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Climate change projections are commonly based on multi-model ensembles of climate simulations. In this paper we consider the choice of bias models in Bayesian multimodel predictions. Buser et al. (Clim Res 44(2-3):227-241, 2010a) introduced a hybrid bias model which combines commonly used constant bias and constant relation bias assumptions. The hybrid model includes a weighting parameter which balances these bias models. In this study, we use a cross-validation approach to study which bias model or bias parameter leads to, in a specific sense, optimal climate change projections. The analysis is carried out for summer and winter season means of 2 m-temperatures spatially averaged over the IPCC SREX regions, using 19 model runs from the CMIP5 data set. The cross-validation approach is applied to calculate optimal bias parameters (in the specific sense) for projecting the temperature change from the control period (1961-2005) to the scenario period (2046-2090). The results are compared to the results of the Buser et al. (Clim Res 44(2-3):227-241, 2010a) method which includes the bias parameter as one of the unknown parameters to be estimated from the data. [ABSTRACT FROM AUTHOR]

On the basis of climate zones classified by the number of days of the daily average temperature ≥ 10 °C (DT10) over China, the performance of the 9 CMIP5 climate models is evaluated in this paper. The results indicate that the CMCC-CMS and MPI-ESM-MR show higher skill than the other 7 models in simulating spatial pattern and its decadal change of climate zones over China. The simulation results for FGOALS-g2 and INM-CM4 both show relatively lower skill than the other 7 models. Meanwhile, the performance of multi-model ensemble in simulating climate zones over China is obviously better than the simulated result of any single model. So, it is a good way to simulate climate zones by multi-model ensemble to reduce some uncertainty of climate models. However, it is crucial to select appropriate ensemble members. Compared with 1960-2005, the climatic zones in China have an obvious trend of northward shift in 2021-2100. The range of southern sub-tropical belt expands to the most areas in the south of Yangtze River under RCP4.5 emission scenarios, and further extends to the north areas of Yangtze River with a maximum of 2-6° of latitude under RCP8.5 emission scenarios. Middle sub-tropical belt shifts gradually to the areas between Yellow River and north areas of the middle and lower reaches of the Yangtze River. Northern sub-tropical belt shifts northward to southeastern North China. Warm extra-tropical belt extends to the most of Northeast China, most of central Inner Mongolia, and northern Xinjiang under RCP8.5 emission scenarios. [ABSTRACT FROM AUTHOR]

The possible change in the characteristics of weather in the future should be considered as important as the mean climate change because the increasing risk of extremes is related to the variability on daily time scales. The weather characteristics can be represented by the climatological mean interdiurnal (day-to-day) variability (MIDV). This paper first assessed the phase five of the Coupled Model Intercomparison Project coupled climate models’ capability to represent MIDV for the surface maximum and minimum temperature, surface wind speed and precipitation under the present climate condition. Based on the assessment, we selected three best models for projecting future change. We found that the future changes in MIDV are characterized by: (a) a marked reduction in surface maximum and minimum temperature over high latitudes during the cold season; (b) a stronger reduction in the surface minimum temperature than in the maximum temperature; (c) a reduction in surface wind speed over large parts of lands in Northern Hemisphere (NH) during NH spring; (d) a noticeable increase in precipitation in NH mid-high latitudes in NH spring and winter, and in particular over East Asia throughout most of the year. [ABSTRACT FROM AUTHOR]

Decadal predictions have a high profile in the climate science community and beyond, yet very little is known about their skill. Nor is there any agreed protocol for estimating their skill. This paper proposes a sound and coordinated framework for verification of decadal hindcast experiments. The framework is illustrated for decadal hindcasts tailored to meet the requirements and specifications of CMIP5 (Coupled Model Intercomparison Project phase 5). The chosen metrics address key questions about the information content in initialized decadal hindcasts. These questions are: (1) Do the initial conditions in the hindcasts lead to more accurate predictions of the climate, compared to un-initialized climate change projections? and (2) Is the prediction model's ensemble spread an appropriate representation of forecast uncertainty on average? The first question is addressed through deterministic metrics that compare the initialized and uninitialized hindcasts. The second question is addressed through a probabilistic metric applied to the initialized hindcasts and comparing different ways to ascribe forecast uncertainty. Verification is advocated at smoothed regional scales that can illuminate broad areas of predictability, as well as at the grid scale, since many users of the decadal prediction experiments who feed the climate data into applications or decision models will use the data at grid scale, or downscale it to even higher resolution. An overall statement on skill of CMIP5 decadal hindcasts is not the aim of this paper. The results presented are only illustrative of the framework, which would enable such studies. However, broad conclusions that are beginning to emerge from the CMIP5 results include (1) Most predictability at the interannual-to-decadal scale, relative to climatological averages, comes from external forcing, particularly for temperature; (2) though moderate, additional skill is added by the initial conditions over what is imparted by external forcing alone; however, the impact of initialization may result in overall worse predictions in some regions than provided by uninitialized climate change projections; (3) limited hindcast records and the dearth of climate-quality observational data impede our ability to quantify expected skill as well as model biases; and (4) as is common to seasonal-to-interannual model predictions, the spread of the ensemble members is not necessarily a good representation of forecast uncertainty. The authors recommend that this framework be adopted to serve as a starting point to compare prediction quality across prediction systems. The framework can provide a baseline against which future improvements can be quantified. The framework also provides guidance on the use of these model predictions, which differ in fundamental ways from the climate change projections that much of the community has become familiar with, including adjustment of mean and conditional biases, and consideration of how to best approach forecast uncertainty. [ABSTRACT FROM AUTHOR]

This paper provides a first overview of the performance of global climate models participating in the Coupled Model Inter-Comparison Project phase 5 (CMIP5) in simulating the upper troposphere and lower stratosphere (UTLS) temperatures. Temperature from CMIP5 models is evaluated with high resolution global positioning system radio occultation (GPSRO) constellation observing system for meteorology, ionosphere, and climate (COSMIC) data during the period of July 2006-December 2013. Future projections of 17 CMIP5 models based on the representative concentration pathway (RCP) 8.5 scenarios are utilized to assess model performance and to identify the biases in the temperature in the UTLS region at eight different pressure levels. The evaluations were carried out vertically, regionally, and globally to understand the temperature uncertainties in CMIP5 models. It is found that the CMIP5 models successfully reproduce the general features of temperature structure in terms of vertical, annual, and inter-annual variation. The ensemble mean of CMIP5 models compares well with the COSMIC GPSRO data with a mean difference of ±1 K. In the tropical region, temperature biases vary from one model to another. The spatial difference between COSMIC and ensemble mean reveals that at 100 hPa, the models show a bias of about ±2 K. With increase in altitude the bias decreases and turns into a cold bias over the tropical and Antarctic regions. The future projections of the CMIP5 models were presented during 2006-2099 under the RCP 8.5 scenarios. Projections show a warming trend at 300, 200, and 100 hPa levels over a wide region of 60°N-45°S. The warming decreases rapidly and becomes cooling with increase in altitudes by the end of twenty-first century. Significant cooling is observed at 30, 20, and 10 hPa levels. At 300/10 hPa, the temperature trend increases/decreases by ~0.82/0.88 K/decade at the end of twenty-first century under RCP 8.5 scenarios. [ABSTRACT FROM AUTHOR]

Land-sea surface air temperature (SAT) contrast, an index of tropospheric thermodynamic structure and dynamical circulation, has shown a significant increase in recent decades over East Asia during the boreal summer. In Part I of this two-part paper, observational data and the results of transient warming experiments conducted using coupled atmosphere-ocean general circulation models (GCMs) are analyzed to examine changes in land-sea thermal contrast and the associated atmospheric circulation over East Asia from the past to the future. The interannual variability of the land-sea SAT contrast over the Far East for 1950-2012 was found to be tightly coupled with a characteristic tripolar pattern of tropospheric circulation over East Asia, which manifests as anticyclonic anomalies over the Okhotsk Sea and around the Philippines, and a cyclonic anomaly over Japan during a positive phase, and vice versa. In response to CO increase, the cold northeasterly winds off the east coast of northern Japan and the East Asian rainband were strengthened with the circulation pattern well projected on the observed interannual variability. These results are commonly found in GCMs regardless of future forcing scenarios, indicating the robustness of the East Asian climate response to global warming. The physical mechanisms responsible for the increase of the land-sea contrast are examined in Part II. [ABSTRACT FROM AUTHOR]

This is the second of the two-part paper series on the analysis and evaluation of the Fifth phase of Coupled Model Intercomparison Project (CMIP5) simulation of contemporary climate as well as IPCC, AR5 Representative Concentrations Pathways (RCP), 4.5 and 8.5 scenarios projections of the Greater Horn of Africa (GHA) Climate. In the first part (Otieno and Anyah in Clim Dyn, ) we focused on the historical simulations, whereas this second part primarily focuses on future projections based on the two scenarios. Six Earth System Models (ESMs) from CMIP5 archive have been used to characterize projected changes in seasonal and annual mean precipitation, temperature and the hydrological cycle by the middle of twenty-first century over the GHA region, based on IPCC, 5th Assessment Report (AR5) RCP4.5 and RCP8.5 scenarios. Nearly all the models outputs analyzed reproduce the correct mean annual cycle of precipitation, with some biases among the models in capturing the correct peak of precipitation cycle, more so, March-April-May (MAM) seasonal rainfall over the equatorial GHA region. However, there is significant variation among models in projected precipitation anomalies, with some models projecting an average increase as others project a decrease in precipitation during different seasons. The ensemble mean of the ESMs indicates that the GHA region has been experiencing a steady increase in both precipitation and temperature beginning in the early 1980s and 1970s respectively in both RCP4.5 and RCP8.5 scenarios. Going by the ensemble means, temperatures are projected to steadily increase uniformly in all the seasons at a rate of 0.3/0.5 °C/decade under RCP4.5/8.5 scenarios over northern GHA region leading to an approximate temperature increase of 2/3 °C by the middle of the century. On the other hand, temperatures will likely increase at a rate of 0.3/0.4 °C/decade under RCP4.5/8.5 scenarios in both equatorial and southern GHA region leading to an approximate temperature increase of 2/2.5 °C by the middle of twenty-first century. Nonetheless, projected precipitation increase varied across seasons and sub-regions. With the exception of the equatorial region, that is projected to experience precipitation increase during DJF season, most sub-regions are projected to experience precipitation increase within their peak seasons, with the highest rate of increase experienced during DJF and OND seasons over southern and equatorial GHA regions respectively. Notably, as precipitation increases, the deficit (E < P) between evaporation (E) and precipitation (P) increased over the years, with a negatively skewed distribution. This generally implies that there is a high likelihood of an increased deficit in local moisture supply. This remarkable change in the general hydrological cycle (i.e. deficit in local moisture) is projected to be also coincident with intensified westerly anomaly influx from the Congo basin into the region. However, better understanding of the detailed changes in hydrological cycle will require comprehensive water budget analyses that require daily or sub-daily variables, and was not a specific focus of the present study. [ABSTRACT FROM AUTHOR]

The fifth phase of the Coupled Model Intercomparison Project (CMIP5) is the most recent coordinated experiment of global climate modeling. Compared to its predecessor CMIP3, the fifth phase of the homonymous experiment-CMIP5 involves a greater number of GCMs, run at higher resolutions with more complex components. Here we use daily GCM data from both projects to test their efficiency in representing precipitation and temperature parameters with the use of a state of the art high resolution gridded global dataset for land areas and for the period 1960-2005. Two simple metrics, a comprehensive histogram similarity metric based on the match of simulated and observed empirical pdfs and a metric for the representation of the annual cycle were employed as performance indicators. The metrics were used to assess the skill of each GCM at the entire spectrum of precipitation and temperature pdfs but also for the upper and lower tails of it. Results are presented globally and regionally for 26 land regions that represent different climatic regimes, covering the total earth's land surface except for Antarctica. Compared to CMIP3, CMIP5 models perform better in simulating precipitation including relatively intense events and the fraction of wet days. For temperature the improvement is not as clear except for the upper and lower hot and cold events of the distribution. The agreement of model simulations is also considerably increased in CMIP5. Substantial improvement in intense precipitation is observed over North Europe, Central and Eastern North America and North East Europe. Nevertheless, in both ensembles some models clearly perform better than others from a histogram similarity point of view. The derived skill score metrics provide essential information for impact studies based on global or regional land area multi-model ensembles. [ABSTRACT FROM AUTHOR]

Previous studies indicated that boreal spring North Atlantic horseshoe-like (NAH) sea surface temperature (SST) anomaly pattern has a significant impact on the surface air temperature (SAT) variation over the mid-high latitudes of Eurasia via an atmospheric wave train. This study investigates the connection of springtime NAH SST anomaly and the Eurasian SAT variation in thirty-two coupled climate models that participated in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Most of the CMIP5 models simulate well the spatial pattern of SST anomalies in the North Atlantic related to the spring NAH SST, but overestimate the spatial standard deviation. There exists large spreads in the connection of the spring NAH SST anomaly pattern and the Eurasian SAT variation among the CMIP5 models. The models that capture the observed spring NAH SST-Eurasian SAT connection can well reproduce the observed atmospheric wave train, in particular, with a marked anticyclonic anomaly over north Europe and a cyclonic anomaly over central Eurasia. This wave train results in above-normal SAT over west Europe and eastern Eurasia and below-normal SAT over central Eurasia. By contrast, the models that fail to reproduce the spring NAH SST-related Eurasian SAT anomalies show limitations in simulating the atmospheric wave train. Further analysis suggests that the models with larger climatological westerly winds over the mid-latitude North Atlantic and high-latitude Eurasia as well as lower climatological SST in the tropical northern Atlantic have a better ability in simulating the observed atmospheric wave train over the North Atlantic and Eurasia and thus perform better in simulating the spring NAH SST-Eurasian SAT connection. [ABSTRACT FROM AUTHOR]

This study evaluated the performance of 25 earth system models (ESMs), statistically and dynamically downscaled to a high horizontal resolution (0.25° of latitude/longitude), in simulating extreme climate indices of temperature and precipitation for 1980–2005. Datasets analyzed include 21 statistically downscaled ESMs from the National Aeronautics and Space Administration (NASA) Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) and dynamically downscaled Eta Regional Climate Model simulations driven by 4 ESMs generated by the Brazilian National Institute for Space Research (INPE). Downscaled outputs were evaluated against observational gridded datasets at 0.25° resolution over Brazil, quantifying the skill in simulating the observed spatial patterns and trends of climate extremes. Results show that the downscaled products are generally able to reproduce the observed climate indices, although most of them have poorest performance over the Amazon basin for annual and seasonal indices. We find larger discrepancies in the warm spell duration index for almost all downscaled ESMs. The overall ranking shows that three downscaled models (CNRM-CM5, CCSM4, and MRI-CGCM3) perform distinctively better than others. In general, the ensemble mean of the statistically downscaled models achieves better results than any individual models at the annual and seasonal scales. This work provides the largest and most comprehensive intercomparison of statistically and dynamically downscaled extreme climate indices over Brazil and provides a useful guide for researchers and developers to select the models or downscaling techniques that may be most suitable to their applications of interest over a given region. [ABSTRACT FROM AUTHOR]

The effects of climate change are currently a widely investigated issue. However, little attention has been paid to the effects of climate change on regional wave climate. With the growing need towards developing future projections of waves to assess climate-driven impacts on coastal processes, it is required to evaluate the performance of General Circulation Models (GCMs) and Regional Climate Models (RCMs) in simulating wave climate independent of their ability to simulate other standard variables. Near-surface winds, derived from GCMs participating in the Coupled Model Intercomparison Project (CMIP5) and RCMs from Coordinated Regional Climate Downscaling Experiment (CORDEX), are used to force a spectral wave model to simulate hindcast waves over Indian Ocean (IO) region. The GCM and RCM forced climatological wave characteristics (significant wave height, mean wave period, and mean wave direction) are compared with reanalysis data derived from ERA-Interim for performance evaluation. RCMs work at fine resolution and are assumed to simulate regional climate better than GCMs. However, we identified that there is no added value in simulating wave climate using RCMs. We also identified that there is no improvement in wave simulation upon choosing a fine resolution GCM (~ 1.4°) over a coarse GCM (~ 2.5°). Seasonality in wave characteristics is an important aspect in the IO. The skill of climate models in capturing seasonality was also evaluated. It is observed that ensemble GCM forced wave simulations capture seasonality better than other models. Finally, it is recommended to use ensemble GCM wind forcing for better wave simulation in the IO region. [ABSTRACT FROM AUTHOR]

The present study examines climatology and interannual variability of South Asian high (SAH) and its connection with the ENSO based on 38 coupled models from the Coupled Model Intercomparison Project phase 5 (CMIP5). Results show that multi-model ensemble (MME) can reasonably capture the climatological spatial pattern of the SAH, although its intensity is slightly underestimated. The CCSM4, CESM1-BGC and CESM1-FASTCHEM can well simulate the climatological location and intensity of the SAH. The interannual variability of the SAH is investigated by calculating ratio of the standard deviation of the ten parameters in models with those in observations. The results indicate that the MME can reasonably capture magnitudes of the interannual variability of the area index, intensity index, and longitude of the SAH center. Quasi-4-year period of the SAH intensity index can be well simulated by CMCC-CESM, CMCC-CMS and GFDL-ESM2G, and quasi-5-year period of north-south movement index can be captured by CanCM4, CESM1-CAM5, CESM1-FASTCHEM, CNRM-CM5-2, GFDL-ESM2G and HadCM3. Furthermore, MME can reasonably reproduce seasonal evolution of intensity and location of the SAH except for its east-west movement. The ENSO-SAH relationship is further evaluated. It is found that about two-thirds of the CMIP5 models can capture the observed ENSO-SAH relationship, although the relationship is distinctly exaggerated by several models. The success of these models is attributed to the reasonable simulation of both the 'charge' process over the tropical Indian Ocean induced by the ENSO-related anomalous sea surface temperature (SST) over the tropical eastern Pacific (TEP) and longitude extension of the western boundary of the ENSO-related anomalous SST over the TEP. [ABSTRACT FROM AUTHOR]

Surface-based Arctic amplification (AA) has experienced a remarkable increase in recent decades. Therefore, it is important to understand how Arctic warming might change in response to global warming. By analyzing the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model dataset, we examine how AA correlates with changes in tropical Pacific precipitation in response to global warming. It is found that that the changes in the latitudinal position of the Inter-tropical Convergence Zone (ITCZ) are associated to the simulated AA strength in the CMIP5 climate models. Specifically, AA tends to be stronger (weaker) in models where the ITCZ shifts relatively more northward (southward). Further analysis indicates that the inter-model diversity of AA strength in the CMIP5 climate models is related to the changes in large-scale atmospheric circulation associated with the meridional shift of the ITCZ. These results emphasize a close relationship between AA and changes in tropical Pacific precipitation in response to global warming. [ABSTRACT FROM AUTHOR]

Climate models show a broad diversity in the simulations of the Atlantic meridional overturning circulation (AMOC) with its leading modes of variability having different amplitudes, periods and driving mechanisms. Theoretical considerations and computations using ocean GCMs suggest that on interdecadal timescales this variability can be controlled by an internal weakly-damped oceanic mode associated with westward propagation of large-scale density anomalies in the North Atlantic Ocean. These anomalies are dominated by temperature with some compensation from salinity. The quadrature phases of this mode include the strengthening of the AMOC, followed a quarter-period later by the development of a broad warm temperature anomaly in the northern Atlantic extending to about 1000 m, then followed by the weakening of the AMOC, and then the upper-ocean cooling. Here, we investigate whether this mode is present in the simulations of Coupled Model Intercomparison Project 5 (CMIP5). Out of the 25 models investigated, we find that more than half of the models exhibit variability consistent with this mode. Some of the relevant modal features includes statistically significant spectral peaks in the band between 15 and 35 years, the westward propagation of density anomalies in the $$40^{\circ }$$ N- $$60^{\circ }$$ N latitudinal band, which sets the period of the mode, the existence of the distinct quadrature phases of the AMOC variability, and the predominant effect of temperature on density anomalies. [ABSTRACT FROM AUTHOR]

The leading modes of Sea Surface Temperature variability in the Southern Ocean on decadal and even larger time scales are analysed using Coupled Model Intercomparison Project 5 (CMIP5) model simulations and observations. The analysis is based on Empirical Orthogonal Function modes of the CMIP5 model super ensemble. We compare the modes from the CMIP5 super ensemble against several simple null hypotheses, such as isotropic diffusion (red noise) and a Slab Ocean model, to investigate the sources of decadal variability and the physical processes affecting the characteristics of the modes. The results show three main modes in the Southern Ocean: the first and most dominant mode on interannual to decadal time scales is an annular mode with largest amplitudes in the Pacific, which is strongly related to atmospheric forcing by the Southern Annular Mode and El Nino Southern Oscillation. The second mode is an almost basin wide monopole pattern, which has pronounced multi-decadal and longer time scales variability. It is firstly inducted by the Wave-3 patterns in the atmosphere and further developed via ocean dynamics. The third mode is a dipole pattern in the southern Pacific that has a pronounced peak in the power spectrum at multi-decadal time scales. All three leading modes found in the CMIP5 super model have distinct patterns and time scale behaviour that can not be explained by simple stochastic null hypothesis, thus all three leading modes are ocean-atmosphere coupled modes and are likely to be substantially influenced or driven by ocean dynamical processes. [ABSTRACT FROM AUTHOR]

Instrumental temperature records show that the global climate may experience decadal-scale periods without warming despite a long-term warming trend. We analysed 17 global climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5), identifying the likelihood and duration of periods without warming in the four Representative Concentration Pathway (RCP) scenarios RCP2.6, RCP4.5, RCP6.0 and RCP8.5, together with the preindustrial control and historical simulations. We find that non-warming periods may last 10, 15 and 30 years for RCP8.5, RCP6.0 and RCP4.5, respectively. In the models, anomalous ocean heat uptake and storage are the main factors explaining the decadal-scale surface temperature hiatus periods. The low-latitude East Pacific Ocean is a key region for these variations, acting in tandem with basin-scale anomalies in the sea level pressure. During anomalously cold decades, roughly 35-50 % of the heat anomalies in the upper 700 m of the ocean are located in the Pacific Ocean, and 25 % in the Atlantic Ocean. Decadal-scale ocean heat anomalies, integrated over the upper 700 m, have a magnitude of about 7.5 × 10 J. This is comparable to the ocean heat uptake needed to maintain a 10 year period without increasing surface temperature under global warming. On sub-decadal time scales the Atlantic, Pacific and Southern Oceans all have the ability to store large amounts of heat, contributing to variations in global surface temperature. The likelihood of decadal-scale non-warming periods decrease with global warming, firstly at the low latitude region stretching eastward from the tropical Atlantic towards the western Pacific. The North Atlantic and Southern Oceans have largest likelihood of non-warming decades in a warming world. [ABSTRACT FROM AUTHOR]

The western North Pacific anomalous anticyclone (WNPAC) plays an essential role in linking El Niño and the East Asian-western North Pacific monsoon. The WNPAC and the corresponding WNP anomalous cyclone (WNPC) associated with La Niña are studied by examining the pre-industrial control runs of 18 Coupled Model Intercomparison Project Phase 5 models. The WNPAC is asymmetric with the WNPC during ENSO mature winters, which can be reproduced by seven out of the eighteen models. Based on the differences between the seven models and the other models, it is verified that the asymmetry results from the combined effects of the asymmetric remote forcing from the equatorial central-eastern Pacific and the asymmetric local sea surface temperature (SST) anomalies. It is further demonstrated that the asymmetric circulation anomalies over the tropical WNP contribute to the asymmetric decaying rates between El Niño and La Niña. Those models that can (cannot) simulate the asymmetry between the WNPAC and WNPC tend to reproduce ENSO with asymmetric (symmetric) decaying rates. In El Niño decaying summers, the WNPAC is still maintained due to the sequential effects of the local forcing of the underlying cold SST anomalies remaining from the previous winter and spring, and the remote forcing from the tropical Indian Ocean. Multi-model results show that the coupling of the local cold SST anomalies and the WNPAC forms a damping mode, which is only conducive to maintaining the WNPAC in the early summer, while the response of the WNPAC to the remote forcing from the tropical Indian Ocean intensifies from June to July, concurring with the establishment of the climatological WNP summer monsoon trough. [ABSTRACT FROM AUTHOR]

The predictability of the Arctic sea ice is investigated at the interannual time scale using decadal experiments performed within the framework of the fifth phase of the Coupled Model Intercomparison Project with the CNRM-CM5.1 coupled atmosphere-ocean global climate model. The predictability of summer Arctic sea ice extent is found to be weak and not to exceed 2 years. In contrast, robust prognostic potential predictability (PPP) up to several years is found for winter sea ice extent and volume. This predictability is regionally contrasted. The marginal seas in the Atlantic sector and the central Arctic show the highest potential predictability, while the marginal seas in the Pacific sector are barely predictable. The PPP is shown to decrease drastically in the more recent period. Regarding sea ice extent, this decrease is explained by a strong reduction of its natural variability in the Greenland-Iceland-Norwegian Seas due to the quasi-disappearance of the marginal ice zone in the center of the Greenland Sea. In contrast, the decrease of predictability of sea ice volume arises from the combined effect of a reduction of its natural variability and an increase in its chaotic nature. The latter is attributed to a thinning of sea ice cover over the whole Arctic, making it more sensitive to atmospheric fluctuations. In contrast to the PPP assessment, the prediction skill as measured by the anomaly correlation coefficient is found to be mostly due to external forcing. Yet, in agreement with the PPP assessment, a weak added value of the initialization is found in the Atlantic sector. Nevertheless, the trend-independent component of this skill is not statistically significant beyond the forecast range of 3 months. These contrasted findings regarding potential predictability and prediction skill arising from the initialization suggest that substantial improvements can be made in order to enhance the prediction skill. [ABSTRACT FROM AUTHOR]

Global warming is expected to increase the frequency and intensity of droughts in the twenty-first century, but the relative contributions from changes in moisture supply (precipitation) versus evaporative demand (potential evapotranspiration; PET) have not been comprehensively assessed. Using output from a suite of general circulation model (GCM) simulations from phase 5 of the Coupled Model Intercomparison Project, projected twenty-first century drying and wetting trends are investigated using two offline indices of surface moisture balance: the Palmer Drought Severity Index (PDSI) and the Standardized Precipitation Evapotranspiration Index (SPEI). PDSI and SPEI projections using precipitation and Penman-Monteith based PET changes from the GCMs generally agree, showing robust cross-model drying in western North America, Central America, the Mediterranean, southern Africa, and the Amazon and robust wetting occurring in the Northern Hemisphere high latitudes and east Africa (PDSI only). The SPEI is more sensitive to PET changes than the PDSI, especially in arid regions such as the Sahara and Middle East. Regional drying and wetting patterns largely mirror the spatially heterogeneous response of precipitation in the models, although drying in the PDSI and SPEI calculations extends beyond the regions of reduced precipitation. This expansion of drying areas is attributed to globally widespread increases in PET, caused by increases in surface net radiation and the vapor pressure deficit. Increased PET not only intensifies drying in areas where precipitation is already reduced, it also drives areas into drought that would otherwise experience little drying or even wetting from precipitation trends alone. This PET amplification effect is largest in the Northern Hemisphere mid-latitudes, and is especially pronounced in western North America, Europe, and southeast China. Compared to PDSI projections using precipitation changes only, the projections incorporating both precipitation and PET changes increase the percentage of global land area projected to experience at least moderate drying (PDSI standard deviation of ≤−1) by the end of the twenty-first century from 12 to 30 %. PET induced moderate drying is even more severe in the SPEI projections (SPEI standard deviation of ≤−1; 11 to 44 %), although this is likely less meaningful because much of the PET induced drying in the SPEI occurs in the aforementioned arid regions. Integrated accounting of both the supply and demand sides of the surface moisture balance is therefore critical for characterizing the full range of projected drought risks tied to increasing greenhouse gases and associated warming of the climate system. [ABSTRACT FROM AUTHOR]

Previous studies have revealed some common biases in coupled general circulation model's simulations of the East Asian (EA) winter monsoon (EAWM), including colder surface air temperature and more winter precipitation over the EA region. In this study, we examined 41 fully coupled atmosphere-ocean models from fifth phase of the Coupled Model Intercomparison Project (CMIP5), which will be widely used in the fifth assessment report of the Intergovernmental Panel on Climate Change (IPCC), and address whether the current state-of-the-art CMIP5 models can characterise the climatology of the East Asian winter monsoon. We also compared the results with the models from third phase of CMIP, which was extensively used in the fourth assessment report of the IPCC. The results show that the cold surface air temperature (SAT) bias is lessened and the precipitation amount decreased with the current CMIP5 models. Moreover, the CMIP5 models performbetter at predicting surface winds and high-level jet streams than the CMIP3 models. Moreover, CMIP5 models show more model consistency in most EAWM parameters, and the interannual variability of the SAT is closer to the observations. We also examined the change in the radiation energy budget in the CMIP5 models and compared with CMIP3 models. Although the improvements are significant, deficiencies still exist in the simulation of the EAWM, e.g., the stronger EA major trough and the stronger zonal sea level pressure gradient. [ABSTRACT FROM AUTHOR]

Earth system models (ESMs) provide high resolution simulations of variables such as sea surface temperature (SST) that are often used in off-line biological impact models. Coral reef modellers have used such model outputs extensively to project both regional and global changes to coral growth and bleaching frequency. We assess model skill at capturing sub-regional climatologies and patterns of historical warming. This study uses an established wavelet-based spatial comparison technique to assess the skill of the coupled model intercomparison project phase 5 models to capture spatial SST patterns in coral regions. We show that models typically have medium to high skill at capturing climatological spatial patterns of SSTs within key coral regions, with model skill typically improving at larger spatial scales (≥4°). However models have much lower skill at modelling historical warming patters and are shown to often perform no better than chance at regional scales (e.g. Southeast Asian) and worse than chance at finer scales (<8°). Our findings suggest that output from current generation ESMs is not yet suitable for making sub-regional projections of change in coral bleaching frequency and other marine processes linked to SST warming. [ABSTRACT FROM AUTHOR]

State-of-the-art coupled global climate models are evaluated for their simulation of the Atlantic Warm Pool (AWP). Historical runs from 17 coupled climate models included in the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5) serve as the basis for this model evaluation study. The model simulations are directly compared to observations and reanalysis data to evaluate the climatological features and variability of the AWP within each individual model. Results reveal that a select number of models-namely the GISS-E2-R, CSIRO-Mk3.6, and MPI-ESM-LR-are successful at resolving an appropriately sized AWP with some reasonable climatological features. However, these three models exhibit an erroneously broad seasonal peak of the AWP, and its variability is significantly underestimated. Furthermore, all of the CMIP5 models exhibit a significant cold bias across the tropical Atlantic basin, which hinders their ability to accurately resolve the AWP. [ABSTRACT FROM AUTHOR]

This study presents projections of twenty-first century wintertime surface temperature changes over the high-latitude regions based on the third Coupled Model Inter-comparison Project (CMIP3) multi-model ensemble. The state-dependence of the climate change response on the present day mean state is captured using a simple yet robust ensemble linear regression model. The ensemble regression approach gives different and more precise estimated mean responses compared to the ensemble mean approach. Over the Arctic in January, ensemble regression gives less warming than the ensemble mean along the boundary between sea ice and open ocean (sea ice edge). Most notably, the results show 3 °C less warming over the Barents Sea (~7 °C compared to ~10 °C). In addition, the ensemble regression method gives projections that are 30 % more precise over the Sea of Okhostk, Bering Sea and Labrador Sea. For the Antarctic in winter (July) the ensemble regression method gives 2 °C more warming over the Southern Ocean close to the Greenwich Meridian (~7 °C compared to ~5 °C). Projection uncertainty was almost half that of the ensemble mean uncertainty over the Southern Ocean between 30° W to 90° E and 30 % less over the northern Antarctic Peninsula. The ensemble regression model avoids the need for explicit ad hoc weighting of models and exploits the whole ensemble to objectively identify overly influential outlier models. Bootstrap resampling shows that maximum precision over the Southern Ocean can be obtained with ensembles having as few as only six climate models. [ABSTRACT FROM AUTHOR]

We present results from multiple comprehensive models used to simulate an aggressive mitigation scenario based on detailed results of an Integrated Assessment Model. The experiment employs ten global climate and Earth System models (GCMs and ESMs) and pioneers elements of the long-term experimental design for the forthcoming 5th Intergovernmental Panel on Climate Change assessment. Atmospheric carbon-dioxide concentrations pathways rather than carbon emissions are specified in all models, including five ESMs that contain interactive carbon cycles. Specified forcings also include minor greenhouse gas concentration pathways, ozone concentration, aerosols (via concentrations or precursor emissions) and land use change (in five models). The new aggressive mitigation scenario (E1), constructed using an integrated assessment model (IMAGE 2.4) with reduced fossil fuel use for energy production aimed at stabilizing global warming below 2 K, is studied alongside the medium-high non-mitigation scenario SRES A1B. Resulting twenty-first century global mean warming and precipitation changes for A1B are broadly consistent with previous studies. In E1 twenty-first century global warming remains below 2 K in most models, but global mean precipitation changes are higher than in A1B up to 2065 and consistently higher per degree of warming. The spread in global temperature and precipitation responses is partly attributable to inter-model variations in aerosol loading and representations of aerosol-related radiative forcing effects. Our study illustrates that the benefits of mitigation will not be realised in temperature terms until several decades after emissions reductions begin, and may vary considerably between regions. A subset of the models containing integrated carbon cycles agree that land and ocean sinks remove roughly half of present day anthropogenic carbon emissions from the atmosphere, and that anthropogenic carbon emissions must decrease by at least 50% by 2050 relative to 1990, with further large reductions needed beyond that to achieve the E1 concentrations pathway. Negative allowable anthropogenic carbon emissions at and beyond 2100 cannot be ruled out for the E1 scenario. There is self-consistency between the multi-model ensemble of allowable anthropogenic carbon emissions and the E1 scenario emissions from IMAGE 2.4. [ABSTRACT FROM AUTHOR]