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In this paper, the authors address the impact of uncertainty on estimates of transient climate sensitivity (TCS) of the globally averaged surface temperature, including both uncertainty in past forcing and internal variability in the climate record. This study provides a range of probabilistic estimates of the TCS that combine these two sources of uncertainty for various underlying assumptions about the nature of the uncertainty. The authors also provide estimates of how quickly the uncertainty in the TCS may be expected to diminish in the future as additional observations become available. These estimates are made using a nonlinear Kalman filter coupled to a stochastic, global energy balance model, using the filter and observations to constrain the model parameters. This study verifies that model and filter are able to emulate the evolution of a comprehensive, state-of-the-art atmosphere-ocean general circulation model and to accurately predict the TCS of the model, and then apply the methodology to observed temperature and forcing records of the twentieth century. For uncertainty assumptions best supported by global surface temperature data up to the present time, this paper finds a most likely present-day estimate of the transient climate sensitivity to be 1.6 K, with 90%% confidence the response will fall between 1.3 and 2.6 K, and it is estimated that this interval may be 45%% smaller by the year 2030. The authors calculate that emissions levels equivalent to forcing of less than 475 ppmv CO2 concentration are needed to ensure that the transient temperature response will not exceed 2 K with 95%% confidence. This is an assessment for the short-to-medium term and not a recommendation for long-term stabilization forcing; the equilibrium temperature response to this level of CO2 may be much greater. The flat temperature trend of the last decade has a detectable but small influence on TCS. This study describes how the results vary if different uncertainty assumptions are made and shows they are robust to variations in the initial prior probability assumptions. [ABSTRACT FROM AUTHOR]

A full understanding of the causes of the severe drought seen in the Sahel in the latter part of the twentieth-century remains elusive some 25 yr after the height of the event. Previous studies have suggested that this drying trend may be explained by either decadal modes of natural variability or by human-driven emissions (primarily aerosols), but these studies lacked a sufficiently large number of models to attribute one cause over the other. In this paper, signatures of both aerosol and greenhouse gas changes on Sahel rainfall are illustrated. These idealized responses are used to interpret the results of historical Sahel rainfall changes from two very large ensembles of fully coupled climate models, which both sample uncertainties arising from internal variability and model formulation. The sizes of these ensembles enable the relative role of human-driven changes and natural variability on historic Sahel rainfall to be assessed. The paper demonstrates that historic aerosol changes are likely to explain most of the underlying 1940-80 drying signal and a notable proportion of the more pronounced 1950-80 drying. [ABSTRACT FROM AUTHOR]

The primary focus of this paper is the analysis of the roles of long-term increases in carbon dioxide (CO2) and sea surface temperatures (used as indicators of climate change) and man-made halocarbons (indicators of chemical ozone depletion linked to halogens) in explaining the observed trend of ozone in the tropical lower stratosphere and implications for related variables including temperature and tropopause height. Published estimates indicate a decrease of approximately 10% in observed ozone concentrations in this region between 1979 and 2005. Using a coupled chemistry–climate atmosphere model forced by observed sea surface temperatures and surface concentrations of long-lived greenhouse gases and halocarbons, the authors show that the simulations display substantial decreases in tropical ozone that compare well in both latitudinal and vertical structure with those observed. Based on sensitivity simulations, the analysis indicates that the decreases in the lower stratospheric (85–50 hPa) tropical ozone distribution are mostly associated with increases in CO2 and sea surface temperatures, in contrast to those at higher latitudes, which are largely driven by halocarbon increases. Factors influencing temperature trends and tropopause heights in this region are also probed. It is shown that the modeled temperature trends in the lower tropical stratosphere are also associated with increases in CO2 and sea surface temperatures. Following the analysis of lower stratospheric tropical temperature trends, the secondary focus of this paper is on related changes in tropopause height. Much of the simulated tropopause rise in the tropical zone as measured by tropopause height is found to be linked to increases in sea surface temperatures and CO2, while increases in halocarbons dominate the tropopause height changes in the subtropics near 30°; both drivers thus affect different regions of the simulated changes in the position of the tropopause. Finally, it is shown that halocarbon increases dominate the changes in the width of the region where modeled total ozone displays tropical character (as indicated by low values of the column abundance). Hence the findings suggest that climate changes and halocarbon changes make different contributions to different metrics used to characterize tropical change. [ABSTRACT FROM AUTHOR]

This paper investigates changes in the tropical tropopause layer (TTL) in response to carbon dioxide increase and surface warming separately in an atmospheric general circulation model, finding that both effects lead to a warmer tropical tropopause. Surface warming also results in an upward shift of the tropopause. A detailed heat budget analysis is performed to quantify the contributions from different radiative and dynamic processes to changes in the TTL temperature. When carbon dioxide increases with fixed surface temperature, a warmer TTL mainly results from the direct radiative effect of carbon dioxide increase. With surface warming, the largest contribution to the TTL warming comes from the radiative effect of the warmer troposphere, which is partly canceled by the radiative effect of the moistening at the TTL. Strengthening of the stratospheric circulation following surface warming cools the lower stratosphere dynamically and radiatively via changes in ozone. These two effects are of comparable magnitudes. This circulation change is the main cause of temperature changes near 63 hPa but is weak near 100 hPa. Contributions from changes in convection and clouds are also quantified. These results illustrate the heat budget analysis as a useful tool to disentangle the radiative-dynamical-chemical-convective coupling at the TTL and to facilitate an understanding of intermodel difference. [ABSTRACT FROM AUTHOR]

Uncertainty about biases common across models and about unknown and unmodeled feedbacks is important for the tails of temperature change distributions and thus for climate risk assessments. This paper develops a hierarchical Bayes framework that explicitly represents these and other sources of uncertainty. It then uses models’ estimates of albedo, carbon cycle, cloud, and water vapor–lapse rate feedbacks to generate posterior probability distributions for feedback strength and equilibrium temperature change. The posterior distributions are especially sensitive to prior beliefs about models’ shared structural biases: nonzero probability of shared bias moves some probability mass toward lower values for climate sensitivity even as it thickens the distribution’s positive tail. Obtaining additional models of these feedbacks would not constrain the posterior distributions as much as narrowing prior beliefs about shared biases or, potentially, obtaining feedback estimates having biases uncorrelated with those impacting climate models. Carbon dioxide concentrations may need to fall below current levels to maintain only a 10% chance of exceeding official 2°C limits on global average temperature change. [ABSTRACT FROM AUTHOR]

A regional coupled soil–vegetation–atmosphere model is used to study changes and interactions between climate and the ecosystem in East Asia due to increased atmospheric CO[sub 2] . The largest simulated climate changes are due to the radiative influence of CO[sub 2] , modified slightly by vegetation feedbacks. Annual precipitation increases by about 20% in coastal areas of northern China and in central China, but only by 8% in southern China. The strongest warming of up to 4°C occurs in summer in northern China. Generally, the climate tends to be warmer and wetter under doubled CO[sub 2] except for inland areas of northern China, where it becomes warmer and drier. Most of the changes discussed in this paper are associated with changes in the East Asian monsoon, which is intensified under doubled CO[sub 2] . The largest changes and feedbacks between vegetation and climate occur in northern China. In some coastal and central areas around 40°N, temperate deciduous forests expand northward, replacing grassland due to warmer and wetter climate. Evergreen taiga retreats in the coastal northeast, causing extra cooling feedback due to less snow masking. The largest changes occur in extensive inland regions northward of 40°N, where deserts and shrub land expand due to warmer and drier conditions, and water supply is a critical factor for vegetation. These northern inland ecosystems experience considerable degradation and desertification, indicating a marked sensitivity and vulnerability to climatic change. [ABSTRACT FROM AUTHOR]

This paper analyzes four methods for estimating the spatial degrees of freedom (dof ) of a climate field: the x 2 method, the Z method, the S method, and the B method. The results show that the B method provides the most accurate estimate of the dof. The x 2 method, S method, and Z method yield underestimates when the number of realizations of the field is not sufficiently large or the field's mean and variance vary with respect to spatial location. The dof of the monthly surface temperature field is studied numerically. The B method shows that the dof of the Northern Hemisphere (NH) has an obvious annual cycle, which is around 60 in the winter months and 90 in the summer months. The dof for the Southern Hemisphere (SH) varies between 35 and 50, with large values during its winter months and small ones during its summer months. The dof of the global temperature field demonstrates a similar annual cycle to that of the NH. The dof estimated from the observational data is smaller than that from the GFDL GCM model output of the surface air temperature. In addition, the model output for the SH shows the opposite phase of the seasonal cycle of the dof: large dof in summer and small ones in winter. [ABSTRACT FROM AUTHOR]

The radiative forcing from carbon dioxide is approximately logarithmic in its concentration, producing about 4 W m−2 of global-mean forcing for each doubling. Although these are basic facts of climate science, competing explanations for them have been given in the literature. Here, the reasons for the logarithmic forcing of carbon dioxide are explored in detail and a simplified model for the forcing is constructed. An essential component is the particular distribution of absorption coefficients within the 15-μm band of carbon dioxide. An alternative explanation, which does not depend on the spectrum of carbon dioxide but instead hinges on the tropospheric lapse rate, is shown to be neither necessary nor sufficient to explain the logarithmic forcing of carbon dioxide and to be generally inapplicable to well-mixed greenhouse gases in Earth's atmosphere. [ABSTRACT FROM AUTHOR]

In this study, we investigate links between Arctic sea ice loss and the variability of 2-m temperatures over a 6-month period (November–April) over two domains centered over northern Eurasia and northern North America. Based on data from the Climate Forecast System Reanalysis (CFSR), there has been an increase (a decrease) in recent seasonal temperature variability over Eurasia (North America), which can be attributed to cooling (warming) during the winter months. Decreases in the intraseasonal variability of temperature anomalies, however, are noted in both regions for the November–April period. This study investigates the role of different forcings on the changes seen in the reanalysis product using Atmospheric Model Intercomparison Project simulations forced with repeating sea surface temperature, sea ice, and carbon dioxide concentration relative to climatologies from two different base periods, 1981–90 and 2005–14. The seasonal temperature and intraseasonal anomaly variabilities are examined, and we find that only the simulations with reduction in sea ice (2005–14 base-period sea ice concentration) produce significant decreases in intraseasonal temperature anomaly variability over these regions, agreeing with the CFSR analysis. Runs that reduce sea ice also result in a significant decrease in the frequency and magnitude of extreme warm and cold temperature anomalies. It is proposed that the weakened latitudinal temperature gradient, resulting from decreased sea ice, leads to reduced meridional temperature advection variability, which in turn contributes to the reduction in the variability of temperature anomalies. [ABSTRACT FROM AUTHOR]

The current generation of climate models, as represented by phase 5 of the Coupled Model Intercomparison Project (CMIP5), has previously been assessed as having more skill in simulating the observed climate than the previous ensemble from phase 3 of CMIP (CMIP3). Furthermore, the skill of models in reproducing seasonal means of precipitation, temperature, and pressure from two observational datasets, quantified by the nondimensional Arcsin-Mielke skill score, appeared to be influenced by model resolution. The analysis is extended to 42 CMIP5 and 24 CMIP3 models. For the combined skill scores for six continents, averaged over the three variables and four seasons, the correlation with model grid length in the 66-model ensemble is −0.73. Focusing on the comparison with ERA-Interim data at higher resolution and with greater regional detail, correlations are nearly as strong for scores over the ocean domain as for land. For the global domain (excluding the Antarctic cap), the correlation of the overall skill score with grid length is −0.61, and it is nearly as strong for each variable. For most tests the improved averaged score of CMIP5 models relative to those from CMIP3 is largely consistent with their increased resolution. However, the improvement for precipitation and the correlations with length are both smaller if rmse is used as a metric. They are smaller again using the GPCP observational data, as the regional detail from a high-resolution model can lead to larger differences when compared to relatively smooth observational fields. [ABSTRACT FROM AUTHOR]

Coupled carbon cycle-climate models in the Coupled Model Intercomparison Project, phase 5 (CMIP5), Earth system model ensemble simulate the effects of changes in anthropogenic fossil-fuel emissions and ensuing climatic changes on the global carbon (C) balance but largely ignore the consequences of widespread terrestrial nitrogen (N) limitation. Based on plausible ranges of terrestrial C:N stoichiometry, this study investigates whether the terrestrial C sequestration projections of nine CMIP5 models for four representative concentration pathways (RCPs) are consistent with estimates of N supply from increased biological fixation, atmospheric deposition, and reduced ecosystem N losses. Discrepancies between the timing and places of N demand and supply indicated increases in terrestrial N implicit to the projections of all nine CMIP5 models under all scenarios that are larger than the estimated N supply. Omitting N constraints leads to an overestimation of land C sequestration in these models between the years 1860 and 2100 by between 97 Pg C (69-252 Pg C; RCP 2.6) and 150 Pg C (57-323 Pg C; RCP 8.5), with a large spread across models. The CMIP5 models overestimated the average 2006-2100 fossil-fuel emissions required to keep atmospheric CO2 levels on the trajectories described in the RCP scenarios by between 0.6 Pg C yr−1 (0.4-2.2 Pg C yr−1; RCP 2.6) and 1.2 Pg C yr−1 (0.5-3.3 Pg C yr−1; RCP 8.5). If unabated, reduced land C sequestration would enhance CO2 accumulation in the ocean and atmosphere, increasing atmospheric CO2 burden by 26 ppm (16-88 ppm; RCP 2.6) to 61 ppm (29-147 ppm; RCP 8.5) by the year 2100. [ABSTRACT FROM AUTHOR]

Using the climate feedback response analysis method, the authors examine the individual contributions of the CO2 radiative forcing and climate feedbacks to the magnitude, spatial pattern, and seasonality of the transient surface warming response in a 1% yr−1 CO2 increase simulation of the NCAR Community Climate System Model, version 4 (CCSM4). The CO2 forcing and water vapor feedback warm the surface everywhere throughout the year. The tropical warming is predominantly caused by the CO2 forcing and water vapor feedback, while the evaporation feedback reduces the warming. Most feedbacks exhibit noticeable seasonal variations; however, their net effect has little seasonal variation due to compensating effects, which keeps the tropical warming relatively invariant all year long. The polar warming has a pronounced seasonal cycle, with maximum warming in fall/winter and minimum warming in summer. In summer, the large cancelations between the shortwave and longwave cloud feedbacks and between the surface albedo feedback warming and the cooling from the ocean heat storage/dynamics feedback lead to a warming minimum. In polar winter, surface albedo and shortwave cloud feedbacks are nearly absent due to a lack of insolation. However, the ocean heat storage feedback relays the polar warming due to the surface albedo feedback from summer to winter, and the longwave cloud feedback warms the polar surface. Therefore, the seasonal variations in the cloud feedback, surface albedo feedback, and ocean heat storage/dynamics feedback, directly caused by the strong annual cycle of insolation, contribute primarily to the large seasonal variation of polar warming. Furthermore, the CO2 forcing and water vapor and atmospheric dynamics feedbacks add to the maximum polar warming in fall/winter. [ABSTRACT FROM AUTHOR]

Temporal variability of meteorological variables and extreme weather events is projected to increase in many regions of the world during the next century. Artificial experiments using process-oriented terrestrial ecosystem models make it possible to isolate effects of temporal variability from effects of gradual climate change on terrestrial ecosystem functions and the system state. Such factorial experiments require two long-term climate datasets: 1) a control dataset that represents observed and projected climate and 2) a dataset with the same long-term mean as the control dataset but with altered short-term variability. Using a bias correction method, various climate datasets spanning different periods are harmonized and then combined with the control dataset with consistent time series for Europe during 1901-2100. Then, parameters of a distribution transformation function are estimated for individual meteorological variables to derive the second climate dataset, which has similar long-term means but reduced temporal variability. The transformation conserves the number of rainy days within a month and the shape of the daily meteorological data distributions, which is important to ensure that, for example, drought duration does not modify the suitability of localized vegetation type to precipitation regimes. The median absolute difference between daily data of both datasets is 5% to 20%. On average, decadal extreme values are reduced by 2% to 35%. Driving a terrestrial ecosystem model with both climate datasets shows a general higher gross primary production under reduced temporal climate variability. This effect of climate variability on productivity demonstrates the potential of the climate datasets for studying various effects of temporal variability on ecosystem state and functions over large domains. [ABSTRACT FROM AUTHOR]

Ocean carbon uptake and storage simulated by the Community Earth System Model, version 1-Biogeochemistry [CESM1(BGC)], is described and compared to observations. Fully coupled and ocean-ice configurations are examined; both capture many aspects of the spatial structure and seasonality of surface carbon fields. Nearly ubiquitous negative biases in surface alkalinity result from the prescribed carbonate dissolution profile. The modeled sea-air CO2 fluxes match observationally based estimates over much of the ocean; significant deviations appear in the Southern Ocean. Surface ocean pCO2 is biased high in the subantarctic and low in the sea ice zone. Formation of the water masses dominating anthropogenic CO2 (Cant) uptake in the Southern Hemisphere is weak in the model, leading to significant negative biases in Cant and chlorofluorocarbon (CFC) storage at intermediate depths. Column inventories of Cant appear too high, by contrast, in the North Atlantic. In spite of the positive bias, this marks an improvement over prior versions of the model, which underestimated North Atlantic uptake. The change in behavior is attributable to a new parameterization of density-driven overflows. CESM1(BGC) provides a relatively robust representation of the ocean-carbon cycle response to climate variability. Statistical metrics of modeled interannual variability in sea-air CO2 fluxes compare reasonably well to observationally based estimates. The carbon cycle response to key modes of climate variability is basically similar in the coupled and forced ocean-ice models; however, the two differ in regional detail and in the strength of teleconnections. [ABSTRACT FROM AUTHOR]

The magnitude and evolution of parameters that characterize feedbacks in the coupled carbon-climate system are compared across nine Earth system models (ESMs). The analysis is based on results from biogeochemically, radiatively, and fully coupled simulations in which CO2 increases at a rate of 1% yr−1. These simulations are part of phase 5 of the Coupled Model Intercomparison Project (CMIP5). The CO2 fluxes between the atmosphere and underlying land and ocean respond to changes in atmospheric CO2 concentration and to changes in temperature and other climate variables. The carbon-concentration and carbon-climate feedback parameters characterize the response of the CO2 flux between the atmosphere and the underlying surface to these changes. Feedback parameters are calculated using two different approaches. The two approaches are equivalent and either may be used to calculate the contribution of the feedback terms to diagnosed cumulative emissions. The contribution of carbon-concentration feedback to diagnosed cumulative emissions that are consistent with the 1% increasing CO2 concentration scenario is about 4.5 times larger than the carbon-climate feedback. Differences in the modeled responses of the carbon budget to changes in CO2 and temperature are seen to be 3-4 times larger for the land components compared to the ocean components of participating models. The feedback parameters depend on the state of the system as well the forcing scenario but nevertheless provide insight into the behavior of the coupled carbon-climate system and a useful common framework for comparing models. [ABSTRACT FROM AUTHOR]

The ability of phase 5 of the Coupled Model Intercomparison Project (CMIP5) climate models to simulate the twentieth-century 'warming hole' over North America is explored, along with the warming hole's relationship with natural climate variability. Twenty-first-century warming hole projections are also examined for two future emission scenarios, the 8.5 and 4.5 W m−2 representative concentration pathways (RCP8.5 and RCP4.5). Simulations from 22 CMIP5 climate models were analyzed, including all their ensemble members, for a total of 192 climate realizations. A nonparametric trend detection method was employed, and an alternative perspective emphasizing trend variability. Observations show multidecadal variability in the sign and magnitude of the trend, where the twentieth-century temperature trend over the eastern United States appears to be associated with low-frequency (multidecadal) variability in the North Atlantic temperatures. Most CMIP5 climate models simulate significantly lower 'relative power' in the North Atlantic multidecadal oscillations than observed. Models that have relatively higher skill in simulating the North Atlantic multidecadal oscillation also are more likely to reproduce the warming hole. It was also found that the trend variability envelope simulated by multiple CMIP5 climate models brackets the observed warming hole. Based on the multimodel analysis, it is found that in the twenty-first-century climate simulations the presence or absence of the warming hole depends on future emission scenarios; the RCP8.5 scenario indicates a disappearance of the warming hole, whereas the RCP4.5 scenario shows some chance (10%-20%) of the warming hole's reappearance in the latter half of the twenty-first century, consistent with CO2 stabilization. [ABSTRACT FROM AUTHOR]

This study proposes a systematic approach to investigate cloud-radiative feedbacks to climate change induced by an increase of CO2 concentrations in global climate models (GCMs). Based on two versions of the Model for Interdisciplinary Research on Climate (MIROC), which have opposite signs for cloud-shortwave feedback (ΔSWcld) and hence different equilibrium climate sensitivities (ECSs), hybrid models are constructed by replacing one or more parameterization schemes for cumulus convection, cloud, and turbulence between them. An ensemble of climate change simulations using a suite of eight models, called a multiphysics ensemble (MPE), is generated. The MPE provides a range of ECS as wide as the Coupled Model Intercomparison Project phase 3 (CMIP3) multimodel ensemble and reveals a different magnitude and sign of ΔSWcld over the tropics, which is crucial for determining ECS. It is found that no single process controls ΔSWcld, but that the coupling of two processes does. Namely, changing the cloud and turbulence schemes greatly alters the mean and the response of low clouds, whereas replacing the convection and cloud schemes affects low and middle clouds over the convective region. For each of the circulation regimes, ΔSWcld and cloud changes in the MPE have a nonlinear, but systematic, relationship with the mean cloud amount, which can be constrained from satellite estimates. The analysis suggests a positive feedback over the subsidence regime and a near-neutral or weak negative ΔSWcld over the convective regime in these model configurations, which, however, may not be carried into other models. [ABSTRACT FROM AUTHOR]

The climate response to increased CO2 concentration is generally studied using climate models that have finite spatial and temporal resolutions. Different parameterizations of the effect of unresolved processes can result in different representations of small-scale fluctuations in the climate model. The representation of small-scale fluctuations can, on the other hand, affect the modeled climate response. In this study the mechanisms by which enhanced small-scale fluctuations alter the climate response to CO2 doubling are investigated. Climate experiments with preindustrial and doubled CO2 concentrations obtained from a comprehensive climate model [ECHAM5/Max Planck Institute Ocean Model (MPI-OM)] are analyzed both with and without enhanced small-scale fluctuations. By applying a stochastic model to the experimental results, two different mechanisms are found. First, the small-scale fluctuations can change the statistical behavior of the global mean temperature as measured by its statistical damping. The statistical damping acts as a restoring force that determines, according to the fluctuation–dissipation theory, the amplitude of the climate response to a change in external forcing (here, CO2 doubling). Second, the small-scale fluctuations can affect processes that occur only in response to the CO2 increase, thereby altering the change of the effective forcing on the global mean temperature. [ABSTRACT FROM AUTHOR]

Sea surface temperature (SST) changes constitute a major indicator and driver of climate changes induced by greenhouse gas increases. The objective of the present study is to investigate the role played by the detailed structure of the SST change on the large-scale atmospheric circulation and the distribution of precipitation. For that purpose, simulations from the Institut Pierre-Simon Laplace Coupled Model, version 4 (IPSL-CM4) are used where the carbon dioxide (CO2) concentration is doubled. The response of IPSL-CM4 is characterized by the same robust mechanisms affecting the other coupled models in global warming simulations, that is, an increase of the hydrological cycle accompanied by a global weakening of the large-scale circulation. First, purely atmospheric simulations are performed to mimic the results of the coupled model. Then, specific simulations are set up to further study the underlying atmospheric mechanisms. These simulations use different prescribed SST anomalies, which correspond to a linear decomposition of the IPSL-CM4 SST changes in global, longitudinal, and latitudinal components. The simulation using a globally uniform increase of the SST is able to reproduce the modifications in the intensity of the hydrological cycle or in the mean upward mass flux, which also characterize the double CO2 simulation with the coupled model. But it is necessary (and largely sufficient) to also take into account the zonal-mean meridional structure of the SST changes to represent correctly the changes in the Hadley circulation strength or the zonal-mean precipitation changes simulated by the coupled model, even if these meridional changes by themselves do not change the mean thermodynamical state of the tropical atmosphere. The longitudinal SST anomalies of IPSL-CM4 also have an impact on the precipitation and large-scale tropical circulation and tend to introduce different changes over the Pacific and Atlantic Oceans. The longitudinal SST changes are demonstrated to have a smaller but opposite effect from that of the meridional anomalies on the Hadley cell circulations. Results indicate that the uncertainties in the simulated meridional patterns of the SST warming may have major consequences on the assessment of the changes of the Hadley circulation and zonal-mean precipitation in future climate projections. [ABSTRACT FROM AUTHOR]

Predictability studies of the second kind are often carried out to address the potential in predicting atmospheric variables based on knowledge of changes in sea surface temperature (SST). Here a predictability study of the second kind is performed for the coupled atmosphere–ocean system based on knowledge of changes in CO2 concentration. The focus is on potential predictabilities obtained after imposing a CO2 forcing over a short time period (i.e., a few years), which are less sensitive to the exact future time evolution of the CO2 forcing. Potential predictability is measured by the ensemble mean difference resulting from the CO2 forcing relative to the ensemble spread subjected to the same forcing. The measure is calculated from a 50-member prediction ensemble obtained from an atmosphere–ocean GCM forced by a 3% increase in CO2 concentration per year and a reference ensemble obtained under a constant CO2 concentration. The largest potential predictabilities are found in and over the Southern Ocean. The origin of these predictabilities is a positive feedback involving interactions between the atmosphere and the upper ocean. An increase in the meridional gradient of SST resulting from a large SST increase in the southern subtropics leads to a strengthening of atmospheric circulation, and from that increases in surface zonal wind stress result. The latter enhances the northward Ekman transport over the southern high latitudes, which transports polar water equatorward, whereby maintaining the meridional temperature gradient. Potential predictability is also found in the deep ocean, characterized by the downward propagation of the surface warming within a few years through two “corridors,” located at 40°S and 40°N and extending from the near surface to about 3000–3500 m. The warming in the atmosphere and the upper ocean is reduced by half because of this downward heat propagation. [ABSTRACT FROM AUTHOR]

An approach to test climate models with observations is presented. In this approach, it is possible to directly observe the longwave feedbacks of the climate system in time series of annual average outgoing longwave spectra. Tropospheric temperature, stratospheric temperature, water vapor, and carbon dioxide have clear and distinctive signatures in the infrared spectrum, and it is possible to detect trends of these signals unambiguously from trends in the outgoing longwave spectrum by optimal detection techniques. This approach is applied to clear-sky data in the tropics simulated from the output of an ensemble of climate models. Estimates of the water vapor–longwave feedback by this approach agree to within estimated errors with truth, and it is likely that an uncertainty of 50% can be obtained in 20 yr of a continuous time series. The correlation of tropospheric temperature and water vapor anomalies can provide a constraint on the water vapor–longwave feedback to 5% uncertainty in 20 yr, or 7% in 10 yr. Thus, it should be possible to place a strong constraint on climate models, which currently show a range of 30% in the water vapor–longwave feedback, in just 10 yr. These results may not hold in the presence of clouds, however, and so it may be necessary to supplement time series of outgoing longwave spectra with GPS radio occultation data, which are insensitive to clouds. [ABSTRACT FROM AUTHOR]

Tropical cyclones instigate an isolated blast of vigorous mixing in the upper tropical oceans, stirring warm surface water with cooler water in the thermocline. Previous work suggests that the frequency, intensity, and lifetime of these storms may be functions of the climate state, implying that transient tropical mixing could have been stronger during warmer equable climates with higher concentrations of carbon dioxide. Stronger mixing of the tropical oceans can force the oceans’ meridional heat flux to increase, cooling tropical latitudes while warming higher ones. This response differs significantly from previous modeling studies of equable climates that used static mixing; coupling mixing to climate changes the dynamic response. A parameterization of mixing from tropical cyclones is developed, and including it leads to a cooling of tropical oceans and a warming of subtropical waters compared with control cases with fixed mixing. The mixing penetration depth regulates the magnitude of the response. [ABSTRACT FROM AUTHOR]

Aspects of model emergent behavior and uncertainty in regional- and small-scale effects of increasing CO2 on seasonal (June–August) precipitation are explored. Nineteen different climate models are studied. New methods of comparing multiple climate models reveal a clearer and more impact-relevant view of precipitation projections for the current century. First, the importance of small spatial scales in multimodel projections is demonstrated. Local trends can be much larger than or even have an opposing sign to the large-scale regional averages used in previous studies. Small-scale effects of increasing CO2 and natural internal variability both play important roles here. These small-scale features make multimodel comparisons difficult for precipitation. New methods that allow information from small spatial scales to be usefully compared across an ensemble of multiple models are presented. The analysis philosophy of this study works with statistical distributions of small-scale variations within climatological regions. A major result of this work is a set of emergent relationships coupling the small- and regional-scale effects of CO2 on precipitation trends. Within each region, a single relationship fits the ensemble of 19 different climate models. Using these relationships, a surprisingly large part of the intermodel variance in small-scale effects of CO2 is explainable simply by the intermodel variance in the regional mean (a form of pattern scaling). Different regions show distinctly different relationships. These relationships imply that regional mean results are still useful, as long as the interregional variation in their relationship with impact-relevant extreme trends is recognized. These relationships are used to present a clear but rich picture of an aspect of model uncertainty, characterized by the intermodel spread in seasonal precipitation trends, including information from small spatial scales. [ABSTRACT FROM AUTHOR]

A new physiology-based model of canopy stomatal conductance and photosynthesis is described and included in the latest version of the Goddard Institute for Space Studies (GISS) GCM, ModelE1. The submodel includes responses to atmospheric humidity and CO2 concentration, responses missing from previous GISS GCM land surface schemes. Measurements of moisture, energy, and CO2 fluxes over four vegetation types are used to test and calibrate the submodel. Photosynthetic leaf N is calibrated for each vegetation type from the flux measurements. The new submodel results in surface cooling over many regions previously too warm. Some warm biases of over 2°C are cooled by more than 0.5°C, including over central Eurasia, South America, the western United States, and Australia. In addition, some regions that were previously too cool are warmed, such as northern Eurasia and the Tibetan Plateau. A number of precipitation biases are also reduced, particularly over South America (by up to 1 mm day-1) and the oceanic ITCZs (by over ±1 mm day-1); coastal west Africa becomes significantly wetter. Cloud cover increases over many land areas previously too clear. Higher absolute canopy conductances, and positive feedbacks with atmospheric humidity, are largely responsible for the simulated vegetation influence on the atmosphere. High-latitude climate changes through remote effects of increased tropical latent heating, resulting directly from improved characterization of tropical forest canopy conductance. Realistic representation of the stomatal control on land evaporation is critical for accurate simulation of atmospheric dynamics in the GISS GCM. [ABSTRACT FROM AUTHOR]

The frequency of cloud detection and the frequency with which these clouds are found in the upper troposphere have been extracted from NOAA High Resolution Infrared Radiometer Sounder (HIRS) polar-orbiting satellite data from 1979 to 2001. The HIRS/2 sensor was flown on nine satellites from the Television Infrared Observation Satellite-Next Generation (TIROS-N) through NOAA-14, forming a 22-yr record. Carbon dioxide slicing was used to infer cloud amount and height. Trends in cloud cover and high-cloud frequency were found to be small in these data. High clouds show a small but statistically significant increase in the Tropics and the Northern Hemisphere. The HIRS analysis contrasts with the International Satellite Cloud Climatology Project (ISCCP), which shows a decrease in both total cloud cover and high clouds during most of this period. [ABSTRACT FROM AUTHOR]

The separate climate effects of middle-atmospheric and tropospheric CO2 doubling have been simulated and analyzed with the ECHAM middle-atmosphere climate model. To this end, the CO2 concentration has been separately doubled in the middle-atmosphere, the troposphere, and the entire atmosphere, and the results have been compared to a control run. During NH winter, the simulated uniformly doubled CO2 climate shows an increase of the stratospheric residual circulation, a small warming in the Arctic lower stratosphere, a weakening of the zonal winds in the Arctic middle-atmosphere, an increase of the NH midlatitude tropospheric westerlies, and a poleward shift of the SH tropospheric westerlies. The uniformly doubled CO2 response in most regions is approximately equal to the sum of the separate responses to tropospheric and middle-atmospheric CO2 doubling. The increase of the stratospheric residual circulation can be attributed for about two-thirds to the tropospheric CO2 doubling and one-third to the middle-atmospheric CO2 doubling. This increase contributes to the Arctic lower-stratospheric warming and, through the thermal wind relationship, to the weakening of the Arctic middle-atmospheric zonal wind. The increase of the tropospheric NH midlatitude westerlies can be attributed mainly to the middle-atmospheric CO2 doubling, indicating the crucial importance of the middle-atmospheric CO2 doubling for the tropospheric climate change. Results from an additional experiment show that the CO2 doubling above 10 hPa, which is above the top of many current GCMs, also causes significant changes in the tropospheric climate. [ABSTRACT FROM AUTHOR]

Changes due to CO2 doubling in the extremes of the surface climate as simulated by the second-generation circulation model of the Canadian Centre for Climate Modelling and Analysis are studied in two 20-yr equilibrium simulations. Extreme values of screen temperature, precipitation, and near-surface wind in the control climate are compared to those estimated from 17 yr of the NCEP--NCAR reanalysis data and from some Canadian station data. The extremes of screen temperature are reasonably well reproduced in the control climate. Their changes under CO2 doubling can be connected with other physical changes such as surface albedo changes due to the reduction of snow and sea ice cover as well as a decrease of soil moisture in the warmer world. The signal in the extremes of daily precipitation and near-surface wind speed due to CO2 doubling is less obvious. The precipitation extremes increase almost everywhere over the globe. The strongest change, over northwest India, is related to the intensification of the summer monsoon in this region in the warmer world. The modest reduction of wind extremes in the Tropics and middle latitudes is consistent with the reduction of the meridional temperature gradient in the 23CO2 climate. The larger wind extremes occur in the areas where sea ice has retreated. [ABSTRACT FROM AUTHOR]

The climate sensitivity to various forcings, and in particular to changes in CO[sub2] and sulfate aerosol concentrations, imposed separately or in a combined manner, is studied with an atmospheric general circulation model coupled to a simple slab oceanic model. The atmospheric model includes a rather detailed treatment of warm cloud microphysics and takes the aerosol indirect effects into account explicitly, although in a simplified manner. The structure of the model response appears to be organized at a global scale, with a partial independence from the geographical structure of the forcing. Atmospheric and surface feedbacks are likely to explain this feature. In particular the cloud feedbacks play a very similar role in the CO[sub2] and aerosol experiments, but with opposite sign. These results strengthen the idea, already apparent from other studies, that, in spite of their different nature and their different geographical and vertical distributions, aerosol may have substantially counteracted the climate effect of greenhouse gases, at least in the Northern Hemisphere, during the twentieth century. When the effects of the two forcings are added, the model response is not symmetric between the two hemispheres. This feature is also consistent with the findings of other modeling groups and has implications for the detection of future climate changes. [ABSTRACT FROM AUTHOR]