CLOUD ANALYSIS - PART 7:
Cloud Types and Layer Structure


Cloud-Type Monthly Global Mean Deviations from Long-Term Global Mean

VIS-IR HIGH-LEVEL CLOUDS IR HIGH-LEVEL CLOUDS
VIS-IR High-Level Clouds (%) IR High-Level Clouds (%)
VIS-IR MIDDLE-LEVEL CLOUDS IR MIDDLE-LEVEL CLOUDS
VIS-IR Middle-Level Clouds (%) IR Middle-Level Clouds (%)
VIS-IR LOW-LEVEL CLOUDS IR LOW-LEVEL CLOUDS
VIS-IR Low-Level Clouds (%) IR Low-Level Clouds (%)

The figures above (solid lines) show the deviations of monthly averages from the average over the whole time record of the different cloud types as classified by the ISCCP (see diagram below). Please note that the plots also include the anomalies of monthly averages from each month's average over the whole time record (dashed lines) and that the plots available previously in this web page showed this latter anomaly set. The ISCCP cloud type deviations and anomalies have also been obtained for specific geographic regions separated into oceanic and continental areas, and the plots can be selected through the section below.

You may download the data (ascii format) contained in any of the diagrams available through the following browse section by visiting our download site at isccp.giss.nasa.gov/pub/data/D2CLOUDTYPES. See the README page for more details.

Select a variable:

Select a geographic region:

Clouds are generally produced by atmospheric motions with an upward component that cool the air; in some cases, particularly in the upper atmosphere and polar regions, radiative cooling can also cause clouds to form. The characteristics of these motions associated with different dynamical modes also produce specific cloud morphologies, the major distinction being between localized (small horizontal scales) vertical motions caused by hydrostatic instability producing cumuliform clouds and much larger scale wave motions from a variety of source producing stratiform clouds. Two key features that follow from these facts are that the vertical structure is particularly diagnostic of the motions producing the clouds and that all of the cloud properties are produced by the same event. Thus, understanding how the atmospheric circulation leads to the cloud properties observe, it is crucial to examine the correlated variations of cloud properties, especially their vertical structure (Rossow and Schiffer 1991, 1999).

The ISCCP datasets are obtained from passive measurements of radiation reflected and emitted by the clouds, so that they cannot provide information about the vertical distribution of cloud mass. However, they can show the correlated variations of cloud properties that are characteristic of different kinds of atmospheric motions and indicate the vertical distribution of cloud top locations. The distribution of cloud properties and their correlated variations is best illustrated from ISCCP by two-dimensional frequency distributions (histograms) of the cloud top pressure (PC) and visible optical thickness (TAU): the ISCCP dataset divides the PC and TAU range into nine basic categories as shown in the figure. The middle and low-level cloud types can also be separated into liquid and ice clouds. Each category is given a name that is one of the classical morphological cloud types; however, although the association implied appears to hold in a statistical sense, this relationship is not unique in a specific sense (Hahn et al. 2001).

ISCCP Cloud Types

ISCCP Cloud Types

CIRRUS CIRROSTRATUS DEEP CONVECTION
Cirrus (%) Cirrostratus (%) Deep Convection (%)
ALTOCUMULUS ALTOSTRATUS NIMBOSTRATUS
Altocumulus (%) Altostratus (%) Nimbostratus (%)
CUMULUS STRATOCUMULUS STRATUS
Cumulus (%) Stratocumulus (%) Stratus (%)

Next we provide the PC-TAU obtained from the ISCCP dataset for different geographic regions, separated into oceanic and continental areas and averaged over different time periods from single months to seasons to the whole year. The changing shape of these distributions provides another way to characterize climate regimes (cf. discussion in Rossow and Schiffer 1991). Comparing the schematic figure to these distributions shows the well-known tropical mixture of cirrus (high, thin), deep convective (high, thick) and low-level clouds, the dominance of low-level cloudiness in the subtropics and a mixture of clouds at all levels in midlatitudes. The polar region cloudiness is generally low and middle level but shows to concentrations of optical thickness; this distribution is distorted by the difficulties of retrieving cloud optical thickness over very bright snow and ice surfaces.

Later we will add two other cloud properties to these results, cloud particle size which indicates the microphysical behavior of the cloud (Han et al. 1994, 1999) and precipitation. Also we will add the results of the analysis of cloud vertical structures inferred from the vertical profiles of humidity measured by weather balloons (Wang et al. 2000).

A cluster analysis of the ISCCP DX dataset is used to identify all high cloud systems; then a tracking analysis is applied to determine the evolution of the larger convective systems. These data and a program to access them colocated with a specified location/date/time can be obtained from the ISCCP Convection Colocator.

Three new spacecraft missions are providing or will provide much more information about the vertical structure of clouds and precipitation. Currently, analyses are underway combining the TRMM (Simpson et al. 1988) precipitation radar profiles of precipitation with the ISCCP cloud observations for tropical convection. Later this decade the Calipso lidar mission will provide much more information about thin cirrus and boundary layer clouds and the CloudSat radar mission, especially in combination with ISCCP, will provide globally complete observations of the synoptic variations of cloud structure (Stephens et al. 2002).

Select a geographic region:

Select a time period:

If you chose Monthly Mean, enter YYMM here:

You may download the data (ascii format) contained in any of the diagrams available through this browse page by visiting our download site at isccp.giss.nasa.gov/pub/data/D1PCTAU. See the README page for more details.


References

Hahn, C.J., W.B. Rossow and S.G. Warren, 2001: ISCCP cloud properties associated with standard cloud types identified in individual surface observations. J. Climate, 14, 11-28.

Han, Q-Y., W.B. Rossow and A.A. Lacis, 1994: Near-global survey of effective cloud droplet radii in liquid water clouds using ISCCP data. J. Climate, 7, 465-497.

Han, Q., W.B. Rossow, J. Chou, K-S. Kuo and R.M. Welch, 1999: The effects of aspect ratio and surface roughness on satellite retrievals of ice-cloud properties. J. Quant. Spectrosc. Radiat. Trans., 63, 559-583.

Rossow, W.B., and R.A. Schiffer, 1991: ISCCP cloud data products. Bull. Amer. Meteor. Soc., 72, 2-20.

Rossow, W.B., and R.A. Schiffer, 1999: Advances in understanding clouds from ISCCP. Bull. Amer. Meteor. Soc., 80, 2261-2287.

Rossow, W.B., Y-C. Zhang, and J. Wang, 2005: A statistical model of cloud vertical structure based on reconciling cloud layer amounts inferred from satellites and radiosonde humidity profiles. J. Clim., 18, 3587-3605.

Simpson, J., R.F. Adler and G.R. North, 1988: A proposed Tropical Rainfall Measuring Mission (TRMM) satellite. Bull. Amer. Meteor. Soc., 69, 278-295.

Stephens, G.L., D.G. Vane, R.J. Boain, G.G. Mace, K. Sassen, Z. Wang, A.J. Illingworth, E.J. O'Conner, W.B. Rossow, S.L. Durden, S.D. Miller, R.T. Austin, A. Benedetti, C. Mitrescu and the CloudSat Science Team, 2002: The CloudSat mission and the A-train: A new dimension of space-based observations of clouds and precipitation. Bull. Amer. Meteor. Soc., 83, 1771-1790.

Wang, J., W.B. Rossow and Y-C. Zhang, 2000: Cloud vertical structure and its variations from a 20-year global rawinsonde dataset. J. Climate, 13, 3041-3056.


Cloud Vertical Structure

Further Reading


ISCCP New Algorithm


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