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The fifth phase of the Coupled Model Intercomparison Project (CMIP5) will produce a state-of-the- art multimodel dataset designed to advance our knowledge of climate variability and climate change. Researchers worldwide are analyzing the model output and will produce results likely to underlie the forthcoming Fifth Assessment Report by the Intergovernmental Panel on Climate Change. Unprecedented in scale and attracting interest from all major climate modeling groups, CMIP5 includes “long term” simulations of twentieth-century climate and projections for the twenty-first century and beyond. Conventional atmosphere–ocean global climate models and Earth system models of intermediate complexity are for the first time being joined by more recently developed Earth system models under an experiment design that allows both types of models to be compared to observations on an equal footing. Besides the longterm experiments, CMIP5 calls for an entirely new suite of “near term” simulations focusing on recent decades and the future to year 2035. These “decadal predictions” are initialized based on observations and will be used to explore the predictability of climate and to assess the forecast system's predictive skill. The CMIP5 experiment design also allows for participation of stand-alone atmospheric models and includes a variety of idealized experiments that will improve understanding of the range of model responses found in the more complex and realistic simulations. An exceptionally comprehensive set of model output is being collected and made freely available to researchers through an integrated but distributed data archive. For researchers unfamiliar with climate models, the limitations of the models and experiment design are described.

Meltwater from the Antarctic Ice Sheet is projected to cause up to one metre of sea-level rise by 2100 under the highest greenhouse gas concentration trajectory (RCP8.5) considered by the Intergovernmental Panel on Climate Change (IPCC). However, the effects of meltwater from the ice sheets and ice shelves of Antarctica are not included in the widely used CMIP5 climate models, which introduces bias into IPCC climate projections. Here we assess a large ensemble simulation of the CMIP5 model ‘GFDL ESM2M’ that accounts for RCP8.5-projected Antarctic Ice Sheet meltwater. We find that, relative to the standard RCP8.5 scenario, accounting for meltwater delays the exceedance of the maximum global-mean atmospheric warming targets of 1.5 and 2 degrees Celsius by more than a decade, enhances drying of the Southern Hemisphere and reduces drying of the Northern Hemisphere, increases the formation of Antarctic sea ice (consistent with recent observations of increasing Antarctic sea-ice area) and warms the subsurface ocean around the Antarctic coast. Moreover, the meltwater-induced subsurface ocean warming could lead to further ice-sheet and ice-shelf melting through a positive feedback mechanism, highlighting the importance of including meltwater effects in simulations of future climate. Accounting for meltwater from the Antarctic Ice Sheet in simulations of global climate leads to substantial changes in future climate projections and identifies a potential feedback mechanism that exacerbates melting.

The authors describe carbon system formulation and simulation characteristics of two new global coupled carbon–climate Earth System Models (ESM), ESM2M and ESM2G. These models demonstrate good climate fidelity as described in part I of this study while incorporating explicit and consistent carbon dynamics. The two models differ almost exclusively in the physical ocean component; ESM2M uses the Modular Ocean Model version 4.1 with vertical pressure layers, whereas ESM2G uses generalized ocean layer dynamics with a bulk mixed layer and interior isopycnal layers. On land, both ESMs include a revised land model to simulate competitive vegetation distributions and functioning, including carbon cycling among vegetation, soil, and atmosphere. In the ocean, both models include new biogeochemical algorithms including phytoplankton functional group dynamics with flexible stoichiometry. Preindustrial simulations are spun up to give stable, realistic carbon cycle means and variability. Significant differences in simulation characteristics of these two models are described. Because of differences in oceanic ventilation rates, ESM2M has a stronger biological carbon pump but weaker northward implied atmospheric CO₂ transport than ESM2G. The major advantages of ESM2G over ESM2M are improved representation of surface chlorophyll in the Atlantic and Indian Oceans and thermocline nutrients and oxygen in the North Pacific. Improved tree mortality parameters in ESM2G produced more realistic carbon accumulation in vegetation pools. The major advantages of ESM2M over ESM2G are reduced nutrient and oxygen biases in the southern and tropical oceans.

The physical climate formulation and simulation characteristics of two new global coupled carbon–climate Earth System Models, ESM2M and ESM2G, are described. These models demonstrate similar climate fidelity as the Geophysical Fluid Dynamics Laboratory’s previous Climate Model version 2.1 (CM2.1) while incorporating explicit and consistent carbon dynamics. The two models differ exclusively in the physical ocean component; ESM2M uses Modular Ocean Model version 4p1 with vertical pressure layers while ESM2G uses Generalized Ocean Layer Dynamics with a bulk mixed layer and interior isopycnal layers. Differences in the ocean mean state include the thermocline depth being relatively deep in ESM2M and relatively shallow in ESM2G compared to observations. The crucial role of ocean dynamics on climate variability is highlighted in El Niño–Southern Oscillation being overly strong in ESM2M and overly weak in ESM2G relative to observations. Thus, while ESM2G might better represent climate changes relating to total heat content variability given its lack of long-term drift, gyre circulation, and ventilation in the North Pacific, tropical Atlantic, and Indian Oceans, and depth structure in the overturning and abyssal flows, ESM2M might better represent climate changes relating to surface circulation given its superior surface temperature, salinity, and height patterns, tropical Pacific circulation and variability, and Southern Ocean dynamics. The overall assessment is that neither model is fundamentally superior to the other, and that both models achieve sufficient fidelity to allow meaningful climate and earth system modeling applications. This affords the ability to assess the role of ocean configuration on earth system interactions in the context of two state-of-the-art coupled carbon–climate models.

Setting the scenes Climatologists use model-based 'scenarios' to provide plausible descriptions of how the future might unfold when evaluating uncertainty about the effects of human actions on climate. The traditional method of establishing these scenarios was a time-consuming sequential process, each discipline taking turns to add data and complexity. As Richard Moss and colleagues explain in a Perspectives review, climate change researchers have now established a new coordinated parallel process that integrates the tasks of developing scenarios, making projections and evaluating their impact. These 'next generation' scenarios should make for faster, more rigorous assessment of proposals for climate mitigation and adaptation. Advances in the science and observation of climate change are providing a clearer understanding of the inherent variability of Earth’s climate system and its likely response to human and natural influences. The implications of climate change for the environment and society will depend not only on the response of the Earth system to changes in radiative forcings, but also on how humankind responds through changes in technology, economies, lifestyle and policy. Extensive uncertainties exist in future forcings of and responses to climate change, necessitating the use of scenarios of the future to explore the potential consequences of different response options. To date, such scenarios have not adequately examined crucial possibilities, such as climate change mitigation and adaptation, and have relied on research processes that slowed the exchange of information among physical, biological and social scientists. Here we describe a new process for creating plausible scenarios to investigate some of the most challenging and important questions about climate change confronting the global community.

A set of state-of-the-science climate models are used to investigate global sea level rise (SLR) patterns induced by ocean dynamics in twenty-first-century climate projections. The identified robust features include bipolar and bihemisphere seesaws in the basin-wide SLR, dipole patterns in the North Atlantic and North Pacific, and a beltlike pattern in the Southern Ocean. The physical and dynamical mechanisms that cause these patterns are investigated in detail using version 2.1 of the Geophysical Fluid Dynamics Laboratory (GFDL) Coupled Model (CM2.1). Under the Intergovernmental Panel on Climate Change’s (IPCC) Special Report on Emissions Scenarios (SRES) A1B scenario, the steric sea level changes relative to the global mean (the local part) in different ocean basins are attributed to differential heating and salinity changes of various ocean layers and associated physical processes. As a result of these changes, water tends to move from the ocean interior to continental shelves. In the North Atlantic, sea level rises north of the Gulf Stream but falls to the south. The dipole pattern is induced by a weakening of the meridional overturning circulation. This weakening leads to a local steric SLR east of North America, which drives more waters toward the shelf, directly impacting northeastern North America. An opposite dipole occurs in the North Pacific. The dynamic SLR east of Japan is linked to a strong steric effect in the upper ocean and a poleward expansion of the subtropical gyre. In the Southern Ocean, the beltlike pattern is dominated by the baroclinic process during the twenty-first century, while the barotropic response of sea level to wind stress anomalies is significantly delayed.

Human-induced climate change is expected to cause sea-level rise globally as well as regionally. An analysis of state-of-the-art climate models indicates that the northeastern US coast is particularly likely to experience substantial rises in regional sea level as a result of the projected slowdown of the Atlantic meridional overturning circulation. Human-induced climate change could cause global sea-level rise. Through the dynamic adjustment of the sea surface in response to a possible slowdown of the Atlantic meridional overturning circulation 1 , 2 , a warming climate could also affect regional sea levels, especially in the North Atlantic region 3 , leading to high vulnerability for low-lying Florida and western Europe 4 , 5 , 6 . Here we analyse climate projections from a set of state-of-the-art climate models for such regional changes, and find a rapid dynamical rise in sea level on the northeast coast of the United States during the twenty-first century. For New York City, the rise due to ocean circulation changes amounts to 15, 20 and 21 cm for scenarios with low, medium and high rates of emissions respectively, at a similar magnitude to expected global thermal expansion. Analysing one of the climate models in detail, we find that a dynamic, regional rise in sea level is induced by a weakening meridional overturning circulation in the Atlantic Ocean, and superimposed on the global mean sea-level rise. We conclude that together, future changes in sea level and ocean circulation will have a greater effect on the heavily populated northeastern United States than estimated previously 7 , 8 , 9 .

A coordinated set of global coupled climate model [atmosphere–ocean general circulation model (AOGCM)] experiments for twentieth- and twenty-first-century climate, as well as several climate change commitment and other experiments, was run by 16 modeling groups from 11 countries with 23 models for assessment in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). Since the assessment was completed, output from another model has been added to the dataset, so the participation is now 17 groups from 12 countries with 24 models. This effort, as well as the subsequent analysis phase, was organized by the World Climate Research Programme (WCRP) Climate Variability and Predictability (CLIVAR) Working Group on Coupled Models (WGCM) Climate Simulation Panel, and constitutes the third phase of the Coupled Model Intercomparison Project (CMIP3). The dataset is called the WCRP CMIP3 multimodel dataset, and represents the largest and most comprehensive international global coupled climate model experiment and multimodel analysis effort ever attempted. As of March 2007, the Program for Climate Model Diagnostics and Intercomparison (PCMDI) has collected, archived, and served roughly 32 TB of model data. With oversight from the panel, the multimodel data were made openly available from PCMDI for analysis and academic applications. Over 171 TB of data had been downloaded among the more than 1000 registered users to date. Over 200 journal articles, based in part on the dataset, have been published so far. Though initially aimed at the IPCC AR4, this unique and valuable resource will continue to be maintained for at least the next several years. Never before has such an extensive set of climate model simulations been made available to the international climate science community for study. The ready access to the multimodel dataset opens up these types of model analyses to researchers, including students, who previously could not obtain state-of-the-art climate model output, and thus represents a new era in climate change research. As a direct consequence, these ongoing studies are increasing the body of knowledge regarding our understanding of how the climate system currently works, and how it may change in the future.

Successful projection of the distribution of surface temperature change increases our confidence in climate models. Here we evaluate projections of global warming from almost 30 years ago using the observations made during the past half century.

Sulfate aerosols resulting from strong volcanic explosions last for 2–3 years in the lower stratosphere. Therefore it was traditionally believed that volcanic impacts produce mainly short‐term, transient climate perturbations. However, the ocean integrates volcanic radiative cooling and responds over a wide range of time scales. The associated processes, especially ocean heat uptake, play a key role in ongoing climate change. However, they are not well constrained by observations, and attempts to simulate them in current climate models used for climate predictions yield a range of uncertainty. Volcanic impacts on the ocean provide an independent means of assessing these processes. This study focuses on quantification of the seasonal to multidecadal time scale response of the ocean to explosive volcanism. It employs the coupled climate model CM2.1, developed recently at the National Oceanic and Atmospheric Administration's Geophysical Fluid Dynamics Laboratory, to simulate the response to the 1991 Pinatubo and the 1815 Tambora eruptions, which were the largest in the 20th and 19th centuries, respectively. The simulated climate perturbations compare well with available observations for the Pinatubo period. The stronger Tambora forcing produces responses with higher signal‐to‐noise ratio. Volcanic cooling tends to strengthen the Atlantic meridional overturning circulation. Sea ice extent appears to be sensitive to volcanic forcing, especially during the warm season. Because of the extremely long relaxation time of ocean subsurface temperature and sea level, the perturbations caused by the Tambora eruption could have lasted well into the 20th century.