Peter Best
Joint Director/owner with Dr Karen E Lunney of Cindual Pty Ltd, 1407/170 Grey Street, Brisbane, Queensland, Australia pbestcindual@gmail.com 61407786425BSc (Hons. 1st Class (Bristol), PhD (Monash))Commonwealth Scholarship and Fellowship Plan Award 1972-76Certificate in climate finance, UNEP 2010Adjunct Professorships at University of South Queensland and Queensland University of Technology Associate of Climate Planning Pty (http://www.climateplanning.com.au/ourpeople/)Most of Peter's career has focused on the evaluation of the impacts of extreme events, ranging from air pollution episodes, heat-wave impacts on energy demand generation and distribution, influences of climate variability and change on the characteristics of extreme events to the forecasting of imminent risks. In the past decade, Peter has become increasing involved in climate adaptation projects, in association with a university and two climate risk specialist companies. The industries covered in Peter's thirty years of consulting and research experience include power (generation, transmission, supply) and industrial processing of all types, intensive livestock, mining, cropping, waste processing and environmental management, renewable energy (especially wind resources), water resource planning and transport.In recent years, Peter and Karen have travelled extensively to the more remote locations of the world where climate and social change are occurring rapidly. Some of these experiences are captured in Karen's award-winning photography and in various documentary and children's books.
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Papers by Peter Best
agriculture, energy markets), high-impact extreme
events often result from the confluence of several
contributing causes and can herald major and sustained
changes in behaviour of the physical and socioeconomic
environments. They are often preceded by a
short window of “increased predictability” in an
otherwise essentially non-stationary environment.
This review of the characteristics of extremes
in weather-sensitive, agricultural systems addresses the
overlap of seasonal forecasting and alternative risk
transfer techniques, and the importance of information
content in climate histories. Estimated return periods
and measures such as probable maximum loss (PML)
play a critical role in reinsurance and risk assessments;
these procedures are often quite sensitive to the
statistical nature of the process (including the quasiperiodicities),
the dependence between variables
(especially for distribution tails) and the weaknesses
imposed by both short-term observation sets and the
realisation process from event precursors to measured
outcome.
Recent work on the necessary conditions for
agricultural extremes in Australia and elsewhere
suggests that various climate modes and indicators
(singly or in combination) can provide efficient
explanatory variables at various timescales and act as
suitable bases for seasonal or longer-term forewarning
of exceptional circumstances for vulnerable
communities.
The shortcomings caused by the paucity of
observations and the uncertainties in predictive
capacities may be partially overcome by using (a)
extended historical information (such as the forthcoming
20th Century Reanalysis products) in evaluations of
likely return periods and influences of internal climate
variability, (b) integration of past risk profiles with event
projections from climate models of “known” explanatory
powers and (c) better downscaling or higher resolution
outputs from baseline weather products, such as
historical reanalyses.
Just finding sufficient sets and time evolutions
of climate indicators should assist identifying transition
periods in various agricultural and energy regimes in
Australasia, aid seasonal forecasting of exceptional
circumstances in various sectors and promote a
common currency between insurers, farmers,
climatologists and other industries for developing
regional and global climate risk products.
agriculture, energy markets), high-impact extreme
events often result from the confluence of several
contributing causes and can herald major and sustained
changes in behaviour of the physical and socioeconomic
environments. They are often preceded by a
short window of “increased predictability” in an
otherwise essentially non-stationary environment.
This review of the characteristics of extremes
in weather-sensitive, agricultural systems addresses the
overlap of seasonal forecasting and alternative risk
transfer techniques, and the importance of information
content in climate histories. Estimated return periods
and measures such as probable maximum loss (PML)
play a critical role in reinsurance and risk assessments;
these procedures are often quite sensitive to the
statistical nature of the process (including the quasiperiodicities),
the dependence between variables
(especially for distribution tails) and the weaknesses
imposed by both short-term observation sets and the
realisation process from event precursors to measured
outcome.
Recent work on the necessary conditions for
agricultural extremes in Australia and elsewhere
suggests that various climate modes and indicators
(singly or in combination) can provide efficient
explanatory variables at various timescales and act as
suitable bases for seasonal or longer-term forewarning
of exceptional circumstances for vulnerable
communities.
The shortcomings caused by the paucity of
observations and the uncertainties in predictive
capacities may be partially overcome by using (a)
extended historical information (such as the forthcoming
20th Century Reanalysis products) in evaluations of
likely return periods and influences of internal climate
variability, (b) integration of past risk profiles with event
projections from climate models of “known” explanatory
powers and (c) better downscaling or higher resolution
outputs from baseline weather products, such as
historical reanalyses.
Just finding sufficient sets and time evolutions
of climate indicators should assist identifying transition
periods in various agricultural and energy regimes in
Australasia, aid seasonal forecasting of exceptional
circumstances in various sectors and promote a
common currency between insurers, farmers,
climatologists and other industries for developing
regional and global climate risk products.