Andrew Glen
Summary 1 - Cloud Climatologies
Cloud climatology information is needed for various reasons and is of importance in the
scientific community. For climate modelers and scientists, clouds have a very important impact
due to their relationship with greenhouse gasses, the global radiation balance and aerosols. These
relationships can ultimately change the global average surface temperature, but are also involved
in feedback loops which can help reinforce or negate the processes that modify the temperature
change. Clouds are very difficult to predict and quantify due to their high variability in terms of
thickness, size, life time, growth rates, altitude and composition. Cloud formation can be
enhanced or suppressed by local conditions such as orography or urban structures. With so many
variables involved in clouds they can be very difficult to include in numerical simulations for
everyday weather prediction or long term climate studies, and are often parameterized in one
area or another.
Cloud Types
There are 10 genera and species of cloud (see table 1), all with their own peculiarities and
structures. Some clouds form at low altitude and are stratified into wide flat structures such as
stratus. Others ‘bubble’ upwards to form the ‘fair weather’ cumulus clouds, or if strong deep
convection occurs, a cumulonimbus cloud may appear. The cumulonimbus is often the full depth
of the troposphere as strong convection drives air flow within the cloud up to the much colder
upper levels. At such levels a ‘wispy’ cirrus cloud may form.
Table 1. The 10 Genera of cloud types. WMO (1956)
Cloud Observations
Global cloud climatologies can be derived from two sources, surface observations and
satellite observations. Surface observations of clouds are routine for most meteorological
networks, the UK has possibly the longest record of observations since 1659, in the Central
England Temperature (CET) data set. Cloud observations are point observations when taken
from the ground. The observer therefore runs the risk of overestimating cloud amount by
counting the sides as well as the base of a cloud in their observations, see figure 1. Identification
of high level cloud also becomes problematic when the low level cloud blocks the observation.
Ground observations made by a trained observer give more accurate information regarding the
cloud type.
Figure 1. Line of sight observations of clouds from a single point. Hughes (1984)
The spatial resolution of ground observation sites is far from uniform, with very poor coverage
over oceans and in countries which have under developed meteorological networks.
Satellite observations
Remote sensing methods involve the measurement of the spectral distribution and
intensity of radiation that is emitted from the atmosphere and surface. There are currently several
wavelengths that satellites are sensitive to, including visible at 0.65µm, water vapour at 6.7µm
and thermal Infra-Red at 11µm. Combinations of more than one satellite channel can lead to
products which identify other cloud properties and the use of multisensor systems such as
QPESUMS can determine rain rates. Satellite observations allow for global coverage with high
temporal resolution in the case of geostationary satellites or high spatial resolution from polar
earth orbit satellites. Polar orbiting satellites observed the entire earth over a day, with
approximately 14 revolutions around the earth a day. Each revolution moves the satellite swath
further as the earth rotates beneath the satellite. This means that a polar orbiting satellite passes
over the same location on the equator at approximately the same time everyday. A geostationary
satellite maintains an orbit above a fixed longitude and can only observe one hemisphere of the
earth, which appears as a disc. Satellites give a more accurate cloud cover measurement, as they
can objectively define the cloud amount over an area, however the cloud type is harder to
estimate from satellite observations. The issue of sub pixel sized clouds is also a problem for
satellite observations, as they will not be resolved by the instrument.
The first satellite estimate of global cloud climatology became available in the early
1960s. Estimates of cloud cover can be obtained from measurements of incoming and absorbed
solar radiation over an area, this is done by calculating the albedo of the cloud and that of the
surface in a clear sky situation. Albedo is defined as “the reflective power, or the fraction of
incident light that is reflected by a surface or body.” (Bean & Somerville, 1981) The albedo can
then be obtained from equation 1.
A=
( Iin − I ab )
I in
Equation 1.
Where Iin is the amount of incoming solar radiation
Iab is the amount of absorbed solar radiation
In a clear sky situation the albedo of the surface is determined, this value can range from 5% for
deep oceans to 90% for fresh clean snow, see Table 2.
Table 2. Albedo values for various surfaces, Hartmann (1994)
When calculating cloud cover by comparing differing radiances at a location, a minimum
value of the albedo must be found which is then assumed to be the clear sky surface albedo. This
value will depend on location and time of year, as surface coverage is affected by growing
seasons, water coverage or saturation of soils. Once the minimum albedo value is established,
and a measurement of albedo is made then the fractional cloud cover can be found using
equation 2, assuming a value for the reflectance of the cloud.
x=
( A − Amin )
( r − Amin )
Equation 2
Where x is the fraction of cloud cover
A is an observed albedo value
r is the assumed reflectance
Amin is the clear sky surface albedo
There are many satellites in orbit with different instruments for measuring clouds and
their properties. The Advanced Very High Resolution Radiometer (AVHRR) measures multiple
wavelengths with 6 channels. Each wavelength band is specific to a feature, from daytime cloud
and surface mapping, to snow and ice detection. Tiros Operational Vertical Sounder (TOVS) has
a microwave sounding unit, and a stratospheric sounding unit which uses thermal infrared. Cloud
masks can be used to improve the cloud cover estimation and gather information on cloudiness.
The Stratospheric Aerosol and Gas Experiment (SAGE) uses a limb viewing from a satellite to
measure aerosols and gasses in the stratosphere. The instrument looks through the atmosphere at
an angle towards the sun or moon. The data it collects is therefore from a number of layers
through the atmosphere, and various altitudes for each different layer. This allows for the
measurement of thin high clouds which are relatively transmissive in vertical, to be observed at a
horizontal angle through the layer.
Cloud Climatologies
Clouds have been indicated as a major contributor to global brightening since the early
1990’s as discussed in Wild et al (2005). Changes in the solar radiation reaching the surface will
have consequential effects on local and global scales, from changes in plant growing seasons to
the hydrological cycle. Clouds are the most important factor in controlling the radiation balance,
with different cloud types reflecting different amounts of solar radiation, or absorbing different
amounts of thermal infrared radiation. Warren et al, 1985 discusses the occurrence and-co
occurrence of cloud cover. Figure 2 shows the zonal, annual average frequency of occurrence of
each of the cloud types shown in table 1, for clear sky, and for sky obscured due to fog, over land
and ocean. Frequency of occurrence is defined by Warren et al, (1985) as the fraction of weather
observations in which a cloud type was reported present, given that it was possible to see
whether it was present, irrespective of the fraction of the sky actually covered by that cloud.
Figure 2. Zonal, annual average frequency of occurrence of each cloud type, for clear sky, and
for sky obscured due to fog, over land and ocean parts of each zone. The points are averaged
over all seasons, with resolution of 10˚ over land and 15˚ of oceans. Gaps appear in most of the
plotted values for land at 40˚-60˚S because the small amount of land there often resulted in
unrepresentative or meaningless zonal averages. Warren et al (1985)
The northern hemisphere mid latitude belt appears to be an area of high cloud cover with
maximums in cirro and strato genera clouds. The ITCZ is clearly visible in the cirro and alto
genera clouds over land, and cumulus, cumulonimbus over both land and ocean. From ISCCP,
SOBS and METEOR data the global annual average cloud cover is 62.6 % and this has a net
effect of increasing surface albedo by 15-30%. However there are errors associated with all
measurements. The ISCCP measurements have a bias in the temperature retrieval of <2K with
additional random errors for land or ocean surfaces, 4K and 2K respectively. The surface
reflectance used to calculate albedo are within 3-5% of other measurements over land or ocean.
Cloud climatologies are an important factor in the climate system, and are worthy of
continued observations and modeling. The role of clouds is complex and dynamic and will be a
continuing source of interest as the earth experiences changes in climate due to natural variations
and anthropogenic sources. The use of satellites to observe cloud systems will only increase, but
the usefulness of surface observations must not be forgotten.
References:
Bean, S. J., Somerville, P. N., 1981: Some New Worldwide Cloud Cover Models
J. Appl. Meteor. 3, 223-228
Hartmann, D., L., 1994, Global Physical Climatology, Academic Press
Hughes, N. A., 1984, Global Cloud Climatologies: A Historical Review. J. Clim. Appl. Meteor.,
23, 724-751
New, M., Hulme, M., and Jones, P., 1991: Representing twentieth-century space-time climate
Variability. Part I Development of a 1961-90 mean monthly terrestrial climatology. J.
Clim. 12, 829-856
Warren, S. G., Hahn, C. J., and London, J., 1985: Simultaneous Occurrence of Different Cloud
Types. J. Clim. Appl. Meteor., 658-667
Wild et al., 2005, From dimming to brightening: Decadal changes in solar radiation at Earth’s
surface. Science., 308, 847-854
WMO., 1956, International Cloud Atlas: Abridged Atlas., 1, 7