On the interpretation of inter-model spread in CMIP5 climate sensitivity estimates

This study diagnoses the climate sensitivity, radiative forcing and climate feedback estimates from eleven general circulation models participating in the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5), and analyzes inter-model differences. This is done by taking into account the fact that the climate response to increased carbon dioxide (CO₂) is not necessarily only mediated by surface temperature changes, but can also result from fast land warming and tropospheric adjustments to the CO₂ radiative forcing. By considering tropospheric adjustments to CO₂ as part of the forcing rather than as feedbacks, and by using the radiative kernels approach, we decompose climate sensitivity estimates in terms of feedbacks and adjustments associated with water vapor, temperature lapse rate, surface albedo and clouds. Cloud adjustment to CO₂ is, with one exception, generally positive, and is associated with a reduced strength of the cloud feedback; the multi-model mean cloud feedback is about 33 % weaker. Non-cloud adjustments associated with temperature, water vapor and albedo seem, however, to be better understood as responses to land surface warming. Separating out the tropospheric adjustments does not significantly affect the spread in climate sensitivity estimates, which primarily results from differing climate feedbacks. About 70 % of the spread stems from the cloud feedback, which remains the major source of inter-model spread in climate sensitivity, with a large contribution from the tropics. Differences in tropical cloud feedbacks between low-sensitivity and high-sensitivity models occur over a large range of dynamical regimes, but primarily arise from the regimes associated with a predominance of shallow cumulus and stratocumulus clouds. The combined water vapor plus lapse rate feedback also contributes to the spread of climate sensitivity estimates, with inter-model differences arising primarily from the relative humidity responses throughout the troposphere. Finally, this study points to a substantial role of nonlinearities in the calculation of adjustments and feedbacks for the interpretation of inter-model spread in climate sensitivity estimates. We show that in climate model simulations with large forcing (e.g., 4 × CO₂), nonlinearities cannot be assumed minor nor neglected. Having said that, most results presented here are consistent with a number of previous feedback studies, despite the very different nature of the methodologies and all the uncertainties associated with them.     

Storm track response to ocean fronts in a global high-resolution climate model

Synoptic atmospheric eddies are affected by lower tropospheric air-temperature gradients and by turbulent heat fluxes from the surface. In this study we examine how ocean fronts affect these quantities and hence the storm tracks. We focus on two midlatitude regions where ocean fronts lie close to the storm tracks: the north-west Atlantic and the Southern Ocean. An atmospheric climate model of reasonably high resolution (~50 km) is applied in a climate-length (60 year) simulation in order to obtain stable statistics. Simulations with frontal structure in the sea surface temperature (SST) in one of the regions are compared against simulations with globally smoothed SST. We show that in both regions the ocean fronts have a strong influence on the transient eddy heat and moisture fluxes, not just in the boundary layer, but also in the free troposphere. Local differences in these quantities between the simulations reach 20–40 % of the maximum values in the simulation with smoothed SST. Averaged over the entire region of the storm track over the ocean the corresponding differences are 10–20 %. The effect on the transient eddy meridional wind variance is strong in the boundary layer but relatively weak above that. The potential mechanisms by which the ocean fronts influence the storm tracks are discussed, and our results are compared against previous studies with regional models, Aquaplanet models, and coarse resolution coupled models.     

On the persistent spread in snow-albedo feedback

Snow-albedo feedback (SAF) is examined in 25 climate change simulations participating in the Coupled Model Intercomparison Project version 5 (CMIP5). SAF behavior is compared to the feedback’s behavior in the previous (CMIP3) generation of global models. SAF strength exhibits a fivefold spread across CMIP5 models, ranging from 0.03 to 0.16 W m^?2 K^?1 (ensemble-mean = 0.08 W m^?2 K^?1). This accounts for much of the spread in 21st century warming of Northern Hemisphere land masses, and is very similar to the spread found in CMIP3 models. As with the CMIP3 models, there is a high degree of correspondence between the magnitudes of seasonal cycle and climate change versions of the feedback. Here we also show that their geographical footprint is similar. The ensemble-mean SAF strength is close to an observed estimate of the real climate’s seasonal cycle feedback strength. SAF strength is strongly correlated with the climatological surface albedo when the ground is covered by snow. The inter-model variation in this quantity is surprisingly large, ranging from 0.39 to 0.75. Models with large surface albedo when these regions are snow-covered will also have a large surface albedo contrast between snow-covered and snow-free regions, and therefore a correspondingly large SAF. Widely-varying treatments of vegetation masking of snow-covered surfaces are probably responsible for the spread in surface albedo where snow occurs, and the persistent spread in SAF in global climate models.     

Predictability of the western North Pacific summer climate demonstrated by the coupled models of ENSEMBLES

The Asian monsoon system, including the western North Pacific (WNP), East Asian, and Indian monsoons, dominates the climate of the Asia-Indian Ocean-Pacific region, and plays a significant role in the global hydrological and energy cycles. The prediction of monsoons and associated climate features is a major challenge in seasonal time scale climate forecast. In this study, a comprehensive assessment of the interannual predictability of the WNP summer climate has been performed using the 1-month lead retrospective forecasts (hindcasts) of five state-of-the-art coupled models from ENSEMBLES for the period of 1960–2005. Spatial distribution of the temporal correlation coefficients shows that the interannual variation of precipitation is well predicted around the Maritime Continent and east of the Philippines. The high skills for the lower-tropospheric circulation and sea surface temperature (SST) spread over almost the whole WNP. These results indicate that the models in general successfully predict the interannual variation of the WNP summer climate. Two typical indices, the WNP summer precipitation index and the WNP lower-tropospheric circulation index (WNPMI), have been used to quantify the forecast skill. The correlation coefficient between five models’ multi-model ensemble (MME) mean prediction and observations for the WNP summer precipitation index reaches 0.66 during 1979–2005 while it is 0.68 for the WNPMI during 1960–2005. The WNPMI-regressed anomalies of lower-tropospheric winds, SSTs and precipitation are similar between observations and MME. Further analysis suggests that prediction reliability of the WNP summer climate mainly arises from the atmosphere–ocean interaction over the tropical Indian and the tropical Pacific Ocean, implying that continuing improvement in the representation of the air–sea interaction over these regions in CGCMs is a key for long-lead seasonal forecast over the WNP and East Asia. On the other hand, the prediction of the WNP summer climate anomalies exhibits a remarkable spread resulted from uncertainty in initial conditions. The summer anomalies related to the prediction spread, including the lower-tropospheric circulation, SST and precipitation anomalies, show a Pacific-Japan or East Asia-Pacific pattern in the meridional direction over the WNP. Our further investigations suggest that the WNPMI prediction spread arises mainly from the internal dynamics in air–sea interaction over the WNP and Indian Ocean, since the local relationships among the anomalous SST, circulation, and precipitation associated with the spread are similar to those associated with the interannual variation of the WNPMI in both observations and MME. However, the magnitudes of these anomalies related to the spread are weaker, ranging from one third to a half of those anomalies associated with the interannual variation of the WNPMI in MME over the tropical Indian Ocean and subtropical WNP. These results further support that the improvement in the representation of the air–sea interaction over the tropical Indian Ocean and subtropical WNP in CGCMs is a key for reducing the prediction spread and for improving the long-lead seasonal forecast over the WNP and East Asia.     

The respective roles of surface temperature driven feedbacks and tropospheric adjustment to CO2 in CMIP5 transient climate simulations

An overview of radiative climate feedbacks and ocean heat uptake efficiency diagnosed from idealized transient climate change experiments of 14 CMIP5 models is presented. Feedbacks explain about two times more variance in transient climate response across the models than ocean heat uptake efficiency. Cloud feedbacks can clearly be identified as the main source of inter-model spread. Models with strong longwave feedbacks in the tropics feature substantial increases in cloud ice around the tropopause suggestive of changes in cloud-top heights. The lifting of the tropical tropopause goes together with a general weakening of the tropical circulation. Distinctive inter-model differences in cloud shortwave feedbacks occur in the subtropics including the equatorward flanks of the storm-tracks. Related cloud fraction changes are not confined to low clouds but comprise middle level clouds as well. A reduction in relative humidity through the lower and mid troposphere can be identified as being the main associated large-scale feature. Experiments with prescribed sea surface temperatures are analyzed in order to investigate whether the diagnosed feedbacks from the transient climate simulations contain a tropospheric adjustment component that is not conveyed through the surface temperature response. The strengths of the climate feedbacks computed from atmosphere-only experiments with prescribed increases in sea surface temperatures, but fixed CO₂ concentrations, are close to the ones derived from the transient experiment. Only the cloud shortwave feedback exhibits discernible differences which, however, can not unequivocally be attributed to tropospheric adjustment to CO₂. Although for some models a tropospheric adjustment component is present in the global mean shortwave cloud feedback, an analysis of spatial patterns does not lend support to the view that cloud feedbacks are dominated by their tropospheric adjustment part. Nevertheless, there is positive correlation between the strength of tropospheric adjustment processes and cloud feedbacks across different climate models.     

Are band-pass variance statistics useful measures of storm track activity? Re-examining storm track variability associated with the NAO using multiple storm track measures

Over the past few decades, band-pass filtered (BP) variance statistics have been widely used as indicators of storm track activity. A recent study suggested that these statistics may be subjected to biases related to Doppler shifting of variance into and out of the fixed frequency band, in the process perhaps greatly exaggerating the correlation between BP variance and mean flow variability. In this study, BP statistics are examined together with other storm track measures to assess whether BP variances are useful indicators of the patterns of storm track activity. Storm track variability related to the North Atlantic Oscillation, as well as the five leading EOFs of 300 hPa BP filtered variance statistics, have been examined. Results presented here suggest that BP variance statistics are useful measures of the patterns of storm track activity. Firstly, BP variance statistics largely reflect changes in total unfiltered transient eddy variance as well as spatially filtered statistics. Secondly, different BP statistics all give qualitatively similar patterns. Thirdly, patterns derived from BP statistics are well correlated (spatially) with precipitation anomalies. In addition, BP statistics are straightforward to compute, and easily reproducible. Moreover, BP variance and covariance statistics are closely related to how storm tracks interact with the large scale circulation. However, results shown in this paper support the suggestion that some biases may be caused by the Doppler effect, especially for variations such as the NAO which are tightly tied to changes in the background flow speed. Thus it is argued that BP statistics should be examined together with other measures of storm track activity to obtain a broader perspective on storm track variations.     

Extremes of near-surface wind speed over Europe and their future changes as estimated from an ensemble of RCM simulations

In this study, we analyse the uncertainty of the effect of enhanced greenhouse gas conditions on windiness projected by an ensemble of regional model simulations driven by the same global control and climate change simulations. These global conditions, representative for 1961–1990 and 2071–2100, were prepared by the Hadley Centre based on the IPCC SRES/A2 scenario. The basic data sets consist of simulated daily maximum and daily mean wind speed fields (over land) from the PRUDENCE data archive at the Danish Meteorological Institute. The main focus is on the results from the standard 50 km-resolution runs of eight regional models. The best parameter for determining possible future changes in extreme wind speeds and possible change in the number of storm events is maximum daily wind speed. It turned out during this study that the method for calculating maximum daily wind speed differs among the regional models. A comparison of simulated winds with observations for the control period shows that models without gust parameterisation are not able to realistically capture high wind speeds. The two models with gust parametrization estimate an increase of up to 20% of the number of storm peak (defined as gusts?≥?8 Bft in this paper) events over Central Europe in the future. In order to use a larger ensemble of models than just the two with gust parameterisation, we also look at the 99th percentile of daily mean wind speed. We divide Europe into eight sub-regions (e.g., British Isles, Iberian Peninsula, NE Europe) and investigate the inter-monthly variation of wind over these regions as well as differences between today’s climate and a possible future climate. Results show differences and similarities between the sub-regions in magnitude, spread, and seasonal tendencies. The model ensemble indicates a possible increase in future mean daily wind speed during winter months, and a decrease during autumn in areas influenced by North Atlantic extra-tropical cyclones.     

European temperatures in CMIP5: origins of present-day biases and future uncertainties

European temperatures and their projected changes under the 8.5 W/m² Representative Concentration Pathway scenario are evaluated in an ensemble of 33 global climate models participating in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Respective contributions of large-scale dynamics and local processes to both biases and changes in temperatures, and to the inter-model spread, are then investigated from a recently proposed methodology based on weather regimes. On average, CMIP5 models exhibit a cold bias in winter, especially in Northern Europe. They overestimate summer temperatures in Central Europe, in association with a greater diurnal range than observed. The projected temperature increase is stronger in summer than in winter, with the highest summer warming occurring over Mediterranean regions. Links between biases and sensitivities are evidenced in winter, suggesting a potential influence of snow cover biases on the projected surface warming. A brief analysis of daily temperature extremes suggests that the intra-seasonal variability is projected to decrease (slightly increase) in winter (summer). Then, in order to understand model discrepancies in both present-day and future climates, we disentangle effects of large-scale atmospheric dynamics and regional physical processes. In particular, in winter, CMIP5 models simulate a stronger North-Atlantic jet stream than observed and, in contrast with CMIP3 results, the majority of them suggests an increased frequency of the negative phase of the North-Atlantic Oscillation under future warming. While large-scale circulation only has a minor contribution to ensemble-mean biases or changes, which are primarily dominated by non-dynamical processes, it substantially affects the inter-model spread. Finally, other sources of uncertainties, including the North-Atlantic warming and local radiative feedbacks related to snow cover and clouds, are briefly discussed.     

Understanding uncertainty in future projections for the tropical Atlantic: relationships with the unforced climate

Through its control on the marine ITCZ, future changes in the tropical Atlantic meridional sea-surface temperature gradient (TAG) could have important impacts, on regional to global scales. We study the inter-model spread of projected TAG trends in response to increasing CO₂, using results from 19 coupled GCMs which took part in the IPCC fourth assessment. Some models project substantial changes, with the smallest changes being in boreal autumn. There is substantial uncertainty, with no consistency even in the sign of change, and an ensemble mean close to zero. However, a strong statistical relationship is found between the simulated magnitudes of TAG trends and unforced TAG variability. Models with larger unforced variability in December–February show larger magnitude trends. We speculate that this relationship may be due to an underlying system of feedbacks whose strength varies considerably from model to model (the unforced variability ranges by a factor of 3 amongst these models, and the models exhibit large differences in mean state). We present evidence from further analysis and the literature to suggest which physical mechanisms may be involved. In particular, models projecting larger(smaller) magnitude TAG trends have larger(smaller) SST variability and cooler(warmer) mean SST in not just the Atlantic, but all three tropical/sub-tropical oceans, especially in the southern hemisphere near eastern coasts. These results could assist efforts to understand model errors in present and future tropical climate, and to develop observational constraints on future tropical projections.     

冬季北半球风暴轴的多尺度能量变化特征及其可能机制

基于1971—2016年NCEP/NCAR(美国环境预报中心和国家大气研究中心)的逐日再分析资料及NCPC(美国国家海洋和大气管理局气候预报中心)的海温、大气环流及海洋指数等资料通过多尺度能量分析(MS-EVA)等方法,把冬季北半球风暴轴看做一整体,分析了风暴轴区域多尺度的能量变化特征及其可能机制。主要结论概括如下:(1)多年气候平均状态下,风暴轴的动能来源主要表现为在风暴轴中上游先由低频尺度向天气尺度输送有效位能,随后在风暴轴主体区再由天气尺度有效位能转换为天气尺度动能,其中风暴轴西端可直接由低频尺度向天气尺度输送动能。(2)北半球三大风暴轴联合EOF结果表明:第一模态下,主要体现了北西伯利亚风暴轴与北太平洋风暴轴强度的减弱(增强),同时伴随着北大西洋风暴轴位置北抬(南压);第二模态下,主要体现了北西伯利亚风暴轴强度减弱(增强),同时北太平洋风暴轴位置北抬(南压)中东部强度增强(减弱),而北大西洋风暴轴位置南压(北抬)。(3)回归分析表明:北半球风暴轴异常在不同模态下与低频尺度环流联系密切。低频尺度波动可通过海温及西风急流等异常变化先影响风暴轴区域多尺度间的能量转换,进而影响风暴轴整体的异常变化。     

Sources of uncertainty in projections of twenty-first century westerly wind changes over the Amundsen Sea,West Antarctica,in CMIP5 climate models

The influence of changes in winds over the Amundsen Sea has been shown to be a potentially key mechanism in explaining rapid loss of ice from major glaciers in West Antarctica, which is having a significant impact on global sea level. Here, Coupled Model Intercomparison Project Phase 5 (CMIP5) climate model data are used to assess twenty-first century projections in westerly winds over the Amundsen Sea (U _AS ). The importance of model uncertainty and internal climate variability in RCP4.5 and RCP8.5 scenario projections are quantified and potential sources of model uncertainty are considered. For the decade 2090–2099 the CMIP5 models show an ensemble mean twenty-first century response in annual mean U _AS of 0.3 and 0.7 m s^?1 following the RCP4.5 and RCP8.5 scenarios respectively. However, as a consequence of large internal climate variability over the Amundsen Sea, it takes until around 2030 (2065) for the RCP8.5 response to exceed one (two) standard deviation(s) of decadal internal variability. In all scenarios and seasons the model uncertainty is large. However the present-day climatological zonal wind bias over the whole South Pacific, which is important for tropical teleconnections, is strongly related to inter-model differences in projected change in U _AS (more skilful models show larger U _AS increases). This relationship is significant in winter (r = ?0.56) and spring (r = ?0.65), when the influence of the tropics on the Amundsen Sea region is known to be important. Horizontal grid spacing and present day sea ice extent are not significant sources of inter-model spread.     

On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles

Global and local feedback analysis techniques have been applied to two ensembles of mixed layer equilibrium CO₂ doubling climate change experiments, from the CFMIP (Cloud Feedback Model Intercomparison Project) and QUMP (Quantifying Uncertainty in Model Predictions) projects. Neither of these new ensembles shows evidence of a statistically significant change in the ensemble mean or variance in global mean climate sensitivity when compared with the results from the mixed layer models quoted in the Third Assessment Report of the IPCC. Global mean feedback analysis of these two ensembles confirms the large contribution made by inter-model differences in cloud feedbacks to those in climate sensitivity in earlier studies; net cloud feedbacks are responsible for 66% of the inter-model variance in the total feedback in the CFMIP ensemble and 85% in the QUMP ensemble. The ensemble mean global feedback components are all statistically indistinguishable between the two ensembles, except for the clear-sky shortwave feedback which is stronger in the CFMIP ensemble. While ensemble variances of the shortwave cloud feedback and both clear-sky feedback terms are larger in CFMIP, there is considerable overlap in the cloud feedback ranges; QUMP spans 80% or more of the CFMIP ranges in longwave and shortwave cloud feedback. We introduce a local cloud feedback classification system which distinguishes different types of cloud feedbacks on the basis of the relative strengths of their longwave and shortwave components, and interpret these in terms of responses of different cloud types diagnosed by the International Satellite Cloud Climatology Project simulator. In the CFMIP ensemble, areas where low-top cloud changes constitute the largest cloud response are responsible for 59% of the contribution from cloud feedback to the variance in the total feedback. A similar figure is found for the QUMP ensemble. Areas of positive low cloud feedback (associated with reductions in low level cloud amount) contribute most to this figure in the CFMIP ensemble, while areas of negative cloud feedback (associated with increases in low level cloud amount and optical thickness) contribute most in QUMP. Classes associated with high-top cloud feedbacks are responsible for 33 and 20% of the cloud feedback contribution in CFMIP and QUMP, respectively, while classes where no particular cloud type stands out are responsible for 8 and 21%.     

Ocean Response to a Climate Change Heat-Flux Perturbation in an Ocean Model and Its Corresponding Coupled Model

State-of-the-art coupled general circulation models(CGCMs)are used to predict ocean heat uptake(OHU)and sealevel change under global warming.However,the projections of different models vary,resulting in high uncertainty.Much of the inter-model spread is driven by responses to surface heat perturbations.This study mainly focuses on the response of the ocean to a surface heat flux perturbation F,as prescribed by the Flux-Anomaly-Forced Model Intercomparison Project(FAFMIP).The results of ocean model were compared with those of a CGCM with the same ocean component.On the global scale,the changes in global mean temperature,ocean heat content(OHC),and steric sea level(SSL)simulated in the OGCM are generally consistent with CGCM simulations.Differences in changes in ocean temperature,OHC,and SSL between the two models primarily occur in the Arctic and Atlantic Oceans(AA)and the Southern Ocean(SO)basins.In addition to the differences in surface heat flux anomalies between the two models,differences in heat exchange between basins also play an important role in the inconsistencies in ocean climate changes in the AA and SO basins.These discrepancies are largely due to both the larger initial value and the greater weakening change of the Atlantic meridional overturning circulation(AMOC)in CGCM.The greater weakening of the AMOC in the CGCM is associated with the atmosphere–ocean feedback and the lack of a restoring salinity boundary condition.Furthermore,differences in surface salinity boundary conditions between the two models contribute to discrepancies in SSL changes.     

The use of the land-sea warming contrast under climate change to improve impact metrics

A favoured method of assimilating information from state-of-the-art climate models into integrated assessment models of climate impacts is to use the transient climate response (TCR) of the climate models as an input, sometimes accompanied by a pattern matching approach to provide spatial information. More recent approaches to the problem use TCR with another independent piece of climate model output: the land-sea surface warming ratio (φ). In this paper we show why the use of φ in addition to TCR has such utility. Multiple linear regressions of surface temperature change onto TCR and φ in 22 climate models from the CMIP3 multi-model database show that the inclusion of φ explains a much greater fraction of the inter-model variance than using TCR alone. The improvement is particularly pronounced in North America and Eurasia in the boreal summer season, and in the Amazon all year round. The use of φ as the second metric is beneficial for three reasons: firstly it is uncorrelated with TCR in state-of-the-art climate models and can therefore be considered as an independent metric; secondly, because of its projected time-invariance, the magnitude of φ is better constrained than TCR in the immediate future; thirdly, the use of two variables is much simpler than approaches such as pattern scaling from climate models. Finally we show how using the latest estimates of φ from climate models with a mean value of 1.6—as opposed to previously reported values of 1.4—can significantly increase the mean time-integrated discounted damage projections in a state-of-the-art integrated assessment model by about 15 %. When compared to damages calculated without the inclusion of the land-sea warming ratio, this figure rises to 65 %, equivalent to almost 200 trillion dollars over 200 years.     

Quasi-stationarity of centennial Northern Hemisphere midlatitude winter storm tracks

The winter storm activity on the Northern Hemisphere during the last one thousand years in a global climate simulation was analyzed by determining all midlatitude storms and their tracks, then consecutively clustering them for hundred years’ segments. Storm track clusters with longest lifetime and largest deepening rates are found over the oceans. The numbers of extratropical winter storms exhibit notable yearly variability but hardly any variability on centennial time scales. The clusters of these storm tracks also show only small differences between the centuries. The numbers of members in neighboring oceanic clusters are negatively correlated. A linear relationship was found between the numbers of members per storm track clusters over the Pacific or Atlantic Ocean and seasonal mean atmospheric circulation patterns by a canonical correlation analysis.     

Modelling daily temperature extremes: recent climate and future changes over Europe

Probability distributions of daily maximum and minimum temperatures in a suite of ten RCMs are investigated for (1) biases compared to observations in the present day climate and (2) climate change signals compared to the simulated present day climate. The simulated inter-model differences and climate changes are also compared to the observed natural variability as reflected in some very long instrumental records. All models have been forced with driving conditions from the same global model and run for both a control period and a future scenario period following the A2 emission scenario from IPCC. We find that the bias in the fifth percentile of daily minimum temperatures in winter and at the 95th percentile of daily maximum temperature during summer is smaller than 3 (±5°C) when averaged over most (all) European sub-regions. The simulated changes in extreme temperatures both in summer and winter are larger than changes in the median for large areas. Differences between models are larger for the extremes than for mean temperatures. A comparison with historical data shows that the spread in model predicted changes in extreme temperatures is larger than the natural variability during the last centuries.     

Coupling between subtropical cloud feedback and the local hydrological cycle in a climate model

In HadGEM2-A, AMIP experiments forced with observed sea surface temperatures respond to uniform and patterned +4 K SST perturbations with strong positive cloud feedbacks in the subtropical stratocumulus/trade cumulus transition regions. Over the subtropical Northeast Pacific at 137°W/26°N, the boundary layer cloud fraction reduces considerably in the AMIP +4 K patterned SST experiment. The near-surface wind speed and the air-sea temperature difference reduces, while the near-surface relative humidity increases. These changes limit the local increase in surface evaporation to just 3 W/m² or 0.6 %/K. Previous studies have suggested that increases in surface evaporation may be required to maintain maritime boundary layer cloud in a warmer climate. This suggests that the supply of water vapour from surface evaporation may not be increasing enough to maintain the low level cloud fraction in the warmer climate in HadGEM2-A. Sensitivity tests which force the surface evaporation to increase substantially in the +4 K patterned SST experiment result in smaller changes in boundary layer cloud and a weaker cloud feedback in HadGEM2-A, supporting this idea. Although global mean surface evaporation in climate models increases robustly with global temperature (and the resulting increase in atmospheric radiative cooling), local values may increase much less, having a significant impact on cloud feedback. These results suggest a coupling between cloud feedback and the hydrological cycle via changes in the patterns of surface evaporation. A better understanding of both the factors controlling local changes in surface evaporation and the sensitivity of clouds to such changes may be required to understand the reasons for inter-model differences in subtropical cloud feedback.     

Potential role of winter rainfall in explaining increased moisture in the Mediterranean and Middle East during periods of maximum orbitally-forced insolation seasonality

Precession-related forcing of seasonal insolation changes in the northern hemisphere (NH) alternates between maximum NH seasonality (summer perihelion–increased insolation; winter aphelion–decreased insolation) and minimum NH seasonality (summer aphelion, and winter perihelion). With maximum NH seasonality, climate models simulate stronger NH summer monsoons that bring increased precipitation to North Africa and South and East Asia, in agreement with the in-phase relation of precipitation and NH summer insolation found in many paleoclimatic records. However paleoclimatic records in parts of the Mediterranean, the Middle East, and the interior of Asia also indicate increased moisture at times of maximum NH seasonality, a change not always clearly linked to stronger summer monsoons—either because these regions are at or beyond the boundaries of the present-day monsoon or because the observations allow multiple causal interpretations, or both. This study focuses on the possible role of changes in NH winter climate in explaining these wetter episodes. Using climate model simulations, we show that the ‘NH winter aphelion–decreased NH winter insolation’ orbital configuration is linked to the Mediterranean storm track and increased winter rains in the Mediterranean, the Middle East, and interior Asia. We conclude that wetter periods at precession time scales in these particular regions may have resulted either from increased wintertime storm track precipitation, or from a combination of increased winter and summer rainfall. Given this seasonal ambiguity, both possibilities need to be considered.     

Interdecadal changes in the storm track activity over the North Pacific and North Atlantic

Analysis of NCEP-NCAR I reanalysis data of 1948–2009 and ECMWF ERA-40 reanalysis data of 1958–2001 reveals several significant interdecadal changes in the storm track activity and mean flow-transient eddy interaction in the extratropics of Northern Hemisphere. First, the most remarkable transition in the North Pacific storm track (PST) and the North Atlantic storm track (AST) activities during the boreal cold season (from November to March) occurred around early-to-mid 1970s with the characteristics of global intensification that has been noticed in previous studies. Second, the PST activity in midwinter underwent decadal change from a weak regime in the early 1980s to a strong regime in the late 1980s. Third, during recent decade, the PST intensity has been enhanced in early spring whereas the AST intensity has been weakened in midwinter. Finally, interdecadal change has been also noted in the relationship between the PST and AST activities and between the storm track activity and climate indices. The variability of storm track activity is well correlated with the Pacific Decadal Oscillation and North Atlantic Oscillation prior to the early 1980s, but this relationship has disappeared afterward and a significant linkage between the PST and AST activity has also been decoupled. For a better understanding of the mid-1970s’ shift in storm track activity and mean flow-transient eddy interaction, further investigation is made by analyzing local barotropic and baroclinic energetics. The intensification of global storm track activity after the mid-1970s is mainly associated with the enhancement of mean meridional temperature gradient resulting in favorable condition for baroclinic eddy growth. Consistent with the change in storm track activity, the baroclinic energy conversion is significantly increased in the North Pacific and North Atlantic. The intensification of the PST and AST activity, in turn, helps to reinforce the changes in the middle-to-upper tropospheric circulation but acts to interfere with the changes in the low-tropospheric temperature field.     

Sources of CAM3 temperature bias during northern winter from diagnostic study of the temperature bias equation

The Community Atmosphere Model version 3 (CAM3) temperature simulation bias is examined in this paper. We compare CAM3 output with European Centre for Medium-Range Weather Forecasts (ECMWF) 40 year reanalysis (ERA-40) data. We formulate a time mean temperature bias equation then evaluate each term in the equation. Our focus is on the Northern Hemisphere winter time. We group the temperature equation terms into these categories: linear advection terms, nonlinear advection terms, transient eddy terms and diabatic heating, and find that linear advection and diabatic bias are the largest. The nonlinear terms (velocity bias advection of temperature bias) are much smaller than each of the other groups of terms at all levels except near the surface. Linear advection terms have dipolar pattern in the Atlantic (negative NW of positive) which reflects the shift of the CAM3 model North Atlantic storm track (NAST) into Europe, especially in the upper troposphere; opposite sign dipolar structure occurs over Alaska (positive) and the north Pacific storm track (negative). The transient advection terms in middle latitudes are larger in the upper troposphere and generally positive along the Atlantic storm track. Along the north Pacific storm track (NPST), the transient terms are negative in the mid and lower troposphere over much of the NPST (positive in upper troposphere). The diabatic heating bias has large values in the tropics along the Intertropical Convergence Zone (ICZ) and along the midlatitude storm tracks. During this time of year the ICZ is mainly in the Southern Hemisphere, but CAM3 emphasizes an ICZ-like heating in the northern hemisphere of the Atlantic and Pacific Oceans. CAM3 tends to have a weaker ICZ, especially in the Atlantic. In midlatitudes, we find large bias in heating by precipitation and vertically averaged net radiation over the NAST, Europe, and the Middle East.