203 / 218
[
] 201
Introduction
For thousands of years people have sought to modify
weather and climate so as to augment water resources and
mitigate severe weather. The modern technology of
weather modification was launched by the discovery in
the late 1940s that supercooled cloud droplets could be
converted to ice crystals by insertion of a cooling agent
such as dry ice or an artificial ice nucleus such as silver
iodide. Over 50 years of subsequent research have greatly
enhanced our knowledge about the microphysics, dynam-
ics and precipitation processes of natural clouds (rain,
hail, snow) and the impacts of human interventions on
those processes.
Currently, there are dozens of nations operating more
than 100 weather modification projects, particularly in arid
and semi-arid regions all over the world, where the lack of
sufficient water resources limits their ability to meet food,
fibre, and energy demands. The purpose of this document
is to present a review of the status of weather modification.
The energy involved in weather systems is so large that
it is impossible to create artificially rainstorms or to alter
wind patterns to bring water vapour into a region. The most
realistic approach to modifying weather is to take advan-
tage of microphysical sensitivities wherein a relatively small
human-induced disturbance in the system can substantially
alter the natural evolution of atmospheric processes.
The ability to influence cloud microstructures has been
demonstrated in the laboratory, simulated in numerical
models, and verified through physical measurements in
some natural systems such as fogs, layer clouds and
cumulus clouds. However, direct physical evidence that
precipitation, hail, lightning, or winds can be significantly
modified by artificial means is limited.
The complexity and variability of clouds result in great
difficulties in understanding and detecting the effects of
attempts to modify them artificially. As knowledge of cloud
physics and statistics and their application to weather
modification has increased, new assessment criteria have
evolved for evaluating cloud-seeding experiments. The
development of new equipment – such as aircraft plat-
forms with microphysical and air-motion measuring
systems, radar (including Doppler and polarization capa-
bility), satellites, microwave radiometers, wind profilers,
automated raingauge networks, mesoscale network
stations – has introduced a new dimension. Equally
important are the advances in computer systems that
permit large quantities of data to be processed. New
datasets, used in conjunction with increasingly sophisti-
cated numerical cloud models, help in testing various
weather modification hypotheses.
Chemical and chaff tracer studies help to identify airflow
in and out of clouds and the source of ice or hygroscopic
nucleation as the seeding agent. With some of these new
facilities, a better climatology of clouds and precipitation
can be prepared to test seeding hypotheses prior to the
commencement of weather modification projects.
If one were able to predict precisely the precipitation
from a cloud system, it would be a simple matter to detect
the effect of artificial cloud seeding on that system.
The expected effects of seeding, however, are almost
always within the range of natural variability (low signal-
to-noise ratio) and our ability to predict the natural
behaviour is still limited.
Comparison of precipitation observed during seeded
periods with that during historical periods presents prob-
lems because of climatic and other changes from one period
to another, and therefore is not a reliable technique. This
situation has been made even more difficult with the
mounting evidence that climate change may lead to changes
in global precipitation amounts as well as to spatial redis-
tribution of precipitation.
In currently accepted evaluation practice, randomisation
methods (target/control, crossover or single area) are
considered most reliable for detecting cloud-seeding effects.
Such randomized tests require a number of cases readily
calculated on the basis of the natural variability of the
precipitation and the magnitude of the expected effect. In
the case of very low signal-to-noise ratios, experiment dura-
tions in the range of five to over 10 years may be required.
Whenever a statistical evaluation is required to establish
that a significant change resulted from a given seeding activ-
ity, it must be accompanied by a physical evaluation to:
(a) Confirm that the statistically-observed change is likely
due to the seeding
(b) Determine the capabilities of the seeding method to
produce the desired effects under various conditions.
The effect of natural precipitation variability on the required
length of an experiment can be reduced through the
employment of physical predictors, which are effective in
WMO S
TATEMENT ON
W
EATHER MODIFICATION
(EC-LIII, 2001)
WMO statement on the status
of weather modification