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 GREENHOUSE 2013 Adelaide, October 8-11
New projections in 2014 New climate model simulations Focus on serving the needs of natural resource management Department of Envirnment funded Mid 2014
Regional NRM planning for Climate Change NRM Planning Supporting science Impacts and adaptation Climate projections
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 applicationready locally relevant data sets Provide framework for existing (incl CMIP3) and future downscaled data sets from various sources
Latest global climate models being assessed for Australia: CMIP5 ensemble, as used in IPCC (2013) IPCC SPM (2013)
GCM regional evaluation: Assessment so far 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 Obs (AWAP) Models: Box&whiskers Ackn: A. Moise, L. Wilson
Projected temperature: Rangelands cluster 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: 2090, high emissions Ackn. J. Bhend
Direction of future rainfall change :CMIP5 Ackn: Ian Watterson 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.
Precipitation projections (SW WA): CMIP5 mm per month Percent change observations Ackn. J. Bhend
Projected rainfall change: Rangelands Ackn. J. Bhend 1 2
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 Ackn. J. Bhend
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 Extreme wet days become wetter, even if average conditions don t change Wettest day (20 years) Wettest day (year) All days 2 3 NRM 0813 Louise Wilson & Tony Rafter
Warming of the hottest days: 2090, high emissions Ackn: L Wilson, T. Rafter& J. Bhend Hottest days get hotter Similar for cold nights Hottest day (20 years) Hottest day (year) All days NRM 0813 Louise Wilson & Tony Rafter
Other variables: Some examples Rangelands Relative Humidity Potential Evapotranspiration Solar Radiation 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.
Assessing user needs 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
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 Clusteraverage, 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
Application-ready data: Baseline climate + projected change Model specific!
Summary info versus application-ready data GCM and downscaled output (and other relevant science) Can be developed and filtered for user needs Knowledge of plausible regional change Ranges of change Data sets for applications Individual models
Summary info versus application-ready data GCM and downscaled output (and other relevant science) Can be developed and filtered for user needs Knowledge of plausible regional change Ranges of change Context for Data sets for applications Individual models
Summary info versus application-ready data GCM and downscaled output (and other relevant science) Can be developed and filtered for user needs Knowledge of plausible regional change Ranges of change Needs to be representative of Data sets for applications 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