Collaboration for Australian Weather and Climate Research

Abstract The extent to which the climate will change due to an external forcing depends largely on radiative feedbacks, which act to amplify or damp the surface temperature response. There are a variety of issues that complicate the analysis of radiative feedbacks in global climate models, resulting in some confusion regarding their strengths and distributions. In this paper, the authors present a method for quantifying climate feedbacks based on “radiative kernels” that describe the differential response of the top-of-atmosphere radiative fluxes to incremental changes in the feedback variables. The use of radiative kernels enables one to decompose the feedback into one factor that depends on the radiative transfer algorithm and the unperturbed climate state and a second factor that arises from the climate response of the feedback variables. Such decomposition facilitates an understanding of the spatial characteristics of the feedbacks and the causes of intermodel differences. This technique provides a simple and accurate way to compare feedbacks across different models using a consistent methodology. Cloud feedbacks cannot be evaluated directly from a cloud radiative kernel because of strong nonlinearities, but they can be estimated from the change in cloud forcing and the difference between the full-sky and clear-sky kernels. The authors construct maps to illustrate the regional structure of the feedbacks and compare results obtained using three different model kernels to demonstrate the robustness of the methodology. The results confirm that models typically generate globally averaged cloud feedbacks that are substantially positive or near neutral, unlike the change in cloud forcing itself, which is as often negative as positive.

Abstract This work identifies and documents a suite of large-scale drivers of rainfall variability in the Australian region. The key driver in terms of broad influence and impact on rainfall is the El Niño–Southern Oscillation (ENSO). ENSO is related to rainfall over much of the continent at different times, particularly in the north and east, with the regions of influence shifting with the seasons. The Indian Ocean dipole (IOD) is particularly important in the June–October period, which spans much of the wet season in the southwest and southeast where IOD has an influence. ENSO interacts with the IOD in this period such that their separate regions of influence cover the entire continent. Atmospheric blocking also becomes most important during this period and has an influence on rainfall across the southern half of the continent. The Madden–Julian oscillation can influence rainfall in different parts of the continent in different seasons, but its impact is strongest on the monsoonal rains in the north. The influence of the southern annular mode is mostly confined to the southwest and southeast of the continent. The patterns of rainfall relationship to each of the drivers exhibit substantial decadal variability, though the characteristic regions described above do not change markedly. The relationships between large-scale drivers and rainfall are robust to the selection of typical indices used to represent the drivers. In most regions the individual drivers account for less than 20% of monthly rainfall variability, though the drivers relate to a predictable component of this variability. The amount of rainfall variance explained by individual drivers is highest in eastern Australia and in spring, where it approaches 50% in association with ENSO and blocking.

Since 1995, a large region of Australia has been gripped by the most severe drought in living memory, the so‐called “Big Dry”. The ramifications for affected regions are dire, with acute water shortages for rural and metropolitan areas, record agricultural losses, the drying‐out of two of Australia's major river systems and far‐reaching ecosystem damage. Yet the drought's origins have remained elusive. For Southeast Australia, we show here that the “Big Dry” and other iconic 20th Century droughts, including the Federation Drought (1895–1902) and World War II drought (1937–1945), are driven by Indian Ocean variability, not Pacific Ocean conditions as traditionally assumed. Specifically, a conspicuous absence of Indian Ocean temperature conditions conducive to enhanced tropical moisture transport has deprived southeastern Australia of its normal rainfall quota. In the case of the “Big Dry”, its unprecedented intensity is also related to recent higher temperatures.

This paper documents a global Bayesian variational inversion of CO 2 surface fluxes during the period 1988–2008. Weekly fluxes are estimated on a 3.75° × 2.5° (longitude‐latitude) grid throughout the 21 years. The assimilated observations include 128 station records from three large data sets of surface CO 2 mixing ratio measurements. A Monte Carlo approach rigorously quantifies the theoretical uncertainty of the inverted fluxes at various space and time scales, which is particularly important for proper interpretation of the inverted fluxes. Fluxes are evaluated indirectly against two independent CO 2 vertical profile data sets constructed from aircraft measurements in the boundary layer and in the free troposphere. The skill of the inversion is evaluated by the improvement brought over a simple benchmark flux estimation based on the observed atmospheric growth rate. Our error analysis indicates that the carbon budget from the inversion should be more accurate than the a priori carbon budget by 20% to 60% for terrestrial fluxes aggregated at the scale of subcontinental regions in the Northern Hemisphere and over a year, but the inversion cannot clearly distinguish between the regional carbon budgets within a continent. On the basis of the independent observations, the inversion is seen to improve the fluxes compared to the benchmark: the atmospheric simulation of CO 2 with the Bayesian inversion method is better by about 1 ppm than the benchmark in the free troposphere, despite possible systematic transport errors. The inversion achieves this improvement by changing the regional fluxes over land at the seasonal and at the interannual time scales.

The Australian Community Climate and Earth System Simulator coupled model (ACCESS-CM) has been developed at the Centre for Australian Weather and Climate Research (CAWCR), a partnership between CSIRO 1 and the Bureau of Meteorology. It is built by coupling the UK Met Office atmospheric unified model (UM), and other sub-models as required, to the ACCESS ocean model, which consists of the NOAA/GFDL 2 ocean model MOM4p1 and the LANL 3 sea-ice model CICE4.1, under the CERFACS 4 OASIS3.2-5 coupling framework. The primary goal of the ACCESS-CM development is to provide the Australian climate community with a new generation fully coupled climate model for climate research, and to participate in phase five of the Coupled Model Inter-comparison Project (CMIP5). This paper describes the ACCESS-CM framework and components, and presents the control climates from two versions of the ACCESS-CM, ACCESS1.0 and AC-CESS1.3, together with some fields from the 20 th century historical experiments, as part of model evaluation. While sharing the same ocean sea-ice model (except different setups for a few parameters), ACCESS1.0 and ACCESS1.3 differ from each other in their atmospheric and land surface components: the former is configured with the UK Met Office HadGEM2 (r1.1) atmospheric physics and the Met Office Surface Exchange Scheme land surface model version 2, and the latter with atmospheric physics similar to the UK Met Office Global Atmosphere 1.0 including modifications performed at CAWCR and the CSIRO Community Atmosphere Biosphere Land Exchange land surface model version 1.8. The global average annual mean surface air temperature across the 500-year preindustrial control integrations show a warming drift of 0.35 C in ACCESS1.0 and 0.04 C in AC-CESS1.3. The overall skills of ACCESS-CM in simulating a set of key climatic fields both globally and over Australia significantly surpass those from the preceding CSIRO Mk3.5 model delivered to the previous coupled model inter-comparison. However, ACCESS-CM, like other CMIP5 models, has deficiencies in various aspects, and these are also discussed.

The mean and variable transport of the Indonesian Throughflow (ITF) are determined from full‐depth velocity measurements in the three major exit passages of Lombok Strait, Ombai Strait, and Timor Passage from January 2003 through December 2006. Collectively, these passages convey the full‐depth transport and stratification profile of the ITF from the Pacific Ocean to the Indian Ocean. To first order, the seasonal cycle of transport in the thermocline (∼100–150 m) in all three exit straits is dominated by regional monsoon forcing, with maximum ITF during the southeast monsoon. During the northwest monsoon, the surface transport relaxes in Timor and weakly reverses in Ombai and Lombok, so the main core of the ITF is subsurface. Below the thermocline, semiannual reversals occur in all three straits during the monsoon transitions in response to the passage of Indian Ocean wind‐forced Kelvin waves. However, the reversals occur over different depth levels in each passage reflecting the influence of different sill depths along the coastal waveguide. The seasonal cycle of depth‐integrated transports in Lombok and Ombai are strongly out of phase with Timor Passage, suggesting that the subthermocline flow is largely gated by these Kelvin waves. Despite the different seasonal transport phases, interannual anomalies in all three passages are remarkably similar, particularly during the strong positive Indian Ocean Dipole event in 2006 when transport in the surface layer is toward the Indian Ocean and reversed below. The deep reversals are likely in response to a series of Kelvin waves driven by anomalous zonal winds in the equatorial Indian Ocean. Total mean transport over the 3‐year period is −2.6 Sv in Lombok Strait (i.e., toward the Indian Ocean), −4.9 Sv in Ombai Strait, and −7.5 Sv in Timor Passage. The transport in Timor Passage is nearly twice as large as historical estimates and represents half of the −15 Sv full‐depth ITF transport that enters the Indian Ocean.

The boreal summer intraseasonal oscillation (BSISO) of the Asian summer monsoon (ASM) is one of the most prominent sources of short-term climate variability in the global monsoon system. Compared with the related Madden-Julian Oscillation (MJO) it is more complex in nature, with prominent northward propagation and variability extending much further from the equator. In order to facilitate detection, monitoring and prediction of the BSISO we suggest two real-time indices: BSISO1 and BSISO2, based on multivariate empirical orthogonal function (MV-EOF) analysis of daily anomalies of outgoing longwave radiation (OLR) and zonal wind at 850 hPa (U850) in the region 10°S–40°N, 40°–160°E, for the extended boreal summer (May–October) season over the 30-year period 1981–2010. BSISO1 is defined by the first two principal components (PCs) of the MV-EOF analysis, which together represent the canonical northward propagating variability that often occurs in conjunction with the eastward MJO with quasi-oscillating periods of 30–60 days. BSISO2 is defined by the third and fourth PCs, which together mainly capture the northward/northwestward propagating variability with periods of 10–30 days during primarily the pre-monsoon and monsoon-onset season. The BSISO1 circulation cells are more Rossby wave like with a northwest to southeast slope, whereas the circulation associated with BSISO2 is more elongated and front-like with a southwest to northeast slope. BSISO2 is shown to modulate the timing of the onset of Indian and South China Sea monsoons. Together, the two BSISO indices are capable of describing a large fraction of the total intraseasonal variability in the ASM region, and better represent the northward and northwestward propagation than the real-time multivariate MJO (RMM) index of Wheeler and Hendon.

Abstract Globally averaged surface air temperatures in some decades show rapid increases (accelerated warming decades), and in other decades there is no warming trend (hiatus decades). A previous study showed that the net energy imbalance at the top of the atmosphere of about 1 W m−2 is associated with greater increases of deep ocean heat content below 750 m during the hiatus decades, while there is little globally averaged surface temperature increase or warming in the upper ocean layers. Here the authors examine processes involved with accelerated warming decades and address the relative roles of external forcing from increasing greenhouse gases and internally generated decadal climate variability associated with interdecadal Pacific oscillation (IPO). Model results from the Community Climate System Model, version 4 (CCSM4), show that accelerated warming decades are characterized by rapid warming of globally averaged surface air temperature, greater increases of heat content in the upper ocean layers, and less heat content increase in the deep ocean, opposite to the hiatus decades. In addition to contributions from processes potentially linked to Antarctic Bottom Water (AABW) formation and the Atlantic meridional overturning circulation (AMOC), the positive phase of the IPO, adding to the response to external forcing, is usually associated with accelerated warming decades. Conversely, hiatus decades typically occur with the negative phase of the IPO, when warming from the external forcing is overwhelmed by internally generated cooling in the tropical Pacific. Internally generated hiatus periods of up to 15 years with zero global warming trend are present in the future climate simulations. This suggests that there is a chance that the current observed hiatus could extend for several more years.

Ensemble forecasting is increasingly accepted as a powerful tool to improve early warnings for high-impact weather. Recently, ensembles combining forecasts from different systems have attracted a considerable level of interest. The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Globa l Ensemble (TIGGE) project, a prominent contribution to THORPEX, has been initiated to enable advanced research and demonstration of the multimodel ensemble concept and to pave the way toward operational implementation of such a system at the international level. The objectives of TIGGE are 1) to facilitate closer cooperation between the academic and operational meteorological communities by expanding the availability of operational products for research, and 2) to facilitate exploring the concept and benefits of multimodel probabilistic weather forecasts, with a particular focus on high-impact weather prediction. Ten operational weather forecasting centers producing daily global ensemble forecasts to 1–2 weeks ahead have agreed to deliver in near–real time a selection of forecast data to the TIGGE data archives at the China Meteorological Agency, the European Centre for Medium-Range Weather Forecasts, and the National Center for Atmospheric Research. The volume of data accumulated daily is 245 GB (1.6 million global fields). This is offered to the scientific community as a new resource for research and education. The TIGGE data policy is to make each forecast accessible via the Internet 48 h after it was initially issued by each originating center. Quicker access can also be granted for field experiments or projects of particular interest to the World Weather Research Programme and THORPEX. A few examples of initial results based on TIGGE data are discussed in this paper, and the case is made for additional research in several directions.

Abstract Advancements in weather forecast models and their enhanced resolution have led to substantially improved and more realistic-appearing forecasts for some variables. However, traditional verification scores often indicate poor performance because of the increased small-scale variability so that the true quality of the forecasts is not always characterized well. As a result, numerous new methods for verifying these forecasts have been proposed. These new methods can mostly be classified into two overall categories: filtering methods and displacement methods. The filtering methods can be further delineated into neighborhood and scale separation, and the displacement methods can be divided into features based and field deformation. Each method gives considerably more information than the traditional scores, but it is not clear which method(s) should be used for which purpose. A verification methods intercomparison project has been established in order to glean a better understanding of the proposed methods in terms of their various characteristics and to determine what verification questions each method addresses. The study is ongoing, and preliminary qualitative results for the different approaches applied to different situations are described here. In particular, the various methods and their basic characteristics, similarities, and differences are described. In addition, several questions are addressed regarding the application of the methods and the information that they provide. These questions include (i) how the method(s) inform performance at different scales; (ii) how the methods provide information on location errors; (iii) whether the methods provide information on intensity errors and distributions; (iv) whether the methods provide information on structure errors; (v) whether the approaches have the ability to provide information about hits, misses, and false alarms; (vi) whether the methods do anything that is counterintuitive; (vii) whether the methods have selectable parameters and how sensitive the results are to parameter selection; (viii) whether the results can be easily aggregated across multiple cases; (ix) whether the methods can identify timing errors; and (x) whether confidence intervals and hypothesis tests can be readily computed.

Abstract Two univariate indices of the Madden–Julian oscillation (MJO) based on outgoing longwave radiation (OLR) are developed to track the convective component of the MJO while taking into account the seasonal cycle. These are compared with the all-season Real-time Multivariate MJO (RMM) index of Wheeler and Hendon derived from a multivariate EOF of circulation and OLR. The gross features of the OLR and circulation of composite MJOs are similar regardless of the index, although RMM is characterized by stronger circulation. Diversity in the amplitude and phase of individual MJO events between the indices is much more evident; this is demonstrated using examples from the Dynamics of the Madden–Julian Oscillation (DYNAMO) field campaign and the Year of Tropical Convection (YOTC) virtual campaign. The use of different indices can lead to quite disparate conclusions concerning MJO timing and strength, and even as to whether or not an MJO has occurred. A disadvantage of using daily OLR as an EOF basis is that it is a much noisier field than the large-scale circulation, and filtering is necessary to obtain stable results through the annual cycle. While a drawback of filtering is that it cannot be done in real time, a reasonable approximation to the original fully filtered index can be obtained by following an endpoint smoothing method. When the convective signal is of primary interest, the authors advocate the use of satellite-based metrics for retrospective analysis of the MJO for individual cases, as well as for the analysis of model skill in initiating and evolving the MJO.

Abstract The modulation of tropical cyclone activity by the Madden–Julian oscillation (MJO) is explored using an empirical genesis potential (GP) index. Composite anomalies of the genesis index associated with the different MJO phases are consistent with the composite anomalies in TC genesis frequency that occur in the same phases, indicating that the index captures the changes in the environment that are at least in part responsible for the genesis frequency changes. Of the four environmental variables that enter the genesis potential index, the midlevel relative humidity makes the largest contribution to the MJO composite GP anomalies. The second largest contribution comes from the low-level absolute vorticity, and only very minor contributions come from the vertical wind shear and potential intensity. When basin-integrated MJO composite anomalies of the GP index are regressed against basin-integrated composite anomalies of TC genesis frequency, the results differ quantitatively from those obtained from the analogous calculation performed on the annual climatologies in the two quantities. The GP index captures the MJO modulation of TC genesis to a lesser degree than the climatological annual cycle of genesis (to which it was originally tuned). This may be due to weaknesses of the reanalysis or indicative of the importance of precursor disturbances, not well captured in the GP index computed from weekly data, to the intraseasonal TC genesis frequency fluctuations.

Comparing the high-quality oxygen climatology fromthe World Ocean Circulation Experiment to earlier data wereveal near-global decreases in oxygen levels in the upperocean between the 1970s and the 1990s. This globallyaveraged oxygen decrease is −0.93 0.23 mol l<sup>−1</sup>, whichis equivalent to annual oxygen losses of −0.55 0.13 10<sup>14</sup> mol yr<sup>−1</sup> (1001000 m). The strongest decreases inoxygen occur in the mid-latitudes of both hemispheres,near regions where there is strong water renewal andexchange between the ocean interior and surface waters.Approximately 15% of global oxygen decrease can beexplained by a warmer mixed-layer reducing the capacityof water to store oxygen, while the remainder is consistentwith an overall decrease in the exchange between surfacewaters and the ocean interior. Here we suggest that thisreduction in water mass renewal rates on a global scale is aconsequence of increased stratification caused by warmersurface waters. These observations support climate modelsimulations of oxygen change under global warmingscenarios.

Abstract The Madden–Julian oscillation (MJO) interacts with and influences a wide range of weather and climate phenomena (e.g., monsoons, ENSO, tropical storms, midlatitude weather), and represents an important, and as yet unexploited, source of predictability at the subseasonal time scale. Despite the important role of the MJO in climate and weather systems, current global circulation models (GCMs) exhibit considerable shortcomings in representing this phenomenon. These shortcomings have been documented in a number of multimodel comparison studies over the last decade. However, diagnosis of model performance has been challenging, and model progress has been difficult to track, because of the lack of a coherent and standardized set of MJO diagnostics. One of the chief objectives of the U.S. Climate Variability and Predictability (CLIVAR) MJO Working Group is the development of observation-based diagnostics for objectively evaluating global model simulations of the MJO in a consistent framework. Motivation for this activity is reviewed, and the intent and justification for a set of diagnostics is provided, along with specification for their calculation, and illustrations of their application. The diagnostics range from relatively simple analyses of variance and correlation to more sophisticated space–time spectral and empirical orthogonal function analyses. These diagnostic techniques are used to detect MJO signals, to construct composite life cycles, to identify associations of MJO activity with the mean state, and to describe interannual variability of the MJO.

Abstract Aim This paper reviews the biogeography of the Australian monsoon tropical biome to highlight general patterns in the distribution of a range of organisms and their environmental correlates and evolutionary history, as well as to identify knowledge gaps. Location Northern Australia, Australian Monsoon Tropics (AMT). The AMT is defined by areas that receive more than 85% of rainfall between November and April. Methods Literature is summarized, including the origin of the monsoon climate, present‐day environment, biota and habitat types, and phylogenetic and geographical relationships of selected organisms. Results Some species are widespread throughout the AMT while others are narrow‐range endemics. Such contrasting distributions correspond to present‐day climates, hydrologies (particularly floodplains), geological features (such as sandstone plateaux), fire regimes, and vegetation types (ranging from rain forest to savanna). Biogeographical and phylogenetic studies of terrestrial plants (e.g. eucalypts) and animals (vertebrates and invertebrates) suggest that distinct bioregions within the AMT reflect the aggregated effects of landscape and environmental history, although more research is required to determine and refine the boundaries of biogeographical zones within the AMT. Phylogenetic analyses of aquatic organisms (fishes and prawns) suggest histories of associations with drainage systems, dispersal barriers, links to New Guinea, and the existence of Lake Carpentaria, now submerged by the Gulf of Carpentaria. Complex adaptations to the landscape and climate in the AMT are illustrated by a number of species. Main conclusions The Australian monsoon is a component of a single global climate system, characterized by a dominant equator‐spanning Hadley cell. Evidence of hot, seasonally moist climates dates back to the Late Eocene, implying that certain endemic elements of the AMT biota have a long history. Vicariant differentiation is inferred to have separated the Kimberley and Arnhem Land bioregions from Cape York Peninsula/northern Queensland. Such older patterns are overlaid by younger events, including dispersal from Southeast Asia, and range expansions and contractions. Future palaeoecological and phylogenetic investigations will illuminate the evolution of the AMT biome. Understanding the biogeography of the AMT is essential to provide a framework for ecological studies and the sustainable development of the region.

Abstract Impacts of the Madden–Julian oscillation (MJO) on Australian rainfall and circulation are examined during all four seasons. The authors examine circulation anomalies and a number of different rainfall metrics, each composited contemporaneously for eight MJO phases derived from the real-time multivariate MJO index. Multiple rainfall metrics are examined to allow for greater relevance of the information for applications. The greatest rainfall impact of the MJO occurs in northern Australia in (austral) summer, although in every season rainfall impacts of various magnitude are found in most locations, associated with corresponding circulation anomalies. In northern Australia in all seasons except winter, the rainfall impact is explained by the direct influence of the MJO’s tropical convective anomalies, while in winter a weaker and more localized signal in northern Australia appears to result from the modulation of the trade winds as they impinge upon the eastern coasts, especially in the northeast. In extratropical Australia, on the other hand, the occurrence of enhanced (suppressed) rainfall appears to result from induced upward (downward) motion within remotely forced extratropical lows (highs), and from anomalous low-level northerly (southerly) winds that transport moisture from the tropics. Induction of extratropical rainfall anomalies by remotely forced lows and highs appears to operate mostly in winter, whereas anomalous meridional moisture transport appears to operate mainly in the summer, autumn, and to some extent in the spring.

Abstract. The recent increase of atmospheric methane is investigated by using two atmospheric inversions to quantify the distribution of sources and sinks for the 2006–2008 period, and a process-based model of methane emissions by natural wetland ecosystems. Methane emissions derived from the two inversions are consistent at a global scale: emissions are decreased in 2006 (−7 Tg) and increased in 2007 (+21 Tg) and 2008 (+18 Tg), as compared to the 1999–2006 period. The agreement on the latitudinal partition of the flux anomalies for the two inversions is fair in 2006, good in 2007, and not good in 2008. In 2007, a positive anomaly of tropical emissions is found to be the main contributor to the global emission anomalies (~60–80%) for both inversions, with a dominant share attributed to natural wetlands (~2/3), and a significant contribution from high latitudes (~25%). The wetland ecosystem model produces smaller and more balanced positive emission anomalies between the tropics and the high latitudes for 2006, 2007 and 2008, mainly due to precipitation changes during these years. At a global scale, the agreement between the ecosystem model and the inversions is good in 2008 but not satisfying in 2006 and 2007. Tropical South America and Boreal Eurasia appear to be major contributors to variations in methane emissions consistently in the inversions and the ecosystem model. Finally, changes in OH radicals during 2006–2008 are found to be less than 1% in inversions, with only a small impact on the inferred methane emissions.

Accurate observations of cloud microphysical properties are needed for evaluating and improving the representation of cloud processes in climate models and better estimate of the Earth radiative budget. However, large differences are found in current cloud products retrieved from ground‐based remote sensing measurements using various retrieval algorithms. Understanding the differences is an important step to address uncertainties in the cloud retrievals. In this study, an in‐depth analysis of nine existing ground‐based cloud retrievals using ARM remote sensing measurements is carried out. We place emphasis on boundary layer overcast clouds and high level ice clouds, which are the focus of many current retrieval development efforts due to their radiative importance and relatively simple structure. Large systematic discrepancies in cloud microphysical properties are found in these two types of clouds among the nine cloud retrieval products, particularly for the cloud liquid and ice particle effective radius. Note that the differences among some retrieval products are even larger than the prescribed uncertainties reported by the retrieval algorithm developers. It is shown that most of these large differences have their roots in the retrieval theoretical bases, assumptions, as well as input and constraint parameters. This study suggests the need to further validate current retrieval theories and assumptions and even the development of new retrieval algorithms with more observations under different cloud regimes.

Abstract Future climate change projections for phase 5 of the Coupled Model Intercomparison Project (CMIP5) are presented for the Community Earth System Model version 1 that includes the Community Atmospheric Model version 5 [CESM1(CAM5)]. These results are compared to the Community Climate System Model, version 4 (CCSM4) and include simulations using the representative concentration pathway (RCP) mitigation scenarios, and extensions for those scenarios beyond 2100 to 2300. Equilibrium climate sensitivity of CESM1(CAM5) is 4.10°C, which is higher than the CCSM4 value of 3.20°C. The transient climate response is 2.33°C, compared to the CCSM4 value of 1.73°C. Thus, even though CESM1(CAM5) includes both the direct and indirect effects of aerosols (CCSM4 had only the direct effect), the overall climate system response including forcing and feedbacks is greater in CESM1(CAM5) compared to CCSM4. The Atlantic Ocean meridional overturning circulation (AMOC) in CESM1(CAM5) weakens considerably in the twenty-first century in all the RCP scenarios, and recovers more slowly in the lower forcing scenarios. The total aerosol optical depth (AOD) changes from ~0.12 in 2006 to ~0.10 in 2100, compared to a preindustrial 1850 value of 0.08, so there is less negative forcing (a net positive forcing) from that source during the twenty-first century. Consequently, the change from 2006 to 2100 in aerosol direct forcing in CESM1(CAM5) contributes to greater twenty-first century warming relative to CCSM4. There is greater Arctic warming and sea ice loss in CESM1(CAM5), with an ice-free summer Arctic occurring by about 2060 in RCP8.5 (2040s in September) as opposed to about 2100 in CCSM4 (2060s in September).

Results are presented from experiments performed with the Community Climate System Model, version 4 (CCSM4) for the Coupled Model Intercomparison Project phase 5 (CMIP5). These include multiple ensemble members of twentieth-century climate with anthropogenic and natural forcings as well as single-forcing runs, sensitivity experiments with sulfate aerosol forcing, twenty-first-century representative concentration pathway (RCP) mitigation scenarios, and extensions for those scenarios beyond 2100–2300. Equilibrium climate sensitivity of CCSM4 is 3.20°C, and the transient climate response is 1.73°C. Global surface temperatures averaged for the last 20 years of the twenty-first century compared to the 1986–2005 reference period for six-member ensembles from CCSM4 are +0.85°, +1.64°, +2.09°, and +3.53°C for RCP2.6, RCP4.5, RCP6.0, and RCP8.5, respectively. The ocean meridional overturning circulation (MOC) in the Atlantic, which weakens during the twentieth century in the model, nearly recovers to early twentieth-century values in RCP2.6, partially recovers in RCP4.5 and RCP6, and does not recover by 2100 in RCP8.5. Heat wave intensity is projected to increase almost everywhere in CCSM4 in a future warmer climate, with the magnitude of the increase proportional to the forcing. Precipitation intensity is also projected to increase, with dry days increasing in most subtropical areas. For future climate, there is almost no summer sea ice left in the Arctic in the high RCP8.5 scenario by 2100, but in the low RCP2.6 scenario there is substantial sea ice remaining in summer at the end of the century.