[1] The new Max-Planck-Institute Earth System Model (MPI-ESM) is used in the Coupled Model Intercomparison Project phase 5 (CMIP5) in a series of climate change experiments for either idealized CO 2 -only forcing or forcings based on observations and the Representative Concentration Pathway (RCP) scenarios. The paper gives an overview of the model configurations, experiments related forcings, and initialization procedures and presents results for the simulated changes in climate and carbon cycle. It is found that the climate feedback depends on the global warming and possibly the forcing history. The global warming from climatological 1850 conditions to 2080-2100 ranges from 1.5 C under the RCP2.6 scenario to 4.4 C under the RCP8.5 scenario. Over this range, the patterns of temperature and precipitation change are nearly independent of the global warming. The model shows a tendency to reduce the ocean heat uptake efficiency toward a warmer climate, and hence acceleration in warming in the later years. The precipitation sensitivity can be as high as 2.5% K 21 if the CO 2 concentration is constant, or as small as 1.6% K 21, if the CO 2 concentration is increasing. The oceanic uptake of anthropogenic carbon increases over time in all scenarios, being smallest in the experiment forced by RCP2.6 and largest in that for RCP8.5. The land also serves as a net carbon sink in all scenarios, predominantly in boreal regions. The strong tropical carbon sources found in the RCP2.6 and RCP8.5 experiments are almost absent in the RCP4.5 experiment, which can be explained by reforestation in the RCP4.5 scenario.Citation: Giorgetta, M. A., et al. (2013), Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the Coupled Model Intercomparison Project phase 5, J. Adv. Model. Earth Syst., 5, 572-597,

[1] MPI-ESM is a new version of the global Earth system model developed at the Max Planck Institute for Meteorology. This paper describes the ocean state and circulation as well as basic aspects of variability in simulations contributing to the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The performance of the ocean/ sea-ice model MPIOM, coupled to a new version of the atmosphere model ECHAM6 and modules for land surface and ocean biogeochemistry, is assessed for two model versions with different grid resolution in the ocean. The low-resolution configuration has a nominal resolution of 1.5, whereas the higher resolution version features a quasiuniform, eddy-permitting global resolution of 0.4. The paper focuses on important oceanic features, such as surface temperature and salinity, water mass distribution, large-scale circulation, and heat and freshwater transports. In general, these integral quantities are simulated well in comparison with observational estimates, and improvements in comparison with the predecessor system are documented; for example, for tropical variability and sea ice representation. Introducing an eddy-permitting grid configuration in the ocean leads to improvements, in particular, in the representation of interior water mass properties in the Atlantic and in the representation of important ocean currents, such as the Agulhas and Equatorial current systems. In general, however, there are more similarities than differences between the two grid configurations, and several shortcomings, known from earlier versions of the coupled model, prevail.

The decline in the floating sea ice cover in the Arctic is one of the most striking manifestations of climate change. In this review, we examine this ongoing loss of Arctic sea ice across all seasons. Our analysis is based on satellite retrievals, atmospheric reanalysis, climate-model simulations and a literature review. We find that relative to the 1981-2010 reference period, recent anomalies in spring and winter sea ice coverage have been more significant than any observed drop in summer sea ice extent (SIE) throughout the satellite period. For example, the SIE in May and November 2016 was almost four standard deviations below the reference SIE in these months. Decadal ice loss during winter months has accelerated from −2.4 %/decade from 1979 to 1999 to −3.4%/decade from 2000 onwards. We also examine regional ice loss and find that for any given region, the seasonal ice loss is larger the closer that region is to the seasonal outer edge of the ice cover. Finally, across all months, we identify a robust linear relationship between pan-Arctic SIE and total anthropogenic CO 2 emissions. The annual cycle of Arctic sea ice loss per ton of CO 2 emissions ranges from slightly above 1 m 2 throughout winter to more than 3 m 2 throughout summer. Based on a linear extrapolation of these trends, we find the Arctic Ocean will become sea-ice free throughout August and September for an additional 800±300 Gt of CO 2 emissions, while it becomes ice free from July to October for an additional 1400±300 Gt of CO 2 emissions.

A new release of the Max Planck Institute for Meteorology Earth System Model version 1.2 (MPI‐ESM1.2) is presented. The development focused on correcting errors in and improving the physical processes representation, as well as improving the computational performance, versatility, and overall user friendliness. In addition to new radiation and aerosol parameterizations of the atmosphere, several relatively large, but partly compensating, coding errors in the model's cloud, convection, and turbulence parameterizations were corrected. The representation of land processes was refined by introducing a multilayer soil hydrology scheme, extending the land biogeochemistry to include the nitrogen cycle, replacing the soil and litter decomposition model and improving the representation of wildfires. The ocean biogeochemistry now represents cyanobacteria prognostically in order to capture the response of nitrogen fixation to changing climate conditions and further includes improved detritus settling and numerous other refinements. As something new, in addition to limiting drift and minimizing certain biases, the instrumental record warming was explicitly taken into account during the tuning process. To this end, a very high climate sensitivity of around 7 K caused by low‐level clouds in the tropics as found in an intermediate model version was addressed, as it was not deemed possible to match observed warming otherwise. As a result, the model has a climate sensitivity to a doubling of CO2 over preindustrial conditions of 2.77 K, maintaining the previously identified highly nonlinear global mean response to increasing CO2 forcing, which nonetheless can be represented by a simple two‐layer model.

[1] During a development stage global climate models have their properties adjusted or tuned in various ways to best match the known state of the Earth's climate system. These desired properties are observables, such as the radiation balance at the top of the atmosphere, the global mean temperature, sea ice, clouds and wind fields. The tuning is typically performed by adjusting uncertain, or even non-observable, parameters related to processes not explicitly represented at the model grid resolution. The practice of climate model tuning has seen an increasing level of attention because key model properties, such as climate sensitivity, have been shown to depend on frequently used tuning parameters. Here we provide insights into how climate model tuning is practically done in the case of closing the radiation balance and adjusting the global mean temperature for the Max Planck Institute Earth System Model (MPI-ESM). We demonstrate that considerable ambiguity exists in the choice of parameters, and present and compare three alternatively tuned, yet plausible configurations of the climate model. The impacts of parameter tuning on climate sensitivity was less than anticipated.

The Max Planck Institute Grand Ensemble (MPI-GE) is the largest ensemble of a single comprehensive climate model currently available, with 100 members for the historical simulations and four forcing scenarios. It is currently the only large ensemble available that includes scenario representative concentration pathway (RCP) 2.6 and a 1% CO 2 scenario. These advantages make MPI-GE a powerful tool. We present an overview of MPI-GE, its components, and detail the experiments completed. We demonstrate how to separate the forced response from internal variability in a large ensemble. This separation allows the quantification of both the forced signal under climate change and the internal variability to unprecedented precision. We then demonstrate multiple ways to evaluate MPI-GE and put observations in the context of a large ensemble, including a novel approach for comparing model internal variability with estimated observed variability. Finally, we present four novel analyses, which can only be completed using a large ensemble. First, we address whether temperature and precipitation have a pathway dependence using the forcing scenarios. Second, the forced signal of the highly noisy atmospheric circulation is computed, and different drivers are identified to be important for the North Pacific and North Atlantic regions. Third, we use the ensemble dimension to investigate the time dependency of Atlantic Meridional Overturning Circulation variability changes under global warming. Last, sea level pressure is used as an example to demonstrate how MPI-GE can be utilized to estimate the ensemble size needed for a given scientific problem and provide insights for future ensemble projects.Large-ensemble projects of comprehensive coupled climate models are gaining traction as methods to robustly estimate internal variability in transient simulations and to quantify the forced signal (e.g., Kay

Arctic sea ice is retreating rapidly, raising prospects of a future ice-free Arctic Ocean during summer. Since climate-model simulations of the sea-ice loss differ substantially, we here use a robust linear relationship between monthly-mean September sea-ice area and cumulative CO 2 emissions to infer the future evolution of Arctic summer sea ice directly from the observational record. The observed linear relationship implies a sustained loss of 3±0.3 m 2 of September sea-ice area per metric ton of CO 2 emission. Based on this sensitivity, Arctic sea-ice will be lost throughout September for an additional 1000 Gt of CO 2 emissions. Most models show a lower sensitivity, which is possibly linked to an underestimation of the modeled increase in incoming longwave radiation and of the modeled Transient Climate Response. The ongoing rapid loss of Arctic sea ice has far reaching consequences for climate, ecology, and human activities alike. These include amplified warming of the Arctic[1], possible linkages of sea-ice loss to mid-latitude weather patterns[2], changing habitat for flora and fauna [3], and changing prospects for human activities in the high North [3]. To understand and manage these consequences and their possible future manifestation, we need to understand the sensitivity of Arctic sea-ice evolution to changes in the prevailing climate conditions. However, assessing this sensitivity has been challenging. For example, climate-model simulations differ widely in their timing of the loss of Arctic sea ice for a given trajectory of anthropogenic CO 2 emissions: While in the most recent Climate Model Intercomparison Project 5 (CMIP5)[4] some models project a near ice-free Arctic during the summer minimum already towards the beginning of this century, other models keep a substantial amount of ice well into the next century even for an external forcing based on largely undamped anthropogenic CO 2 emissions as described by the Representative Concentration Pathway scenario RCP8.5 [4,5].To robustly estimate the sensitivity of Arctic sea ice to changes in the external forcing, we here identify and examine a fundamental relationship in which the CMIP5 models agree with

[1] We reexamine five processes that have been suggested to be important for the loss of salt from sea ice. These processes are the initial fractionation of salt at the ice-ocean interface, brine diffusion, brine expulsion, gravity drainage, and flushing with surface meltwater. We present results from analytical and numerical studies, as well as from laboratory and field experiments, that show that, among these processes, only gravity drainage and flushing contribute to any measurable net loss of salt. We show that during ice growth the salinity field is continuous across the ice-ocean interface. Hence there is no immediate segregation of salt at the advancing front.