Climate projections have demonstrated the need to adapt to a changing climate, but have been less helpful (so far) in guiding how to effectively adapt. Uncertainty in climate change projections poses a challenge to infrastructure planning for climate change adaptation 1.Because of the large expense and … The highest amplitude variability occurs the NH continents in winter, with values ~ 1.2–1.5°C in nature compared to 1.5–1.8°C in the model. J Clim 13:1000–1016Trenberth KE, Branstator GW, Karoly D, Kumar A, Lau N-C, Ropelewski C (1998) Progress during TOGA in understanding and modeling global teleconnections associated with tropical sea surface temperatures. The SST and sea ice conditions are based on observations during the period 1980–2000 from the data set of Hurrell et al. A projection, on the other hand, … These patterns project onto the zonally-symmetric Northern and Southern Annular Modes (NAM and SAM, respectively; e.g., Thompson and Wallace The tropical Precip response consists of mainly positive values along the equator flanked by compensating negative values, especially to the south, with maximum amplitudes ~ 2 mm day(As with the standard error formula, the factor ‘8’ in the formula for Ensemble mean epoch difference maps and ensemble size requirements for the June–July–August (JJA) season are shown in Fig. In this integration, the specified repeating seasonal cycles of SST and sea ice are based on observations from the period 1980–2000. CCSM3, CAM3 SST+ATM, the sum of CAM3 SST and CAM3 ATM, CAM3 SST, and CAM3 ATM for (a),(c) trends in HC strength and (b),(d) corresponding CCSM3, CAM3 SST+ATM, the sum of CAM3 SST and CAM3 ATM, CAM3 SST, and CAM3 ATM for (a),(c) trends in HC strength and (b),(d) corresponding Turning next to the widening of the HC, the trends and We now characterize the dominant patterns of uncertainty in future trends, along the lines of Global distribution of Ψ trend uncertainty (ΔΨ′) regressed upon PC1 of ΔΨ′ (J kgGlobal distribution of Ψ trend uncertainty (ΔΨ′) regressed upon PC1 of ΔΨ′ (J kgPattern correlation between the EOF1 of uncertainty in Ψ trends from 40-member CCSM3 and CAM3 SST+ATM. Uncertainty in future climate change derives from three main sources: forcing, model response, and internal variability (e.g., Hawkins and Sutton Internal atmospheric variability, also termed “climate noise” (e.g., Madden The unprecedented assemblage of climate model projections from the World Climate Research Programme’s (WCRP) Coupled Model Intercomparison Project Phase 3 (CMIP3) archive (Meehl et al. doi:Yiou P, Vautard R, Naveau P, Cassou C (2007) Inconsistency between atmospheric dynamics and temperatures during the exceptional 2006/2007 fall/winter and recent warming in Europe. The models and methods are given in Sect.

J Clim 20:2416–2433Madden RA (1976) Estimates of the natural variability of time-averaged sea-level pressure.

The climate will continue to warm during the 21st century due to the large inertia of the Earth System and in response to additional GHG emissions, but by how much remains highly uncertain.

Black contour interval: 5 × 10(a),(c) CCSM3 40-member ensemble-mean Ψ climatology (black contours) and trends (colors). Some feedbacks determining the rate of global warming are not well understood. doi:Wunsch C (1999) The interpretation of short climate records, with comments on the North Atlantic and Southern Oscillations. In this integration, sea surface temperatures (SSTs) and sea ice are prescribed to vary with a repeating seasonal cycle but no year-to-year variability. What are the minimum ensemble size requirements for detecting the forced climate signal near the mid-point of the integration period?