Climatic Change (2010) 99:27–46
DOI 10.1007/s10584-009-9681-4
Objective probabilities about future climate
are a matter of opinion
Carlos Gay · Francisco Estrada
Received: 23 March 2007 / Accepted: 29 May 2009 / Published online: 8 October 2009
© Springer Science + Business Media B.V. 2009
Abstract In this paper, the unfeasibility of producing “objective” probabilistic cli-
mate change scenarios is discussed. Realizing that the knowledge of “true” probabil-
ities of the different scenarios and temperature changes is unachievable, the objective
must be to find the probabilities that are the most consistent with what our state of
knowledge and expert judgment are. Therefore, subjective information plays, and
should play, a crucial role. A new methodology, based on the Principle of Maximum
Entropy, is proposed for constructing probabilistic climate change scenarios when
only partial information is available. The objective is to produce relevant information
for decision-making according to different agents’ judgment and subjective beliefs.
These estimates have desirable properties such as: they are the least biased estimate
possible on the available information; maximize the uncertainty (entropy) subject to
the partial information that is given; The maximum entropy distribution assigns a
positive probability to every event that is not excluded by the given information;
no possibility is ignored. The probabilities obtained in this manner are the best
predictions possible with the state of knowledge and subjective information that
is available. This methodology allows distinguishing between reckless and cautious
positions regarding the climate change threat.
1 Introduction
Efficient use of economic resources to cope with global warming in terms of
adaptation, mitigation and impacts (remediation and avoidance) depends on the
C. Gay (
B
) · F. Estrada
Centro de Ciencias de la Atmósfera, UNAM, Ciudad Universitaria,
Circuito Exterior, 04510, Mexico, DF, Mexico
e-mail: cgay@servidor.unam.mx
F. Estrada
e-mail: feporrua@atmosfera.unam.mx