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Although it is critical to assess the accuracy of attribution studies, the fraction of attributable risk (FAR) cannot be directly assessed from observations since it involves the probability of an event in a world that did not happen, the 'natural' world where there was no human influence on climate. Instead, reliability diagrams (usually used to compare probabilistic forecasts to the observed frequencies of events) have been used to assess climate simulations employed for attribution and by inference to evaluate the attribution study itself. The Brier score summarizes this assessment of a model by the reliability diagram. By constructing a modeling framework where the true FAR is already known, this paper shows that Brier scores are correlated to the accuracy of a climate model ensemble's calculation of FAR, although only weakly. This weakness exists because the diagram does not account for accuracy of simulations of the natural world. This is better represented by two reliability diagrams from early and late in the period of study, which would have, respectively, less and greater anthropogenic climate forcing. Two new methods are therefore proposed for assessing the accuracy of FAR, based on using the earlier observational period as a proxy for observations of the natural world. It is found that errors from model-based estimates of these observable quantities are strongly correlated with errors in the FAR estimated in the model framework. These methods thereby provide new observational estimates of the accuracy in FAR. [ABSTRACT FROM AUTHOR]

Reconstructions of historical climate changes indicate that surface air temperatures decreased over the preindustrial last millennium. Conflicting explanations have been proposed for the cause of the transition from the Medieval Climate Anomaly (MCA) in the early part of the last millennium to the Little Ice Age (LIA) near its end. The possible causes include volcanic emissions, total solar irradiance (TSI) variations, greenhouse gas concentration fluctuations, and orbital forcing variations. In the present paper, it is demonstrated that all of these climate forcings contribute significantly to simulated surface air temperature (SAT) and sea ice concentration changes over this period. On the other hand, simulated ocean heat content appears to respond significantly only to volcanic and TSI variations. In model simulations at T85 spectral resolution, TSI reductions and volcanic emissions together generate significant increases in sea ice extent in the Barents Sea, which is found to be responsible for most of the temperature reductions over northwestern Europe. TSI appears less important to Arctic sea ice and SAT changes in simulations at T42 spectral resolution, which are weaker than at T85 resolution. Such resolution dependence is attributed to differences in background conditions in the responses to these external climate forcings. Nonlinearities in the forcing responses and sensitivities to background conditions challenge the assumption that sensitivity tests for given forcings can be run independently. Additionally, it is demonstrated that an ensemble of model simulations is required to isolate forcing responses even over a period as long as the last millennium. [ABSTRACT FROM AUTHOR]

Large-scale synoptic circulations have a profound effect on western U.S. summer weather and climate. Heat waves, water availability, the distribution of monsoonal moisture, fire-weather conditions, and other phenomena are impacted by the position and amplitude of large-scale synoptic circulations. Furthermore, regional weather is modulated by the interactions of the large-scale flow with terrain and land-water contrasts. It is therefore crucial to understand projected changes in large-scale circulations and their variability under anthropogenic global warming. Although recent research has examined changes in the jet stream, storm tracks, and synoptic disturbances over the Northern Hemisphere under global warming, most papers have focused on the cold season. In contrast, this work analyzes the projected trends in the spatial distribution and amplitude of large-scale synoptic disturbances over the western United States and eastern Pacific during July and August. It is shown that CMIP5 models project weaker mean midtropospheric gradients in geopotential height as well as attenuated temporal variability in geopotential height, temperature, vorticity, vertical motion, and sea level pressure over this region. Most models suggest reduced frequency of troughs and increased frequency of ridges over the western United States. These changes in the variability of synoptic disturbances have substantial implications for future regional weather and climate. [ABSTRACT FROM AUTHOR]

Potential and real predictive skill of the frequency of extreme rainfall in southeastern South America for the December-February season are evaluated in this paper, finding evidence indicating that mechanisms of climate variability at one time scale contribute to the predictability at another scale; that is, taking into account the interference of different potential sources of predictability at different time scales increases the predictive skill. Part I of this study suggested that a set of daily atmospheric circulation regimes, or weather types, was sensitive to these cross-time scale interferences, conducive to the occurrence of extreme rainfall events in the region, and could be used as a potential predictor. At seasonal scale, a combination of those weather types indeed tends to outperform all the other candidate predictors explored (i.e., sea surface temperature patterns, phases of the Madden-Julian oscillation, and combinations of both). Spatially averaged Kendall's τ improvements of 43% for the potential predictability and 23% for real-time predictions are attained with respect to standard models considering sea surface temperature fields alone. A new subseasonal-to-seasonal predictive methodology for extreme rainfall events is proposed based on probability forecasts of seasonal sequences of these weather types. The cross-validated real-time skill of the new probabilistic approach, as measured by the hit score and the Heidke skill score, is on the order of twice that associated with climatological values. The approach is designed to offer useful subseasonal-to-seasonal climate information to decision-makers interested not only in how many extreme events will happen in the season but also in how, when, and where those events will probably occur. [ABSTRACT FROM AUTHOR]

Changes in internal variability of seasonal and annual mean 2-m temperature in response to anthropogenic forcing are quantified for a global domain using climate models driven by a twenty-first-century high-emissions scenario. While changes in variance have been quantified previously in a univariate sense, the field significance of such changes has remained unclear. This paper proposes a new field significance test for changes in variance that accounts for spatial and temporal relationships within the domain. The test proposed here uses an optimization technique based on discriminant analysis, yielding results that are invariant to linear transformations of the data and therefore independent of normalization procedures. Multiple significance tests are employed because spatial fields can differ in many ways in a multivariate space. All climate models investigated here predict significant changes in internal variability of temperature in response to anthropogenic forcing. The models consistently predict decreases to temperature variance in regions of seasonal sea ice formation and across the Southern Ocean by the end of the twenty-first century. While more than half the models also predict significant changes in variance over ENSO regions and the North Atlantic Ocean, the direction of this change is model dependent. Seasonal mean changes are remarkably similar to annual mean changes, but there are model-dependent exceptions. Some models predict future variability that is more than double their preindustrial control variability, raising questions about the adequacy of doubling uncertainty estimates to test robustness in detection and attribution studies. [ABSTRACT FROM AUTHOR]

The intertropical convergence zone (ITCZ) has been the focus of considerable research in recent years, with much of this work concerned with how the latitude of maximum tropical precipitation responds to natural climate variability and to radiative forcing. The width of the ITCZ, however, has received little attention despite its importance for regional climate and for understanding the general circulation of the atmosphere. This paper investigates the ITCZ width in simulations with an idealized general circulation model over a wide range of climates. The ITCZ, defined as the tropical region where there is time-mean ascent, displays rich behavior as the climate varies, widening with warming in cool climates, narrowing in temperate climates, and maintaining a relatively constant width in hot climates. The mass and energy budgets of the Hadley circulation are used to derive expressions for the area of the ITCZ relative to the area of the neighboring descent region, and for the sensitivity of the ITCZ area to changes in climate. The ITCZ width depends primarily on four quantities: the net energy input to the tropical atmosphere, the advection of moist static energy by the Hadley circulation, the transport of moist static energy by transient eddies, and the gross moist stability. Different processes are important for the ITCZ width in different climates, with changes in gross moist stability generally having a weak influence relative to the other processes. The results are likely to be useful for analyzing the ITCZ width in complex climate models and for understanding past and future climate change in the tropics. [ABSTRACT FROM AUTHOR]

Solar radiation management (SRM) has been proposed as a form of geoengineering to reduce the climate effects of anthropogenic greenhouse gas emissions. Modeling studies have concluded that SRM, through a reduction in total solar irradiance by approximately 2%, roughly compensates for global mean temperature changes from a doubling of carbon dioxide concentrations. This paper examines the impact of SRM on the terrestrial hydrologic cycle using the Community Land Model, version 4, coupled to the Community Atmosphere Model, version 4, with reductions in solar radiation relative to simulations with present-day and elevated CO2 concentrations. There are significant global and regional impacts due to vegetation-climate interactions that are not compensated when reductions in total solar irradiance of 1%, 2%, and 3% are imposed on top of a doubling of present-day CO2 concentrations. Water cycling slows down under SRM, including decreases in global mean precipitation and evapotranspiration. Changes in runoff and soil moisture are spatially and temporally variable, with implications for local water availability. In the tropics, evapotranspiration decreases because of increases in vegetation water use efficiency. In northern midlatitudes, soil moisture increases when evapotranspiration decreases, with some exceptions during boreal summer. Changes in soil evaporation influence water cycling in the southern subtropics, rather than changes in transpiration. The hydrologic response to SRM is nonlinear, with global mean decreases greater than expected. These results imply that SRM may not compensate for higher greenhouse gas concentrations when one considers land-atmosphere interactions. [ABSTRACT FROM AUTHOR]

This paper assesses intermodel spread in the slope of global-mean precipitation change Δ P with respect to surface temperature change. The ambiguous estimates in the literature for this slope are reconciled by analyzing four experiments from phase 5 of CMIP (CMIP5) and considering different definitions of the slope. The smallest intermodel spread (a factor of 1.5 between the highest and lowest estimate) is found when using a definition that disentangles temperature-independent precipitation changes (the adjustments) from the slope of the temperature-dependent precipitation response; here this slope is referred to as the hydrological sensitivity parameter η. The estimates herein show that η is more robust than stated in most previous work. The authors demonstrate that adjustments and η estimated from a steplike quadrupling CO2 experiment serve well to predict Δ P in a transient CO2 experiment. The magnitude of η is smaller in the coupled ocean-atmosphere quadrupling CO2 experiment than in the noncoupled atmosphere-only experiment. The offset in magnitude due to coupling suggests that intermodel spread may undersample uncertainty. Also assessed are the relative contribution of η, the surface warming, and the adjustment on the spread in Δ P on different time scales. Intermodel variation of both η and the adjustment govern the spread in Δ P in the years immediately after the abrupt forcing change. In equilibrium, the uncertainty in Δ P is dominated by uncertainty in the equilibrium surface temperature response. A kernel analysis reveals that intermodel spread in η is dominated by intermodel spread in tropical lower tropospheric temperature and humidity changes and cloud changes. [ABSTRACT FROM AUTHOR]

This paper examines trends in the southern annular mode (SAM) and the strength, position, and width of the Southern Hemisphere surface westerly wind jet in observations, reanalyses, and models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). First the period over 1951-2011 is considered, and it is shown that there are differences in the SAM and jet trends between the CMIP5 models, the Hadley Centre gridded SLP (HadSLP2r) dataset, and the Twentieth Century Reanalysis. The relationships between these trends demonstrate that the SAM index cannot be used to directly infer changes in any one kinematic property of the jet. The spatial structure of the observed trends in SLP and zonal winds is shown to be largest, but also most uncertain, in the southeastern Pacific. To constrain this uncertainty six reanalyses are included and compared with station-based observations of SLP. The CMIP5 mean SLP trends generally agree well with the direct observations, despite some climatological biases, while some reanalyses exhibit spuriously large SLP trends. Similarly, over the more reliable satellite era the spatial pattern of CMIP5 SLP trends is in excellent agreement with HadSLP2r, whereas several reanalyses are not. Then surface winds are compared with a satellite-based product, and it is shown that the CMIP5 mean trend is similar to observations in the core region of the westerlies, but that several reanalyses overestimate recent trends. The authors caution that studies examining the impact of wind changes on the Southern Ocean could be biased by these spuriously large trends in reanalysis products. [ABSTRACT FROM AUTHOR]

Climate models have emerged as an essential tool for studying the earth's climate. Global models are computationally expensive, and so a relatively coarse spatial resolution must be used within the model. This hinders direct application for many impacts studies that require regional and local climate information. A regional model with boundary conditions taken from the global model achieves a finer spatial scale for local analysis. In this paper the authors propose a new method for assessing the value added by these higher-resolution models, and they demonstrate the method within the context of regional climate models (RCMs) from the North American Regional Climate Change Assessment Program (NARCCAP) project. This spectral approach using the discrete cosine transformation (DCT) is based on characterizing the joint relationship between observations, coarser-scale models, and higher-resolution models to identify how the finer scales add value over the coarser output. The joint relationship is computed by estimating the covariance of the data sources at different spatial scales with a Bayesian hierarchical model. Using this model the authors can then estimate the value added by each data source over the others. For the NARCCAP data, they find that the higher-resolution models add value starting with low wavenumbers corresponding to features 550 km apart (or 11 total 50-km grid boxes per cycle) all the way down to higher wavenumbers at 150 km apart (3 grid boxes per cycle). [ABSTRACT FROM AUTHOR]

In earlier work, it was proposed that the reliability of climate change projections, particularly of regional rainfall, could be improved if such projections were calibrated using quantitative measures of reliability obtained by running the same model in seasonal forecast mode. This proposal is tested for fast atmospheric processes (such as clouds and convection) by considering output from versions of the same atmospheric general circulation model run at two different resolutions and forced with prescribed sea surface temperatures and sea ice. Here output from the high-resolution version of the model is treated as a proxy for truth. The reason for using this approach is simply that the twenty-first-century climate change signal is not yet known and, hence, no climate change projections can be verified using observations. Quantitative assessments of reliability of the low-resolution model, run in seasonal hindcast mode, are used to calibrate climate change time-slice projections made with the same low-resolution model. Results show that the calibrated climate change probabilities are closer to the proxy truth than the uncalibrated probabilities. Given that seasonal forecasts are performed operationally already at several centers around the world, in a seamless forecast system they provide a resource that can be used without cost to help calibrate climate change projections and make them more reliable for users. [ABSTRACT FROM AUTHOR]

Earth system models are indispensable tools in climate studies. The Coupled Model Intercomparison Project (CMIP) is a coordinated effort of the Earth system modeling community to intercompare existing models. An accurate simulation of surface solar radiation fluxes is of major importance for the accuracy of simulations of the near-surface climate in Earth system models. The present study provides a quantitative assessment of the accuracy and multidecadal changes of surface solar radiation fluxes for model results from two phases of CMIP. The entire archives of phase 5 of CMIP (CMIP5) and its predecessor phase 3 (CMIP3) are analyzed for present-day climate conditions. A relative model ranking is provided, and its uncertainty is quantified using different global observational records. It is shown that the choice of an observational dataset can have a major influence on relative model ranking between CMIP models. However the multidecadal variability of surface solar radiation fluxes, also known as global 'dimming' or 'brightening,' is largely underestimated by the CMIP models. [ABSTRACT FROM AUTHOR]

How El Niño-Southern Oscillation (ENSO) will change under global warming affects changes in extreme events around the world. The change of ENSO amplitude is investigated based on the historical simulations and representative concentration pathway (RCP) 8.5 experiments in phase 5 of the Coupled Model Intercomparison Project (CMIP5). The projected change in ENSO amplitude is highly uncertain with large intermodel uncertainty. By using the relative sea surface temperature (SST) as a measure of convective instability, this study finds that the spatial pattern of tropical Pacific surface warming is the major source of intermodel uncertainty in ENSO amplitude change. In models with an enhanced mean warming in the eastern equatorial Pacific, the barrier to deep convection is reduced, and the intensified rainfall anomalies of ENSO amplify the wind response and hence SST variability. In models with a reduced eastern Pacific warming, conversely, ENSO amplitude decreases. Corroborating the mean SST pattern effect, intermodel uncertainty in changes of ENSO-induced rainfall variability decreases substantially in atmospheric simulations forced by a common ocean warming pattern. Thus, reducing the uncertainty in the Pacific surface warming pattern helps improve the reliability of ENSO projections. To the extent that correcting model biases favors an El Niño-like mean warming pattern, this study suggests an increase in ENSO-related SST variance likely under global warming. [ABSTRACT FROM AUTHOR]

This study used air temperatures from a suite of regional climate models participating in the North American Climate Change Assessment Program (NARCCAP) together with two atmospheric reanalysis datasets to investigate changes in freezing days (defined as days with daily average temperature below freezing) likely to occur between 30-yr baseline (1971-2000) and midcentury (2041-70) periods across most of North America. Changes in NARCCAP ensemble mean winter temperature show a strong gradient with latitude, with warming of over 4°C near Hudson Bay. The decline in freezing days ranges from less than 10 days across north-central Canada to nearly 90 days in the warmest areas of the continent that currently undergo seasonally freezing conditions. The area experiencing freezing days contracts by 0.9-1.0 × 106 km2 (5.7%-6.4% of the total area). Areas with mean annual temperature between 2° and 6°C and a relatively low rate of change in climatological daily temperatures (<0.2°C day−) near the time of spring thaw will encounter the greatest decreases in freezing days. Advances in the timing of spring thaw will exceed the delay in fall freeze across much of the United States, with the reverse pattern likely over most of Canada. [ABSTRACT FROM AUTHOR]

The aerial hydrological cycle response to CO2 doubling from a Lagrangian, rather than Eulerian, perspective is evaluated using information from numerical water tracers implemented in a global climate model. While increased surface evaporation (both local and remote) increases precipitation globally, changes in transport are necessary to create a spatial pattern where precipitation decreases in the subtropics and increases substantially at the equator. Overall, changes in the convergence of remotely evaporated moisture are more important to the overall precipitation change than changes in the amount of locally evaporated moisture that precipitates in situ. It is found that CO2 doubling increases the fraction of locally evaporated moisture that is exported, enhances moisture exchange between ocean basins, and shifts moisture convergence within a given basin toward greater distances between moisture source (evaporation) and sink (precipitation) regions. These changes can be understood in terms of the increased residence time of water in the atmosphere with CO2 doubling, which corresponds to an increase in the advective length scale of moisture transport. As a result, the distance between where moisture evaporates and where it precipitates increases. Analyses of several heuristic models further support this finding. [ABSTRACT FROM AUTHOR]

Using simulations performed with 24 coupled atmosphere-ocean global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5), projections of Northern Hemisphere daily snowfall events under the RCP8.5 emissions scenario are analyzed for the periods of 2021-50 and 2071-2100 and compared to the historical period of 1971-2000. The overall frequency of daily snowfall events is simulated to decrease across much of the Northern Hemisphere, except at the highest latitudes such as northern Canada, northern Siberia, and Greenland. Seasonal redistributions of daily snowfall event frequency and average daily snowfall are also projected to occur in some regions. For example, large portions of the Northern Hemisphere, including much of Canada, Tibet, northern Scandinavia, northern Siberia, and Greenland, are projected to experience increases in average daily snowfall and event frequency in midwinter. But in warmer months, the regions with increased snowfall become fewer in number and are limited to northern Canada, northern Siberia, and Greenland. These simulations also show changes in the frequency distribution of daily snowfall event intensity, including an increase in heavier snowfall events even in some regions where the overall snowfall decreases. The projected changes in daily snowfall event frequency exhibit some dependence on the temperature biases of the individual models in certain regions and times of the year, with colder models typically toward the positive end of the distribution of event frequency changes and warmer models toward the negative end, particularly in regions near the transition zone between increasing and decreasing snowfall. [ABSTRACT FROM AUTHOR]

El Niño-Southern Oscillation (ENSO) is one of the most important drivers of climatic variability on the global scale. Much of this variability arises in response to ENSO-driven changes in tropical Pacific rainfall. Previous research has shown that the ENSO-driven tropical Pacific rainfall variability can shift east and intensify in response to global warming, even if ENSO-related SST variability remains unchanged. Here, the twenty-first century changes in ENSO-driven tropical Pacific rainfall variability in 32 CMIP5 models forced under the representative concentration pathway 8.5 (RCP8.5) scenario are examined, revealing that the pattern of changes in ENSO-driven rainfall is not only gradually enhanced but also shifts steadily eastward along with the global-mean temperature increase. Using a recently developed moisture budget decomposition method, it is shown that the projected changes in ENSO-driven rainfall variability in the tropical Pacific can be primarily attributed to a projected increase in both mean-state surface moisture and spatially relative changes in mean-state SST, defined as the departure of local SST changes from the tropical mean. The enhanced moisture increase enlarges the thermodynamic component of ENSO rainfall changes. The enhanced El Niño-like changes in mean-state SST steadily move the dynamic component of changes in ENSO-driven rainfall variability to the central-eastern Pacific, along with increasing global-mean temperature. [ABSTRACT FROM AUTHOR]

Previous studies show that the first principal mode of the variability of the seasonal mean Hadley circulation (HC) is an equatorial asymmetric mode (AM) with long-term trend. This study demonstrates that the variability of the boreal autumn [September-November (SON)] HC is also dominated by an AM, but with multidecadal variability. The SON AM has ascending and descending branches located at approximately 20°N and 20°S, respectively, and explains about 40% of the total variance. Further analysis reveals that the AM is closely linked to the Atlantic multidecadal oscillation (AMO), which is associated with a large cross-equatorial sea surface temperature (SST) gradient and sea level pressure (SLP) gradient. The cross-equatorial thermal contrast further induces an equatorial asymmetric HC anomaly. Numerical simulations conducted on an atmospheric general circulation model also suggest that AMO-associated SST anomalies can also induce a cross-equatorial SLP gradient and anomalous vertical shear of the meridional wind at the equator, both of which indicate asymmetric HC anomaly. Therefore, the AM of the variability of the boreal autumn HC has close links to the AMO. Further analysis demonstrates that the AMO in SON has a closer relationship with AM than those in the other seasons. A possible reason is that the AMO-associated zonal mean SST anomaly in the tropics has differences among the four seasons, which leads to different atmospheric circulation responses. The AM in SON has inversed impacts on the tropical precipitation, suggesting that the precipitation difference between the northern and southern tropics has multidecadal variability. [ABSTRACT FROM AUTHOR]

The ocean's surface salinity field has changed over the observed record, driven by an intensification of the water cycle in response to global warming. However, the origin and causes of the coincident subsurface salinity changes are not fully understood. The relationship between imposed surface salinity and temperature changes and their corresponding subsurface changes is investigated using idealized ocean model experiments. The ocean's surface has warmed by about 0.5°C (50 yr)−1 while the surface salinity pattern has amplified by about 8% per 50 years. The idealized experiments are constructed for a 50-yr period, allowing a qualitative comparison to the observed salinity and temperature changes previously reported. The comparison suggests that changes in both modeled surface salinity and temperature are required to replicate the three-dimensional pattern of observed salinity change. The results also show that the effects of surface changes in temperature and salinity act linearly on the changes in subsurface salinity. Surface salinity pattern amplification appears to be the leading driver of subsurface salinity change on depth surfaces; however, surface warming is also required to replicate the observed patterns of change on density surfaces. This is the result of isopycnal migration modified by the ocean surface warming, which produces significant salinity changes on density surfaces. [ABSTRACT FROM AUTHOR]

Climate models consistently project reduced surface warming over the eastern equatorial Indian Ocean (IO) under increased greenhouse gas (GHG) forcing. This IO dipole (IOD)-like warming pattern, regarded as robust based on consistency among models by the new Intergovernmental Panel on Climate Change (IPCC) report, results in a large increase in the frequency of extreme positive IOD (pIOD) events, elevating the risk of climate and weather disasters in the future over IO rim countries. These projections, however, do not consider large model biases in both the mean state and interannual IOD variance. In particular, a 'present-future relationship' is identified between the historical simulations and representative concentration pathway (RCP) 8.5 experiments from phase 5 of the Coupled Model Intercomparison Project (CMIP5) multimodel ensemble: models with an excessive IOD amplitude bias tend to project a strong IOD-like warming pattern in the mean and a large increase in extreme pIOD occurrences under increased GHG forcing. This relationship links the present simulation errors to future climate projections, and is also consistent with our understanding of Bjerknes ocean-atmosphere feedback. This study calibrates regional climate projections by using this present-future relationship and observed IOD amplitude. The results show that the projected IOD-like pattern of mean changes and frequency increase of extreme pIOD events are largely artifacts of model errors and unlikely to emerge in the future. These results illustrate that a robust projection may still be biased and it is important to consider the model bias effect. [ABSTRACT FROM AUTHOR]

A dry dynamical core is used to investigate the seasonal sensitivity of the circulation to two idealized thermal forcings: a tropical upper-tropospheric heating and a polar lower-tropospheric heating. The thermal forcings are held constant, and the response of the circulation in each month of the year is explored. First, the circulation responses to tropical warming and polar warming are studied separately, and then the response to the simultaneously applied forcings is analyzed. Finally, the seasonality of the internal variability of the circulation is explored as a possible mechanism to explain the seasonality of the responses. The primary results of these experiments are as follows: 1) There is a seasonal sensitivity in the circulation response to both the tropical and polar forcings. 2) The jet position response to each forcing is greatest in the transition seasons, and the jet speed response exhibits a seasonal sensitivity to both forcings, although the seasonal sensitivities are not the same. 3) The circulation response is nonlinear in the transition seasons, but approximately linear in the winter months. 4) The internal variability of the unforced circulation exhibits a seasonal sensitivity that may partly explain the seasonal sensitivity of the forced response. The seasonality of the internal variability of daily MERRA reanalysis data is compared to that of the model, demonstrating that the broad conclusions drawn from this idealized modeling study may be useful for understanding the jet response to anthropogenic forcing. [ABSTRACT FROM AUTHOR]

Previous observations and simulations suggest that an approximate 3°-5°C warming occurred at intermediate depths in the North Atlantic over several millennia during Heinrich stadial 1 (HS1), which induces warm salty water (WSW) lying beneath surface cold freshwater. This arrangement eventually generates ocean convective available potential energy (OCAPE), the maximum potential energy releasable by adiabatic vertical parcel rearrangements in an ocean column. The authors find that basin-scale OCAPE starts to appear in the North Atlantic (~67.5°-73.5°N) and builds up over decades at the end of HS1 with a magnitude of about 0.05 J kg−1. OCAPE provides a key kinetic energy source for thermobaric cabbeling convection (TCC). Using a high-resolution TCC-resolved regional model, it is found that this decadal-scale accumulation of OCAPE ultimately overshoots its intrinsic threshold and is released abruptly (~1 month) into kinetic energy of TCC, with further intensification from cabbeling. TCC has convective plumes with approximately 0.2-1-km horizontal scales and large vertical displacements (~1 km), which make TCC difficult to be resolved or parameterized by current general circulation models. The simulation herein indicates that these local TCC events are spread quickly throughout the OCAPE-contained basin by internal wave perturbations. Their convective plumes have large vertical velocities (~8-15 cm s−1) and bring the WSW to the surface, causing an approximate 2°C sea surface warming for the whole basin (~700 km) within a month. This exposes a huge heat reservoir to the atmosphere, which helps to explain the abrupt Bølling-Allerød warming. [ABSTRACT FROM AUTHOR]

The climate sensitivity of the Madden-Julian oscillation (MJO) is measured across a broad range of temperatures (1°-35°C) using a convection-permitting global climate model with homogenous sea surface temperatures. An MJO-like signal is found to be resilient in all simulations. These results are used to investigate two ideas related to the modern 'moisture mode' view of MJO dynamics. The first hypothesis is that the MJO has dynamics analogous to a form of radiative convective self-aggregation in which longwave energy maintenance mechanisms shut down for SST ≪ 25°C. Inconsistent with this hypothesis, the explicitly simulated MJO survives cooling and retains leading moist static energy (MSE) budget terms associated with longwave destabilization even at SST < 10°C. Thus, if the MJO is a form of longwave-assisted self-aggregation, it is not one that is temperature critical, as is observed in some cases of radiative-convective equilibrium (RCE) self-aggregation. The second hypothesis is that the MJO is propagated by horizontal advection of column MSE. Inconsistent with this view, the simulated MJO survives reversal of meridional moisture gradients in the basic state and a striking role for horizontal MSE advection in its propagation energy budget cannot be detected. Rather, its eastward motion is balanced by vertical MSE advection reminiscent of gravity or Kelvin wave dynamics. These findings could suggest a tight relation between the MJO and classic equatorial waves, which would tend to challenge moisture mode views of MJO dynamics that assume horizontal moisture advection as the MJO's propagator. The simulation suite provides new opportunities for testing predictions from MJO theory across a broad climate regime. [ABSTRACT FROM AUTHOR]

The Southern Ocean is a critical region for global climate, yet large cloud and solar radiation biases over the Southern Ocean are a long-standing problem in climate models and are poorly understood, leading to biases in simulated sea surface temperatures. This study shows that supercooled liquid clouds are central to understanding and simulating the Southern Ocean environment. A combination of satellite observational data and detailed radiative transfer calculations is used to quantify the impact of cloud phase and cloud vertical structure on the reflected solar radiation in the Southern Hemisphere summer. It is found that clouds with supercooled liquid tops dominate the population of liquid clouds. The observations show that clouds with supercooled liquid tops contribute between 27% and 38% to the total reflected solar radiation between 40° and 70°S, and climate models are found to poorly simulate these clouds. The results quantify the importance of supercooled liquid clouds in the Southern Ocean environment and highlight the need to improve understanding of the physical processes that control these clouds in order to improve their simulation in numerical models. This is not only important for improving the simulation of present-day climate and climate variability, but also relevant for increasing confidence in climate feedback processes and future climate projections. [ABSTRACT FROM AUTHOR]

Changes in column-integrated water vapor ( Q) in response to increased CO2 and ocean heat uptake (OHU) are investigated in slab-ocean aquaplanet simulations. The simulations span a wide range of warming and moistening patterns due to the spatial structures of the imposed OHU. Fractional changes in Q per degree of surface warming range from 0% to 20% K−1 locally and from 3.6% to 11% K−1 globally. A new diagnostic technique decomposes these changes into relative humidity (RH), surface temperature, and lapse rate contributions. Single-column calculations demonstrate substantial departures from apparent (surface temperature based) Clausius-Clapeyron (CC) scaling due to lapse rates changes; a moist-adiabatic column with fixed, uniform RH exceeds the CC rate by 2.5% K−1. The RH contribution is very small in most simulations. The various Q scalings are thus all consistent CC, but result from different patterns of polar amplification and lapse rate change. Lapse rates are sensitive to location and magnitude of OHU, with implications for Q under transient climate change. CO2 with subpolar (tropical) OHU results in higher (lower) Q scalings than CO2 alone. The weakest Q scaling (and largest RH effects) is found for increased poleward ocean heat transport, which causes strongly polar-amplified warming and near-zero tropical temperature change. Despite weak RH changes and fidelity to the CC relation, Q is expected to vary widely on different time scales in nature due to sensitivity of lapse rates to OHU along with the nonlinearity of the diagnostics. [ABSTRACT FROM AUTHOR]

Projections of three important seasonal rainfall parameters-total precipitation (), wet-day mean () and wet-day frequency ()-considered to be relevant to crop agriculture were performed. Links between large-scale climate variables and local precipitation in Tanzania were investigated during the March-May (MAM), October-December (OND), and December-April (DJFMA) rainfall seasons. Variables found to have strong links were used to downscale the local precipitation for three future periods; near term, midcentury, and end of century. Downscaling models for , and were calibrated using observed large-scale seasonal rainfall and projected downscaled parameters were obtained based on rainfall simulations from ensembles of GCMs. The models' skill scores were found to be sensitive to the domain size and number of leading EOFs used. The common EOF method employed in the downscaling modulated the skills depending on the GCMs used. The spread in the rainfall projections was found to be larger in OND and moderate in MAM and DJFMA. The multimodel mean projections in response to two RCPs (RCP4.5 and RCP8.5) suggest a shift toward wetter (drier) conditions () for OND (DJFMA) for all three periods. There is no uniform projection for MAM; some stations are projected to feature wetter and some drier conditions. In the midcentury and end of century, there is an increase of precipitation to about 40% for some areas getting OND rainfall and a decrease of precipitation up to about 10% for some areas getting MAM or DJFMA rainfall. Generally, the magnitude of change strongly differs across the areas. [ABSTRACT FROM AUTHOR]

Arctic amplification (AA) is a major characteristic of observed global warming, yet the different mechanisms responsible for it and their quantification are still under investigation. In this study, the roles of different factors contributing to local surface warming are quantified using the radiative kernel method applied at the surface after 100 years of global warming under a representative concentration pathway 4.5 (RCP4.5) scenario simulated by 32 climate models from phase 5 of the Coupled Model Intercomparison Project. The warming factors and their seasonality for land and oceanic surfaces were investigated separately and for different domains within each surface type where mechanisms differ. Common factors contribute to both land and oceanic surface warming: tropospheric-mean atmospheric warming and greenhouse gas increases (mostly through water vapor feedback) for both tropical and Arctic regions, nonbarotropic warming and surface warming sensitivity effects (negative in the tropics, positive in the Arctic), and warming cloud feedback in the Arctic in winter. Some mechanisms differ between land and oceanic surfaces: sensible and latent heat flux in the tropics, albedo feedback peaking at different times of the year in the Arctic due to different mean latitudes, a very large summer energy uptake and winter release by the Arctic Ocean, and a large evaporation enhancement in winter over the Arctic Ocean, whereas the peak occurs in summer over the ice-free Arctic land. The oceanic anomalous energy uptake and release is further studied, suggesting the primary role of seasonal variation of oceanic mixed layer temperature changes. [ABSTRACT FROM AUTHOR]

The intertropical convergence zone (ITCZ) migrates north-south on seasonal and longer time scales. Previous studies have shown that the zonal-mean ITCZ displacement off the equator is negatively correlated with the energy flux across the equator; when the ITCZ lies in the Northern Hemisphere, energy flows southward across the equator, and vice versa. The hemisphere that exports energy across the equator is the hemisphere with more net energy input, and it is usually the warmer hemisphere. But states with a double ITCZ straddling the equator also occur, for example, seasonally over the eastern Pacific and frequently in climate models. Here it is shown how the ITCZ position is connected to the energy balance near the equator in a broad range of circumstances, including states with single and double ITCZs. Taylor expansion of the variation of the meridional energy flux around the equator leads to the conclusion that for large positive net energy input into the equatorial atmosphere, the ITCZ position depends linearly on the cross-equatorial energy flux. For small positive equatorial net energy input, the dependence of the ITCZ position on the cross-equatorial energy flux weakens to the third root. When the equatorial net energy input or its curvature become negative, a bifurcation to double-ITCZ states occurs. Simulations with an idealized aquaplanet general circulation model (GCM) confirm the quantitative adequacy of these relations. The results provide a framework for assessing and understanding causes of common climate model biases and for interpreting tropical precipitation changes, such as those evident in records of climates of the past. [ABSTRACT FROM AUTHOR]

Uncertainty in tropical rainfall projections under increasing radiative forcing is studied by using 26 models from phase 5 of the Coupled Model Intercomparison Project. Intermodel spread in projected rainfall change generally increases with interactive sea surface temperature (SST) warming in coupled models compared to atmospheric models with a common pattern of prescribed SST increase. Moisture budget analyses reveal that much of the model uncertainty in tropical rainfall projections originates from intermodel discrepancies in the dynamical contribution due to atmospheric circulation change. Intermodel singular value decomposition (SVD) analyses further show a tight coupling between the intermodel variations in SST warming pattern and circulation change in the tropics. In the zonal mean, the first SVD mode features an anomalous interhemispheric Hadley circulation, while the second mode displays an SST peak near the equator. The asymmetric mode is accompanied by a coupled pattern of wind-evaporation-SST feedback in the tropics and is further tied to interhemispheric asymmetric change in extratropical shortwave radiative flux at the top of the atmosphere. Intermodel variability in the tropical circulation change exerts a strong control on the spread in tropical cloud cover change and cloud radiative effects among models. The results indicate that understanding the coupling between the anthropogenic changes in SST pattern and atmospheric circulation holds the key to reducing uncertainties in projections of future changes in tropical rainfall and clouds. [ABSTRACT FROM AUTHOR]

Changes in extreme temperatures, heat waves, and heavy rainfall events have adverse effects on human health, air quality, and water resources. With aerosol-only (AER) and greenhouse gas-only (GHG) simulations from 1860 to 2005 in the GFDL CM3 chemistry-climate model, aerosol-induced versus greenhouse gas-induced changes in temperature (summer) and precipitation (all seasons) extremes over the United States are investigated. Small changes in these extremes in the all forcing simulations reflect cancellations between the effects of increasing anthropogenic aerosols and greenhouse gases. In AER, extreme high temperatures and the number of days with temperatures above the 90th percentile decline over most of the United States. The strongest response occurs in the western United States (−2.0°C and −14 days, regionally averaged) and the weakest response occurs in the southeastern United States (−0.6°C and −4.8 days). An opposite-signed response pattern occurs in GHG (+2.3°C and +11.5 days over the western United States and +1.6°C and +7.2 days over the southeastern United States). The similar spatial response patterns in AER versus GHG suggest a preferred regional mode of response that is largely independent of the type of forcing. Extreme precipitation over the eastern United States decreases in AER, particularly in winter, and increases over the eastern and central United States in GHG, particularly in spring. Over the twenty-first century under the representative concentration pathway 8.5 (RCP8.5) emissions scenario, the patterns of extreme temperature and precipitation associated with greenhouse gas forcing dominate. [ABSTRACT FROM AUTHOR]

Recent temperature extremes have highlighted the importance of assessing projected changes in the variability of temperature as well as the mean. A large fraction of present-day temperature variance is associated with thermal advection, as anomalous winds blow across the land-sea temperature contrast, for instance. Models project robust heterogeneity in the twenty-first-century warming pattern under greenhouse gas forcing, resulting in land-sea temperature contrasts increasing in summer and decreasing in winter and the pole-to-equator temperature gradient weakening in winter. In this study, future changes in monthly variability of near-surface temperature in the 17-member ensemble ESSENCE (Ensemble Simulations of Extreme Weather Events under Nonlinear Climate Change) are assessed. In winter, variability in midlatitudes decreases whereas in very high latitudes and the tropics it increases. In summer, variability increases over most land areas and in the tropics, with decreasing variability in high latitude oceans. Multiple regression analysis is used to determine the contributions to variability changes from changing temperature gradients and circulation patterns. Thermal advection is found to be of particular importance in the Northern Hemisphere winter midlatitudes, where the change in mean state temperature gradients alone could account for over half the projected changes. Changes in thermal advection are also found to be important in summer in Europe and coastal areas, although less so than in winter. Comparison with CMIP5 data shows that the midlatitude changes in variability are robust across large regions, particularly high northern latitudes in winter and middle northern latitudes in summer. [ABSTRACT FROM AUTHOR]

Based on models from phase 5 of the Coupled Model Intercomparison Project (CMIP5), the present study investigates the South Asian high (SAH) change in response to global warming. Under global warming, the selected 16 coupled general circulation models all feature an elevation of geopotential height at 100 hPa to the south of the SAH climatological position; an easterly response is found over the northern Indian Ocean in all the models, while a westerly response is found over subtropical Asia. The ridges of the SAH shift equatorward in 75% of models. Using the linear baroclinic model, it is found that the combined effects of latent heating and the mean advection of stratification change (MASC) are mainly responsible for those responses. The MASC mainly leads to the aforementioned easterly and westerly responses; the latent heating contributes to the geopotential height response and the easterly response over the northern Indian Ocean. The most important intermodel diversity is found in the 100-hPa circulation change under global warming, accounting for more than half of the total intermodel variance. The intermodel spread of latent heating and the MASC are important factors in driving the 100-hPa circulation diversity. Furthermore, analysis shows that the projected uncertainties in humidity, vertical velocity, and global mean temperature change are the three most important sources of intermodel diversity for the 100-hPa circulation change. [ABSTRACT FROM AUTHOR]

Climate model simulations of changes to Earth's energy budget are fundamental to improve understanding of both historical and future climate change. However, coupled models are prone to 'drift' (i.e., they contain spurious unforced trends in state variables) due to incomplete spinup or nonclosure of the energy budget. This work assesses the globally integrated energy budgets of 25 models in phase 5 of CMIP (CMIP5). It is shown that for many of the models there is a significant disagreement between ocean heat content changes and net top-of-atmosphere radiation. The disagreement is largely time-constant and independent of forcing scenario. Furthermore, most of the nonconservation seems to occur as a result of energy leaks external to the ocean model realm. After drift correction, the time-varying energy budget is consistent at decadal time scales, and model responses to climate forcing are not sensitive to the magnitude of their drift. This demonstrates that, although drift terms can be significant, model output can be corrected post hoc without biasing results. [ABSTRACT FROM AUTHOR]

Effective radiative forcing (ERF) is calculated as the flux change at the top of the atmosphere after allowing rapid adjustments resulting from a forcing agent, such as greenhouse gases. Rapid adjustments include changes to atmospheric temperature, water vapor, and clouds. Accurate estimates of ERF are necessary in order to understand the drivers of climate change. This work presents a new method of calculating ERF using a kernel derived from the time series of a model variable (e.g., global mean surface temperature) in a model-step change experiment. The top-of-atmosphere (TOA) radiative imbalance has the best noise tolerance for retrieving the ERF of the model variables tested. This temporal kernel method is compared with an energy balance method, which equates ERF to the TOA radiative imbalance plus the scaled surface temperature change. Sensitivities and biases of these methods are quantified using output from phase 5 of the the Coupled Model Intercomparison Project (CMIP5). The temporal kernel method is likely more accurate for models in which a linear fit is a poor approximation for the relationship between temperature change and TOA imbalance. The difference between these methods is most apparent in forcing estimates for the representative concentration pathway 8.5 (RCP8.5) scenario. The CMIP5 multimodel mean ERF calculated for large volcanic eruptions is 80% of the adjusted forcing reported by the IPCC Fifth Assessment Report (AR5). This suggests that about 5% more energy has come into the earth system since 1870 than suggested by the IPCC AR5. [ABSTRACT FROM AUTHOR]

This study aims to assess whether, and the extent to which, an increase in atmospheric resolution of the Geophysical Fluid Dynamics Laboratory (GFDL) Forecast-Oriented Low Ocean Resolution version of CM2.5 (FLOR) with 50-km resolution and the High-Resolution FLOR (HiFLOR) with 25-km resolution improves the simulation of the El Niño-Southern Oscillation (ENSO)-tropical cyclone (TC) connections in the western North Pacific (WNP). HiFLOR simulates better ENSO-TC connections in the WNP including TC track density, genesis, and landfall than FLOR in both long-term control experiments and sea surface temperature (SST)- and sea surface salinity (SSS)-restoring historical runs (1971-2012). Restoring experiments are performed with SSS and SST restored to observational estimates of climatological SSS and interannually varying monthly SST. In the control experiments of HiFLOR, an improved simulation of the Walker circulation arising from more realistic SST and precipitation is largely responsible for its better performance in simulating ENSO-TC connections in the WNP. In the SST-restoring experiments of HiFLOR, more realistic Walker circulation and steering flow during El Niño and La Niña are responsible for the improved simulation of ENSO-TC connections in the WNP. The improved simulation of ENSO-TC connections with HiFLOR arises from a better representation of SST and better responses of environmental large-scale circulation to SST anomalies associated with El Niño or La Niña. A better representation of ENSO-TC connections in HiFLOR can benefit the seasonal forecasting of TC genesis, track, and landfall; improve understanding of the interannual variation of TC activity; and provide better projection of TC activity under climate change. [ABSTRACT FROM AUTHOR]

The response of the Northern Hemisphere winter stratosphere to the Pacific decadal oscillation (PDO) is examined using the Whole Atmosphere Community Climate Model. A 200-yr preindustrial control simulation that includes fully interactive chemistry, ocean and sea ice, constant solar forcing, and greenhouse gases fixed to 1850 levels is analyzed. Based on principal component analysis, the PDO spatial pattern, frequency, and amplitude agree well with the observed PDO over the period 1900-2014. Consistent with previous studies, the positive phase of the PDO is marked by a strengthened Aleutian low and a wave train of geopotential height anomalies reminiscent of the Pacific-North American pattern in the troposphere. In addition to a tropospheric signal, a zonal-mean warming of about 2 K in the northern polar stratosphere and a zonal-mean zonal wind decrease of about 4 m s−1 in the PDO positive phase are found. When compositing PDO positive or negative winters during neutral El Niño years, the magnitude is reduced and depicts an early winter forcing of the stratosphere compared to a late winter response from El Niño. Contamination between PDO and ENSO signals is also discussed. Stratospheric sudden warmings occur 63% of the time in the PDO positive phase compared to 40% in the negative phase. Although this sudden warming frequency is not statistically significant, it is quantitatively consistent with NCEP-NCAR reanalysis data and recent observational evidence linking the PDO positive phase to weak stratospheric vortex events. [ABSTRACT FROM AUTHOR]

The role of radiative forcings and climate feedbacks on global cooling over the last millennium is quantified in the CMIP5-PMIP3 transient climate model simulations. Changes in the global energy budget over the last millennium are decomposed into contributions from radiative forcings and climate feedbacks through the use of the approximate partial radiative perturbation method and radiative kernels. Global cooling occurs circa 1200-1850 CE in the multimodel ensemble mean with pronounced minima corresponding with volcanically active periods that are outside the range of natural variability. Analysis of the global energy budget during the last millennium indicates that Little Ice Age (LIA; 1600-1850 CE) cooling is largely driven by volcanic forcing (comprising an average of 65% of the total forcing among models), while contributions due to changes in land use (13%), greenhouse gas concentrations (12%), and insolation (10%) are substantially lower. The combination of these forcings directly contributes to 47% of the global cooling during the LIA, while the remainder of the cooling arises from the sum of the climate feedbacks. The dominant positive feedback is the water vapor feedback, which contributes 29% of the global cooling. Additional positive feedbacks include the surface albedo feedback (which contributes 7% of the global cooling and arises owing to high-latitude sea ice expansion and increased snow cover) and the lapse rate feedback (which contributes an additional 7% of the global cooling and arises owing to greater cooling near the surface than aloft in the middle and high latitudes). [ABSTRACT FROM AUTHOR]

The authors study the effect of clouds on the atmospheric circulation response to CO2 quadrupling in an aquaplanet model with a slab ocean lower boundary. The cloud effect is isolated by locking the clouds to either the control or 4xCO2 state in the shortwave (SW) or longwave (LW) radiation schemes. In the model, cloud radiative changes explain more than half of the total poleward expansion of the Hadley cells, midlatitude jets, and storm tracks under CO2 quadrupling, even though they cause only one-fourth of the total global-mean surface warming. The effect of clouds on circulation results mainly from the SW cloud radiative changes, which strongly enhance the equator-to-pole temperature gradient at all levels in the troposphere, favoring stronger and poleward-shifted midlatitude eddies. By contrast, quadrupling CO2 while holding the clouds fixed causes strong polar amplification and weakened midlatitude baroclinicity at lower levels, yielding only a small poleward expansion of the circulation. The results show that 1) the atmospheric circulation responds sensitively to cloud-driven changes in meridional and vertical temperature distribution and 2) the spatial structure of cloud feedbacks likely plays a dominant role in the circulation response to greenhouse gas forcing. While the magnitude and spatial structure of the cloud feedback are expected to be highly model dependent, an analysis of 4xCO2 simulations of CMIP5 models shows that the SW cloud feedback likely forces a poleward expansion of the tropospheric circulation in most climate models. [ABSTRACT FROM AUTHOR]

Uncertainty in equilibrium climate sensitivity impedes accurate climate projections. While the intermodel spread is known to arise primarily from differences in cloud feedback, the exact processes responsible for the spread remain unclear. To help identify some key sources of uncertainty, the authors use a developmental version of the next-generation Geophysical Fluid Dynamics Laboratory global climate model (GCM) to construct a tightly controlled set of GCMs where only the formulation of convective precipitation is changed. The different models provide simulation of present-day climatology of comparable quality compared to the model ensemble from phase 5 of CMIP (CMIP5). The authors demonstrate that model estimates of climate sensitivity can be strongly affected by the manner through which cumulus cloud condensate is converted into precipitation in a model's convection parameterization, processes that are only crudely accounted for in GCMs. In particular, two commonly used methods for converting cumulus condensate into precipitation can lead to drastically different climate sensitivity, as estimated here with an atmosphere-land model by increasing sea surface temperatures uniformly and examining the response in the top-of-atmosphere energy balance. The effect can be quantified through a bulk convective detrainment efficiency, which measures the ability of cumulus convection to generate condensate per unit precipitation. The model differences, dominated by shortwave feedbacks, come from broad regimes ranging from large-scale ascent to subsidence regions. Given current uncertainties in representing convective precipitation microphysics and the current inability to find a clear observational constraint that favors one version of the authors' model over the others, the implications of this ability to engineer climate sensitivity need to be considered when estimating the uncertainty in climate projections. [ABSTRACT FROM AUTHOR]

A new approach of coordinated global and regional climate modeling is presented. It is applied to the Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) and its parent global climate model CanESM2. CanRCM4 was developed specifically to downscale climate predictions and climate projections made by its parent global model. The close association of a regional climate model (RCM) with a parent global climate model (GCM) offers novel avenues of model development and application that are not typically available to independent regional climate modeling centers. For example, when CanRCM4 is driven by its parent model, driving information for all of its prognostic variables is available (including aerosols and chemical species), significantly improving the quality of their simulation. Additionally, CanRCM4 can be driven by its parent model for all downscaling applications by employing a spectral nudging procedure in CanESM2 designed to constrain its evolution to follow any large-scale driving data. Coordination offers benefit to the development of physical parameterizations and provides an objective means to evaluate the scalability of such parameterizations across a range of spatial resolutions. Finally, coordinating regional and global modeling efforts helps to highlight the importance of assessing RCMs' value added relative to their driving global models. As a first step in this direction, a framework for identifying appreciable differences in RCM versus GCM climate change results is proposed and applied to CanRCM4 and CanESM2. [ABSTRACT FROM AUTHOR]

A time series resulting from a single initial condition is shown to be insufficient for quantifying the internal variability in a climate model, and thus one is unable to make meaningful climate projections based on it. The authors argue that the natural distribution, obtained from an ensemble of trajectories differing solely in their initial conditions, of the snapshot attractor corresponding to a particular forcing scenario should be determined in order to quantify internal variability and to characterize any instantaneous state of the system in the future. Furthermore, as a simple measure of internal variability of any particular variable of the model, the authors suggest using its instantaneous ensemble standard deviation. These points are illustrated with the intermediate-complexity climate model Planet Simulator forced by a CO2 scenario, with a 40-member ensemble. In particular, the leveling off of the time dependence of any ensemble average is shown to provide a much clearer indication of reaching a steady state than any property of single time series. Shifts in ensemble averages are indicative of climate changes. The dynamical character of such changes is illustrated by hysteresis-like curves obtained by plotting the ensemble average surface temperature versus the CO2 concentration. The internal variability is found to be the most pronounced on small geographical scales. The traditionally used 30-yr temporal averages are shown to be considerably different from the corresponding ensemble averages. Finally, the North Atlantic Oscillation (NAO) index, related to the teleconnection paradigm, is also investigated. It is found that the NAO time series strongly differs in any individual realization from each other and from the ensemble average, and climatic trends can be extracted only from the latter. [ABSTRACT FROM AUTHOR]

A case study is presented using the northeast United States to evaluate information contained in the monthly mean annual cycle that has yet to be exploited. This research documents the performance and projections for the northeast United States from a suite of 16 climate models in the archive of phase 5 of the Coupled Model Intercomparison Project (CMIP5) from the World Climate Research Programme (WCRP). Analysis is performed for the late twentieth-century monthly mean annual cycle and changes in the late twenty-first century. A weak seasonality in temperature and a strong seasonality in precipitation changes are found. The seasonality of changes is distinct from the mean annual cycles, such that temperature increases are largest in midwinter (December-February) and late summer [July-September (JAS)]. Precipitation increases peak in late winter-early spring (February-April), associated with increased moisture convergence and a more active storm track, and exhibit greatest model disagreement in late summer (JAS) when the models suggest weak divergence and a westward extension of the Atlantic subtropical anticyclone. The late summer-early fall maximum in temperature and late winter-early spring maximum in precipitation changes have not been seen previously in annual or seasonal mean analyses. Yet there is model agreement in these results, indicating that there is important information in the annual cycle for understanding the changes in the physical climate system and for evaluating impacts and adaptation strategies. It is argued that improved understanding of seasonal transitions has potential to increase confidence in projections, and to provide additional information of use to the impacts and decision-maker communities. [ABSTRACT FROM AUTHOR]

The current California drought has cast a heavy burden on statewide agriculture and water resources, further exacerbated by concurrent extreme high temperatures. Furthermore, industrial-era global radiative forcing brings into question the role of long-term climate change with regard to California drought. How has human-induced climate change affected California drought risk? Here, observations and model experimentation are applied to characterize this drought employing metrics that synthesize drought duration, cumulative precipitation deficit, and soil moisture depletion. The model simulations show that increases in radiative forcing since the late nineteenth century induce both increased annual precipitation and increased surface temperature over California, consistent with prior model studies and with observed long-term change. As a result, there is no material difference in the frequency of droughts defined using bivariate indicators of precipitation and near-surface (10 cm) soil moisture, because shallow soil moisture responds most sensitively to increased evaporation driven by warming, which compensates the increase in the precipitation. However, when using soil moisture within a deep root zone layer (1 m) as covariate, droughts become less frequent because deep soil moisture responds most sensitively to increased precipitation. The results illustrate the different land surface responses to anthropogenic forcing that are relevant for near-surface moisture exchange and for root zone moisture availability. The latter is especially relevant for agricultural impacts as the deep layer dictates moisture availability for plants, trees, and many crops. The results thus indicate that the net effect of climate change has made agricultural drought less likely and that the current severe impacts of drought on California's agriculture have not been substantially caused by long-term climate changes. [ABSTRACT FROM AUTHOR]

Projections of regional climate, net basin supply (NBS), and water levels are developed for the mid- and late twenty-first century across the Laurentian Great Lakes basin. Two state-of-the-art global climate models (GCMs) are dynamically downscaled using a regional climate model (RCM) interactively coupled to a one-dimensional lake model, and then a hydrologic routing model is forced with time series of perturbed NBS. The dynamical downscaling and coupling with a lake model to represent the Great Lakes create added value beyond the parent GCM in terms of simulated seasonal cycles of temperature, precipitation, and surface fluxes. However, limitations related to this rudimentary treatment of the Great Lakes result in warm summer biases in lake temperatures, excessive ice cover, and an abnormally early peak in lake evaporation. While the downscaling of both GCMs led to consistent projections of increases in annual air temperature, precipitation, and all NBS components (overlake precipitation, basinwide runoff, and lake evaporation), the resulting projected water level trends are opposite in sign. Clearly, it is not sufficient to correctly simulate the signs of the projected change in each NBS component; one must also account for their relative magnitudes. The potential risk of more frequent episodes of lake levels below the low water datum, a critical shipping threshold, is explored. [ABSTRACT FROM AUTHOR]

The long-term climate variations of the Quaternary were primarily influenced by concurrent changes in Earth's orbit, greenhouse gases, and ice sheets. However, because climate changes over the coming century will largely be driven by changes in greenhouse gases alone, it is important to better understand the separate contributions of each of these forcings in the past. To investigate this, idealized equilibrium simulations are conducted in which the climate is driven by separate changes in obliquity, precession, CO2, and ice sheets. To test the linearity of past climate change, anomalies from these single-forcing experiments are scaled and summed to compute linear reconstructions of past climate, which are then compared to mid-Holocene and last glacial maximum (LGM) snapshot simulations, where all forcings are applied together, as well as proxy climate records. This comparison shows that much of the climate response may be approximated as a linear response to forcings, while some features, such as modeled changes in sea ice and Atlantic meridional overturning circulation (AMOC), appear to be heavily influenced by nonlinearities. In regions where the linear reconstructions replicate the full-forcing experiments well, this analysis can help identify how each forcing contributes to the climate response. Monsoons at the mid-Holocene respond strongly to precession, while LGM monsoons are heavily influenced by the altered greenhouse gases and ice sheets. Contrary to previous studies, ice sheets produce pronounced tropical cooling at the LGM. Compared to proxy temperature records, the linear reconstructions replicate long-term changes well and also show which climate variations are not easily explained as direct responses to long-term forcings. [ABSTRACT FROM AUTHOR]

El Niño-Southern Oscillation (ENSO) is an important driver of regional hydroclimate variability through far-reaching teleconnections. This study uses simulations performed with coupled general circulation models (CGCMs) to investigate how regional precipitation in the twenty-first century may be affected by changes in both ENSO-driven precipitation variability and slowly evolving mean rainfall. First, a dominant, time-invariant pattern of canonical ENSO variability (cENSO) is identified in observed SST data. Next, the fidelity with which 33 state-of-the-art CGCMs represent the spatial structure and temporal variability of this pattern (as well as its associated precipitation responses) is evaluated in simulations of twentieth-century climate change. Possible changes in both the temporal variability of this pattern and its associated precipitation teleconnections are investigated in twenty-first-century climate projections. Models with better representation of the observed structure of the cENSO pattern produce winter rainfall teleconnection patterns that are in better accord with twentieth-century observations and more stationary during the twenty-first century. Finally, the model-predicted twenty-first-century rainfall response to cENSO is decomposed into the sum of three terms: 1) the twenty-first-century change in the mean state of precipitation, 2) the historical precipitation response to the cENSO pattern, and 3) a future enhancement in the rainfall response to cENSO, which amplifies rainfall extremes. By examining the three terms jointly, this conceptual framework allows the identification of regions likely to experience future rainfall anomalies that are without precedent in the current climate. [ABSTRACT FROM AUTHOR]

Climate change and rapidly rising global water demand are expected to place unprecedented pressures on already strained water resource systems. Successfully planning for these future changes requires a sound scientific understanding of the timing, location, and magnitude of climate change impacts on water needs and availability-not only average trends but also interannual variability and quantified uncertainties. In recent years, two types of large-ensemble runs of climate projections have become available: those from groups of more than 20 different climate models and those from repeated runs of several individual models. These provide the basis for novel probabilistic evaluation of both projected climate change and the resulting effects on water resources. Using a broad range of available ensembles, this research explores the spatial and temporal patterns of high confidence as well as uncertainty in projected river runoff, irrigation water requirements, basin storage yield, and cost estimates of adapting regional water systems to maintain historical supply. Projections of river runoff show robust between-ensemble agreement in regional drying (e.g., southern Africa and southern Europe) and wetting trends (e.g., northeastern United States). By integrating runoff over space and time, the economic effects of adapting supply systems to 2050 water availability show still broader trend agreement across ensembles. That agreement, obtained across such a wide range of multiple-member climate model ensembles in some locations, suggests a high degree of confidence in direction of change in water availability and provides clearer signals for longer-term investment decisions in water infrastructure. [ABSTRACT FROM AUTHOR]

The ocean stores more than 90% of the energy excess associated with anthropogenic climate change. The resulting ocean warming and thermal expansion are leading contributors to global mean sea level (GMSL) rise. Confidence in projections of GMSL rise therefore depends on the ability of climate models to reproduce global mean thermosteric sea level (GMTSL) rise over the twentieth century. This study first compares the GMTSL of the climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) to observations over 1961-2005. Although the model ensemble mean is within the uncertainty of observations, the model ensemble exhibits a large spread. The authors then aim to explain the spread in CMIP5 climate model GMTSL over the twentieth and twenty-first centuries. It is shown that the climate models' GMTSL rise depends linearly on the time-integrated radiative forcing F (under continuously increasing radiative forcing). The constant of proportionality μ expresses the transient thermosteric sea level response of the climate system, and it depends on the fraction of excess heat stored in the ocean, the expansion efficiency of heat, the climate feedback parameter, and the ocean heat uptake efficiency. The across-model spread in μ explains most (>70%) of the across-model spread in GMTSL rise over the twentieth and twenty-first centuries, while the across-model spread in time-integrated F explains the rest. The time-integrated F explains less variance in the across-model GMTSL rise in twenty-first-century than in twentieth-century simulations, as the spread in F is reduced over the twenty-first century because the anthropogenic aerosol forcing, which is a large source of uncertainty in F, becomes relatively smaller. [ABSTRACT FROM AUTHOR]

Climate models suffer from long-standing biases, including the double intertropical convergence zone (ITCZ) problem and the excessive westward extension of the equatorial Pacific cold tongue. An atmospheric general circulation model is used to investigate how model biases in the mean state affect the projection of tropical climate change. The model is forced with a pattern of sea surface temperature (SST) increase derived from a coupled simulation of global warming but uses an SST climatology derived from either observations or a coupled historical simulation. The comparison of the experiments reveals that the climatological biases have important impacts on projected changes in the tropics. Specifically, during February-April when the climatological ITCZ displaces spuriously into the Southern Hemisphere, the model overestimates (underestimates) the projected rainfall increase in the warmer climate south (north) of the equator over the eastern Pacific. Furthermore, the global warming-induced Walker circulation slowdown is biased weak in the projection using coupled model climatology, suggesting that the projection of the reduced equatorial Pacific trade winds may also be underestimated. This is related to the bias that the climatological Walker circulation is too weak in the model, which is in turn due to a too-weak mean SST gradient in the zonal direction. The results highlight the importance of improving the climatological simulation for more reliable projections of regional climate change. [ABSTRACT FROM AUTHOR]

Tropical climate feedback mechanisms are assessed using satellite-observed and model-simulated trends in tropical tropospheric temperature from the MSU/AMSU instruments and upper-tropospheric humidity from the HIRS instruments. Despite discrepancies in the rates of tropospheric warming between observations and models, both are consistent with constant relative humidity over the period 1979-2008. Because uncertainties in satellite-observed tropical-mean trends preclude a constraint on tropical-mean trends in models regional features of the feedbacks are also explored. The regional pattern of the lapse rate feedback is primarily determined by the regional pattern of surface temperature changes, as tropical atmospheric warming is relatively horizontally uniform. The regional pattern of the water vapor feedback is influenced by the regional pattern of precipitation changes, with variations of 1-2 W m−2 K−1 across the tropics (compared to a tropical-mean feedback magnitude of 3.3-4 W m−2 K−1). Thus the geographical patterns of water vapor and lapse rate feedbacks are not correlated, but when the feedbacks are calculated in precipitation percentiles rather than in geographical space they are anticorrelated, with strong positive water vapor feedback associated with strong negative lapse rate feedback. The regional structure of the feedbacks is not related to the strength of the tropical-mean feedback in a subset of the climate models from the CMIP5 archive. Nevertheless the approach constitutes a useful process-based test of climate models and has the potential to be extended to constrain regional climate projections. [ABSTRACT FROM AUTHOR]