hahn, and J. London, Analysis of Cloud Information from Surface Weather Reports, Report of the Workshop on Clouds in Climate II, 19-23 October 1987, 55-60 (1988a).

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7. S. D. Woodruff, R. J. Slutz, R. L. Jenne, and P. M. Steurer, A comprehensive ocean-atmosphere data set, Bull. Am. Meteor. Sac., 68, 1239-1250 (1987).

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10. C. J. Hahn, S. G. Warren, J. London, and R. L. Jenne, Climatological data for clouds over the globe from surface observations, CDIAC Numeric Data Collection, NDP-026), Oak Ridge National Lab., Oak Ridge, TN (1988).

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13. T. G. Beryland and L. A. Strokina, Zonal cloud distribution on the earth, Meteorologiya i Gidrologiya, No. 3, 15-33 (1980).

14. W. B. Rossow, International satellite cloud climatology project, Report of the Workshop on Clouds in Climate II, 19-23 October 1987, 3-9 (1988).