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The cloud feedback may result in amplification or damping of Arctic warming. Two common techniques used to diagnose the top‐of‐the‐atmosphere cloud feedback are the Adjusted Cloud Radiative Effect (AdjCRE) method and the Cloud Radiative Kernel (CRK) method. We apply both to CMIP5 and CMIP6 model data, finding that the AdjCRE calculated Arctic shortwave cloud feedback is twice as correlated with sea ice loss in CMIP5, and four times in CMIP6, as the CRK method. We find that the CRK method produces Arctic all‐sky residual percentages exceeding 20% in 15 of 18 models. We use the CRK method to decompose the feedback in CMIP5 and CMIP6 finding that its median value changed from negative to positive driven by a less‐negative cloud optical depth feedback. Despite its lack of closure, we conclude that the CRK method is better suited for Arctic SW feedbacks as it is less impacted by surface albedo changes. Plain Language Summary: The cloud feedback is the process by which cloud property changes in a warming climate can either further enhance warming or damp it. The Arctic is warming faster than the rest of the globe, and one of the largest sources of uncertainty in its climate projections is the cloud feedback. There are two popular methods to calculate the cloud feedback: the Adjusted Cloud Radiative Effect technique, and the Cloud Radiative Kernel technique. In this paper we compare the two methods in a suite of climate models by considering the extent to which changes in Arctic sea ice impact the cloud feedbacks. From this analysis we conclude that the Cloud Radiative Kernel method is less affected by sea ice loss. We then apply the Cloud Radiative Kernel technique to data from the two most recent generations of global climate models to investigate how polar day Arctic cloud feedbacks have changed between these generations. We find that the median value of these Arctic feedbacks is slightly positive in the newest generation of models, a change from slightly negative in the previous generation that is largely fueled by a weakening of the feedback associated with changes in cloud optical depth. Key Points: The Cloud Radiative Kernel method is less sensitive to surface albedo changes than the Adjusted Cloud Radiative Effect techniqueThe Cloud Radiative Kernel method provides poor radiative closure in a suite of global climate modelsThe median shortwave Arctic cloud feedback in recent climate models is slightly positive due to a weakened cloud optical depth feedback [ABSTRACT FROM AUTHOR]

A reference or "no‐feedback" radiative response to warming is fundamental to understanding how much global warming will occur for a given change in greenhouse gases or solar radiation incident on the Earth. The simplest estimate of this radiative response is given by the Stefan‐Boltzmann law as −4σTe‾3≈−3.8 ${-}4\sigma {\overline{{T}_{e}}}^{3}\approx -3.8$ W m−2 K−1 for Earth's present climate, where Te‾ $\overline{{T}_{e}}$ is a global effective emission temperature. The comparable radiative response in climate models, widely called the "Planck feedback," averages −3.3 W m−2 K−1. This difference of 0.5 W m−2 K−1 is large compared to the uncertainty in the net climate feedback, yet it has not been studied carefully. We use radiative transfer models to analyze these two radiative feedbacks to warming, and find that the difference arises primarily from the lack of stratospheric warming assumed in calculations of the Planck feedback (traditionally justified by differing constraints on and time scales of stratospheric adjustment relative to surface and tropospheric warming). The Planck feedback is thus masked for wavelengths with non‐negligible stratospheric opacity, and this effect implicitly acts to amplify warming in current feedback analysis of climate change. Other differences between Planck and Stefan‐Boltzmann feedbacks arise from temperature‐dependent gas opacities, and several artifacts of nonlinear averaging across wavelengths, heights, and different locations; these effects partly cancel but as a whole slightly destabilize the Planck feedback. Our results point to an important role played by stratospheric opacity in Earth's climate sensitivity, and clarify a long‐overlooked but notable gap in our understanding of Earth's reference radiative response to warming. Plain Language Summary: Earth's climate is stable because a warmer planet loses more energy to space, at infrared wavelengths invisible to the naked eye. The rate of change of this energy loss as the planet warms provides an estimate how Earth's energy balance responds to warming, which is simple enough to write on a small piece of paper. When scientists investigate the warming predicted by climate models, they often start from a similar but not identical calculation of how Earth's energy balance responds to warming. This calculation, based on model output, is about 15% less stabilizing than the simple pencil‐and‐paper estimate. In this paper, we explore the causes of this 15% difference between the pencil‐and‐paper estimate and the calculations using climate models. We show that the difference is primarily caused by the lack of assumed warming in climate models high in Earth's atmosphere, where temperatures are not closely linked to surface warming. This lack of warming acts as a hidden destabilizing feedback in current analysis of climate models. Key Points: Earth's reference radiative response, or "Planck feedback," is ∼0.5 W m−2 K−1 less stabilizing than a Stefan‐Boltzmann estimateWe find this deviation is mostly due to the assumed lack of stratospheric warming in calculations of the Planck feedbackThe lack of stratospheric warming serves as an implicit positive feedback in analysis of climate model warming [ABSTRACT FROM AUTHOR]

Scenarios are central to fisheries and aquatic conservation research on climate change. Scenarios project future greenhouse-gas emissions, which climate models translate into warming projections. Recent climate research and global development trends have significantly changed our understanding of plausible emissions pathways to 2100 and climate sensitivities to emissions. Here, we review these developments and make recommendations for scenario use in fisheries and aquatic conservation research. Although emissions pathways are uncertain, recent research suggests that scenarios producing ∼3.4–4.5 W/m2 radiative forcing by 2100 (e.g. scenarios SSP2-3.4 and SSP2-4.5/RCP4.5) might be most plausible. This corresponds to ∼2–3 degrees C global warming by 2100 with median climate sensitivities, or 1.5–4 degrees C considering climate-system uncertainties. Higher- and lower-emissions scenarios (e.g. RCP2.6 and RCP6.0) might be plausible and should be explored in research. However, high-emission scenarios (RCP8.5/SSP5-8.5, SSP3-7.0) seem implausible and should be used with clear rationales and caveats to ensure results are not misinterpreted by scholars, policymakers, and media. We analyse fisheries and aquatic conservation papers published from 2015 to 2022 in major journals, and find that RCP8.5/SSP5-8.5 are the most commonly used scenarios, though RCP4.5/SSP2-4.5 use has increased since 2020. Studies predominantly project quantitative rather than qualitative differences between these scenarios' impacts. [ABSTRACT FROM AUTHOR]

This paper presents the response to anthropogenic forcing in the GISS‐E2.1 climate models for the 21st century Shared Socioeconomic Pathways emission scenarios within the Coupled Model Intercomparison Project Phase 6 (CMIP6). The experiments were performed using an updated and improved version of the NASA Goddard Institute for Space Studies (GISS) coupled general circulation model that includes two different versions for atmospheric composition: A non‐interactive version (NINT) with prescribed composition and a tuned aerosol indirect effect and the One‐Moment Aerosol model (OMA) version with fully interactive aerosols which includes a parameterized first indirect aerosol effect on clouds. The effective climate sensitivities are 3.0°C and 2.9°C for the NINT and OMA models, respectively. Each atmospheric version is coupled to two different ocean general circulation models: The GISS ocean model (E2.1‐G) and HYCOM (E2.1‐H). We describe the global mean responses for all future scenarios and spatial patterns of change for surface air temperature and precipitation for four of the marker scenarios: SSP1‐2.6, SSP2‐4.5, SSP4‐6.0, and SSP5‐8.5. By 2100, global mean warming ranges from 1.5°C to 5.2°C relative to 1,850–1,880 mean temperature. Two high‐mitigation scenarios SSP1‐1.9 and SSP1‐2.6 limit the surface warming to below 2°C by the end of the 21st century, except for the NINT E2.1‐H model that simulates 2.2°C of surface warming. For the high emission scenario SSP5‐8.5, the range is 4.6–5.2°C at 2100. Due to about 15% larger effective climate sensitivity and stronger transient climate response in both NINT and OMA CMIP6 models compared to CMIP5 versions, there is a stronger warming by 2100 in the SSP emission scenarios than in the comparable Representative Concentration Pathway (RCP) scenarios in CMIP5. Changes in sea ice area are highly correlated to global mean surface air temperature anomalies and show steep declines in both hemispheres, with the largest sea ice area decreases occurring during September in the Northern Hemisphere in both E2.1‐G (−1.21 × 106 km2/°C) and E2.1‐H models (−0.94 × 106 km2/°C). Both coupled models project decreases in the Atlantic overturning stream function by 2100. The largest decrease of 56%–65% in the 21st century overturning stream function is produced in the warmest scenario SSP5‐8.5 in the E2.1‐G model, comparable to the reduction in the corresponding CMIP5 GISS‐E2 RCP8.5 simulation. Both low‐end scenarios SSP1‐1.9 and SSP1‐2.6 also simulate substantial reductions of the overturning (9%–37%) with slow recovery of about 10% by the end of the 21st century (relative to the maximum decrease at the middle of the 21st century). Plain Language Summary: The projections of future climate change are uncertain because they are dependent on different possible scenarios of human‐caused emissions and their interaction with natural forcings, internal climate variability, and inter‐model differences. This paper presents the results of the climate model of the NASA Goddard Institute for Space Studies, GISS‐E2.1, for the anthropogenically forced climate response for the twenty first century Shared Socioeconomic Pathways emission scenarios within the Coupled Model Intercomparison Project Phase 6 (CMIP6). The sensitivity of the model response to different magnitudes of anthropogenic forcings in the twenty‐first‐century scenarios were performed using two different versions for the atmospheric composition and two different ocean general circulation models. Compared to CMIP5 GISS‐E2 versions, the CMIP6 GISS‐E2.1 climate model shows a stronger warming by 2100 in comparable scenarios due to larger effective climate sensitivity and transient climate response. Both climate models with two different ocean components project decreases in the Atlantic overturning stream function by 2100. Key Points: GISS E2.1 model with different configurations is used to carry out 134 Shared Socioeconomic Pathway (SSP) experimentsGISS‐E2.1 climate model shows a stronger warming by 2,100 in comparable Representative Concentration Pathway scenarios in CMIP5 due to larger effective climate sensitivity and stronger transient climate responseBoth coupled models, E2.1‐G and E2.1‐H, project decreases in the Atlantic overturning stream function by 2100 with the largest decrease in the warmest scenario SSP5‐8.5 in the E2.1‐G model [ABSTRACT FROM AUTHOR]

The Agulhas Current (AC) is a critical component of global ocean circulation. However, due to a lack of multidecadal observations, it is not clear how the AC has changed in response to anthropogenic forcing. A recent observational study suggests a broadening and slight weakening of the AC in the past few decades, while others suggest a strengthening of the AC during the historical period. In this paper, we find substantial internal variability of the AC on decadal to multidecadal time scales in high-resolution models. We show that the AC consistently exhibits two modes of decadal and multidecadal (i.e., low frequency) variability in a series of high-resolution climate models: a uniform mode that is largely associated with changes in the AC strength and a dipole mode that is mainly related to width changes of the AC. We demonstrate that the uniform mode is mainly forced externally by the decadal variations of the wind field and presents a decline under global warming, suggesting a weakening of the AC in response to anthropogenic forcing. The dipole mode, on the other hand, is mainly due to internal dynamics and does not show a trend during the historical period. Using a quasigeostrophic model that captures the dipole mode, we attribute the dipole mode to low-frequency potential vorticity changes in the western boundary, driven by a divergence of relative potential vorticity due to eddy activity. Thus, our results present further context for the interpretation of the AC responses in a changing climate based on a short observational record. [ABSTRACT FROM AUTHOR]

This paper describes the downscaling of an ensemble of 12 general circulation models (GCMs) using the Weather Research and Forecasting (WRF) Model at 12-km grid spacing over the period 1970–2099, examining the mesoscale impacts of global warming as well as the uncertainties in its mesoscale expression. The RCP8.5 emissions scenario was used to drive both global and regional climate models. The regional climate modeling system reduced bias and improved realism for a historical period, in contrast to substantial errors for the GCM simulations driven by lack of resolution. The regional climate ensemble indicated several mesoscale responses to global warming that were not apparent in the global model simulations, such as enhanced continental interior warming during both winter and summer as well as increasing winter precipitation trends over the windward slopes of regional terrain, with declining trends to the lee of major barriers. During summer there is general drying, except to the east of the Cascades. The 1 April snowpack declines are large over the lower-to-middle slopes of regional terrain, with small snowpack increases over the lower elevations of the interior. Snow-albedo feedbacks are very different between GCM and RCM projections, with the GCMs producing large, unphysical areas of snowpack loss and enhanced warming. Daily average winds change little under global warming, but maximum easterly winds decline modestly, driven by a preferential sea level pressure decline over the continental interior. Although temperatures warm continuously over the domain after approximately 2010, with slight acceleration over time, occurrences of temperature extremes increase rapidly during the second half of the twenty-first century. Significance Statement: This paper provides a unique high-resolution view of projected climate change over the Pacific Northwest and does so using an ensemble of regional climate models, affording a look at the uncertainties in local impacts of global warming. The paper examines regional meteorological processes influenced by global warming and provides guidance for adaptation and preparation. [ABSTRACT FROM AUTHOR]

This paper describes the downscaling of an ensemble of 12 general circulation models (GCMs) using the Weather Research and Forecasting (WRF) Model at 12-km grid spacing over the period 1970–2099, examining the mesoscale impacts of global warming as well as the uncertainties in its mesoscale expression. The RCP8.5 emissions scenario was used to drive both global and regional climate models. The regional climate modeling system reduced bias and improved realism for a historical period, in contrast to substantial errors for the GCM simulations driven by lack of resolution. The regional climate ensemble indicated several mesoscale responses to global warming that were not apparent in the global model simulations, such as enhanced continental interior warming during both winter and summer as well as increasing winter precipitation trends over the windward slopes of regional terrain, with declining trends to the lee of major barriers. During summer there is general drying, except to the east of the Cascades. The 1 April snowpack declines are large over the lower-to-middle slopes of regional terrain, with small snowpack increases over the lower elevations of the interior. Snow-albedo feedbacks are very different between GCM and RCM projections, with the GCMs producing large, unphysical areas of snowpack loss and enhanced warming. Daily average winds change little under global warming, but maximum easterly winds decline modestly, driven by a preferential sea level pressure decline over the continental interior. Although temperatures warm continuously over the domain after approximately 2010, with slight acceleration over time, occurrences of temperature extremes increase rapidly during the second half of the twenty-first century. Significance Statement: This paper provides a unique high-resolution view of projected climate change over the Pacific Northwest and does so using an ensemble of regional climate models, affording a look at the uncertainties in local impacts of global warming. The paper examines regional meteorological processes influenced by global warming and provides guidance for adaptation and preparation. [ABSTRACT FROM AUTHOR]

Since the early 1990s the Pacific Walker circulation shows a multi‐decadal strengthening, which contradicts future model projections. Whether this trend, evident in many climate indices especially before the 2015 El Niño, reflects the coupled ocean‐atmosphere response to global warming or the negative phase of the Pacific Decadal Oscillation (PDO) remains debated. Here we show that sea surface temperature trends during 1980–2020 are dominated by three signals: a spatially uniform warming trend, a negative PDO pattern, and a Northern Hemisphere‐Indo‐West Pacific warming pattern. The latter pattern, which closely resembles the transient ocean thermostat‐like response to global warming emerging in a subset of CMIP6 models, shows cooling in the central‐eastern equatorial Pacific but warming in the western Pacific and tropical Indian Ocean. Together with the PDO, this pattern drives the Walker circulation strengthening in the equatorial band. Historical simulations appear to underestimate this pattern, contributing to the models' inability to replicate the Walker cell strengthening. Plain Language Summary: This paper investigates the observed changes in the tropical Pacific during the satellite era, including the recent decadal strengthening of the atmospheric zonal circulation—the Walker cell. We aim to understand the extent to which these changes represent a forced response to rising CO2 concentrations versus natural variability. We apply an approach in which we decompose the observed sea surface temperature trends into three components—a pattern associated with the Pacific Decadal Oscillation, which is part of natural variability, a uniform warming pattern, and a residual pattern. This residual pattern shows a remarkable resemblance to a forced ocean thermostat‐like transient response generated in some of the climate models, characterized by equatorial Pacific (EP) cooling, and a broad warming of the Northern Hemisphere, and the Indian Ocean and West Pacific. These results challenge studies arguing that the recent strengthening of the Pacific Walker cell can be explained simply by multi‐decadal natural variability in the tropics. Furthermore, the inability of climate models at large to fully capture this forced pattern with historical forcing puts into focus the reliability of future projections of climate change in the tropical Pacific, specifically the timing of emergence of the eastern EP warming. Key Points: A multi‐decadal strengthening of the Pacific Walker cell is observed in a wide range of indices, especially after 1990A Northern Hemisphere ‐ Indo West Pacific warming sea surface temperature pattern, which differs from the Pacific Decadal Oscillation, is evident since 1980This pattern resembles a forced response to abrupt CO2 forcing, emerging in a subset of climate models, and contributes to the Walker circulation strenthening [ABSTRACT FROM AUTHOR]

Paleontological studies of the distant past and historical chronicles of the last millennia indicate that warming and cooling of the climate on our planet, replacing each other, have taken place in a continuous series. An important role in this process has been and is played by cosmic factors: variations in solar activity and parameters of the Earth's orbital motion in the gravitational field of the Sun and the planets of the Solar System. It is suggested that the currently observed climate change is associated with a decrease in the eccentricity of the Earth's orbit and the inclination of the axis of its rotation relative to the plane of the ecliptic, which has been going on for almost 30 thousand years. Both processes lead to changes in the boundaries of climatic zones. In the foreseeable future, these processes will proceed in the same direction. Therefore, the current trend towards climate change will continue. Despite the importance of addressing the problem of reducing greenhouse-gas emissions as soon as possible, this paper expresses doubts about the possibility of fending off climate warming in this way. It is proposed to focus on the development of mathematical climate models taking into account space factors and on finding the best ways to adapt industry, transport systems, and the environment to the conditions of expected climate change. [ABSTRACT FROM AUTHOR]

Regional climate projections indicate that European summer precipitation may change considerably in the future. Southern Europe can expect substantial drying while Northern Europe could actually become wetter. Model spread and internal variability in these projections are large, however, and unravelling the processes that underlie the changes is essential to get more confidence in these projections. Large-scale circulation change is one of the contributors to model spread. In this paper we quantify the role of future large-scale circulation changes to summer precipitation change, using a 16-member single-model ensemble obtained with the regional climate model RACMO2, forced by the global climate model EC-Earth2.3 and the RCP8.5 emission scenario. Using the method of circulation analogues three contributions to the future precipitation change are distinguished. The first is the precipitation change occurring without circulation change (referred to as the thermodynamic term). This contribution is characterised by a marked drying-to-wetting gradient as one moves north from the Mediterranean. The second contribution measures the effects of changes in the mean circulation. It has a very different spatial pattern and is closely related to the development of a region of high pressure (attaining its maximum west of Ireland) and the associated anti-cyclonic circulation response. For a large area east of Ireland including parts of western Europe, it is the major contributor to the overall drying signal, locally explaining more than 90% of the ensemble-mean change. In regions where the patterns overlap, the signal-to-noise ratio of the total change is either enhanced or reduced depending on their relative signs. Although the second term is expected to be particularly model dependent, the high-pressure region west of Ireland also appears in CMIP5 and CMIP6 ensemble-mean projections. The third contribution records the effects of changes in the circulation variability. This term has the smallest net contribution, but a relatively large uncertainty. The analogues are very good in partitioning the ensemble-mean precipitation change, but describe only up to 40% of the ensemble-spread. This demonstrates that other precipitation-drivers (SST, spring soil moisture etc.) will generally strongly influence trends in single climate realisations. This also re-emphasises the need for large ensembles or using alternative methods like the Pseudo Global Warming approach where signal to noise ratios are higher. Nevertheless, identifying the change mechanisms helps to understand the future uncertainties and differences between models. [ABSTRACT FROM AUTHOR]

Climate classifications are useful to synthesize the physical state of the climate with a proxy that can be directly related to biota. However, they present a potential drawback, namely a strong sensitivity because of the use of hard thresholds (step functions). Thus, minor discrepancies in the base data produce large differences in the type of climate. However, such an a priori limitation is also a strength because such sensitivity can be used to better gauge model performance. Although previous attempts of classifying climates of the world using global climate model outputs were encouraging, the applicability of their classifications to impact studies has been limited by past model issues. Notwithstanding the persistence of certain imperfections and limitations in current models, the high‐quality physical simulations from phase six of the Coupled Intercomparison Project (CMIP6) has opened new possibilities in the field, thanks to their improved representation of atmospheric and oceanic physics. The purpose of this paper is twofold: to show that climate classifications from CMIP6 are sufficiently robust for use in impact studies, and to use those classifications for identifying error sources and potential issues that deserve further attention in models. Thus, 52 CMIP6 climate models were evaluated by using three climate classifications schemes, classical Köppen, extended‐Köppen, and modified Thornthwaite. We first assessed model ability to reproduce present climate types by comparing their outputs with observational data. Models performed best for the Köppen and extended‐Köppen classification methods (Cohen's kappa κ = 0.7), and had moderate scores for the Thornthwaite climate classification (κ = 0.4). By tracing back the observed biases, we were able to pinpoint the misrepresentation of dry climates as a major source of error. Another finding was that most models still had some difficulties in representing the seasonal variability of precipitation over several monsoonal regions, thereby yielding the wrong climate type there. Models were also evaluated for future climate. Substantial changes in climate types are projected in the SSP5‐8.5 scenario. These changes include a shrinkage of polar/frigid climates (22%) and an increase of dry climates (7%). [ABSTRACT FROM AUTHOR]

This study investigates some of the uncertainties sources associated with the pseudo global warming (PGW) approach which was employed to project future patterns of tropical cyclones (TCs) over the Arabian Sea (AS). First, the climate variables controlling the patterns of tropical cyclones were extracted from reanalysis datasets of ERA5, ERAI, CFSR, and NCEP/NCAR. Then, each dataset was evaluated against long‐term measurements to identify the best‐performing reanalysis dataset. ERA5 showed the best performance for most of the variables. Outputs of 20 CMIP5 global climate models (GCMs) were then evaluated against the ERA5 data resulting in an ensemble of the best performing GCMs. A PGW framework was then used to project the changes in patterns of three significant historical cyclones: Gonu, Phet, and Ashobaa. In doing so, the signals of future climate variables were extracted from the GCMs ensemble to modify the initial and boundary conditions of the WRF model which was previously tuned for reproducing the historical TCs. Different tests were conducted to address the sources of uncertainty in the PGW approach, including the selection of the climate variables contributing to the computation of the signals, the selection of GCMs, and the spatial variation of signals. A considerable sensitivity of the projected track and intensity of TCs to the choice of GCMs was observed, acknowledging the importance of GCMs evaluation before calculating the signals. Moreover, it was found that among all variables, signals of sea surface temperature and air temperature have major effects on the cyclone's track and intensity. Apart from that, when the signals were applied to the domain of the WRF model uniformly, compared to applying spatially varying signals, different tracks and intensities for future TCs were also observed. Overall, the findings of this paper challenge the reliability of the projected changes in TCs patterns obtained from PGW. [ABSTRACT FROM AUTHOR]

In this paper, an innovative framework is introduced for assessing the impact of climate change on coastal structures, with a primary emphasis on modeling future climate conditions. The framework encompasses several key components: the development of a new climate emulator to facilitate multivariate extreme value analysis; a hybrid statistical–numerical wave propagation strategy; and the integration of a novel compound modeling approach specific to coastal structure sites. These advancements are designed to effectively manage multiple climate scenarios and models within the context of high uncertainty. The methodology is applied and validated for a coastal structure located on the Mediterranean coast in Spain. Focusing on compound wave and sea-level events, the projections indicate an increase in the frequency and severity of extreme conditions, exacerbating coastal impacts such as wave overtopping. For instance, the present-day 500-year coastal flooding level would be associated with a return period of 50 years by mid-century under a stabilization scenario and would be further reduced to 25 years under a high-emission global warming scenario, resulting in important consequences for structure performance if no adaptation is implemented. • Develops a framework for assessing the impact of climate change on coastal structures. • It develops a new climate emulator to facilitate multivariate extreme value analysis. • It encompasses a hybrid statistical–numerical wave propagation strategy. • It integrates a novel compound modeling approach specific to coastal structures sites. • It has been applied and validated for a coastal structure in Spain. [ABSTRACT FROM AUTHOR]

Advances in high‐performance computing have enabled large‐eddy simulations (LES) of turbulence, convection, and clouds. However, their potential to improve parameterizations in global climate models (GCMs) is only beginning to be harnessed, with relatively few canonical LES available so far. The purpose of this paper is to begin creating a public LES library that expands the training data available for calibrating and evaluating GCM parameterizations. To do so, we use an experimental setup in which LES are driven by large‐scale forcings from GCMs, which in principle can be used at any location, any time of year, and in any climate state. We use this setup to create a library of LES of clouds across the tropics and subtropics, in the present and in a warmer climate, with a focus on the transition from stratocumulus to shallow cumulus over the East Pacific. The LES results are relatively insensitive to the choice of host GCM driving the LES. Driven with large‐scale forcing under global warming, the LES simulate a positive but weak shortwave cloud feedback, adding to the accumulating evidence that low clouds amplify global warming. Plain Language Summary: Clouds remain one of the largest uncertainties in our understanding and in predictions of climate change because it is challenging to represent their small‐scale dynamics in climate models. However, high‐resolution simulations can provide faithful simulations of clouds and turbulence in limited areas, and these can be used to calibrate climate models. So far, only a limited set of simulations has been used for calibration of climate models, with focus on a few specific locations. This study presents an experimental setup that allows the high‐resolution simulations to be run anywhere on the globe, in any climate state, driven by output from different climate models. The setup is used to create a library of high‐resolution simulations of clouds across the tropics and subtropics in both the current and a warmer climate. The library substantially expands the data set available for the calibration and evaluation of climate models. Key Points: A library of high‐resolution simulations of clouds is created with large‐eddy simulations (LES) driven by a few global climate models (GCMs)Clouds simulated by LES driven by different GCMs are more similar to one another than the corresponding GCM‐simulated cloudsUnder global warming, LES‐simulated low clouds exhibit a weak but positive feedback on warming [ABSTRACT FROM AUTHOR]

Global warming projections of dynamics are less robust than projections of thermodynamics. However, robust aspects of the thermodynamics can be used to constrain some dynamical aspects. This paper argues that tropospheric expansion under global warming (a thermodynamical process) explains changes in the amplitude of the quasi-biennial oscillation (QBO) in the lower and middle stratosphere (a dynamical process). A theoretical scaling for tropospheric expansion of approximately 6 hPa K−1 is derived, which agrees well with global climate model (GCM) experiments. Using this theoretical scaling, the response of QBO amplitude to global warming is predicted by shifting the climatological QBO amplitude profile upward by 6 hPa per kelvin of global warming. In global warming simulations, QBO amplitude in the lower to middle stratosphere shifts upward as predicted by tropospheric expansion. Applied to observations, the tropospheric expansion framework suggests a historical weakening of QBO amplitude at 70 hPa of 3% decade−1 from 1953 to 2020. This expected weakening trend is half of the 6% decade−1 from 1953 to 2012 detected and attributed to global warming in a recent study. The previously reported trend was reinforced by record low QBO amplitudes during the mid-2000s, from which the QBO has since recovered. Given the modest weakening expected on physical grounds, past decadal modulations of QBO amplitude are reinterpreted as a hitherto unrecognized source of internal variability. This large internal variability dominates over the global warming signal such that, despite 65 years of observations, there is not yet a statistically significant weakening trend. [ABSTRACT FROM AUTHOR]

This paper presents a novel data set of regional climate model simulations over Europe that significantly improves our ability to detect changes in weather extremes under low and moderate levels of global warming. The data set provides a unique and physically consistent data set, as it is derived from a large ensemble of regional climate model simulations. These simulations were driven by two global climate models from the international HAPPI consortium. The set consists of 100 × 10-year simulations and 25 × 10-year simulations, respectively. These large ensembles allow for regional climate change and weather extremes to be investigated with an improved signal-to-noise ratio compared to previous climate simulations. The changes in four climate indices for temperature targets of 1.5 °C and 2.0 °C global warming are quantified: number of days per year with daily mean near-surface apparent temperature of > 28 °C (ATG28); the yearly maximum 5-day sum of precipitation (RX5day); the daily precipitation intensity of the 50-yr return period (RI50yr); and the annual Consecutive Dry Days (CDD). This work shows that even for a small signal in projected global mean temperature, changes of extreme temperature and precipitation indices can be robustly estimated. For temperature related indices changes in percentiles can also be estimated with high confidence. Such data can form the basis for tailor-made climate information that can aid adaptive measures at a policy-relevant scales, indicating potential impacts at low levels of global warming at steps of 0.5 °C. [ABSTRACT FROM AUTHOR]

Climate classifications based on temperature and precipitation measurements are increasingly being used for environmental and climate change studies. Using three classification methods (Köppen, Extended Köppen, and Holdridge) and one observational dataset for present climate (CRU, Climate Research Unit), we show that GCMs have bridged the gap that led to the emergence of RCMs thirty years ago, as GCMs can now provide global climate classifications whose accuracy and precision are comparable to those of regional outputs of the RCMs. Projections of high-resolution GCMs for future climates under the assumptions of three Representative Concentration Pathways (RCP26, RCP45 and RCP85) can therefore be used as a primary source for climate change and global warming studies at high resolution. This paper provides comprehensive, model-derived climate classifications for the entire planet, using RCMs and two GCMs for present and future climate-change scenarios, and discusses how well the models actually represent the climates of the world when compared with reference, ground validation data. It turns out that both GCMs and RCMs appear still limited to provide practical estimates of the world climates even for present climate conditions. The modeling of precipitation remains the Achilles' heel of models and thus of multidimensional indices, which are very sensitive to this variable. The conclusion is that model outputs at regional scale need to be taken with extreme caution without venturing into informing policies presenting potentially large societal impacts. Nonetheless, the role of models as privileged tools to advance our scientific knowledge of the Earth's system remains undisputed. • A systematic analysis of climate classifications with RCMs and two high resolution GCMs is presented. • Three classification methods are used to illustrate the differences between models and observations. • Current high-resolution GCMs can provide climate classifications with the same accuracy as those from RCMs. • Uncertainties in modeling precipitation persist for large parts of the world. [ABSTRACT FROM AUTHOR]

This is the first paper that analyzes data from atmosphere model intercomparison project‐type climate simulations using a cloud‐system‐resolving global nonhydrostatic model without cumulus parameterization focussing particulaly on the relationship between clouds and circulation, and their changes due to global warming. The decrease in fractional coverage of low clouds is key to evaluating cloud radiative effects, because changes in shortwave cloud radiative effects overwhelm those of longwave cloud radiative effects. Thus, improved evaluation of low clouds is important, even in high‐resolution climate simulations. An analysis of heat redistribution by explicitly computed clouds revealed that column‐integrated heating rate due to phase changes correlates highly with vertical velocity at the altitude corresponding to 500 hPa and is closely linked to column water vapor, similar to the present climate result. Using data from year 1 to year 5, the effective climate sensitivity was evaluated to be 3.6−3.7°C. Possible convective aggregation is also examined using an index of modified subsidence fraction and characteristic changes in the number of cold pools. Despite previous idealized‐planet simulations showing more aggregated tropical convection under warmer conditions, here we show a decrease in the subsidence fraction and an increase in the number of smaller cold pools, suggesting that it is possible to realize less convective organization with warming under real atmospheric conditions. Key Points: We used global nonhydrostatic climate simulations to study how clouds and large‐scale circulations change in response to global warmingChanges in the shortwave cloud radiative effect are key to evaluating the net cloud radiative effect, even in high‐resolution simulationsWe found no evidence of an increased amount of tropical convective aggregation in response to global warming [ABSTRACT FROM AUTHOR]

The traditional dynamical downscaling (TDD) method employs continuous integration of regional climate models (RCM) with the general circulation model (GCM) providing the initial and lateral boundary conditions. Dynamical downscaling simulations are constrained by physical principles and can generate a full set of climate information, providing one of the important approaches to projecting fine spatial-scale future climate information. However, the systematic biases of climate models often degrade the TDD simulations and hinder the application of dynamical downscaling in the climate-change related studies. New methods developed over past decades improve the performance of dynamical downscaling simulations. These methods can be divided into four groups: the TDD method, the pseudo global warming method, dynamical downscaling with GCM bias corrections, and dynamical downscaling with both GCM and RCM bias corrections. These dynamical downscaling methods are reviewed and compared in this paper. The merits and limitations of each dynamical downscaling method are also discussed. In addition, the challenges and potential directions in progressing dynamical downscaling methods are stated. [ABSTRACT FROM AUTHOR]

Serbia is situated at Balkan Peninsula, and currently majority of the territory is under warm temperate - fully humid climate type with warm summers (Cfb type, according to Koppen-Geiger Climate Classification). Observed changes in climate conditions since 1961 until present time show significant increase in temperature change and change in precipitation patterns. Disturbances in heat conditions, which are recorded to affect human health, agricultural production and forest ecosystem, are priority in climate change analysis and application in adaptation planning. Future change analysis show accelerated increase of temperature by the end of the 21st century, which proves the needs for immediate measures for mitigation of negative impacts. Temperature increase averaged over the territory of Serbia is 1.2 °C for the period 1996-2015 with respect to the period 1961-1980, with highest increase of maximum daily temperature during the summer season, 2.2 °C. Using high resolution multi-model ensemble approach for analysis of the future changes with respect to the base period 1986-2005, in compliance with Intergovernmental Panel on Climate Change (IPCC) fifth assessment report (AR5), it is estimated that temperature may increase by 1.9 °C according to Representative Concentration Pathway 4.5 (RCP4.5) scenario and by 4.4 °C according to RCP8.5 by the end of the century. Spatial distribution of temperature increase, intensification of high precipitation events and decrease of summer precipitation, show intrusion of subtropical climate over the Serbia and increase of high temperature and high precipitation risks. Results presented in this paper, using high-resolution multi-model ensemble approach, provide climate change information for short term to long term planning in different sectors of economy and preservation of human health and environment. [ABSTRACT FROM AUTHOR]

In this paper in three parts, climate change is approached by dealing with the three sides from which the danger comes: (i) global warming, (ii) increasing climate variability, (iii) more (and possibly more severe) meteorological and climatological extreme events. These are the three panels of this triptych review and this left panel is about (ii). This second panel starts with a compelling review of the present situation of food security, referring to African examples to improve the situation. Then the influence is discussed that the El Niño Southern Oscillation (ENSO) has on increasing climate variability as a consequence of climate change. It is indicated that, to date, climate models have been developed with little knowledge of agricultural systems dynamics. On the other hand one can illustrate that agricultural policy analysis has been conducted with little knowledge of climate dynamics. As a direct consequence of capricious behaviour of particularly rainfall in West Africa, the adaptation of its farmers has lagged behind enormously. This statement is valid for most farmers in sub-Saharan Africa. Within the climate science community there is an emerging effort to make findings more suitable for decision making, but as yet there is little consensus as to how data may be relied upon for decision making. Then a lot of attention is paid to how response farming, that is thoroughly defined, can play an important role in coping with the consequences of climate variability. Response farming is often limited envisaging rainfall events, but coping with weather and climate (and often soil) disasters as well as using windows of weather and climate (and often soil) opportunities are other forms of responding to weather and climate (and often soil) realities. Services such as in advice on design rules on above and below ground microclimate management or manipulation, with respect to any appreciable microclimatic improvement: shading, wind protection, mulching, other surface modification, drying, storage, frost protection and so on belong to such "response farming" agrometeorological services. Ideally, to get optimal preparations, farmers get advisories/services through extension intermediaries, backed by scientists, to properly understand decision options through discussions supported by economic analyses. Throughout the paper text boxes are used that illustrate local conditions that must be taken into account if one wants to understand the impacts/consequences of climate change for African farmers and how they may cope with them. [ABSTRACT FROM AUTHOR]

In this paper in three parts, climate change is approached by dealing with the three sides from which the danger comes: (i) global warming, (ii) increasing climate variability, (iii) more (and possibly more severe) meteorological and climatological extreme events. These are the three panels of this triptych review and the right panel on climate extremes and society's responses, including mitigation attempts as part of preparedness of African farmers, is this part. The occurrence of more (and possibly more severe) extreme meteorological/climatological events, as another likely consequence of climate change, is discussed, reviewing the literature and dealing for Africa with recent droughts and famines. It appears that there is more than sufficient proof that the numbers of disasters have risen globally, and on average at an increasing rate, over the last half a century, with more evidence in the later decades. Extreme hazards have a shorter recurrence time but whether they also have become more severe cannot be easily determined. This is due to developments in observations, populations and vulnerabilities and lack of developments in climate models. Only for increased temperature related disasters, severity has clearly become larger. However, recent more realistic calculations appear to suggest that there has been little change in drought over the past 60 years. In physical terms, there is also little or no evidence of increased severity of floods over the past century. Increasing farmer preparedness will be an important part of better responses to these conditions. The traditional response farming as to droughts, floods (annual recession and recurrent occasional ones), strong winds and other serious disasters should be among starting points. At the end of this paper, the contributions that tropical agriculture can make to reduce greenhouse gases (GHGs) in win-win situations are also dealt with. Soil carbon sequestration has a higher mitigation potential than emission reductions in African agriculture, although both may be important. These are best achieved under management systems with higher carbon density, as well as improved soil conservation. Agroforestry, assisted natural regeneration, forest rehabilitation, forest gardens, and improved forest fallow projects should all be eligible under the Clean Development Mechanism. Throughout the paper text boxes are used that illustrate local conditions that must be taken into account to understand the impacts/consequences of climate change for African farmers and how they may cope with them. [ABSTRACT FROM AUTHOR]

Global climate model simulations project that the tropical Andes Mountains of South America, which are particularly vulnerable to climate change because of a reliance on snow and glacial melt for freshwater resources, will experience enhanced warming in the near future, with both higher rates of warming at higher elevations within the mountain range itself and localized enhancement of warming exceeding surrounding areas of the globe. Yet recent surface temperature changes in the tropical Andes do not show evidence for either elevation-dependent warming or regional enhancement of warming on average. However, it remains a possibility that the expected warming trends in this region have begun to manifest in other ways (e.g., in the free atmosphere or at intermediate mountain elevations). This paper proposes evidence from several reanalysis products that there has indeed been a regional enhancement of midtropospheric warming around the central Andes over the past few decades that makes this region stand out as a hot spot within the broader pantropics. This trend is generally not reproduced by historical AMIP climate model simulations, which suggests that the mechanisms through which the atmosphere is warming over the central Andes are not adequately captured by climate models. Possible explanations for localized enhancement of warming in this region are considered. On the other hand, reanalysis products do not consistently exhibit enhanced warming at intermediate mountain elevations in the central Andes as evidenced by the generally moderate rates of change in the freezing-level height, except perhaps in the highest-resolution reanalysis product. [ABSTRACT FROM AUTHOR]

The projected climate change signals of a five-member high resolution ensemble, based on two global climate models (GCMs: ECHAM5 and CCCma3) and two regional climate models (RCMs: CLM and WRF) are analysed in this paper (Part II of a two part paper). In Part I the performance of the models for the control period are presented. The RCMs use a two nest procedure over Europe and Germany with a final spatial resolution of 7 km to downscale the GCM simulations for the present (1971-2000) and future A1B scenario (2021-2050) time periods. The ensemble was extended by earlier simulations with the RCM REMO (driven by ECHAM5, two realisations) at a slightly coarser resolution. The climate change signals are evaluated and tested for significance for mean values and the seasonal cycles of temperature and precipitation, as well as for the intensity distribution of precipitation and the numbers of dry days and dry periods. All GCMs project a significant warming over Europe on seasonal and annual scales and the projected warming of the GCMs is retained in both nests of the RCMs, however, with added small variations. The mean warming over Germany of all ensemble members for the fine nest is in the range of 0.8 and 1.3 K with an average of 1.1 K. For mean annual precipitation the climate change signal varies in the range of −2 to 9 % over Germany within the ensemble. Changes in the number of wet days are projected in the range of ±4 % on the annual scale for the future time period. For the probability distribution of precipitation intensity, a decrease of lower intensities and an increase of moderate and higher intensities is projected by most ensemble members. For the mean values, the results indicate that the projected temperature change signal is caused mainly by the GCM and its initial condition (realisation), with little impact from the RCM. For precipitation, in addition, the RCM affects the climate change signal significantly. [ABSTRACT FROM AUTHOR]

We evaluated the potential impact of future climate change on spring maize and single-crop rice in northeastern China (NEC) by employing climate and crop models. Based on historical data, diurnal temperature change exhibited a distinct negative relationship with maize yield, whereas minimum temperature correlated positively to rice yield. Corresponding to the evaluated climate change derived from coupled climate models included in the Coupled Model Intercomparison Project Phase 5 (CMIP5) under the Representative Concentration Pathway 4.5 scenario (RCP4.5), the projected maize yield changes for three future periods [2010-39 (period 1), 2040-69 (period 2), and 2070-99 (period 3)] relative to the mean yield in the baseline period (1976-2005) were 2.92%, 3.11% and 2.63%, respectively. By contrast, the evaluated rice yields showed slightly larger increases of 7.19%, 12.39%, and 14.83%, respectively. The uncertainties in the crop response are discussed by considering the uncertainties obtained from both the climate and the crop models. The range of impact of the uncertainty became markedly wider when integrating these two sources of uncertainty. The probabilistic assessments of the evaluated change showed maize yield to be relatively stable from period 1 to period 3, while the rice yield showed an increasing trend over time. The results presented in this paper suggest a tendency of the yields of maize and rice in NEC to increase (but with great uncertainty) against the background of global warming, which may offer some valuable guidance to government policymakers. [ABSTRACT FROM AUTHOR]

ABSTRACT The aim of this paper is to study the model's simulated frequency, track, intensity and location of cyclonic storms (CSs) and severe cyclonic storms (SCSs) in the Bay of Bengal (BoB), India. For the purpose, the PRECIS (Providing REgional Climates for Impacts Studies) a regional climate modelling system, of UK Met Office, is used. This model is integrated for the period 1961-1990 (baseline) and the future time period 2071-2100 (High emission scenario, A2). To run the model, the initial and lateral boundary conditions are supplied by UK Met Office. The analysis of frequency, track, intensity and location are carried out for May, June, September and October for the period 1961-1990 and 2071-2100. To evaluate the model's performance in simulating storms frequency during 1961-1990, chi square test is carried out with observed storms for the same period. The model's simulated frequency of storms is an overestimation of observations although the frequency of model's simulated storms during 2071-2100 is less than that of during 1961-1990. In general, model's simulated storms are found moving in the northwest direction from their initial location in all months during 1961-1990 and 2071-2100. In model's simulations, the drop in central pressure is relatively more in the months of May, June, September and October during 2071-2100 compared with that during 1961-1990. During 2071-2100, more intense storms may be possible in the months of May and June compared with that of September and October. It is observed that the model is able to simulate the initial locations of storms during 1961-1990 and 2071-2100 close to observations for the months of June and September, especially. [ABSTRACT FROM AUTHOR]

An irreducibly simple climate-sensitivity model is designed to empower even non-specialists to research the question how much global warming we may cause. In 1990, the First Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) expressed 'substantial confidence' that near-term global warming would occur twice as fast as subsequent observation. Given rising CO concentration, few models predicted no warming since 2001. Between the pre-final and published drafts of the Fifth Assessment Report, IPCC cut its near-term warming projection substantially, substituting 'expert assessment' for models' near-term predictions. Yet its long-range predictions remain unaltered. The model indicates that IPCC's reduction of the feedback sum from 1.9 to 1.5 W m K mandates a reduction from 3.2 to 2.2 K in its central climate-sensitivity estimate; that, since feedbacks are likely to be net-negative, a better estimate is 1.0 K; that there is no unrealized global warming in the pipeline; that global warming this century will be <1 K; and that combustion of all recoverable fossil fuels will cause <2.2 K global warming to equilibrium. Resolving the discrepancies between the methodology adopted by IPCC in its Fourth and Fifth Assessment Reports that are highlighted in the present paper is vital. Once those discrepancies are taken into account, the impact of anthropogenic global warming over the next century, and even as far as equilibrium many millennia hence, may be no more than one-third to one-half of IPCC's current projections. [ABSTRACT FROM AUTHOR]

Observations and results of numerical experiments with climate models under different green-house-gas emission scenarios point to a reconstruction of the thermal and circulation atmospheric regime induced by global climate changes. In particular, an increase in atmospheric static stability, a poleward shift of midlatitude storm tracks, a decrease in the frequency of extratropical cyclones, and a change in their intensity are found at tropical and middle latitudes. This paper, using a simplified idealized model of baroclinic instability, investigates the influence of small variations in the basic atmospheric parameters governing the development of baroclinic instability, namely, static stability and the vertical quasi-zonal flow velocity shear induced by a meridional temperature gradient, on variations in the growth rate of the amplitude of synopticscale unstable waves. Analytical expressions are derived for absolute and relative sensitivity functions to estimate the absolute and relative contribution of variations in the static stability and the vertical flow velocity shear to a change in the growth rate of the amplitude of unstable modes. [ABSTRACT FROM AUTHOR]

This paper mainly addresses two issues that concern the longwave climate feedbacks. First, it is recognized that the radiative forcing of greenhouse gases, as measured by their impact on the outgoing longwave radiation (OLR), may vary across different climate models even when the concentrations of these gases are identically prescribed. This forcing variation contributes to the discrepancy in these models' projections of surface warming. A method is proposed to account for this effect in diagnosing the sensitivity and feedbacks in the models. Second, it is shown that the stratosphere is an important factor that affects the OLR in transient climate change. Stratospheric water vapor and temperature changes may both act as a positive feedback mechanism during global warming and cannot be fully accounted as a 'stratospheric adjustment' of radiative forcing. Neglecting these two issues may cause a bias in the longwave cloud feedback diagnosed as a residual term in the decomposition of OLR variations. There is no consensus among the climate models on the sign of the longwave cloud feedback after accounting for both issues. [ABSTRACT FROM AUTHOR]

Coupled ocean-atmosphere general circulation models (GCMs) lack sufficient resolution to model the regional detail of changes to mean circulation and rainfall with projected climate warming. In this paper, changes in mean circulation and rainfall in GCMs are compared to those in a variable resolution regional climate model, the Conformal Cubic Atmospheric Model (CCAM), under a high greenhouse gas emissions scenario. The study site is Tasmania, Australia, which is positioned within the mid-latitude westerlies of the southern hemisphere. CCAM projects a different response in mean sea level pressure and mid-latitude westerly circulation to climate warming to the GCMs used as input, and shows greater regional detail of the boundaries between regions of increasing and decreasing rainfall. Changes in mean circulation dominate the mean rainfall response in western Tasmania, whereas changes to rainfall in the East Coast are less related to mean circulation changes. CCAM projects an amplification of the dominant westerly circulation over Tasmania and this amplifies the seasonal cycle of wet winters and dry summers in the west. There is a larger change in the strength than in the incidence of westerly circulation and rainfall events. We propose the regional climate model displays a more sensitive atmospheric response to the different rates of warming of land and sea than the GCMs as input. The regional variation in these results highlight the need for dynamical downscaling of coupled general circulation models to finely resolve the influence of mean circulation and boundaries between regions of projected increases and decreases in rainfall. [ABSTRACT FROM AUTHOR]

Summary: The effect of future climate scenarios on surface water and groundwater resources has been shown to have a consequent impact on water-dependent ecosystems. A regional-scale analysis of changes in water resources as a result of changing climate was undertaken in south-western Australia; a region with a large number of nationally and internationally recognised water-dependent ecosystems. The paper examines the potential environmental impacts of a substantial reduction in rainfall and an increase in temperature as projected by global climate models (GCMs) on river and groundwater-dependent terrestrial vegetation by 2030. Climate change effects on environmentally significant flow regimes were evaluated by applying the climate projections from 15 GCMs under three global warming ‘scenarios to rainfall–runoff and groundwater models. It was estimated that under a dry future climate scenario, the frequency of river flow rates important for ecological communities is likely to be reduced by up to 2months per year, which is likely to cause a significant level of stress to ecological communities. Additionally, the duration of no-flow periods may increase by more than 120days in some streams. Under a dry future climate scenario, groundwater-dependent vegetation is projected to be at a high risk in over 19% of its current habitat area. Water-dependent ecosystems are also projected to be affected by an increase in groundwater abstraction. The results indicate that the projected impacts of future climate conditions are not likely to be uniform across the region but overall they could cause a continuing threat to water-dependent ecosystems. The implementation of water management plans should place particular emphasis on the ecological water requirements in 6 of the 13 river catchments in south-western Australia and in areas where groundwater abstraction is high. The climate projections and ecological impacts are a continuation of the trends that have taken place in the past three decades. [Copyright &y& Elsevier]

Abstract: We compare the performance of a recently proposed empirical climate model based on astronomical harmonics against all CMIP3 available general circulation climate models (GCM) used by the to interpret the 20th century global surface temperature. The proposed astronomical empirical climate model assumes that the climate is resonating with, or synchronized to a set of natural harmonics that, in previous works (), have been associated to the solar system planetary motion, which is mostly determined by Jupiter and Saturn. We show that the GCMs fail to reproduce the major decadal and multidecadal oscillations found in the global surface temperature record from 1850 to 2011. On the contrary, the proposed harmonic model (which herein uses cycles with 9.1, 10–10.5, 20–21, 60–62 year periods) is found to well reconstruct the observed climate oscillations from 1850 to 2011, and it is shown to be able to forecast the climate oscillations from 1950 to 2011 using the data covering the period 1850–1950, and vice versa. The 9.1-year cycle is shown to be likely related to a decadal Soli/Lunar tidal oscillation, while the 10–10.5, 20–21 and 60–62 year cycles are synchronous to solar and heliospheric planetary oscillations. We show that the IPCC GCM''s claim that all warming observed from 1970 to 2000 has been anthropogenically induced is erroneous because of the GCM failure in reconstructing the quasi 20-year and 60-year climatic cycles. Finally, we show how the presence of these large natural cycles can be used to correct the IPCC projected anthropogenic warming trend for the 21st century. By combining this corrected trend with the natural cycles, we show that the temperature may not significantly increase during the next 30 years mostly because of the negative phase of the 60-year cycle. If multisecular natural cycles (which according to some authors have significantly contributed to the observed 1700–2010 warming and may contribute to an additional natural cooling by 2100) are ignored, the same IPCC projected anthropogenic emissions would imply a global warming by about 0.3–1.2°C by 2100, contrary to the IPCC 1.0–3.6°C projected warming. The results of this paper reinforce previous claims that the relevant physical mechanisms that explain the detected climatic cycles are still missing in the current GCMs and that climate variations at the multidecadal scales are astronomically induced and, in first approximation, can be forecast. [Copyright &y& Elsevier]

Abstract: The paper presents a methodology for estimating high quantiles of distributions of daily temperature in a non-stationary context, based on peaks-over-threshold analysis with a time-dependent threshold expressed in terms of regression quantiles. The extreme value models are applied to estimate 20-yr return values of maximum daily temperature over Europe in transient global climate model (GCM) simulations for the 21st century. A comparison of scenarios of changes in the 20-yr return temperatures based on the non-stationary peaks-over-threshold models with conventional stationary models is performed. It is demonstrated that the application of the stationary extreme value models in temperature data from GCM scenarios yields results that may be to a large extent biased, while the non-stationary models lead to spatial patterns that are robust and enable one to detect areas where the projected warming in the tail of the distribution of daily temperatures is largest. The method also allows splitting the projected warming of extremely high quantiles into two parts that reflect change in the location and scale of the distribution of extremes, respectively. Spatial patterns of the two components differ significantly in the examined climate change projections over Europe. [Copyright &y& Elsevier]

This paper examines variations of the surface air temperature (SAT) over China and the globe in the twentieth century simulated by 19 coupled climate models driven by historical natural and anthropogenic forcings. Most models perform well in simulating both the global and the Northern Hemispheric mean SAT evolutions of the twentieth century. The inclusion of natural forcings improves the simulation, in particular for the first half of the century. The reproducibility of the SAT averaged over China is lower than that of the global and hemispheric averages, but it is still acceptable. The contribution of natural forcings to the SAT over China in the first half of the century is not as robust as that to the global and hemispheric averages. No model could successfully produce the reconstructed warming over China in the 1920s. The prescribed natural and anthropogenic forcings in the coupled climate models mainly produce the warming trends and the decadal- to interdecadal-scale SAT variations with poor performances at shorter time scales. The prominent warming trend in the last half of the century over China and its acceleration in recent decades are weakly simulated. There are discrepancies between the simulated and observed regional features of the SAT trend over China. Few models could produce the summertime cooling over the middle part of eastern China (27°–36°N), while two models acceptably produce the meridional gradients of the wintertime warming trends, with north China experiencing larger warming. Limitations of the current state-of-the-art coupled climate models in simulating spatial patterns of the twentieth-century SAT over China cast a shadow upon their capability toward projecting credible geographical distributions of future climate change through Intergovernmental Panel on Climate Change (IPCC) scenario simulations. [ABSTRACT FROM AUTHOR]