Intermodel Spread Research Articles

Response of the large‐scale structure of the atmosphere to global warming

This article discusses the possible response of the large‐scale atmospheric structure to a warmer climate. Using integrations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) in conjunction with physical arguments, we try to identify what changes are likely to be robust and what the underlying mechanisms might be. We focus on the large‐scale zonally averaged circulation, in particular on height of the tropopause, the strength and position of the surface westerlies and the strength and extent of the Hadley Cell. We present analytic arguments and numerical calculations which suggest that under global warming the height of the tropopause will increase in both the transient response and final equilibrium state, and an increase is clearly found in all the comprehensive models in CMIP5. Upper stratospheric cooling is also found in the comprehensive models, and this too can be explained by a radiative argument. Regarding the circulation, most models show a slight expansion and weakening of the Hadley Cell, depending on season and hemisphere. The expansion is small and largely confined to winter but with some expansion in Southern Hemisphere summer. The weakening occurs principally in the Northern Hemisphere but the intermodel scatter is large. There is also a general polewards shift in surface westerlies, but the changes are small and again are little larger than the intermodel variability in the change. This shift is positively correlated with the Hadley Cell expansion to a degree that depends somewhat on the metric chosen for the latter. There is a robust strengthening in the Southern Hemisphere surface winds across seasons. In the Northern Hemisphere there is a slight strengthening in the westerlies in most models in winter but a consistent weakening of the westerlies in summer. We present various physical arguments concerning these circulation changes but none that are both demonstrably correct and that account for the model results. We conclude that the above‐mentioned large‐scale thermodynamic/radiative changes in the large‐scale atmospheric structure are generally robust, in the sense of being both well understood and consistently reproduced by comprehensive models. In that sense the dynamical changes are less robust given the current state of knowledge and simulation, although one cannot conclude that they are, in principle, unknowable or less predictable.

Understanding the Anthropogenically Forced Change of Equatorial Pacific Trade Winds in Coupled Climate Models*

Abstract Understanding the change of equatorial Pacific trade winds is pivotal for understanding the global mean temperature change and the El Niño–Southern Oscillation (ENSO) property change. The weakening of the Walker circulation due to anthropogenic greenhouse gas (GHG) forcing was suggested as one of the most robust phenomena in current climate models by examining zonal sea level pressure gradient over the tropical Pacific. This study explores another component of the Walker circulation change focusing on equatorial Pacific trade wind change. Model sensitivity experiments demonstrate that the direct/fast response due to GHG forcing is to increase the trade winds, especially over the equatorial central-western Pacific (ECWP) (5°S–5°N, 140°E–150°W), while the indirect/slow response associated with sea surface temperature (SST) warming weakens the trade winds. Further, analysis of the results from 19 models in phase 5 of the Coupled Model Intercomparison Project (CMIP5) and the Parallel Ocean Program (POP)–Ocean Atmosphere Sea Ice Soil (OASIS)–ECHAM model (POEM) shows that the projected weakening of the trades is robust only in the equatorial eastern Pacific (EEP) ( 5°S–5°N, 150°–80°W), but highly uncertain over the ECWP with 9 out of 19 CMIP5 models producing intensified trades. The prominent and robust weakening of EEP trades is suggested to be mainly driven by a top-down mechanism: the mean vertical advection of more upper-tropospheric warming downward to generate a cyclonic circulation anomaly in the southeast tropical Pacific. In the ECWP, the large intermodel spread is primarily linked to model diversity in simulating the relative warming of the equatorial Pacific versus the tropical mean sea surface temperature. The possible root causes of the uncertainty for the trade wind change are also discussed.

Impact of Weddell Sea deep convection on natural and anthropogenic carbon in a climate model

AbstractA climate model is used to investigate the influence of Weddell Sea open ocean deep convection on anthropogenic and natural carbon uptake for the period 1860–2100. In a three‐member ensemble climate change simulation, convection ceases on average by year 1981, weakening the net oceanic cumulative uptake of atmospheric CO2 by year 2100 (−4.3 Pg C) relative to an ocean that has continued convection. This net weakening results from a decrease in anthropogenic carbon uptake (−10.1 Pg C), partly offset by an increase in natural carbon storage (+5.8 Pg C). Despite representing only 4% of its area, the Weddell Sea is responsible for 22% of the Southern Ocean decrease in total climate‐driven carbon uptake and 52% of the decrease in the anthropogenic component of oceanic uptake. Although this is a model‐specific result, it illustrates the potential of deep convection to produce an intermodel spread in future projections of ocean carbon uptake.

Climate impacts on human livelihoods: where uncertainty matters in projections of water availability

Abstract. Climate change will have adverse impacts on many different sectors of society, with manifold consequences for human livelihoods and well-being. However, a systematic method to quantify human well-being and livelihoods across sectors is so far unavailable, making it difficult to determine the extent of such impacts. Climate impact analyses are often limited to individual sectors (e.g. food or water) and employ sector-specific target measures, while systematic linkages to general livelihood conditions remain unexplored. Further, recent multi-model assessments have shown that uncertainties in projections of climate impacts deriving from climate and impact models, as well as greenhouse gas scenarios, are substantial, posing an additional challenge in linking climate impacts with livelihood conditions. This article first presents a methodology to consistently measure what is referred to here as AHEAD (Adequate Human livelihood conditions for wEll-being And Development). Based on a trans-disciplinary sample of concepts addressing human well-being and livelihoods, the approach measures the adequacy of conditions of 16 elements. We implement the method at global scale, using results from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) to show how changes in water availability affect the fulfilment of AHEAD at national resolution. In addition, AHEAD allows for the uncertainty of climate and impact model projections to be identified and differentiated. We show how the approach can help to put the substantial inter-model spread into the context of country-specific livelihood conditions by differentiating where the uncertainty about water scarcity is relevant with regard to livelihood conditions – and where it is not. The results indicate that livelihood conditions are compromised by water scarcity in 34 countries. However, more often, AHEAD fulfilment is limited through other elements. The analysis shows that the water-specific uncertainty ranges of the model output are outside relevant thresholds for AHEAD for 65 out of 111 countries, and therefore do not contribute to the overall uncertainty about climate change impacts on livelihoods. In 46 of the countries in the analysis, water-specific uncertainty is relevant to AHEAD. The AHEAD method presented here, together with first results, forms an important step towards making scientific results more applicable for policy decisions.

Added-value from initialization in predictions of Atlantic multi-decadal variability

Identifying regions sensitive to external radiative changes, including anthropogenic (sulphate aerosols and greenhouse gases) and natural (volcanoes and solar variations) forcings, is important to formulate actionable information at multi-year time-scales. Internally-generated climate variability can overcome this radiative forcing, especially at regional level, so that detecting the areas for this potential dominance is likewise critical for decadal prediction. This work aims to clarify where each contribution has the largest effect on North Atlantic sea surface temperature (SST) predictions in relation to the Atlantic multi-decadal variability (AMV). Initialized decadal hindcasts and radiatively-forced historical simulations from the fifth phase of the Climate Model Intercomparison Project are analysed to assess multi-year skill of the AMV. The initialized hindcasts reproduce better the phase of the AMV index fluctuations. The radiatively-forced component consists of a residual positive trend, although its identification is ambiguous. Initialization reduces the inter-model spread when estimating the level of AMV skill, thus reducing its uncertainty. Our results show a skilful performance of the initialized hindcasts in capturing the AMV-related SST anomalies over the subpolar gyre and Labrador Sea regions, as well as in the eastern subtropical basin, and the inability of the radiatively-forced historical runs to simulate the horseshoe-like AMV signature over the North Atlantic. Initialization outperforms empirical predictions based on persistence beyond 1–4 years ahead, suggesting that ocean dynamics play a role in the AMV predictability beyond the thermal inertia. The initialized hindcasts are also more skilful at reproducing the observed AMV teleconnection to the West African monsoon. The impact of the start date frequency is also described, showing that the standard of 5-year interval between start dates yields the main features of the AMV skill that are robustly detected in hindcasts with yearly start date sampling. This work updates previous studies, complementing them, and concludes that skilful initialized multi-model forecasts of the AMV-related climate variability can be formulated, improving uninitialized projections, until 3–6 years ahead.

Interacting components of the top‐of‐atmosphere energy balance affect changes in regional surface temperature

AbstractThe role of interactions between components of the top‐of‐atmosphere (TOA) energy balance in determining regional surface temperature changes, such as polar amplification, is examined in diffusive energy balance model (EBM) simulations. These interactions have implications for the interpretation of local feedback analyses when they are applied to regional surface temperature changes. Local feedback analysis succeeds at accounting for the EBM‐simulated temperature change given the changes in the radiative forcing, atmospheric energy transport, and radiative feedbacks. However, the inferences about the effect of individual components of the TOA energy balance on regional temperature changes do not account for EBM simulations in which individual components are prescribed or “locked.” As changes in one component of the TOA energy balance affect others, unambiguous attribution statements relating changes in regional temperature or its intermodel spread to individual terms in the TOA energy balance cannot be made.

A simple carbon cycle representation for economic and policy analyses

Integrated Assessment Models (IAMs) that couple the climate system and the economy require a representation of ocean CO2 uptake to translate human-produced emissions to atmospheric concentrations and in turn to climate change. The simple linear carbon cycle representations in most IAMs are not however physical at long timescales, since ocean carbonate chemistry makes CO2 uptake highly nonlinear. No linearized representation can capture the ocean's dual-mode behavior, with initial rapid uptake and then slow equilibration over ∼10,000 years. In a business-as-usual scenario followed by cessation of emissions, the carbon cycle in the 2007 version of the most widely used IAM, DICE (Dynamic Integrated model of Climate and the Economy), produces errors of ∼ 2 ◦ C by the year 2300 and ∼ 6 ◦ C by the year 3500. We suggest here a simple alternative representation that captures the relevant physics and show that it reproduces carbon uptake in several more complex models to within the inter-model spread. The scheme involves little additional complexity over the DICE model, making it a useful tool for economic and policy analyses.

A Simple Carbon Cycle Representation for Economic and Policy Analyses

Integrated Assessment Models (IAMs) that couple the climate system and the economy require a representation of ocean CO2 uptake to translate human-produced emissions to atmospheric concentrations and in turn to climate change. The simple linear carbon cycle representations in most IAMs are not however physical at long timescales, since ocean carbonate chemistry makes CO2 uptake highly nonlinear. No linearized representation can capture the ocean’s dual-mode behavior, with initial rapid uptake and then slow equilibration over ~10,000 years. In a business-as-usual scenario followed by cessation of emissions, the carbon cycle in the 2007 version of the most widely used IAM, DICE (Dynamic Integrated model of Climate and the Economy), produces errors of ~2°C by the year 2300 and ~6°C by the year 3500. We suggest here a simple alternative representation that captures the relevant physics and show that it reproduces carbon uptake in several more complex models to within the inter-model spread. The scheme involves little additional complexity over the DICE model, making it a useful tool for economic and policy analyses.

Projected Changes in Temperature and Precipitation Extremes in China by the CMIP5 Multimodel Ensembles

Abstract This paper presents projected changes in temperature and precipitation extremes in China by the end of the twenty-first century based on the Coupled Model Intercomparison Project phase 5 (CMIP5) simulations. The temporal changes and their spatial patterns in the Expert Team on Climate Change Detection and Indices (ETCCDI) indices under the RCP4.5 and RCP8.5 emission scenarios are analyzed. Compared to the reference period 1986–2005, substantial changes are projected in temperature and precipitation extremes under both emission scenarios. These changes include a decrease in cold extremes, an increase in warm extremes, and an intensification of precipitation extremes. The intermodel spread in the projection increases with time, with wider spread under RCP8.5 than RCP4.5 for most indices, especially at the subregional scale. The difference in the projected changes under the two RCPs begins to emerge in the 2040s. Analyses based on the mixed-effects analysis of variance (ANOVA) model indicate that by the end of the twenty-first century, at the national scale, the dominant contributor to the projection uncertainty of most temperature-based indices, and some precipitation extremes [including maximum 1-day precipitation (RX1day) and maximum 5-day precipitation (RX5day), and total extremely wet day total amount (R95p)], is the difference in emission scenarios. By the end of the twenty-first century, model uncertainty is the dominant factor at the regional scale and for the other indices. Natural variability can also play very important role.

Improved Representation of Marine Stratocumulus Cloud Shortwave Radiative Properties in the CMIP5 Climate Models

Abstract The radiative properties of subtropical marine stratocumulus clouds are investigated in an ensemble of current-generation global climate models from phase 5 of the Climate Model Intercomparison Project (CMIP5). Using a previously documented method for determining regional mean cloud albedo, the authors find a closer agreement with observations in the CMIP5 models as compared to the previous generation of models (phase 3 of CMIP). The multimodel average indicates regional mean, monthly mean cloud albedos ranging from 0.32 to 0.5 among 26 models and five regions, to be compared with satellite observations that indicate a range from 0.32 to 0.39 for the same five regions. The intermodel spread in cloud fraction gives rise to a spread in albedo. Within models, there is a tendency for large cloud fraction to be related to low cloud albedo and vice versa, a relationship that dampens the intermodel variability in total albedo. The intramodel variability in albedo, for a given cloud fraction, is found to be up to twice as large in magnitude in models as in satellite observations. The reason for this larger variability in models is not settled, but possible contributing factors may be imperfect representation in the models of cloud type distribution or of sensitivity to meteorological variability or aerosols. Changes in aerosol loading are found to be the likely cause of an increase in cloud albedo over time. The radiative effect of such a scene brightening in marine stratocumulus cloud regions, from preindustrial times to present day, is estimated to be up to −1 W m−2 for the global ocean, but there are no observations to verify this number.

The diurnal cycle of marine cloud feedback in climate models

We examine the diurnal cycle of marine cloud feedback using high frequency outputs in CFMIP-2 idealised uniform +4 K SST perturbation experiments from seven CMIP5 models. Most of the inter-model spread in the diurnal mean marine shortwave cloud feedback can be explained by low cloud responses, although these do not explain the model responses at the neutral/weakly negative end of the feedback range, where changes in mid and high level cloud properties are more important. All of the models show reductions in marine low cloud fraction in the warmer climate, and these are in almost all cases largest in the mornings when more cloud is present in the control simulations. This results in shortwave cloud feedbacks being slightly stronger and having the largest inter-model spread at this time of day. The diurnal amplitudes of the responses of marine cloud properties to the warming climate are however small compared to the inter-model differences in their diurnally meaned responses. This indicates that the diurnal cycle of cloud feedback is not strongly relevant to understanding inter-model spread in overall cloud feedback and climate sensitivity. A number of unusual behaviours in individual models are highlighted for future investigation.

The Southern Ocean in the Coupled Model Intercomparison Project phase5.

The Southern Ocean is an important part of the global climate system, but its complex coupled nature makes both its present state and its response to projected future climate forcing difficult to model. Clear trends in wind, sea-ice extent and ocean properties emerged from multi-model intercomparison in the Coupled Model Intercomparison Project phase 3 (CMIP3). Here, we review recent analyses of the historical and projected wind, sea ice, circulation and bulk properties of the Southern Ocean in the updated Coupled Model Intercomparison Project phase 5 (CMIP5) ensemble. Improvements to the models include higher resolutions, more complex and better-tuned parametrizations of ocean mixing, and improved biogeochemical cycles and atmospheric chemistry. CMIP5 largely reproduces the findings of CMIP3, but with smaller inter-model spreads and biases. By the end of the twenty-first century, mid-latitude wind stresses increase and shift polewards. All water masses warm, and intermediate waters freshen, while bottom waters increase in salinity. Surface mixed layers shallow, warm and freshen, whereas sea ice decreases. The upper overturning circulation intensifies, whereas bottom water formation is reduced. Significant disagreement exists between models for the response of the Antarctic Circumpolar Current strength, for reasons that are as yet unclear.

Northern winter climate change: Assessment of uncertainty in CMIP5 projections related to stratosphere-troposphere coupling

Future changes in the stratospheric circulation could have an important impact on northern winter tropospheric climate change, given that sea level pressure (SLP) responds not only to tropospheric circulation variations but also to vertically coherent variations in troposphere-stratosphere circulation. Here we assess northern winter stratospheric change and its potential to influence surface climate change in the Coupled Model Intercomparison Project-Phase 5 (CMIP5) multimodel ensemble. In the stratosphere at high latitudes, an easterly change in zonally averaged zonal wind is found for the majority of the CMIP5 models, under the Representative Concentration Pathway 8.5 scenario. Comparable results are also found in the 1% CO2 increase per year projections, indicating that the stratospheric easterly change is common feature in future climate projections. This stratospheric wind change, however, shows a significant spread among the models. By using linear regression, we quantify the impact of tropical upper troposphere warming, polar amplification, and the stratospheric wind change on SLP. We find that the intermodel spread in stratospheric wind change contributes substantially to the intermodel spread in Arctic SLP change. The role of the stratosphere in determining part of the spread in SLP change is supported by the fact that the SLP change lags the stratospheric zonally averaged wind change. Taken together, these findings provide further support for the importance of simulating the coupling between the stratosphere and the troposphere, to narrow the uncertainty in the future projection of tropospheric circulation changes.

Arctic summer storm track in CMIP3/5 climate models

Model performance and future projection of Arctic summertime storm-track activity and associated background states are assessed on the basis of Coupled Model Intercomparison Project Phase 3 (CMIP3)/5 (CMIP5) climate models. Despite some improvement in the CMIP5 models relative to the CMIP3 models, most of the climate models underestimate summertime storm-track activity over the Arctic Ocean compared to six reanalysis data sets as measured locally as the variance of subweekly fluctuations of sea level pressure. Its large inter-model spread (i.e., model-to-model differences) is correlated with that of the intensity of the Beaufort Sea High and the lower-tropospheric westerlies in the Arctic region. Most of the CMIP3/5 models project the enhancement of storm-track activity over the Arctic Ocean off the eastern Siberian and Alaskan coasts, the region called the Arctic Ocean Cyclone Maximum, in association with the strengthening of the westerlies in the warmed climate. A model with stronger enhancement of the storm-track activity tends to accompany stronger land-sea contrast in surface air temperature across the Siberian coast, which reflects greater surface warming over the continent and slower warming over the Arctic Ocean. Other processes, however, may also be likely to contribute to the future changes of the storm-track activity, which gives uncertainty in the projection by multiple climate models. Our analysis suggests that further clarification of those processes that influence storm-track activity over the Arctic is necessary for more reliable future projections of the Arctic climate.

Quantifying components of aerosol-cloud-radiation interactions in climate models

The interaction of anthropogenic aerosols with radiation and clouds is the largest source of uncertainty in the radiative forcing of the climate during the industrial period. Here we apply novel techniques to diagnose the contributors to the shortwave (SW) effective radiative forcing (ERF) from aerosol-radiation-interaction (ERFari) and from aerosol cloud interaction (ERFaci) in experiments performed in phase 5 of the Coupled Model Intercomparison Project. We find that the ensemble mean SW ERFari+aci of −1.40±0.56 W m−2 comes roughly 25% from ERFari (−0.35±0.20 W m−2) and 75% from ERFaci (−1.04±0.67 W m−2). ERFari is made up of −0.62±0.30 W m−2 due to aerosol scattering opposed by +0.26 ± 0.12 W m−2 due to aerosol absorption and is largest near emission sources. The ERFari from nonsulfate aerosols is +0.13 ± 0.09 W m−2, consisting of −0.15±0.11 W m−2 of scattering and +0.29 ± 0.15 W m−2 of absorption. The change in clear-sky flux is a negatively biased measure of ERFari, as the presence of clouds reduces the magnitude and intermodel spread of ERFari by 40–50%. ERFaci, which is large both near and downwind of emission sources, is composed of −0.99±0.54 W m−2 from enhanced cloud scattering, with much smaller contributions from increased cloud amount and absorption. In models that allow aerosols to affect ice clouds, large increases in the optical depth of high clouds cause substantial longwave and shortwave radiative anomalies. Intermodel spread in ERFaci is dominated by differences in how aerosols increase cloud scattering, but even if all models agreed on this effect, over a fifth of the spread in ERFaci would remain due solely to differences in total cloud amount.

Global-mean radiative feedbacks and forcing in atmosphere-only and coupled atmosphere-ocean climate change experiments

Analysis of the available Coupled Model Intercomparison Project Phase 5 models suggests that sea surface temperature-forced, atmosphere-only global warming experiments (“amip4K,” “amipFuture,” and “aqua4K”) are a good guide to the global cloud feedbacks determined from coupled atmosphere-ocean CO2-forced simulations, including the intermodel spread. Differences in the total climate feedback parameter between the experiments arise primarily from differences in the clear-sky feedbacks which can largely be anticipated from the nature of the experimental design. The effective CO2 radiative forcing is anticorrelated with the total feedback in the coupled simulations. This anticorrelation strengthens as the experimental design becomes simpler, the number of potential degrees of freedom of the system's response reduces, and the relevant physical processes can be identified. In the aquaplanet simulations the anticorrelation is primarily driven by opposing changes in the rapid cloud adjustment to CO2 and the net cloud response to increased surface warming. Establishing a physical explanation for this behavior is important future work.

Low‐cloud optical depth feedback in climate models

AbstractThe relationship between low‐level cloud optical depth and atmospheric and surface air temperature is examined in the control climate of 13 climate models to determine if cloud optical depth‐temperature relationships found in observations are replicated in climate models and if climate model behavior found in control climate simulations provides information about the optical depth feedback in climate warming simulations forced by increasing carbon dioxide. A positive relationship between cloud optical depth and cloud temperature exists in all models for low clouds with relatively cold temperatures at middle and high latitudes, whereas a negative relationship exists for warmer low clouds in the tropics and subtropics. This relationship is qualitatively similar to that in an earlier analysis of satellite observations, although modeled regression slopes tend to be too positive and their intermodel spread is large. In the models, the cold cloud response comes from increases in cloud water content with increasing temperature, while the warm cloud response comes from decreases in physical thickness with increasing cloud temperature. The intermodel and interregional spread of low‐cloud optical depth feedback in climate warming simulations is well predicted by the corresponding spread in the relationships between optical depth and temperature for the current climate, suggesting that this aspect of cloud feedback may be constrained by observations. Because models have a positive bias relative to observations in the optical depth‐temperature relationship, shortwave cloud feedback for climate changes may be more positive than climate models currently simulate.

Weakening and strengthening structures in the Hadley Circulation change under global warming and implications for cloud response and climate sensitivity

AbstractIt has long been recognized that differences in climate model‐simulated cloud feedbacks are a primary source of uncertainties for the model‐predicted surface temperature change induced by increasing greenhouse gases such as CO2. Large‐scale circulation broadly determines when and where clouds form and how they evolve. However, the linkage between large‐scale circulation change and cloud radiative effect (CRE) change under global warming has not been thoroughly studied. By analyzing 15 climate models, we show that the change of the Hadley Circulation exhibits meridionally varying weakening and strengthening structures, physically consistent with the cloud changes in distinct cloud regimes. The regions that experience a weakening (strengthening) of the zonal‐mean circulation account for 54% (46%) of the multimodel‐mean top‐of‐atmosphere (TOA) CRE change integrated over 45°S–40°N. The simulated Hadley Circulation structure changes per degree of surface warming differ greatly between the models, and the intermodel spread in the Hadley Circulation change is well correlated with the intermodel spread in the TOA CRE change. This correlation underscores the close interactions between large‐scale circulation and clouds and suggests that the uncertainties of cloud feedbacks and climate sensitivity reside in the intimate coupling between large‐scale circulation and clouds. New model performance metrics proposed in this work, which emphasize how models reproduce satellite‐observed spatial variations of zonal‐mean cloud fraction and relative humidity associated with the Hadley Circulation, indicate that the models closer to the satellite observations tend to have equilibrium climate sensitivity higher than the multimodel mean.

The Role of the Mean State of Arctic Sea Ice on Near-Surface Temperature Trends

Abstract Century-scale global near-surface temperature trends in response to rising greenhouse gas concentrations in climate models vary by almost a factor of 2, with greatest intermodel spread in the Arctic region where sea ice is a key climate component. Three factors contribute to the intermodel spread: 1) model formulation, 2) control climate state, and 3) internal climate variability. This study focuses on the influence of Arctic sea ice in the control climate on the intermodel spread in warming, using idealized 1% yr−1 CO2 increase simulations of 33 state-of-the-art global climate models, and combining sea ice–temperature relations on local to large spatial scales. On the Arctic mean scale, the spread in temperature trends is only weakly related to ice volume or area in the control climate, and is probably not dominated by internal variability. This suggests that other processes, such as ocean heat transport and meteorological conditions, play a more important role in the spread of long-term Arctic warming than control sea ice conditions. However, on a local scale, sea ice–warming relations show that in regions with more sea ice, models generally simulate more warming in winter and less warming in summer. The local winter warming is clearly related to control sea ice and universal among models, whereas summer sea ice–warming relations are more diverse, and are probably dominated by differences in model formulation. To obtain a more realistic representation of Arctic warming, it is recommended to simulate control sea ice conditions in climate models so that the spatial pattern is correct.

Radiative Forcing of Quadrupling CO2

AbstractAn analysis method proposed by Huang is improved and used to dissect the radiative forcing in the instantaneous quadrupling CO2 experiment from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Multiple validation tests show that the errors in the forcing estimates are generally within 10%. The results show that quadrupling CO2, on average, induces a global-mean all-sky instantaneous top-of-the-atmosphere forcing of 5.4 W m−2, which is amended by a stratospheric adjustment of 1.9 W m−2 and a tropospheric adjustment of −0.1 W m−2. The resulting fully adjusted radiative forcing has an ensemble mean of 7.2 W m−2 and a substantial intermodel spread (maximum–minimum) of 2.4 W m−2, which results from all the forcing components, especially the instantaneous forcing and tropospheric adjustment. The fidelity of the linear decomposition of the overall radiation variation is improved when forcing is explicitly estimated for each model. A significant contribution by forcing uncertainty to the intermodel spread of the surface temperature projection is verified. The results reaffirm the importance of evaluating the radiative forcing components in climate feedback analyses.