Policy implications of uncertainties related to climate change
Submitting Institution
University of DurhamUnit of Assessment
Mathematical SciencesSummary Impact Type
EnvironmentalResearch Subject Area(s)
Mathematical Sciences: Statistics
Summary of the impact
The Climate Change Act, 2008, constructed a legally-binding long-term
framework for the UK to cut greenhouse gas emissions and a framework for
building the UK's ability to adapt to a changing climate. The Act requires
a UK-wide climate change risk assessment (CCRA) that must take place every
five years and a national adaptation programme (NAP), setting out the
Government's objectives, proposals and policies for responding to the
risks identified in the CCRA. The CCRA, and thus the NAP, drew heavily on
the uncertainty analysis for future climate outcomes, published in 2009 by
the Met Office as the UK Climate Projections UKCP09, which in turn drew
heavily on research into the Bayesian analysis of uncertainty for physical
systems modelled by computer simulators carried out at Durham University.
A wide range of industries and public sector organisations likely to be
affected by climate change have consulted with the Met Office on UKCP09 to
inform decisions on policy and investment, involving billions of pounds,
in sectors as diverse as flood defence, transport, energy supply and
tourism.
Underpinning research
The Durham statistics group has developed a very general probabilistic
framework for linking one or several mathematical models to the physical
systems that the models purport to represent, taking account of all
sources of uncertainty, including model and simulator imperfections. This
framework is a necessary precondition for making probabilistic statements
about the system on the basis of historical observations and evaluations
of the computer simulators. The formulation distinguishes simulators
according to their quality and the nature of their inputs. Further
modelling constructs are introduced to account for imperfections in the
available simulators and, within the framework of Bayesian graphical
modelling, to unify the composite inference, from the collection of
available simulators, observed historical data and the judgements of
experts, for the behaviour of the actual physical system. The work [1]
in section 3 is quite general, but the group did have in mind the
application to collections of evaluations of climate models in this
development and part of the research is the paper [2] making this
connection explicit. The research led to a very general formalism [3]
for relating models to physical systems.
The particular work leading to the climate-related impacts in this case
study was carried out over the period 2001-2006 by Michael Goldstein,
permanent member of staff, and Jonathan Rougier, PDRA. Dr Rougier left
Durham at the end of 2006 and took up a lectureship at the University of
Bristol.
References to the research
The basic work that summarises, formalises and generalises all of the
preceding work in Durham on uncertainty in physical systems represented by
computer models, and with which this impact case is directly concerned, is
contained in the paper
[1] Goldstein, M & Rougier, J (2004) Probabilistic
formulations for transferring inferences from mathematical models to
physical systems, Siam J. Sci Comput., 26, 467-487,
doi:10.1137/S106482750342670X.
The paper [1] has been well referenced and its practical value
can be judged by the role that it has played in areas such as climate
science, as will be discussed in the next section. This paper forms a part
of the ongoing exploration at Durham of the question, of fundamental
interest in all areas of science and technology, as to what is the actual
information about a physical system that is conveyed by one or more models
for that system, and how can that information be uncovered and exploited
for better understanding of the behaviour of the system. It provided the
core ideas for much further development of that theme at Durham; in
particular, Dr Rougier, while at Durham, wrote a paper which applied its
formulation directly to the problem of climate inference, namely
[2] Rougier, J.C. (2007), Probabilistic inference for future
climate using an ensemble of climate model evaluations, Climatic
Change, 81, 247-264, doi:10.1007/s10584-006-9156-9
and Goldstein and Rougier wrote the first draft of the general conceptual
paper which extended the formulation and eventually appeared as
[3] Goldstein M and Rougier J.C. (2009), Reified Bayesian
modelling and inference for physical systems, Journal of Statistical
Planning and Inference, 139, 1221-1239,
doi:10.1016/j.jspi.2008.07.019
which was chosen as the first ever discussion paper in that journal.
During the period of this research, Dr Rougier was funded by the
following grants:
The probability of rapid climate change (01/01/2004 - 31/12/2006)
Funder: NERC; grant value: £173 074.68
Uncertainties integrated assessment process (01/09/2002 -
31/08/2005)
Funder: Tyndall Centre; grant value: £13 606.40
Details of the impact
There were regular discussions on probabilistic climate projection, from
2002, between members of the Durham Statistics group and individuals with
responsibility for uncertainty analysis in climate projections in the Met
Office Hadley Centre. Therefore, there was general familiarity with our
approach, in which Dr. Rougier consulted closely with the Hadley Centre.
By this route, the Durham research into Bayesian modelling became a
central methodological component of the UK Climate Projections 2009
(UKCP09), the Met Office's climate analysis tool for the UK for the 21st
century, funded by DEFRA. The science and methodology used to construct
UKCP09 is described in detail in the 200 page report1, from the
Met office. The report 1 emphasises the importance of the
careful treatment of uncertainty in the climate projections. Here is an
indicative quotation from the introduction:
"Uncertainty in climate change projections is a major problem for those
planning to adapt to a changing climate. Adapting to a smaller change than
that which actually occurs (or one of the wrong sign) could result in
costly impacts and endanger lives, yet adapting to too large a change (or,
again, one of the wrong sign), could waste money. In addition there is the
risk of maladaptation — adapting to climate change in a way that prevents
or inhibits future adaptation. The 2008 projections are the first from
UKCIP to be designed to treat uncertainties explicitly ... This means that
probabilities are attached to different climate change outcomes, giving
more information to planners and decision makers." [page 19]
The methods developed at Durham play an important role in the uncertainty
analysis throughout the report. Here are some indicative quotes from the
report (all references to Goldstein and Rougier (2004) and Rougier (2007)
refer to papers [1] and [2] cited in the preceding
section).
"These results are then incorporated into our uncertainty analysis, based
on a statistical framework devised by Goldstein and Rougier (2004),
discussed in Chapter 3. This allows us to create a probability
distribution function accounting for uncertainties arising from both model
parameters and structural errors, and constrained by observations," [page
39]
"The method is based on a general statistical framework for the
derivation of probabilistic projections of real systems from simulations
carried out using complex but imperfect models of those systems (Goldstein
and Rougier, 2004; Rougier, 2007)." [page 49]
"Our ensemble projections are converted into probabilistic projections
using a Bayesian statistical framework developed to support inference of
future information about real systems from complex but imperfect models
(Goldstein and Rougier, 2004; Rougier, 2007). This process allows our
projections to be constrained by a set of observations of past climate
(Section 3.2.9), and also involves the use of expert judgements ... The
probabilities which emerge from this approach represent the relative
credibility of a family of different possible outcomes, taking into
account our understanding of physics, chemistry, biology, observational
evidence, and expert judgement." [page 82]
The contribution of the Durham approach to UKCP09 is amplified in a paper2
by several of the authors involved with that uncertainty analysis, which
explains in detail the uncertainty methodology used by UKCP09. For
example, section 3 of the paper, "Outline of the calculations", begins
"Here we describe the general steps in Goldstein and Rougier (2004)
necessary to determine a probability distribution of some aspects of
climate change that we want to predict." Similarly, the final subsection,
section 6.2 begins "... Goldstein and Rougier (2004) gives us several key
advantages. ...First, the multivariate nature of this probabilistic
framework allows us to have more than one prediction variable. Predicting
joint probabilities provides us with important information on how
uncertainty is related across different climate variables..."
UKCP09 plays a key role within the Government's statutory
responsibilities for assessing and responding to climate change. The
Climate Change Act 2008 constructed a legally-binding long-term framework
for the UK to cut greenhouse gas emissions and a framework for building
the UK's ability to adapt to a changing climate. The Act requires a
UK-wide climate change risk assessment (CCRA) that must take place every
five years and a national adaptation programme (NAP), setting out the
Government's objectives, proposals and policies for responding to the
risks identified in the CCRA. The CCRA, and thus the NAP, drew heavily on
the uncertainty analysis in UKCP09. The purpose of CCRA and the role of
UKCP09 are indicated by the following two quotes from the Evidence Report3:
"The UK Climate Change Act (CCA) 2008 makes the UK the first country in
the world to have a legally binding, long-term framework to cut carbon
emissions. It also requires a series of assessments of the risks of
climate for the UK, under both current conditions and over the long term,
to 2100. The CCRA provides the first of these assessments and was laid
before parliament in January 2012." [page V]
"The CCRA makes use of the UKCP09 climate projections that represent a
range of possible future changes in UK climate. The range of possibilities
is necessarily wide to take account of uncertainties in natural climate
variability, how the UK's climate may respond to global warming, the
future trajectory of emissions, and how these might magnify any regional
climate change effects." [page 9]
The CCRA constructed sector reports describing a wide range of potential
risks in each of the following sectors (followed by a more detailed
analysis of selected risks that were judged to be the most important):
Agriculture; Biodiversity & Ecosystem Services; Built Environment;
Business, Industry & Services; Energy; Floods & Coastal Erosion;
Forestry; Health; Marine & Fisheries; Transport; Water. The CCRA used
the UK Climate Projections (UKCP09) for three time periods — 30-year
periods centred on the 2020s, 2050s and 2080s. The CCRA attempted to
monetise the most important risks to the UK, and concluded that the
results indicated that the net economic costs to the UK are of the order
of tens of billions/year by the 2050s (in current prices) even for the
middle of the uncertainty range for these costs at the middle of the
projected emission scenarios (see the Scoping Study4, page 6,
which suggests that this figure is an underestimate).
The CCRA is constructed to facilitate the Climate Change Act mandated
National Adaptation Programme (NAP, 2013). The NAP report5
(laid before Parliament in 2013) explains:
"The Climate Change Risk Assessment 2012 (CCRA) for the UK brought
together the best available evidence, using a consistent framework to
identify the risks and opportunities related to climate change. The
assessment distilled approximately 700 potential risks down to more than
100 for detailed review. The government's response to the CCRA, which
meets the requirements laid down in the Climate Change Act 2008, is the
first NAP. In developing the NAP for England, we have taken the highest
order risks from the CCRA and working in partnership with businesses,
local government and other organisations, have developed objectives,
policies and proposals to address them." [page 8]
In addition to its statutory role, the Met Office has worked with a wide
range of public and private sector organisations to use UKCP09 to inform
decisions on investment amounting to billions of pounds to 'future proof'
projects against climate change. On the UKCP09 website (http://ukclimateprojections.defra.gov.uk)
there is a link to a Case Studies web-page6, which states
"Working with our stakeholders, we have put together a number of case
studies to show how UKCP09 data can be used." As of 17/10/13, these
included case studies with Councils for Devon, Hampshire, Kent, Milton
Keynes and Oxford City, and organisations including Atkins/UKWIR, CEH,
Environment Agency/Acclimatise /JBA consulting, Macaulay Institute, United
Sustainable Energy Agency, Proclimation, Prometheus, Royal Haskoning,
Severn Trent Water, South West Tourism. Each case study describes how the
UKCP09 products were used, and how the results would be communicated to
the target audience. The range of topics covered includes: national
assessment of river flows, climate change and pollution at water courses
in Birmingham, strategic planning for flood management, changes in flood
damages at a catchment scale, assessments of storm surge and sea level
rise, emergency planning, defining land capability for agriculture
specifications, assessing potential vulnerabilities to climate change,
future proofing design decisions in the buildings sector, investigating
coastal recession & shore profile development, storm surge and sea
level rise and assessing impacts of climate change on tourism in South
West England.
Sources to corroborate the impact
- Murphy JM, Sexton DMH, Jenkins GJ, Booth BBB, Brown CC, Clark RT,
Collins M, Harris GR, Kendon EJ, Betts RA, Brown SJ, Humphrey KA,
McCarthy MP, McDonald RE, Stephens A, Wallace C, Warren R, Wilby R, Wood
RA (2009) UK climate projections science report: climate projections,
Met Office Hadley Centre, Exeter, available from
http://ukclimateprojections.defra.gov.uk/22544
- Sexton DMH, Murphy JM, Collins M, Webb MJ (2012) Multivariate
probabilistic projections using imperfect climate models part 1:
outline of methodology, Climate Dynamics, 38, 2513-2542,
doi:10.1007/s00382-011-1208-9.
-
The UK Climate Change Risk Assessment 2012, Evidence Report,
DEFRA 2012.
-
Scoping Study: Reviewing the Coverage of Economic Impacts in the
CCRA, Report to the Committee on Climate Change, Adaptation
Sub-Committee, Paul Watkiss Associates, 2009.
-
The National Adaptation Programme, Making the country resilient to
a changing climate, July 2013, available at https://www.gov.uk/government/publications/adapting-to-climate-change-
national-adaptation-programme.
- UKCP09 Case Studies webpage http://ukclimateprojections.defra.gov.uk/23081
(accessed 17/10/2013).