WMOD00176

• Project Name: Annual Report
• Title: Seeding Operations & Atmospheric Research, 2005 Annual Report
• Prepared By: Duncan Axisia
• Date: 12/31/2005
• Weather Modification - Doc Type: Report

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Evaluation requirements for cloud seeding
A very daunting task

Methods of evaluating cloud seeding operations

If one were able to predict precisely the
precipitation from a doud system. it would be a
simple matter to detect the effect of artificial doud
seeding on thaI system. The Wor1d
Meteorological Organization (WMO) keeps an
updated Statement on the Status of Weather
Modification for use by its member countries.
This statement is written by a WMO Committee
of Experts (with membership from the USA)
and approved by the Executive Committee of the
WMQ, The Statement dearly indicates that.
although many countries around the world are
involved in operational projects. evaluation of
doud seeding effectiveness using conventional
methods is not acceptable. The WMO (2001)
comments that the expected effects of seeding
are almost always within the range of natural
variability (low signal-to-noise ratio). "Comparison
of precipitation observed during seeded periods
with that during historical periods presents
problems because of dimatic 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 dimate change may lead to changes in
global precipitation amounts as well as to spatial
redistribution of precipitation." The WMO (2001)
recommends that whenever a statistical
evaluation is required with cases of very low
signal-ta-noise ratios, "experiment durations in
the range of five to over 10 years may be
required "

The definition of scientific proof

The evidence that is required to establish that a
doud seeding methodology is "scientifically

proven~ can be divided into two aspects, namely.
statistical and physical evidence. Statistical
evidence is usually obtained by an experiment
based on a seeding concept (Bruinljes, 1999).
This experiment has to be conducted and
evaluated in accordance with its original design
using acceptable statistical methods. This
statistical evidence IS required to detect the
seeding response as specified by the conceptual
model. Physical evidence constitutes the
measurement of key links in the chain of events
associated with the seeding conceptual model.
This physical evidence is required to establish
that !he positive effect of seeding has been
caused by the seeding intervention.

In addition. Silverman (2001) points out that
experiments should be reviewed critically using
the proof-of-concept criteria which emphasizes
the results of randomized statistical experiments
conducted and evaluated in accordance with the
a priori design. Failure to satisfy these criteria
does not connole that seeding is ineffective;
rather, it simply means that the evidence was
insufficient to establish that seeding worked as
hypothesized in the original design.

Hobbs (2001) adds the requirement of
independent duplication of results before
conduding that any partiOJlar cloud seeding
technique is effective. The author also states
that strong statistical and physical evidence,
replication. and independent confirmation, are
stricter than those generally required in
meteorological research. Hobbs (2001) further
states that: