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Scaling Laws, Scale Invariance, and Climate Prediction Bill Collins UC Berkeley and LBL Berkeley, California.

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Presentation on theme: "Scaling Laws, Scale Invariance, and Climate Prediction Bill Collins UC Berkeley and LBL Berkeley, California."— Presentation transcript:

1 Scaling Laws, Scale Invariance, and Climate Prediction Bill Collins UC Berkeley and LBL Berkeley, California

2 Topics Application of climate models for mean climate change Application of climate models for climate extremes Scaling and convergence of atmospheric dynamical fields Changes with resolution in mean and extreme rainfall Changes with resolution in clouds

3 Projection of regional temperatures IPCC AR4, 2007 Roughly 2/3 of warming by 2030 is from historical changes. Warming by 2030 exceeds 20 th C natural variability by >2x.

4 Climate impacts: precipitation intensity Precipitation intensity is annual rainfall divided by the number of wet days. Precipitation intensity increases significantly at higher latitudes by IPCC AR4, 2007

5 Climate extremes: 2003 European heat wave NASA August 2003 temperature anomalies Key vulnerabilities of industry, settlements and society are most often related to: climate phenomena that exceed thresholds for adaptation, related to the rate and magnitude of climate change, particularly extreme weather events and/or abrupt climate change limited access to resources (financial, human, institutional) to cope, rooted in issues of development context

6 An “extreme” is an usual climate state Monthly average August 2003 temperatures IPCC AR4, 2007

7 Increasingly warmer conditions Days/decade Days Alexander et al, % –41%

8 Increase in strong precipitation events Days/decade Days %/decade % Alexander et al, %

9 Climate extreme indices for North America Time series of regionally averaged Indices for the three IPCC emissions Scenarios, averaged across the models. Shaded areas = the inter-model range Change in index over 21st century for the B1 scenario (550 ppm CO 2 at 2100) Stippled regions = all models agree on sign. Change in index over 21st century for the A1B scenario (720 ppm CO 2 at 2100) Stippled regions = all models agree on sign. Change in index over 21st century for the A2 scenario (850 ppm CO 2 at 2100) Stippled regions = all models agree on sign.

10 Growing season length

11 Heat wave duration

12 Precipitation fraction > 95th percentile

13 Maximum number of dry days

14 Resolution of climate models IPCC AR4, Resolution has increased by a factor of 5. Are the model(s) converging with increased resolution?

15 Fidelity of atmospheric winds vs. resolution Collins et al, 2006 Error in means Error in variance Error in correlation Scaled Variance Ratio The resolution of Community Model has increased by a factor of ~6. The fidelity of its simulated winds has improved by a factor of ~20.

16 Spectra of winds over western Pacific Wikle et al, 1999 Dynamical improvements are consistent with numerical formulation. Simulated dynamics reproduce observed scaling laws at largest scales.

17 Low confidence in impact on rainfall IPCC AR4, 2007

18 Predictive confidence vs. resolution IPCC AR4, 2007 Consistency among simulated rainfall decreases at smaller scales. Internal variability in simulated rainfall increases at smaller scales.

19 Net surface water flux vs. resolution Global PacificAtlantic Williamson et al, 1995 Do the time-mean fluxes of water converge with increasing resolution. NO? The time-men fluxes do not converge, and can even change sign.

20 Precipitation extremes vs. resolution Williamson, 2007 Do the extreme rainfall rates converge with increasing resolution? NO? The rates do not converge for higher spatio-temporal resolution.

21 Inter-model differences in climate sensitivity Kiehl et al, 2006 Does climate sensitivity converge with increasing resolution? NO? The sensitivity and feedbacks do not converge for resolution.

22 Changes in cloud amount vs. resolution Williamson, 2007 Do cloud properties and amounts converge with increasing resolution? NO? Cloud amounts show no sign of convergence (in at least 1 model).

23 Conclusions Climate change prediction will increasingly focus on regional and intermittent phenomena. These predictions require models that converge with increasing spatial and temporal resolution. Simulated dynamics generally converges with resolution. However, simulated hydrological processes do not converge with spatial and temporal resolution. Climate models need physics that obeys the scale invariance of the real atmosphere.


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