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Peter C. McIntosh
,
Andrew J. Ash
, and
Mark Stafford Smith

Abstract

The economic value of seasonal climate forecasting is assessed using a whole-of-chain analysis. The entire system, from sea surface temperature (SST) through pasture growth and animal production to economic and resource outcomes, is examined. A novel statistical forecast method is developed using the partial least squares spatial correlation technique with near-global SST. This method permits forecasts to be tailored for particular regions and industries. The method is used to forecast plant growth days rather than rainfall. Forecast skill is measured by performing a series of retrospective forecasts (hindcasts) over the previous century. The hindcasts are cross-validated to guard against the possibility of artificial skill, so there is no skill at predicting random time series. The hindcast skill is shown to be a good estimator of the true forecast skill obtained when only data from previous years are used in developing the forecast.

Forecasts of plant growth, reduced to three categories, are used in several agricultural examples in Australia. For the northeast Queensland grazing industry, the economic value of this forecast is shown to be greater than that of a Southern Oscillation index (SOI) based forecast and to match or exceed the value of a “perfect” category rainfall forecast. Reasons for the latter surprising result are given. Resource degradation, in this case measured by soil loss, is shown to remain insignificant despite increasing production from the land. Two further examples in Queensland, one for the cotton industry and one for wheat, are illustrated in less depth. The value of a forecast is again shown to match or exceed that obtained using the SOI, although further investigation of the decision-making responses to forecasts is needed to extract the maximum benefit for these industries.

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Sarah J. Doherty
,
Stephan Bojinski
,
Ann Henderson-Sellers
,
Kevin Noone
,
David Goodrich
,
Nathaniel L. Bindoff
,
John A. Church
,
Kathy A. Hibbard
,
Thomas R. Karl
,
Lucka Kajfez-Bogataj
,
Amanda H. Lynch
,
David E. Parker
,
I. Colin Prentice
,
Venkatachalam Ramaswamy
,
Roger W. Saunders
,
Mark Stafford Smith
,
Konrad Steffen
,
Thomas F. Stocker
,
Peter W. Thorne
,
Kevin E. Trenberth
,
Michel M. Verstraete
, and
Francis W. Zwiers

The Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC) concluded that global warming is “unequivocal” and that most of the observed increase since the mid-twentieth century is very likely due to the increase in anthropogenic greenhouse gas concentrations, with discernible human influences on ocean warming, continental-average temperatures, temperature extremes, wind patterns, and other physical and biological indicators, impacting both socioeconomic and ecological systems. It is now clear that we are committed to some level of global climate change, and it is imperative that this be considered when planning future climate research and observational strategies. The Global Climate Observing System program (GCOS), the World Climate Research Programme (WCRP), and the International Geosphere-Biosphere Programme (IGBP) therefore initiated a process to summarize the lessons learned through AR4 Working Groups I and II and to identify a set of high-priority modeling and observational needs. Two classes of recommendations emerged. First is the need to improve climate models, observational and climate monitoring systems, and our understanding of key processes. Second, the framework for climate research and observations must be extended to document impacts and to guide adaptation and mitigation efforts. Research and observational strategies specifically aimed at improving our ability to predict and understand impacts, adaptive capacity, and societal and ecosystem vulnerabilities will serve both purposes and are the subject of the specific recommendations made in this paper.

Full access
Richard L. Thoman
,
Matthew L. Druckenmiller
,
Twila A. Moon
,
L. M. Andreassen
,
E. Baker
,
Thomas J. Ballinger
,
Logan T. Berner
,
Germar H. Bernhard
,
Uma S. Bhatt
,
Jarle W. Bjerke
,
L.N. Boisvert
,
Jason E. Box
,
B. Brettschneider
,
D. Burgess
,
Amy H. Butler
,
John Cappelen
,
Hanne H. Christiansen
,
B. Decharme
,
C. Derksen
,
Dmitry Divine
,
D. S. Drozdov
,
Chereque A. Elias
,
Howard E. Epstein
,
Sinead L. Farrell
,
Robert S. Fausto
,
Xavier Fettweis
,
Vitali E. Fioletov
,
Bruce C. Forbes
,
Gerald V. Frost
,
Sebastian Gerland
,
Scott J. Goetz
,
Jens-Uwe Grooß
,
Christian Haas
,
Edward Hanna
,
-Bauer Inger Hanssen
,
M. M. P. D. Heijmans
,
Stefan Hendricks
,
Iolanda Ialongo
,
K. Isaksen
,
C. D. Jensen
,
Bjørn Johnsen
,
L. Kaleschke
,
A. L. Kholodov
,
Seong-Joong Kim
,
J. Kohler
,
Niels J. Korsgaard
,
Zachary Labe
,
Kaisa Lakkala
,
Mark J. Lara
,
Simon H. Lee
,
Bryant Loomis
,
B. Luks
,
K. Luojus
,
Matthew J. Macander
,
R. Í Magnússon
,
G. V. Malkova
,
Kenneth D. Mankoff
,
Gloria L. Manney
,
Walter N. Meier
,
Thomas Mote
,
Lawrence Mudryk
,
Rolf Müller
,
K. E. Nyland
,
James E. Overland
,
F. Pálsson
,
T. Park
,
C. L. Parker
,
Don Perovich
,
Alek Petty
,
Gareth K. Phoenix
,
J. E. Pinzon
,
Robert Ricker
,
Vladimir E. Romanovsky
,
S. P. Serbin
,
G. Sheffield
,
Nikolai I. Shiklomanov
,
Sharon L. Smith
,
K. M. Stafford
,
A. Steer
,
Dimitri A. Streletskiy
,
Tove Svendby
,
Marco Tedesco
,
L. Thomson
,
T. Thorsteinsson
,
X. Tian-Kunze
,
Mary-Louise Timmermans
,
Hans Tømmervik
,
Mark Tschudi
,
C. J. Tucker
,
Donald A. Walker
,
John E. Walsh
,
Muyin Wang
,
Melinda Webster
,
A. Wehrlé
,
Øyvind Winton
,
G. Wolken
,
K. Wood
,
B. Wouters
, and
D. Yang
Free access