8.10 Sources of Uncertainty and Levels of Confidence in Coupled Models
8.10.1 Uncertainties in Evaluating Coupled Models
Our attempts to evaluate coupled models have been limited by the lack of a
more comprehensive and systematic approach to the collection and analysis of
model output from well co-ordinated and well designed experiments. Important
gaps still remain in our ability to evaluate the natural variability of models
over the last several centuries. There are gaps in the specification of the
radiative forcing (especially the vertical profile) as well as gaps in proxy
palaeo-data necessary for the production of long time series of important variables
such as surface air temperature and precipitation.
In order to assist future coupled model evaluation exercises, we would strongly
encourage substantially expanded international programmes of systematic evaluation
and intercomparison of coupled models under standardised experimental conditions.
Such programmes should include a much more comprehensive and systematic system
of model analysis and diagnosis, and a Monte Carlo approach to model uncertainties
associated with parametrizations and initial conditions. The computing power
now available to most major modelling centres is such that an ambitious programme
that explores the differing direct responses of parametrizations (as well as
some indirect effects) is now quite feasible.
Further systematic and co-ordinated intercomparison of the impact of physical
parametrizations both on the ability to simulate the present climate (and its
variability) and on the transient climate response (and its variability) is
urgently needed.
The systematic analysis of extremes in coupled models remains considerably
underdeveloped. Use of systematic analysis techniques would greatly assist future
assessments.
It is important that in future model intercomparison projects the experimental
design and data management takes heed of the detailed requirements of diagnosticians
and the impacts community to ensure the widest possible participation in analysing
the performance of coupled models.
8.10.2 Levels of Confidence
We have chosen to use the following process in assigning confidence to our
assessment statements; the level of confidence we place in a particular finding
reflects both the degree of consensus amongst modellers and the quantity of
evidence that is available to support the finding. We prefer to use a qualitative
three-level classification system following a proposal by Moss and Schneider
(1999), where a finding can be considered:
“well established” - nearly all models behave the same way;
observations are consistent with nearly all models; systematic experiments conducted
with many models support the finding;
“evolving” - some models support the finding; different models
account for different aspects of the observations; different aspects of key
processes can be invoked to support the finding; limited experiments with some
models support the finding; parametrizations supporting the finding are incompletely
tested;
“speculative” - conceptually plausible idea that has only been
tried in one model or has very large uncertainties associated with it.
8.10.3 Assessment
In this chapter, we have evaluated a number of climate models of the types
used in Chapter 9. The information we have collected
gives an indication of the capability of coupled models in general and some
details of how individual coupled models have performed.
We regard the following as “well established”:
- Incremental improvements in the performance of coupled models have occurred
since the SAR, resulting from advances in the modelling of the oceans, atmosphere
and land surface, as well as improvements in the coupling of these components.
- Coupled models can provide credible simulations of both the annual mean
climate and the climatological seasonal cycle over broad continental scales
for most variables of interest for climate change. Clouds and humidity remain
sources of significant uncertainty but there have been incremental improvements
in simulations of these quantities.
- Some non-flux adjusted models are now able to maintain stable climatologies
of comparable quality to flux adjusted models.
- There is no systematic difference between flux adjusted and non-flux adjusted
models in the simulation of internal climate variability. This supports the
use of both types of model in detection and attribution of climate change.
- Several coupled models are able to reproduce the major trend in surface
air temperature, when driven by radiative forcing scenarios corresponding
to the 20th century. However, in these studies only idealised scenarios of
only sulphate radiative forcing have been used.
- Many atmospheric models are able to simulate an increase of the African
summer monsoon in response to insolation forcing for the Holocene but they
all underestimate this increase if vegetation feedbacks are ignored.
We regard the following as “evolving”:
- Coupled model simulation of phenomena such as monsoons and the NAO has improved
since the SAR.
- Analysis of, and confidence in, extreme events simulated within climate
models is emerging, particularly for storm tracks and storm frequency.
- The performance of coupled models in simulating ENSO has improved; however,
the region of maximum SST variability is displaced westward and its strength
is generally underestimated. When suitably initialised, some coupled models
have had a degree of success in predicting ENSO events.
- Models tend to underestimate natural climate variability derived from proxy
data over the last few centuries. This may be due to missing forcings, but
this needs to be explored more systematically, with a wider range of more
recent models.
- A reasonable simulation of a limited set of past climate states (over the
past 20,000 years) has been achieved using a range of climate models, enhancing
our confidence in using models to simulate climates different from the present
day.
- Our ability to increase confidence in the simulation of land surface quantities
in coupled models is limited by the need for significant advances in the simulation
of snow, liquid and frozen soil moisture (and their associated water and energy
fluxes).
- Coupled model simulations of the palaeo-monsoons produce better agreement
with proxy palaeo-data when vegetation feedbacks are taken into account; this
suggests that vegetation changes, both natural and anthropogenic, may need
to be incorporated into coupled models used for climate projections.
- Models have some skill in simulating ocean ventilation rates, which are
important in transient ocean heat uptake. However these processes are sensitive
to choice of ocean mixing parametrizations.
- Some coupled models now include improved sea-ice components, but they do
not yield systematic improvements in the sea-ice distributions. This may reflect
the impact of errors in the simulated near surface wind fields, which offsets
any improvement due to including sea-ice motion.
- Some coupled models produce good simulations of the large-scale heat transport
in the coupled atmosphere-ocean system. This appears to be an important factor
in achieving good model climatology without flux adjustment.
- The relative importance of increased resolution in coupled models remains
to be evaluated systematically but many models show benefits from increased
resolution.
- Our ability to make firmer statements regarding the minimum resolution (both
horizontal and vertical) required in the components of coupled models is limited
by the lack of systematic modelling studies.
We regard the following as “speculative”:
- Tropical vortices with some of the characteristics of “tropical cyclones”
may be simulated in high resolution atmospheric models but not yet in coupled
climate models. Considerable debate remains over their detailed interpretation
and behaviour.
- Some modelling studies suggest that adding forcings such as solar variability
and volcanic aerosols to greenhouse gases and the direct sulphate aerosol
effect improves the simulation of climate variability of the 20th century.
- Emerging modelling studies that add the indirect effect of aerosols and
of ozone changes to greenhouse gases and the direct sulphate aerosol effect
suggest that the direct aerosol effect may previously have been overestimated.
- Lack of knowledge of the vertical distribution of radiative forcing (especially
aerosol and ozone) is contributing to the discrepancies between models and
observations of the surface-troposphere temperature record.
Our overall assessment
Coupled models have evolved and improved significantly since the SAR. In general,
they provide credible simulations of climate, at least down to sub-continental
scales and over temporal scales from seasonal to decadal. The varying sets of
strengths and weaknesses that models display lead us to conclude that no single
model can be considered “best” and it is important to utilise results
from a range of coupled models. We consider coupled models, as a class, to be
suitable tools to provide useful projections of future climates.
