© Crown copyright Met Office Regional/local climate projections: present ability and future plans...

© Crown copyright Met Office

Regional/local climate projections: present ability and future plans

Research funded by

Richard Jones: WCRP workshop on regional climate, Lille, 14-16 June 2010


Outline – version 1

• Regional climate projections and predictions: present ability

• Detailed (spatially and temporally) climate projections: present ability

• Regional and detailed climate projections and predictions: future plans

• Expected outcomes of these plans and the resulting implications


Outline – version 2

• What we can say and why

• What we cannot say and why

• What we are planning next

• What will this (not) deliver


Regional climate projections and predictions: present ability

Large-area “average” indications of ranges of plausible (and in some cases “likely”, i.e. predicted) climate changes for all regions via e.g. CMIP3, other (ensemble) global models

• IPCC AR4 states that there will likely (or very likely) be :

• seasonal temperature increases in all regions

• sea-level rises in all regions

• seasonal precipitation changes (either increased or decreases) in many regions


Observed, simulated and projected temperature ranges with human and natural forcings

Significant “predicted” regional temperatures rises, “likely” ranges given by IPCC based on model responses to observed forcing etc.


Global to regional sea level rise ratio in 11 CMIP3 models

Regional sea-level rise - China


Temperature/precipitation changes: Asia, A1B emissions, 2090s, CMIP3

Figure 11.9

Significant high-latitude precip. increase via moister atmosphere;

West Asian dries via warming-driven lower relative humidity and surface drying in spring


Regional climate projections – what we can say and why

The following broad overview of likely sub-continental changes (i.e. a range of values in which the observed change is expected to lie), i.e.:

• seasonal temperature increases in all regions – we understand the processes and models respond correctly to observed forcings

• sea-level rises in all regions – likely range for global average from observations and process understanding with regional wider due to model-dependent variability in patterns

• seasonal precipitation in many regions – confident where we understand the processes and when the dominant ones are driven by warming


Detailed climate projections: present ability and limiting factors

Detailed temperature changes (including extremes) can often be inferred from the large-scale changes

Similarly, some detailed precipitation changes can be inferred but sampling issues often limit the information

Various factors, including climate variability and processes that are poorly understood or not represented, act to limit the information that can be obtained


Changes in Caribbean islands in global and regional models

ECHAM4 – B2

ECHAM4- A2 HADCM3 – A2

HADCM3 – B2

Pattern of change over the sea-surface is very different using different GCMs

Temperature changes over the islands are larger, more consistent and we are confident of the processes involved


The influence of internal variability

Changes in average intensity of top 5% of wet days, SRES A2, 2080s forecast with 3-member ensemble

• Many areas of significant change in each ensemble member

• Key point is not where change is significant but reliable

• Changes similar on large-scales

• Locally considerable differences between 3 realisations

Run 1, winter

Run 2, summer

Run 3, winter

Run 2, winter

Run 1, summer

Run 3, summer

-80 -40 -20 -10 -5 5 10 20 40 80Change (%)


Use signal to noise analysis for robust changes

• Can discern significant changes over much of Europe in winter and parts of Europe in summer

• Changes quantified with reasonable accuracy where |SNR|>, i.e. only in limited areas

• Robust change limited even in mean with 3-member ensemble and is less for extremes

Mean, winter

Top 5%, summer

Top 1%, winter

Top 5%, winter

Mean, summer

Top 1%, summer

-10 -5 -2 -1 0 1 2 5 10

Kennett, E. J., D. P. Rowell, R. G. Jones, and E. Buonomo, 2008: Robustness of future changes in local precipitation extremes. J. Climate, doi: 10.1175/2008JCLI2082.1.


Climate variability and information available from a climate projection

Single 30 year integrations can be insufficient to infer detailed changes in precipitation

With 3-member ensemble sampling top 5%, changes at grid box level discernible over much of Europe in winter, but less than half of Europe in summer

Changes quantified only in some northern European locations

More than 3x30yr ensemble integrations needed for significant local changes over large parts of Mediterranean in winter and central and eastern Europe in summer


Future precipitation: a regional example – the Indian monsoon

Changes over India are mostly large and positive, supported by physical insight


Top 5% precipitation change drivers – 3 member ensemble experiments

Winter

Summer

Percentage change in extreme precipitation for each mechanism

Warming Large-scale Soil moisture Total change


Some information on changes in top 5% daily precipitation intensity

Increases across much of Europe in winter are dominated by increasing atmospheric moisture in a warmer climate

The prediction of increased extreme precipitation for Europe as a whole in winter is reliable

At the regional scale (~1000 km or less) an enhanced increase or a decrease due to changing circulation patterns is possible.

In summer there are competing processes which tend to respectively enhance and reduce precipitation


Contributions to the ranges in projected winter precipitation changes for 2070-99 relative to 1961-90 at selected 25km grid squares in an ensemble global/regional projection.

Internal variability, carbon cycle, downscaling, account for ~50%, i.e. not accounting for these reduces range of change around projected or likely value by factor of 2

Factors influencing ranges of local precipitation projections


Detailed climate projections – what we cannot say and why

Regional patterns of changes, even in the mean, for a given decade or thirty-year period under transient climate change are affected by sampling (only small areas of change in precipitation quantified with a 3x30y sample) – and the situation is worse for extremes

Spatially and temporally detailed changes are often unclear because they results from:

(a) processes we are uncertain about, e.g. large-scale circulation changes,

(b) a combination of processes which we cannot quantify or do not represent


What we are planning next

CMIP5 will deliver, for centennial projections, an increase in the processes simulated and more models with higher resolution

CMIP5 will deliver ensemble decadal projections initialised from the observed state of the system including 30-year projections from 2005

CORDEX is providing a framework for, and will deliver for Africa, coordinated downscaling of the CMIP5 centennial projections using the rcp4.5 and rcp8.5 concentration scenarios


CMIP5 Experiments


What this will (not) deliver

A broad picture of sub-continental changes likely to lie in given ranges (similar to those in AR4) from the CMIP5 GCMs

This information on changes will include more spatial detail and a greater range of processes and thus provide a more realistic range of possible outcomes around the likely value

The CMIP5 30-year initialised ensembles should provide reasonable sampling of patterns of near-term projected climate change where downscaling would not add information

CORDEX will further enhance the realism of ranges around likely centennial climate changes for Africa

Little additional information will be provided on other aspects of detailed climate change


Conclusions

To provide information on detailed patterns of even mean climate change for periods under transient climate change requires sample-sizes that can only be derived from ensembles

Even with ensemble sampling, uncertain aspects of climate change such as possible circulation change or the magnitude of competing processes (even if we have confidence in their sign of change) will limit what we can say with confidence on detailed climate change

AR5 is likely to improve on the picture of area-averaged regional climate change providing some increases in spatial detail and more realistic range of possible outcomes around the likely value (from including more processes) and, for the near term, ensemble 30-year initialised projections – but little will be provided on other aspects of detailed climate change

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