Estimated PDFs of climate system properties including natural and anthropogenic forcings and implications for 21 st century climate change predictions. Dr. Chris E. Forest MIT Joint Program on the Science and Policy of Global Change Presentation to: Climate Decision Making Center Seminar Series Carnegie Mellon University April 24, 2006

Calibrated Climate Model Results Observed climate changes provide constraints on climate response to forcings. Forest et al. (2006) use observed climate changes to place probabilistic bounds on parameters in the IGSM climate component These constraints provide bounds for climate system response to any scenario of future climate forcings and help provide information for decision making process.

Future forcings –Pathways of climate relevant emissions and concentrations (GHGs, aerosols,... ) (IPCC: SRES?) –How much can pollutants reflect sunlight? (Net Aerosol forcing, F aer (  IPCC: ??) Climate System Response Uncertainty –Equilibrium temperature change How much will global-mean temperature change after oceans, ice, or ecosystems adjust? (Climate Sensitivity to 2x[CO 2 ], S) (IPCC: K) –Transient climate change How fast can oceans (and ice) take up excess heat? (Rate of heat uptake by the deep ocean, K v ) (IPCC: ??) Major Climate Projection Uncertainties Climate System Properties

MIT 2D Climate Model Description  2D statistical-dynamical atmospheric model derived from 3D GISS II AGCM (GSO, 7.86 o latitude x 11 vertical layers, GSOVSV, 4 o x11 layers with 2.5D ocean and sea-ice) [Sokolov and Stone, 1998]  Q-flux mixed layer ocean model where temperature anomalies are mixed into deep-ocean. Q-flux held fixed in transient simulations.  Adjustable model properties: climate sensitivity (S, via cloud feedback strength), rate of deep-ocean heat uptake (via Effective K v ), and net aerosol forcing (F aer, via optical depth)

Uncertainty in Climate Change Major uncertainty in future climate change is determined by forcings and large-scale response (Climate Sensitivity and Rate of Deep-ocean Heat Uptake) –Climate change is caused by changes in the radiative balance of Earth –Radiative balance is changed by increasing greenhouse gas concentrations and other climatically important substances

Estimating Uncertainty in Climate System Properties: p(S,K v,F aer  T obs ) 1.Simulate 20 th century climate using anthropogenic and natural forcings while systematically varying the choices of climate system properties: S, K v, and F aer 2.Compare each model response against observed  T as in optimal fingerprint detection algorithm 3.Compare goodness-of-fit statistics to estimate p(S,K v,F aer  T obs ) for individual  T diagnostics 4.Estimate p(S,K v,F aer  T obs ) for multiple diagnostics and combine results using Bayes’ Theorem From: Forest et al. (2002), Science

Climate-change diagnostics (  T i ) 1)Upper-air temperature changes, latitude- height pattern, [ ] - [ ] (Parker et al. 1997) (M=36x8) 2)Deep-ocean temperature trend, global, 0-3km ( ) (Levitus et al. 2000, 2005) (M=1) 3)Surface temperature change, latitude-time pattern, ( decadal means, climatology, 4 zonal bands) (updated from Jones, 1994) (M=4 x 5)

Calculations with GSO forcings

Updated Climate Forcings Anthropogenic –Greenhouse gases (eqCO 2 vs CO 2, CH 4, CFCs, N 2 O) –Sulfate Aerosols (emissions updated to 2001) –Ozone: Stratospheric and Tropospheric (GISS SI2002) –Vegetation Land-use changes Natural –Volcanic aerosols (Sato et al.) –Solar forcing (Lean et al.) GSO (old work) vs. GSOVSV (new work) –Both use sulfate aerosols for uncertainty in net forcing

Summary of Changes from GSO  GSOLSV Updated Forcings for –Updated Greenhouse Gas concentrations –Updated Sulfur emissions from –Updated Ozone concentrations –Added Land-use Vegetation Changes –Added Volcanic and Solar forcings Updated climate model to 4 o resolution and included new sea-ice model  T Diagnostics identical to GSO

Constraints on climate parameters set from past observations: the effects of including volcanic forcing Are Aerosols & Volcanoes Masking the real effect of greenhouse gases? Greater Sensitivity? Less ocean mixing? Less non-volcanic aerosol cooling? from Forest et al. (2002, Science) and Forest et al. (2006, Geophys. Res. Letters)

Slow Sea level rise Fast Probability Distribution for Climate Sensitivity and Rate of Deep-ocean heat uptake Cluster of AOGCMs (Sokolov et al., 2003) from Forest et al. (2006, GRL) Implication: Models overestimate rate of ocean heat uptake for transient response leading to faster adjustment to climate forcings. Rejected Accepted 90% 99%

Marginal Density: p(S,K v |  T,C N ) GSO – Uniform Priors GSOLSV – Uniform Priors Rate of Deep-Ocean Heat Uptake (Sqrt(cm 2 /s)) Climate Sensitivity (K)

Conclusions from updated PDFs Major changes in GSO  GSOLSV –Higher lower bound on Clim. Sensitivity (~2K) –Weaker deep-ocean heat uptake indicates a bias in AOGCM results –Reduced Net Aerosol forcing strength –Highlights need for multiple lines of evidence Note: Expert priors are justified by including LGM paleoclimate changes (e.g., Annan and Hargreaves, 2006, GRL) GSO = Forest et al. (2002), Science GSOLSV = Forest et al. (2006), GRL

Deep-Ocean Temperature Data Higher coverage in NH than SH Still poor coverage in SH for surface Two alternatives to using Global estimate –Delete SH data and use trend in NH alone –Treat hemispheres separately as independent diagnostics

Ocean Temperature Observations at 1km depth for two 5-yr periods: (top) (bottom) (from Levitus et al. (2005) Auxiliary Material) Z depth =1km,

Effects of missing data for ocean heat content anomaly estimates (  HC) Test two assumptions for values at missing data points: 1.  HC = 0 2.  HC = representative average If existing data are a good representation of missing data, the change in heat content would have been larger. From Gregory et al., GRL, VOL. 31, L15312, doi: /2004GL020258, 2004

Observed  T ocean issues Without a detailed analysis, there is no clear guide for deleting estimates from Southern Hemisphere although data are sparse. A judgment call is required. Appears to be equal justification for using global or NH ocean temperatures. –Natural variability estimated by AOGCMs in NH is much larger leading to weaker constraints. No change in mode indicates AOGCMs’ distribution is still biased.

Implications for future Two sensitivity tests –Effect of reduced oceanic heat uptake (OHU) Three runs with different K v Mode  K v = 0.64 cm 2 /s 2x OHU  K v = 2.56 cm 2 /s ~4x OHU = old mode  K v = 9.2 cm 2 /s –Additional volcanic forcing for 21 st century Repeated past 50 yrs twice Added past 100 yrs

Simulations by MIT IGSM2 (Sokolov et al., 2005) with reference emissions scenario from MIT EPPA4 (Paltzev et al., 2005). [ S= 2.9 K, F aer = -0.5 W/m 2 ]

Implications for future climate change These features indicate that the reduction in the ocean heat content has a much larger effect on temperature changes than the volcanic forcing scenario. In terms of temperature changes from the present, the inclusion of the volcanic forcing appears to reduce temperature increase only by at most ~0.5 o C while reducing K v leads to an increase of ~1.8 o C by 2100 with S = 2.9 o C and F aer = -0.5 W/m 2 for this reference emissions scenario.