GREENHOUSE 2013 Adelaide, October 8 - 11

Climate change projections to support natural resource management planning

Penny Whetton, with acknowledgements to Aurel Moise, Jonas Bhend, Louise Wilson, Anthony Rafter, Leanne Webb, Ian Watterson, John Clarke, Tim Erwin, Marie Ekstrom, Kevin Hennessy & others

New projections in 2014 • New climate

model simulations

• Focus on serving the needs of natural resource management

• Department of Envirnment funded

• Mid 2014

NRM Planning

Impacts and adaptation

Climate projections

Supporting science

Regional NRM planning for Climate Change

Key elements of NRM projections project

Various emission scenarios and time slices out to 2100

Ranges of plausible changes for multiple variables with explanations about driving processes

Address a range of user needs •NRM planners •NRM impact

researchers •Eventually, every

one else?

Provide users with application-ready locally relevant data sets

Provide framework for existing (incl CMIP3) and future downscaled data sets from various sources

IPCC SPM (2013)

Latest global climate models being assessed for Australia: CMIP5 ensemble, as used in IPCC (2013)

Assessing Biases, seasonality, Variability models (e.g. ENSO), etc. • Most models do well (and

generally a little better than CMIP3)

• IPSL, (some) MIROCS, FGOALS,NorESM and the GISS models are potentially problematic

GCM regional evaluation: Assessment so far

Obs (AWAP) Models: Box&whiskers

Ackn: A. Moise, L. Wilson

Interim annual projected temperate change time series to 2090 for mid-range (RCP4.5; left) and high (RCP 8.5; right)

Understanding interim projection plots

Projected temperature: Rangelands cluster

Projected temperature: 2090, high emissions

Ackn. J. Bhend

Level of confidence in rainfall projections with warmer tones indicating rainfall decrease and cooler tones an increase in rainfall. The intensity of colour indicates the level of model agreement.

Direction of future rainfall change :CMIP5

Ackn: Ian Watterson

Precipitation projections (SW WA): CMIP5

observations

mm

per

mon

th

Perc

ent c

hang

e

Ackn. J. Bhend

| 12 |

Projected rainfall change: Rangelands

Ackn. J. Bhend

Ackn. J. Bhend

Winter- spring drying

Ackn. J. Bhend

Winter wetting

Ackn. J. Bhend

Winter-spring drying, some summer wetting

Ackn. J. Bhend

Summer: little change in many models, but large changes in some

Forming ranges of change from CMIP5 ensemble: Some issues to consider

• How to select simulations from the ensemble • Partitioning the ensemble • What is the effect of applying pattern scaling, if

applied? • Should we constrain the observations (effectively

weighting by historical performance)? – Climatological averages – Observed trends

Acknowledgment to Jonas Bhend

Ackn. Jonas Bhend

Forming ranges: summary points

• Most of the time differences between approaches are small

• However, resolution may be important in some smaller regions

• Constraining by model performance may have a significant effect in some cases

• But to generally adopt an approach other than the empirical distribution across all regions does not appear justified at this stage

Comparison with downscaled results (SDM method of Bertrand Timbal, BoM)

Projected changes to extremes

Wettest days (annual) Ackn: L Wilson, T. Rafter& J. Bhend

NRM 0813 | Louise Wilson & Tony Rafter 23 |

All days Wettest day (year) Wettest day (20 years)

Extreme wet days become wetter, even if average conditions don’t change

Warming of the hottest days: 2090, high emissions Ackn: L Wilson, T. Rafter& J. Bhend

NRM 0813 | Louise Wilson & Tony Rafter

All days Hottest day (year) Hottest day (20 years)

Hottest days get hotter Similar for cold nights

Mainly decrease

Under a high emissions scenario evapotranspiration is projected to increase in all seasons.

Solar radiation is expected to increase during winter, consistent with projected decline in rainfall.

Relative Humidity Potential Evapotranspiration Solar Radiation

Other variables: Some examples Rangelands

• Attended NRM meetings • Contribution to Element 2 project activities • Climate projection user panel

– Climate projection user interviews – Usage theme cluster meetings

• Interim projection statement • Data support and liaison

Assessing user needs

Response to user needs • Application-ready data and summary information in

various forms • Data for a wide variety of variables, such as

temperature and rainfall, will be made available in different formats

• Due to constraints on data availability for some variables, spatial detail will range from Cluster-average, to a 5 km grid-average, to specific sites

• Temporal detail will also depend on data availability, ranging from 20-year periods centred on 1995, 2030, 2050, 2070 and 2090, to annual, seasonal, monthly and daily time-series

• Data sets will be made available through a web portal

Model specific!

Application-ready data: Baseline climate + projected change

GCM and downscaled output (and other relevant science)

Can be developed and filtered for user needs

≠ Knowledge of plausible regional

change

Data sets for applications

Summary info versus application-ready data

Ranges of change Individual models

GCM and downscaled output (and other relevant science)

Can be developed and filtered for user needs

Knowledge of plausible regional

change

Data sets for applications

Context for

Summary info versus application-ready data

Ranges of change Individual models

GCM and downscaled output (and other relevant science)

Can be developed and filtered for user needs

Knowledge of plausible regional

change

Data sets for applications

Needs to be representative of

Summary info versus application-ready data

Ranges of change Individual models

Climate Futures software: A tool for developing a small set of individual model–based scenarios, tailored for decision making contexts

• Currently populated

with GCM cases only • Downscaled runs will

classified and available in this system too

• Will allow other climate model ensembles to be seen in the context of CMIP5 results

Acknowledgement to Tim Erwin and John Clarke

To conclude Many challenges presented by our NRM project responsibilities

• Getting the best we can out of CMIP5 • Identifying where downscaled data add value to the climate

change story • For technical users of the downscaled data sets (old and new),

making sure that they these data sets are set in the context of current understanding of regional climate change

Our developing approach • Keep things simple, unless additional complexity adds value • Plausible ranges versus representative applicable data sets • Organising application data sets based on descriptions of

future: Climate Futures • Completion by June 2014 and release sometime after that

Interim results so far, papers and reports to follow