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Abha Sood Brett Mullan , Stephen Stuart & Sam Dean Climate Variability Group, NIWA, Wellington

Towards determining ‘ reliable ’ 21st century precipitation and temperature change signal from IPCC CMIP3 climate simulations. Abha Sood Brett Mullan , Stephen Stuart & Sam Dean Climate Variability Group, NIWA, Wellington. Task:.

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Abha Sood Brett Mullan , Stephen Stuart & Sam Dean Climate Variability Group, NIWA, Wellington

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  1. Towards determining ‘reliable’ 21st century precipitation and temperature change signal from IPCC CMIP3 climate simulations AbhaSood Brett Mullan, Stephen Stuart & Sam Dean Climate Variability Group, NIWA, Wellington

  2. Task: To quantify 21st century regional PrecipitationandTemperatureclimate change signal for end usersin agriculture, industry, government, … Consistency and predictability & Accuracy and Reliability Model Credibility Can this be achieved?

  3. Some problems!! Start from the beginning! Change in December-February precipitation (in %), between 1971-2000 and 2071-2099, under an A2 emission scenario

  4. The Experiment SST forcing, DJF, 1971-2000 (20cL) ‘Warm’ Control ‘Warm’ - Control -1.8°C cutoff in SST -1.7°C cutoff in SST

  5. Results: MSLP MSLP Changes , DJF, 21cL-20cL Control ‘Warm’ ‘Warm’ - Control More blocking - but not as much as Ctl More blocking

  6. Consistency and predictability • . . . • is realized in models based on physical principles • all components of climate system are represented • tuning models is restricted • more advanced model include crucial chemical and biological processes • Advances are achieved by • iteratively improving representation of climate relevant processes in all components of climate models guided by advances in understanding of • climate dynamics, • feedback mechanisms, • representation of climate states for initialization, • drivers of climate change

  7. Accuracy and reliability • . . . • is realized in models by • evaluating the ability of reconstructing pertinent features of recent climate and wide range of past climates • more information allow probabilistic approach which leads to decrease in uncertainty and ultimately to ‘narrowing’ of the confidence levels • - advances achieved by • sample CMIP3/5 model subset based on model performance over the region of interest • removing known biases in forcing fields (egSST,SIC) and in projected climate data Caution: Future climate may still stray beyond IPCC projection some estimates may be too conservative

  8. Approach: • Multi-Model Ensemble (MME): • - more information reduces uncertainties • - identification and quantification of modes of internal variability • - determine extremes • Model Evaluation and Bias Correction (BC): • - ‘realistic’ input for climate impact studies and risk evaluation • - helps reveal key model errors • Model Improvement: • - remove obvious forcing errors (SST, Sea Ice) • - atmosphere ocean coupling at the marginal sea ice zone, • - marine boundary layer clouds, • - atmospheric chemistry, ♦ ♦ ♦

  9. incomplete information based on limited ensemble based on prior knowledge of the system also Validation and Verification

  10. CMIP3 - IPCC 20cL: 1971-2000 21cN: 2011-2040 21cM: 2041-2070 21cL: 2071-2099 Mullan, Dean (2008) • upper and lower bounds, ‘middle of road’ of SRES emission scenarios • multidecadal ocean variability and initial ocean/climate state • perturbations of SST forcing • Selection of CMIP3 models • bias correction of SST forcing

  11. Regional Modelling & Physical Impacts Climate Change Studies GCM 1 Bias-Correction & Downscaling Downstream Models: River Snow Glacier Regional Climate Model GCM 2 GCM 3 Statistical Downscaling Emission Scenarios Climate Change Studies Climate Change Studies GCM x Present, Future, Paleo

  12. A2 SST-BC forcing: revised, 20cL DJF 20cL: 1971-2000 21cL: 2071-2099

  13. Validation:1972-2000 (VCSN) reanalysis driven DJF JJA Bias correction increases variability and corrects mean

  14. A2 SST-BC forcing: revised, 21cL - 20cL DJF 20cL: 1971-2000 21cL: 2071-2099

  15. BC HadCM3 SST forcing (A2) : rev, DJF 21cN - 20cL 21cL - 20cL 21cM - 20cL 20cL: 1971-2000 21cN: 2011-2040 21cM: 2041-2070 21cL: 2071-2099 Summer Precipitation Change (in %)

  16. BC HadCM3 SST forcing (A2) : rev, DJF 21cL - 20cL 21cN - 20cL 21cM - 20cL 20cL: 1971-2000 21cN: 2011-2040 21cM: 2041-2070 21cL: 2071-2099 Bias corrected Summer Precipitation Change (in %)

  17. A2 SST-BC forcing: rev – ctl, 21cL- 20cL DJF 20cL: 1971-2000 21cL: 2071-2099

  18. Transient climate change signal: DJF Precipitation revised - control 20cL: 1971-2000 21cN: 2011-2040 21cM: 2041-2070 21cL: 2071-2099

  19. Transient climate change signal: JJA Precipitation revised - control 20cL: 1971-2000 21cN: 2011-2040 21cM: 2041-2070 21cL: 2071-2099

  20. Transient climate change signal: JJA Precipitation revised - control 20cL: 1971-2000 21cN: 2011-2040 21cM: 2041-2070 21cL: 2071-2099

  21. DJF MSLP & Precipitation – 20cL (Observed SST) Control observed SST Revised observed SST

  22. DJF MSLP & Precipitation – 20cL (HadCM3 SST) HadCM3 SST Bias Corrected HadCM3 SST

  23. DJF Southern Annular Mode Index HadISST+HadCM3bias corrected HadCM3

  24. MSLP and Precipitation Changes, DJF, 21cL-20cL (MPI)

  25. MSLP and Precipitation Changes, DJF, 21cL-20cL (MIROCM)

  26. Conclusions • Regional climate change over NZ domain is dominated by changes in large scale circulation pattern • Large climate change signal • 21st century trend may be nonlinear • bias correction reduces signal • Trends in temperature increase over time whereas precipitation may fluctuate • Climate change involves not only changes in mean but also in variability • Reasonably ‘reliable’ climate change signal by bias correcting but is superimposed by large internal variability – low precision Are there preferred climate states, climate attractors … associated with climate change?

  27. Future Work Are there preferred climate states, climate attractors … associated with climate change? & • Climate model development and improvements • Run more ensemble members; physical and initial state • Projection of the behaviour of climate modes into future considering multi-decadal variability • Improvements in bias correction methodology and initialization concerns

  28. Questions?

  29. Summary • Sensitivity in projections of rainfall change - caused by ‘trivially small’ differences in prescribed SSTs - result in changes in stationary wave patterns & rainfall - now have a number of GCM/RCM runs that reproduce this instability • Similar sensitivity present for initial condition ensembles as for parameter/physics ensembles • Challenges for interpretation of NZ climate changes - a problem with ‘climate scenario paradigm’ - ICs don’t matter!? - alternatively, maybe 30-year future climatology is too short a period - nevertheless, there is a climate change ‘signal’ • What now? - explore with further ensemble runs & further analysis - use a different atmosphere GCM Slide 18 of 18

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