Internal variability in the climate system confounds assessment of human-induced climate change and imposes irreducible limits on the accuracy of climate change projections, especially at regional and decadal scales. A new collection of initial-condition large ensembles (LEs) generated with seven Earth system models under historical and future radiative forcing scenarios provides new insights into uncertainties due to internal variability versus model differences. These data enhance the assessment of climate change risks, including extreme events, and offer a powerful testbed for new methodologies aimed at separating forced signals from internal variability in the observational record. Opportunities and challenges confronting the design and dissemination of future LEs, including increased spatial resolution and model complexity alongside emerging Earth system applications, are discussed.

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Despite continued growth in atmospheric levels of greenhouse gases, globalmean surface and tropospheric temperatures show slower warming since 1998 1−5 . Possible explanations for this "warming hiatus" include internal climate variability 3,4,6,7 , external cooling influences 1,2,4,8−11 , and observational errors 12,13 . One contributory factor to the relatively muted surface warming -early 21st century volcanic forcing -has been examined in several modelling studies 1,2,4,8 . Here we present the first analysis of the impact of recent volcanic forcing on tropospheric temperature, and the first observational assessment of the significance of early 21st century volcanic signals. We identify statistically significant signals in the correlations between stratospheric aerosol optical depth and satellite-based estimates of both tropospheric temperature and short-wave fluxes at the top of the atmosphere. We show that climate model simulations without early 21st century volcanic forcing overestimate the tropospheric warming observed since 1998. In two simulations with more realistic volcanic forcing following the 1991 Pinatubo eruption, differences between modelled and observed tropospheric temperature trends over 1998 to 2012 are decreased by up to 15%, with large uncertainties in the size of the effect. Reducing these uncertainties will require better observational understanding of eruption-specific differences in volcanic aerosol properties, and improved representation of these differences in model simulations. B. D. Santer et al. 3Our analysis uses satellite measurements of changes in the temperature of the lower troposphere (TLT) made by Microwave Sounding Units (MSU) on NOAA polarorbiting satellites 13,14 . Satellite TLT data have near-global, time-invariant spatial coverage; in contrast, global-mean trends estimated from surface thermometer records can be biased by spatially-and temporally non-random coverage changes 15 . We compare MSU TLT data to synthetic satellite temperatures 3 calculated from simulations Although our primary focus is on the recent "warming hiatus", we also examine volcanically-induced changes in warming rate following the eruptions of El Chichón (April 1982) and Pinatubo (June 1991). Both volcanic events increased stratospheric loadings of liquid-phase sulfate aerosols, leading to stratospheric warming and tropospheric cooling ( Supplementary Fig. 1) 17−19 . Stratospheric temperature recovers within 1-2 years after El Chichón and Pinatubo. Because of the large thermal inertia of the ocean, the recovery of tropospheric temperatures is slower (ca. 8-10 years) 20,21 .To analyze volcanic contributions to observed changes in warming rates, it is useful to reduce the amplitude of internal noise 20−22 . Our noise reduction strategy involves removing the temperature signal of the El Niño/Southern Oscillation (ENSO), a (Fig. 1C). After 1999, however, a "warming hiatus" is still apparent in the observed residual TLT time series, but the lower troposphere continues to warm in the CMIP-5 multi-mo...

Despite a steady increase in atmospheric greenhouse gases (GHGs), global-mean surface temperature (T) has shown no discernible warming since about 2000, in sharp contrast to model simulations, which on average project strong warming 1-3 . The recent slowdown in observed surface warming has been attributed to decadal cooling in the tropical Pacific 1,4,5 , intensifying trade winds 5 , changes in El Niño activity 6,7 , increasing volcanic activity 8-10 and decreasing solar irradiance 7 . Earlier periods of arrested warming have been observed but received much less attention than the recent period, and their causes are poorly understood. Here we analyse observed and model-simulated global T fields to quantify the contributions of internal climate variability (ICV) to decadal changes in global-mean T since 1920. We show that the Interdecadal Pacific Oscillation (IPO) has been associated with large T anomalies over both ocean and land. Combined with another leading mode of ICV, the IPO explains most of the di erence between observed and model-simulated rates of decadal change in global-mean T since 1920, and particularly over the so-called 'hiatus' period since about 2000. We conclude that ICV, mainly through the IPO, was largely responsible for the recent slowdown, as well as for earlier slowdowns and accelerations in global-mean T since 1920, with preferred spatial patterns di erent from those associated with GHG-induced warming or aerosol-induced cooling. Recent history suggests that the IPO could reverse course and lead to accelerated global warming in the coming decades.The Pacific Decadal Oscillation (PDO; refs 11,12), or more generally the IPO (refs 13,14), switched from a warm phase to a cold phase around 1999 15 . This switch has been associated with a cooling trend since the early 1990s over the Equatorial Central and Eastern Pacific (ECEP; 15 • S-15 • N, 180 • -80 • W) that has contributed to the recent hiatus in global-mean T (refs 4,5). Modelling studies 1,16,17 have also shown that the IPO can modulate the rate of global warming through changes in ocean heat uptake. Given the welldocumented extra-tropical response to tropical forcings 18,19 , it is not surprising that IPO-associated sea surface temperature (SST) variations in the ECEP have had a large impact on global-mean T (ref. 1). The recent cooling of the ECEP has been accompanied by strengthening trade winds 5 and increasing ocean heat uptake 4,16,17,20 , typical of a La Niña event 21 but over decadal timescales. Although these studies all point to a major contribution of the ECEP to the recent global warming slowdown, it is unclear how much of the observed SST change in the ECEP is associated with ICV, particularly the IPO, and how much is due to external forcing change, such as stratospheric aerosols [7][8][9][10] . Previous analyses 22,23 a b Global-mean temperature anomaly difference (°C) r = 0.80, 0.94 OBS − model OBS EOF1 .2 0.1 0.0 −0.1 −0.2 −0.3 0.8 OBS (GISTEMP) Model (CMIP5) Model + 2 OBS EOFs Global-mean temperature anomaly (°C) 0.5 0..1...

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[1] Changes in the position and strength of the Southern Hemisphere surface westerlies have significant implications for ocean circulation and the global carbon cycle. Here we compare the climatologies, as well as the trends, in the position and strength of the surface westerly wind-stress jet in reanalyses with the Coupled Model Intercomparison Project (CMIP) phase 3 and phase 5 models over the historical period from 1979-2010. We show that both the CMIP3 and CMIP5 models exhibit an equatorward biased climatological jet position. The reanalyses and climate models both show significant trends in annual mean jet strength, though the climate models underestimate the strengthening. Neither reanalyses nor models show a robust trend in annual mean jet position over the historical period, though significant trends do occur in the Austral summer position. We also compare the response of the CMIP3 and CMIP5 model wind-stresses to a range of anthropogenic forcing scenarios for the 21st century. Citation: Swart, N. C., and J. C. Fyfe (2012), Observed and simulated changes in the Southern Hemisphere surface westerly wind-stress, Geophys. Res.

The ability of 15 atmospheric GCM models (AGCM) to simulate the tropical intraseasonal oscillation has been studied as part of AMIP. Time series of the daily upper tropospheric velocity potential and zonal wind, averaged over the equatorial belt, were provided from each AGCM simulation. These data were analyzed using a variety of techniques such as time filtering and space-time spectral analysis to identify eastward and westward propagating waves. The results have been compared with an identical assessment of ECMWF analyses for the period 1982-1991. The models display a wide range of skill in simulating the intraseasonal oscillation. Most models show evidence of an eastward propagating anomaly in the velocity potential field, although in some models there is a greater tendency for a standing oscillation, and in one or two the field is rather chaotic with no preferred direction of propagation. Where a model has a clear eastward propagating signal, typical periodicities seem quite reasonable although there is a tendency for the models to simulate shorter periods than in the ECMWF analyses, where it is near 50 days. The results of the space-time spectral analysis have shown that no model has captured the dominance of the intraseasonal oscillation found in the analyses. Several models have peaks at intraseasonal time scales, but nearly all have relatively more power at higher frequencies