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Hydrological sensitivity is the change in global-mean precipitation per degree of global-mean temperature change. This paper shows that the hydrological sensitivity of the response to anthropogenic aerosol forcing is distinct from that of the combined response to all other forcings and that this difference is sufficient to infer the associated cooling in global-mean temperature. This result is demonstrated using temperature and precipitation data generated by climate models and is robust across different climate models. Remarkably, greenhouse gas warming and aerosol cooling can be estimated in a model without using any spatial or temporal gradient information in the response, provided temperature data are augmented by precipitation data. Over the late twentieth century, the hydrological sensitivities of climate models differ significantly from that of observations. Whether this discrepancy can be attributed to observational error, which is substantial as different estimates of global-mean precipitation are not even significantly correlated with each other, or to model error is unclear. The results highlight the urgency to construct accurate estimates of global precipitation from past observations and for reducing model uncertainty in hydrological sensitivity. This paper also clarifies that previous estimates of hydrological sensitivity are limited in that standard regression methods neglect temperature-precipitation relations that occur through internal variability. An alternative method for estimating hydrological sensitivity that overcomes this limitation is presented. [ABSTRACT FROM AUTHOR]

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]

The spatial domain of the Asian monsoon has been defined by the intensity, seasonal concentration, and annual range of precipitation. Monsoon subdomains, such as the Indian monsoon, East Asian monsoon, and western North Pacific monsoon, have also been identified based on seasonal wind reversals as well as the timing and source of monsoon moisture. However, precipitation across the Asian monsoon region is heterogeneous and spatially complex and may have influences farther north than commonly assumed, particularly if scientists consider records of past variability spanning the current interglacial period. This paper presents an additional means of identifying the Asian monsoon domain and monsoon subsystems using an empirical orthogonal function (EOF)-based regionalization of gridded precipitation values. Regions of unique precipitation variability for the Asian monsoon region are determined using monthly precipitation anomalies from the Climate Prediction Center Merged Analysis of Precipitation (CMAP) gridded precipitation dataset from 1979 to 2009. From these regions, an area of Asian monsoon influence extending from the Arabian Sea eastward to the western North Pacific Ocean is defined, similar to other studies. One key difference is that this region of monsoon influence penetrates farther north into the Tibetan Plateau and northern China. Thus, paleoclimate observations of wetter conditions in these northern arid regions may suggest an intensification of monsoon moisture, rather than a northward shift in the boundary of the monsoon. In contrast, the Arabian Peninsula, largely removed from monsoon precipitation today, likely saw a shift of monsoon influence inland earlier in the Holocene. Also identified are different subdomains of distinct precipitation variability in southeastern Asia, the western North Pacific, and the East Asian monsoon region of northeastern China that agree with previous studies. Not identified in the paper is a single Indian summer monsoon region. Instead, the Arabian Sea was found to have unique precipitation variability relative to the Indian subcontinent. Summers with enhanced precipitation over the Arabian Sea coincide with decreased summer precipitation in the western North Pacific. This relationship is likely a result of the El Niñño--Southern Oscillation (ENSO)-induced development of the Philippine Sea anticyclone. Local and remote sea surface temperatures were generally found to covary with regional precipitation, but not all regions respond similarly to the remote climate variability associated with ENSO. There is some evidence that the EOF-defined regions were stable ...... through the Holocene, although additional regionalization analyses of paleorecords and model simulations of past precipitation variability are needed to reconstruct past regions of coherent precipitation variability. [ABSTRACT FROM AUTHOR]

This paper dynamically combined three multivariate forecasts where spatially and temporally variant combination weights are estimated using a nearest-neighbor approach. The case study presented combines forecasts from three climate models for the period 1958--2001. The variables of interest here are the monthly global sea surface temperature anomalies (SSTA) at a 5°° ×× 5°° latitude--longitude grid, predicted 3 months in advance. The forecast from the static weight combination is used as the base case for comparison. The forecasted sea surface temperature using the dynamic combination algorithm offers consistent improvements over the static combination approach for all seasons. This improved skill is achieved over at least 93%% of the global grid cells, in four 10-yr independent validation segments. Dynamically combined forecasts reduce the mean-square error of the SSTA by at least 25%% for 72%% of the global grid cells when compared against the best-performing single forecast among the three climate models considered. [ABSTRACT FROM AUTHOR]

This paper reports on an analysis of the tropical cyclone (TC) potential intensity (PI) and its control parameters in transient global warming simulations. Specifically, the TC PI is calculated for phase 3 of the Coupled Model Intercomparison Project (CMIP3) integrations during the first 70 yr of a transient run forced by a 1% yr-1 CO2 increase. The linear trend over the period is used to project a 70-yr change in relevant model parameters. The results for a 15-model ensemble-mean climate projection show that the thermodynamic potential intensity (THPI) increases on average by 1.0% to ∼3.1% over various TC basins, which is mainly attributed to changes in the disequilibrium in enthalpy between the ocean and atmosphere in the transient response to increasing CO2 concentrations. This modest projected increase in THPI is consistent with that found in other recent studies. In this paper the effects of evolving large-scale dynamical factors on the projected TC PI are also quantified, using an empirical formation that takes into account the effects of vertical shear and translational speed based on a statistical analysis of present-day observations. Including the dynamical efficiency in the formulation of PI leads to larger projected changes in PI relative to that obtained using just THPI in some basins and smaller projected changes in others. The inclusion of the dynamical efficiency has the largest relative effect in the main development region (MDR) of the North Atlantic, where it leads to a 50% reduction in the projected PI change. Results are also presented for the basin-averaged changes in PI for the climate projections from each of the 15 individual models. There is considerable variation among the results for individual model projections, and for some models the projected increase in PI in the eastern Pacific and south Indian Ocean regions exceeds 10%. [ABSTRACT FROM AUTHOR]

The dominant interannual El Niño–Southern Oscillation (ENSO) phenomenon and the short length of climate observation records make it difficult to study long-term climate variations in the spatiotemporal domain. Based on the fact that the ENSO signal spreads to remote regions and induces delayed climate variation through atmospheric teleconnections, an ENSO-removal method is developed through which the ENSO signal can be approximately removed at the grid box level from the spatiotemporal field of a climate parameter. After this signal is removed, long-term climate variations are isolated at mid- and low latitudes in the climate parameter fields from observed and reanalysis datasets. This paper addresses the long-term global warming trend (GW); a companion paper concentrates on Pacific pan-decadal variability (PDV). The warming that occurs in the Pacific basin (approximately 0.4 K in the twentieth century) is much weaker than in surrounding regions and the other two ocean basins (approximately 0.8 K). The modest warming in the Pacific basin is likely due to its dynamic nature on the interannual and decadal time scales and/or the leakage of upper ocean water through the Indonesian Throughflow. Based on the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) and the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40), a comprehensive atmospheric structure associated with the GW trend is given. Significant discrepancies exist between the two datasets, especially in the tightly coupled dynamics and water vapor fields. The dynamics fields based on NCEP–NCAR, which show a change in the Walker Circulation, are consistent with the GW change in the surface temperature field. However, intensification in the Hadley Circulation is associated with GW trend in ERA-40 instead. [ABSTRACT FROM AUTHOR]

One of the possible consequences of global warming is that there will be more days with precipitation throughout the year, and also that the level of precipitation will be higher. In this paper a detailed statistical analysis of a century of daily precipitation levels is provided for the central meteorological station in the Netherlands. This paper shows that the often-considered gamma distribution does not fit well to samples of yearly data. It is argued that its incorrect use can lead to spuriously high probabilities of extreme precipitation levels. Relying on advanced nonparametric techniques, it is first found that there are fewer rainy days in the central part of the Netherlands. Next, more rainy days involve higher precipitation levels. Most importantly, no statistically significant shift is found in the annual largest values of daily rainfall over the course of the century, which suggest that the probability of extremely high levels has not changed over time. [ABSTRACT FROM AUTHOR]

A thorough analysis of the stability of a coupled version of an interhemispheric three-box model of thermohaline circulation (THC) is presented. This study follows a similarly structured analysis of an uncoupled version of the same model presented in Part I of this paper. The model consists of a northern high-latitude box, a tropical box, and a southern high-latitude box, which can be thought of as corresponding to the northern, tropical, and southern Atlantic Ocean, respectively. This paper examines how the strength of THC changes when the system undergoes forcings representing global warming conditions. Since a coupled model is used, a direct representation of the radiative forcing is possible because the main atmospheric physical processes responsible for freshwater and heat fluxes are formulated separately. Each perturbation to the initial equilibrium is characterized by the total radiative forcing realized, by the rate of increase, and by the north–south asymmetry. Although only weakly asymmetric or symmetric radiative forcings are representative of physically reasonable conditions, general asymmetric forcings are considered in order to get a more complete picture of the mathematical properties of the system. The choice of suitably defined metrics makes it possible to determine the boundary dividing the set of radiative forcing scenarios that lead the system to equilibria characterized by a THC pattern similar to the present one, from those that drive the system to equilibria where the THC is reversed. This paper also considers different choices for the atmospheric transport parameterizations and for the ratio between the high-latitude and tropical radiative forcing. It is generally found that fast forcings are more effective than slow forcings in disrupting the present THC pattern, forcings that are stronger in the northern box are also more effective in destabilizing the system, and very slow forcings do not destabilize the system whatever their asymmetry, unless the radiative forcings are very asymmetric and the atmospheric transport is a relatively weak function of the meridional temperature gradient. In this latter case some relevant hysteresis graphs of the system are presented. The changes in the strength of the THC are primarily forced by changes in the latent heat transport in the hemisphere because of its sensitivity to temperature, which arises from the Clausius–Clapeyron relation. [ABSTRACT FROM AUTHOR]

Kretzschmar et al., in a comment in 2017, use the spread in the output of aerosol-climate models to argue that the models refute the hypothesis (presented in a paper by Stevens in 2015) that for the mid-twentieth-century warming to be consistent with observations, then the present-day aerosol forcing, must be less negative than −1 W m−2. The main point of contention is the nature of the relationship between global SO2 emissions and In contrast to the concave (log-linear) relationship used by Stevens and in earlier studies, whereby becomes progressively less sensitive to SO2 emissions, some models suggest a convex relationship, which would imply a less negative lower bound. The model that best exemplifies this difference, and that is most clearly in conflict with the hypothesis of Stevens, does so because of an implausible aerosol response to the initial rise in anthropogenic aerosol precursor emissions in East and South Asia-already in 1975 this model's clear-sky reflectance from anthropogenic aerosol over the North Pacific exceeds present-day estimates of the clear-sky reflectance by the total aerosol. The authors perform experiments using a new (observationally constrained) climatology of anthropogenic aerosols to further show that the effects of changing patterns of aerosol and aerosol precursor emissions during the late twentieth century have, for the same global emissions, relatively little effect on These findings suggest that the behavior Kretzschmar et al. identify as being in conflict with the lower bound in Stevens arises from an implausible relationship between SO2 emissions and and thus provides little basis for revising this lower bound. [ABSTRACT FROM AUTHOR]

Projections of precipitation extremes over land are crucial for socioeconomic risk assessments, yet model discrepancies limit their application. Here we use a pattern-filtering technique to identify low-frequency changes in individual members of a multimodel ensemble to assess discrepancies across models in the projected pattern and magnitude of change. Specifically, we apply low-frequency component analysis (LFCA) to the intensity and frequency of daily precipitation extremes over land in 21 CMIP-6 models. LFCA brings modest but statistically significant improvements in the agreement between models in the spatial pattern of projected change, particularly in scenarios with weak greenhouse forcing. Moreover, we show that LFCA facilitates a robust identification of the rates at which increasing precipitation extremes scale with global temperature change within individual ensemble members. While these rates approximately match expectations from the Clausius-Clapeyron relation on average across models, individual models exhibit considerable and significant differences. Monte Carlo simulations indicate that these differences contribute to uncertainty in the magnitude of projected change at least as much as differences in the climate sensitivity. Last, we compare these scaling rates with those identified from observational products, demonstrating that virtually all climate models significantly underestimate the rates at which increases in precipitation extremes have scaled with global temperatures historically. Constraining projections with observations therefore amplifies the projected intensification of precipitation extremes as well as reducing the relative error of their distribution. [ABSTRACT FROM AUTHOR]

The importance of investigating regional climate changes associated with degrees of global warming is increasingly being recognized, but the majority of relevant research has been based on multimodel ensembles (MMEs) from the Coupled Model Intercomparison Project (CMIP). This has left two important questions unanswered: Are there plausible futures which are not represented by the models in CMIP? And, how would regional climates evolve under enhanced global warming, beyond 4°C? In this paper, two perturbed physics ensembles (PPEs) are used to address these issues with reference to African precipitation. Examination of model versions that generate warming greater than 4°C in the twenty-first century shows that changes in African precipitation are enhanced gradually, even to high global temperatures; however, there may be nonlinearities that are not incorporated here due to limited model complexity. The range of projections from the PPEs is compared to data from phases 3 and 5 of CMIP (CMIP3 and CMIP5), revealing regional differences. This is partly the result of implausible model versions, but the PPE dataset can be justifiably constrained given its size and systematic nature, highlighting an additional advantage over MMEs. After applying constraints, the PPEs still show changes that are outside the range of CMIP, most prominently strong dry signals in west equatorial Africa and the Sahel, implying that MMEs may underestimate risks for these regions. Analysis of African precipitation changes therefore demonstrates that regional assessments that rely on CMIP3 and CMIP5 may overlook uncertainties associated with model parameterizations and pronounced warming. More systematic approaches are needed for conservative estimates of danger. [ABSTRACT FROM AUTHOR]

In a recent paper, Schwartz et al. suggest that 1) over the last century the earth has warmed less than expected, and they discuss several factors that could explain the discrepancy, including climate sensitivity estimates and aerosol forcing. Schwartz et al. then continue to 2) estimate the allowed carbon emissions for stabilization of global temperature, and find that given the uncertainty in the climate sensitivity even the sign of these allowed carbon emissions is unknown, implying that past emissions may already have committed the earth to 2°C warming for a best-estimate value of climate sensitivity of 3 K. Both of these conclusions in the Schwartz et al. study are revisited herein, and it is shown that 1) in contrast to Schwartz et al., current assessments of climate sensitivity, radiative forcing, and thermal disequilibrium do not support the claim of a discrepancy between expected and observed warming; and 2) the allowed emissions estimated by Schwartz et al. are in conflict with results from a hierarchy of climate-carbon cycle models and are strongly underestimated due to erroneous assumptions about the behavior of the carbon cycle and a confusion of the relevant time scales. [ABSTRACT FROM AUTHOR]

In this paper, the modulations of the North Atlantic tripole (NAT) decadal variability from global warming are studied by conducting a series of coupled ocean-atmosphere experiments using the Fast Ocean Atmosphere Model (FOAM). The model reasonably captures the observed NAT decadal variability with a preferred time scale of about 11 years. With the aid of partial-blocking and partial-coupling experiments, it is found that the NAT decadal cycle can be attributed to oceanic planetary wave adjustment in the subtropical basin and ocean-atmosphere coupling over the North Atlantic. In a doubled CO2 experiment, the spatial pattern of the NAT is preserved; however, the decadal cycle is significantly suppressed. This suppression appears to be associated with the acceleration of oceanic planetary waves due to an increase of buoyancy frequency in global warming. This shortens the time from a decadal to an interannual time scale for the first-mode baroclinic Rossby waves to cross the subtropical North Atlantic basin, the primary memory for the NAT decadal variability in the model. The modeling study also found that the global warming does not modulate the North Atlantic air-sea coupling significantly, but it may be model dependent. [ABSTRACT FROM AUTHOR]

The spatial domain of the Asian monsoon has been defined by the intensity, seasonal concentration, and annual range of precipitation. Monsoon subdomains, such as the Indian monsoon, East Asian monsoon, and western North Pacific monsoon, have also been identified based on seasonal wind reversals as well as the timing and source of monsoon moisture. However, precipitation across the Asian monsoon region is heterogeneous and spatially complex and may have influences farther north than commonly assumed, particularly if scientists consider records of past variability spanning the current interglacial period. This paper presents an additional means of identifying the Asian monsoon domain and monsoon subsystems using an empirical orthogonal function (EOF)-based regionalization of gridded precipitation values. Regions of unique precipitation variability for the Asian monsoon region are determined using monthly precipitation anomalies from the Climate Prediction Center Merged Analysis of Precipitation (CMAP) gridded precipitation dataset from 1979 to 2009. From these regions, an area of Asian monsoon influence extending from the Arabian Sea eastward to the western North Pacific Ocean is defined, similar to other studies. One key difference is that this region of monsoon influence penetrates farther north into the Tibetan Plateau and northern China. Thus, paleoclimate observations of wetter conditions in these northern arid regions may suggest an intensification of monsoon moisture, rather than a northward shift in the boundary of the monsoon. In contrast, the Arabian Peninsula, largely removed from monsoon precipitation today, likely saw a shift of monsoon influence inland earlier in the Holocene. Also identified are different subdomains of distinct precipitation variability in southeastern Asia, the western North Pacific, and the East Asian monsoon region of northeastern China that agree with previous studies. Not identified in the paper is a single Indian summer monsoon region. Instead, the Arabian Sea was found to have unique precipitation variability relative to the Indian subcontinent. Summers with enhanced precipitation over the Arabian Sea coincide with decreased summer precipitation in the western North Pacific. This relationship is likely a result of the El Niñño--Southern Oscillation (ENSO)-induced development of the Philippine Sea anticyclone. Local and remote sea surface temperatures were generally found to covary with regional precipitation, but not all regions respond similarly to the remote climate variability associated with ENSO. There is some evidence that the EOF-defined regions were stable ...... through the Holocene, although additional regionalization analyses of paleorecords and model simulations of past precipitation variability are needed to reconstruct past regions of coherent precipitation variability. [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]

This paper presents an analysis of the precipitation climate signal in Europe emerging from a simulation of heterogeneous regional climate models (RCMs) using five observational datasets as the reference for present day climate conditions. Current climate simulations, as well as those from the A2 family of scenarios from the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (SRES-A2), from eight RCMs involved in the Prediction of Regional Scenarios and Uncertainties for Defining European Climate Change Risks and Effects (PRUDENCE) project have been cross-compared with data from the Climate Research Unit (CRU), the Global Precipitation Climatology Project (GPCP), the Global Precipitation Climatology Centre (GPCC), the Climate Prediction Center (CPC), and the CPC Merged Analysis of Precipitation (CMAP) databases for Europe. The RCMs used are HIRHAM, the Climate High Resolution Model (CHRM), the Rossby Centre Atmosphere–Ocean (RCAO) model, the GKSS Climate Version of the Local Model (CLM), the Hadley Center RCM (HadRM3H), the Atmospheric Hydrostatic Regional Model (REMO), the Prognostic Model at the Mesoscale (PROMES), and the regional coupled ocean–atmosphere–ice model (RACMO). The comparison shows that the climate signal has to be interpreted depending on the reference data used. Although each validation dataset has its own relative merits and shortcomings, it is known that all of the datasets present variable uncertainties and error sources, which impedes consideration of a single dataset as the only valid representation of actual precipitation. Hence, it is suggested that a robust joint estimate of changes in future precipitation might include the uncertainties of both the RCMs and those of the observational datasets. After accounting for the difference between observed and simulated precipitation in the present climate, the analysis of such joint estimates reveals significant agreement in the climate signal for most of Europe. This lends confidence to the idea that the RCMs are able to correctly simulate future changes in precipitation. [ABSTRACT FROM AUTHOR]

A variety of observational and modeling studies show that changes in the Atlantic meridional overturning circulation (AMOC) can induce rapid global-scale climate change. In particular, a substantially weakened AMOC leads to a southward shift of the intertropical convergence zone (ITCZ) in both the Atlantic and the Pacific Oceans. However, the simulated amplitudes of the AMOC-induced tropical climate change differ substantially among different models. In this paper, the sensitivity to cloud feedback of the climate response to a change in the AMOC is studied using a coupled ocean–atmosphere model [the GFDL Coupled Model, version 2.1 (CM2.1)]. Without cloud feedback, the simulated AMOC-induced climate change in this model is weakened substantially. Low-cloud feedback has a strong amplifying impact on the tropical ITCZ shift in this model, whereas the effects of high-cloud feedback are weaker. It is concluded that cloud feedback is an important contributor to the uncertainty in the global response to AMOC changes. [ABSTRACT FROM AUTHOR]

Reconstruction of the earth's surface temperature from proxy data is an important task because of the need to compare recent changes with past variability. However, the statistical properties and robustness of climate reconstruction methods are not well known, which has led to a heated discussion about the quality of published reconstructions. In this paper a systematic study of the properties of reconstruction methods is presented. The methods include both direct hemispheric-mean reconstructions and field reconstructions, including reconstructions based on canonical regression and regularized expectation maximization algorithms. The study will be based on temperature fields where the target of the reconstructions is known. In particular, the focus will be on how well the reconstructions reproduce low-frequency variability, biases, and trends. A climate simulation from an ocean–atmosphere general circulation model of the period A.D. 1500–1999, including both natural and anthropogenic forcings, is used. However, reconstructions include a large element of stochasticity, and to draw robust statistical interferences, reconstructions of a large ensemble of realistic temperature fields are needed. To this end a novel technique has been developed to generate surrogate fields with the same temporal and spatial characteristics as the original surface temperature field from the climate model. Pseudoproxies are generated by degrading a number of gridbox time series. The number of pseudoproxies and the relation between the pseudoproxies and the underlying temperature field are determined realistically from Mann et al. It is found that all reconstruction methods contain a large element of stochasticity, and it is not possible to compare the methods and draw conclusions from a single or a few realizations. This means that very different results can be obtained using the same reconstruction method on different surrogate fields. This might explain some of the recently published divergent results. Also found is that the amplitude of the low-frequency variability in general is underestimated. All methods systematically give large biases and underestimate both trends and the amplitude of the low-frequency variability. The underestimation is typically 20%–50%. The shape of the low-frequency variability, however, is well reconstructed in general. Some potential in validating the methods on independent data is found. However, to gain information about the reconstructions' ability to capture the preindustrial level it is necessary to consider the average level in the validation period and not the year-to-year correlations. The influence on the reconstructions of the number of proxies, the type of noise used to generate the proxies, the strength of the variability, as well as the effect of detrending the data prior to the calibration is also reported. [ABSTRACT FROM AUTHOR]

In this paper, an idealized framework based on a cloud-topped mixed layer model is developed for investigating feedbacks between subtropical stratocumulus (Sc) and global warming. The two principal control parameters are Sc-region sea surface temperature (SST) and intertropical convergence zone (ITCZ) SST (which controls the temperature and mean subsidence profiles above the Sc). The direct effect of CO2 doubling (leaving all other parameters fixed) is tested and found to somewhat reduce liquid water path; discussion of this effect on the SST-change simulations is included. The presence of a cold boundary layer is found to significantly affect the temperature and subsidence rate just above cloud top by enhancing lower-tropospheric diabatic cooling in this region. A simple representation of this effect (easily generalizable to a more realistic boundary layer model) is developed. Steady-state solutions are analyzed as a function of local and ITCZ SST. Two climate change scenarios are considered. The first scenario is an equal increase of local and ITCZ SSTs. In this case, predicted boundary layer depth and cloud thickness increase. This is found in a simplified context to result from subsidence and entrainment decreases due to increased static stability in a warmer climate. In the second case, local SST change is diagnosed from a surface energy balance under the assumption that ocean heat transport remains unchanged. In this case, predicted boundary layer depth decreases. Cloud continues to thicken with rising ITCZ SST, but at a rate much reduced in comparison to the equal-warming scenario. This cloud shading feedback keeps SST in the Sc region nearly constant as the ITCZ SST increases. Model sensitivity to aerosol indirect effects is also considered by varying the assumed droplet concentration. The resulting change in liquid water path is small, suggesting a weaker dependence on second indirect effect than found in previous studies. [ABSTRACT FROM AUTHOR]

Uncertainties in observed records of atmospheric temperature aloft remain poorly quantified. This has resulted in considerable controversy regarding signals of climate change over recent decades from temperature records of radiosondes and satellites. This work revisits the problems associated with the removal of inhomogeneities from the historical radiosonde temperature records, and provides a method for quantifying uncertainty in an adjusted radiosonde climate record due to the subjective choices made during the data homogenization. This paper presents an automated homogenization method designed to replicate the decisions made by manual judgment in the generation of an earlier radiosonde dataset [i.e., the Hadley Centre radiosonde temperature dataset (HadAT)]. A number of validation experiments have been conducted to test the system performance and impact on linear trends. Using climate model data to simulate biased radiosonde data, the authors show that limitations in the homogenization method are sufficiently large to explain much of the tropical trend discrepancy between HadAT and estimates from satellite platforms and climate models. This situation arises from the combination of systematic (unknown magnitude) and random uncertainties (of order 0.05 K decade-1) in the radiosonde data. Previous assessment of trends and uncertainty in HadAT is likely to have underestimated the systematic bias in tropical mean temperature trends. This objective assessment of radiosonde homogenization supports the conclusions of the synthesis report of the U.S. Climate Change Science Program (CCSP), and associated research, regarding potential bias in tropospheric temperature records from radiosondes. [ABSTRACT FROM AUTHOR]

Predictability limits for seasonal atmospheric climate variability depend on the fraction of variability that is due to factors external to the atmosphere (e.g., boundary conditions) and the fraction that is internal. From the analysis of observed data alone, however, separation of the total seasonal atmospheric variance into its external and internal components remains a difficult and controversial issue. In this paper a simple procedure for estimating atmospheric internal variability is outlined. This procedure is based on the expected value of the mean square error between the observed and the general circulation model simulated (or predicted) seasonal mean anomaly. The end result is a spatial map for the estimate of the observed seasonal atmospheric internal (or unpredictable) variability. As improved general circulation models become available, mean square error estimated from the new generation of general circulation models can be easily included in the procedure proposed herein, bringing the estimate for the internal variability closer to its true estimate. [ABSTRACT FROM AUTHOR]

In this paper the extensive integrations produced for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) are used to examine the relationship between ENSO and monsoons at interannual and decadal time scales. The study begins with an analysis of the monsoon simulation in the twentieth-century integrations. Six of the 18 models were found to have a reasonably realistic representation of monsoon precipitation climatology. For each of these six models SST and anomalous precipitation evolution along the equatorial Pacific during El Niño events display considerable differences when compared to observations. Out of these six models only four [Geophysical Fluid Dynamics Laboratory Climate Model versions 2.0 and 2.1 (GFDL_CM_2.0 and GFDL_CM_2.1), Meteorological Research Institute (MRI) model, and Max Planck Institute ECHAM5 (MPI_ECHAM5)] exhibit a robust ENSO–monsoon contemporaneous teleconnection, including the known inverse relationship between ENSO and rainfall variations over India. Lagged correlations between the all-India rainfall (AIR) index and Niño-3.4 SST reveal that three models represent the timing of the teleconnection, including the spring predictability barrier, which is manifested as the transition from positive to negative correlations prior to the monsoon onset. Furthermore, only one of these three models (GFDL_CM_2.1) captures the observed phase lag with the strongest anticorrelation of SST peaking 2–3 months after the summer monsoon, which is partially attributable to the intensity of the simulated El Niño itself. The authors find that the models that best capture the ENSO–monsoon teleconnection are those that correctly simulate the timing and location of SST and diabatic heating anomalies in the equatorial Pacific and the associated changes to the equatorial Walker circulation during El Niño events. The strength of the AIR-Niño-3.4 SST correlation in the model runs waxes and wanes to some degree on decadal time scales. The overall magnitude and time scale for this decadal modulation in most of the models is similar to that seen in observations. However, there is little consistency in the phase among the realizations, suggesting a lack of predictability of the decadal modulation of the monsoon–ENSO relationship. The analysis was repeated for each of the four models using results from integrations in which the atmospheric CO2 concentration was raised to twice preindustrial values. From these “best” models in the double CO2 simulations there are increases in both the mean monsoon rainfall over the Indian subcontinent (by 5%–25%) and in its interannual variability (5%–10%). For each model the ENSO–monsoon correlation in the global warming runs is very similar to that in the twentieth-century runs, suggesting that the ENSO–monsoon connection will not weaken as global climate warms. This result, though plausible, needs to be taken with some caution because of the diversity in the simulation of ENSO variability in the coupled models that have been analyzed. Implications of the present results for monsoon prediction are discussed. [ABSTRACT FROM AUTHOR]

The detection and attribution of climate change in the observed record play a central role in synthesizing knowledge of the climate system. Unfortunately, the traditional method for detecting and attributing changes due to multiple forcings requires large numbers of general circulation model (GCM) simulations incorporating different initial conditions and forcing scenarios, and these have only been performed with a small number of GCMs. This paper presents an extension to the fingerprinting technique that permits the inclusion of GCMs in the multisignal analysis of surface temperature even when the required families of ensembles have not been generated. This is achieved by fitting a series of energy balance models (EBMs) to the GCM output in order to estimate the temporal response patterns to the various forcings. This methodology is applied to the very large Challenge ensemble of 62 simulations of historical climate conducted with the NCAR Community Climate System Model version 1.4 (CCSM1.4) GCM, as well as some simulations from other GCMs. Considerable uncertainty exists in the estimates of the parameters in fitted EBMs. Nevertheless, temporal response patterns from these EBMs are more reliable and the combined EBM time series closely mimics the GCM in the context of transient forcing. In particular, detection and attribution results from this technique appear self-consistent and consistent with results from other methods provided that all major forcings are included in the analysis. Using this technique on the Challenge ensemble, the estimated responses to changes in greenhouse gases, tropospheric sulfate aerosols, and stratospheric volcanic aerosols are all detected in the observed record, and the responses to the greenhouse gases and tropospheric sulfate aerosols are both consistent with the observed record without a scaling of the amplitude being required. The result is that the temperature difference of the 1996–2005 decade relative to the 1940–49 decade can be attributed to greenhouse gas emissions, with a partially offsetting cooling from sulfate emissions and little contribution from natural sources. The results support the viability of the new methodology as an extension to current analysis tools for the detection and attribution of climate change, which will allow the inclusion of many more GCMs. Shortcomings remain, however, and so it should not be considered a replacement to traditional techniques. [ABSTRACT FROM AUTHOR]

This paper presents an update on the detection and attribution of global annual mean surface air temperature changes, using recently developed climate models. In particular, it applies a new methodology that permits the inclusion of many more general circulation models (GCMs) into the analysis, and it also includes more recent observations. This methodology involves fitting a series of energy balance models (EBMs) to the GCM output in order to estimate the temporal response patterns to the various forcings. Despite considerable spread in estimated EBM parameters, characteristics of model performance, such as the transient climate response, appear to be more constrained for each of the forcings. The resulting estimated response patterns are provided as input to the standard fingerprinting method used in previous studies. The estimated GCM responses to changes in greenhouse gases are detected in the observed record for all of the GCMs, and are generally found to be consistent with the observed changes; the same is generally true for the responses to changes in stratospheric aerosols from volcanic eruptions. GCM responses to changes in tropospheric sulfate aerosols and solar irradiance also appear consistent with the observed record, although the uncertainty is larger. Greenhouse gas and solar irradiance changes are found to have contributed to a best guess of ∼0.8 and ∼0.3 K warming over the 1901–2005 period, respectively, while sulfate aerosols have contributed a ∼0.4 K cooling. This analysis provides an observationally constrained estimate of future warming, which is found to be fairly robust across GCMs. By 2100, a warming of between about 1.5 and 4.5 K can be expected according to the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A1B emissions scenario. These results indicate an emerging constraint for global mean surface temperature responses to external forcings across GCMs, which is corroborated in the observed record. This implies that observationally constrained estimates of past warming and predictions of future warming are indeed becoming robust. [ABSTRACT FROM AUTHOR]

This review paper discusses the physical basis and the potential for decadal climate predictability over the Atlantic and its adjacent land areas. Many observational and modeling studies describe pronounced decadal and multidecadal variability in the Atlantic Ocean. However, it still needs to be quantified to which extent the variations in the ocean drive variations in the atmosphere and over land. In particular, although a clear impact of the Tropics on the midlatitudes has been demonstrated, it is unclear if and how the extratropical atmosphere responds to midlatitudinal sea surface temperature anomalies. Although the mechanisms behind the decadal to multidecadal variability in the Atlantic sector are still controversial, there is some consensus that some of the longer-term multidecadal variability is driven by variations in the thermohaline circulation. The variations in the North Atlantic thermohaline circulation appear to be predictable one to two decades ahead, as shown by a number of perfect model predictability experiments. The next few decades will be dominated by these multidecadal variations, although the effects of anthropogenic climate change are likely to introduce trends. Some impact of the variations of the thermohaline circulation on the atmosphere has been demonstrated in some studies so that useful decadal predictions with economic benefit may be possible. [ABSTRACT FROM AUTHOR]

Land surface albedo, snow cover fraction (SCF), and snow depth (SD) from two versions of the ECHAM climate model are compared to available ground-based and remote-sensed climatologies. ECHAM5 accurately reproduces the annual cycle of SD and correctly captures the timing of the snowmelt. ECHAM4, in contrast, simulates an excessive Eurasian snow mass in spring due to a delayed snowmelt. Annual cycles of continental snow cover area (SCA) are captured fairly well in both ECHAM4 and ECHAM5. The negative SCA trend observed during the last two decades of the twentieth century is evident also in the ECHAM5 simulation but less pronounced. ECHAM5 captures the interannual variability of SCA reasonably well, which is in contrast with results that were reported earlier for second-phase Atmospheric Model Intercomparison Project (AMIP II) models. An error analysis revealed that, for studies on SCA, it is essential to test the data records for their homogeneity and trends. The second part of the paper compares simulated surface albedos with remote-sensed climatologies derived from PINKER and the Moderate Resolution Imaging Spectroradiometer (MODIS). ECHAM5 is in better agreement with observations in the Himalayan–Tibetan area than ECHAM4. In contrast, the positive surface albedo bias over boreal forests under snow conditions in ECHAM4 is even more pronounced in ECHAM5. This deficiency is mainly due to the neglect of the snow-masking effect of stems and branches after trees have lost their foliage. The analysis demonstrates that positive biases in the SCA are not necessarily related to positive albedo biases. Furthermore, an overestimation of the area-averaged SD is not always related to positive SCF anomalies since the relationship between SD and SCF is highly nonlinear. [ABSTRACT FROM AUTHOR]

This paper gives an update on the observed decadal variability of the earth radiation budget (ERB) using the latest altitude-corrected Earth Radiation Budget Experiment (ERBE)/Earth Radiation Budget Satellite (ERBS) Nonscanner Wide Field of View (WFOV) instrument Edition3 dataset. The effects of the altitude correction are to modify the original reported decadal changes in tropical mean (20°N to 20°S) longwave (LW), shortwave (SW), and net radiation between the 1980s and the 1990s from 3.1, -2.4, and -0.7 to 1.6, -3.0, and 1.4 W m-2, respectively. In addition, a small SW instrument drift over the 15-yr period was discovered during the validation of the WFOV Edition3 dataset. A correction was developed and applied to the Edition3 dataset at the data user level to produce the WFOV Edition3_Rev1 dataset. With this final correction, the ERBS Nonscanner-observed decadal changes in tropical mean LW, SW, and net radiation between the 1980s and the 1990s now stand at 0.7, -2.1, and 1.4 W m-2, respectively, which are similar to the observed decadal changes in the High-Resolution Infrared Radiometer Sounder (HIRS) Pathfinder OLR and the International Satellite Cloud Climatology Project (ISCCP) version FD record but disagree with the Advanced Very High Resolution Radiometer (AVHRR) Pathfinder ERB record. Furthermore, the observed interannual variability of near-global ERBS WFOV Edition3_Rev1 net radiation is found to be remarkably consistent with the latest ocean heat storage record for the overlapping time period of 1993 to 1999. Both datasets show variations of roughly 1.5 W m-2 in planetary net heat balance during the 1990s. [ABSTRACT FROM AUTHOR]

This paper introduces the three-dimensional Hamburg Model of the Neutral and Ionized Atmosphere (HAMMONIA), which treats atmospheric dynamics, radiation, and chemistry interactively for the height range from the earth’s surface to the thermosphere (approximately 250 km). It is based on the latest version of the ECHAM atmospheric general circulation model of the Max Planck Institute for Meteorology in Hamburg, Germany, which is extended to include important radiative and dynamical processes of the upper atmosphere and is coupled to a chemistry module containing 48 compounds. The model is applied to study the effects of natural and anthropogenic climate forcing on the atmosphere, represented, on the one hand, by the 11-yr solar cycle and, on the other hand, by a doubling of the present-day concentration of carbon dioxide. The numerical experiments are analyzed with the focus on the effects on temperature and chemical composition in the mesopause region. Results include a temperature response to the solar cycle by 2 to 10 K in the mesopause region with the largest values occurring slightly above the summer mesopause. Ozone in the secondary maximum increases by up to 20% for solar maximum conditions. Changes in winds are in general small. In the case of a doubling of carbon dioxide the simulation indicates a cooling of the atmosphere everywhere above the tropopause but by the smallest values around the mesopause. It is shown that the temperature response up to the mesopause is strongly influenced by changes in dynamics. During Northern Hemisphere summer, dynamical processes alone would lead to an almost global warming of up to 3 K in the uppermost mesosphere. [ABSTRACT FROM AUTHOR]

This paper describes the mean ocean circulation and the tropical variability simulated by the Max Planck Institute for Meteorology (MPI-M) coupled atmosphere–ocean general circulation model (AOGCM). Results are presented from a version of the coupled model that served as a prototype for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) simulations. The model does not require flux adjustment to maintain a stable climate. A control simulation with present-day greenhouse gases is analyzed, and the simulation of key oceanic features, such as sea surface temperatures (SSTs), large-scale circulation, meridional heat and freshwater transports, and sea ice are compared with observations. A parameterization that accounts for the effect of ocean currents on surface wind stress is implemented in the model. The largest impact of this parameterization is in the tropical Pacific, where the mean state is significantly improved: the strength of the trade winds and the associated equatorial upwelling weaken, and there is a reduction of the model’s equatorial cold SST bias by more than 1 K. Equatorial SST variability also becomes more realistic. The strength of the variability is reduced by about 30% in the eastern equatorial Pacific and the extension of SST variability into the warm pool is significantly reduced. The dominant El Niño–Southern Oscillation (ENSO) period shifts from 3 to 4 yr. Without the parameterization an unrealistically strong westward propagation of SST anomalies is simulated. The reasons for the changes in variability are linked to changes in both the mean state and to a reduction in atmospheric sensitivity to SST changes and oceanic sensitivity to wind anomalies. [ABSTRACT FROM AUTHOR]

The consistency between observed changes in Subantarctic Mode Water (SAMW) properties at 32°S in the Indian Ocean and model simulations is explored using the Third Hadley Centre Coupled Ocean–Atmosphere GCM (HadCM3). Hydrographic data collected in 2002 show that the water mass is warmer and saltier on isopycnals than in 1987, in contrast to the isopycnal freshening observed between 1962 and 1987. The response of HadCM3 under a range of forcing scenarios is explored and the observed freshening is only seen in experiments that include greenhouse gas forcing; however, there is no subsequent return to more saline conditions in 2002. The response of the model to greenhouse gas forcing is dominated by a persistent freshening trend, the simulated water mass variability agrees well with that suggested by the limited observations. Comparing model isopycnal changes from the forced experiments with a control run shows that the changes from the 1960s to 2002 are best explained by internal variability. This is in contrast to earlier work, which attributed the observed isopycnal freshening to anthropogenic forcing. Although the model shows that at present an anthropogenic climate change signal is not detectable in SAMW, the model water mass freshens on isopycnals during the twenty-first century under increased greenhouse gas forcing. This is consistent with recent heat content observations, which suggest that the salting is unlikely to persist. In HadCM3, this freshening is due to an increasing surface heat flux and Ekman heat and freshwater flux into the water mass formation region. This paper emphasizes the importance of higher-frequency observations of SAMW if detection and attribution statements are to be made. [ABSTRACT FROM AUTHOR]

Processes in the climate system that can either amplify or dampen the climate response to an external perturbation are referred to as climate feedbacks. Climate sensitivity estimates depend critically on radiative feedbacks associated with water vapor, lapse rate, clouds, snow, and sea ice, and global estimates of these feedbacks differ among general circulation models. By reviewing recent observational, numerical, and theoretical studies, this paper shows that there has been progress since the Third Assessment Report of the Intergovernmental Panel on Climate Change in (i) the understanding of the physical mechanisms involved in these feedbacks, (ii) the interpretation of intermodel differences in global estimates of these feedbacks, and (iii) the development of methodologies of evaluation of these feedbacks (or of some components) using observations. This suggests that continuing developments in climate feedback research will progressively help make it possible to constrain the GCMs’ range of climate feedbacks and climate sensitivity through an ensemble of diagnostics based on physical understanding and observations. [ABSTRACT FROM AUTHOR]

The Climate Forecast System (CFS), the fully coupled ocean–land–atmosphere dynamical seasonal prediction system, which became operational at NCEP in August 2004, is described and evaluated in this paper. The CFS provides important advances in operational seasonal prediction on a number of fronts. For the first time in the history of U.S. operational seasonal prediction, a dynamical modeling system has demonstrated a level of skill in forecasting U.S. surface temperature and precipitation that is comparable to the skill of the statistical methods used by the NCEP Climate Prediction Center (CPC). This represents a significant improvement over the previous dynamical modeling system used at NCEP. Furthermore, the skill provided by the CFS spatially and temporally complements the skill provided by the statistical tools. The availability of a dynamical modeling tool with demonstrated skill should result in overall improvement in the operational seasonal forecasts produced by CPC. The atmospheric component of the CFS is a lower-resolution version of the Global Forecast System (GFS) that was the operational global weather prediction model at NCEP during 2003. The ocean component is the GFDL Modular Ocean Model version 3 (MOM3). There are several important improvements inherent in the new CFS relative to the previous dynamical forecast system. These include (i) the atmosphere–ocean coupling spans almost all of the globe (as opposed to the tropical Pacific only); (ii) the CFS is a fully coupled modeling system with no flux correction (as opposed to the previous uncoupled “tier-2” system, which employed multiple bias and flux corrections); and (iii) a set of fully coupled retrospective forecasts covering a 24-yr period (1981–2004), with 15 forecasts per calendar month out to nine months into the future, have been produced with the CFS. These 24 years of fully coupled retrospective forecasts are of paramount importance to the proper calibration (bias correction) of subsequent operational seasonal forecasts. They provide a meaningful a priori estimate of model skill that is critical in determining the utility of the real-time dynamical forecast in the operational framework. The retrospective dataset also provides a wealth of information for researchers to study interactive atmosphere–land–ocean processes. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of aerosol forcing uncertainty on the robustness of estimates of the twentieth-century warming attributable to anthropogenic greenhouse gas emissions. Attribution analyses on three coupled climate models with very different sensitivities and aerosol forcing are carried out. The Third Hadley Centre Coupled Ocean–Atmosphere GCM (HadCM3), Parallel Climate Model (PCM), and GFDL R30 models all provide good simulations of twentieth-century global mean temperature changes when they include both anthropogenic and natural forcings. Such good agreement could result from a fortuitous cancellation of errors, for example, by balancing too much (or too little) greenhouse warming by too much (or too little) aerosol cooling. Despite a very large uncertainty for estimates of the possible range of sulfate aerosol forcing obtained from measurement campaigns, results show that the spatial and temporal nature of observed twentieth-century temperature change constrains the component of past warming attributable to anthropogenic greenhouse gases to be significantly greater (at the 5% level) than the observed warming over the twentieth century. The cooling effects of aerosols are detected in all three models. Both spatial and temporal aspects of observed temperature change are responsible for constraining the relative roles of greenhouse warming and sulfate cooling over the twentieth century. This is because there are distinctive temporal structures in differential warming rates between the hemispheres, between land and ocean, and between mid- and low latitudes. As a result, consistent estimates of warming attributable to greenhouse gas emissions are obtained from all three models, and predictions are relatively robust to the use of more or less sensitive models. The transient climate response following a 1% yr-1 increase in CO2 is estimated to lie between 2.2 and 4 K century-1 (5–95 percentiles). [ABSTRACT FROM AUTHOR]

The relative importance of the processes responsible for the annual cycle in the upper-ocean heat content in the Peru Current, in the southeastern tropical Pacific, was diagnosed from an oceanic analysis dataset. It was found that the annual cycle of heat content is forced mainly by insolation. However, the ocean dynamical processes play an important role in producing different regional budget characteristics. In a band 500 km from the coast of Peru, the annual heat content changes in this region are relatively large and can be approximated as sea surface temperature (SST) changes in a fixed-depth mixed layer. The annual cycle of the albedo associated with low-level clouds enhances the annual cycle in insolation, which explains the relatively strong annual cycle of heat content. These clouds, to a large extent, act as a feedback to SST, but a small additional forcing, which is proposed to be cold air advection in this paper, is needed to explain the fact that the maximum cloudiness leads the lowest SST by around a month. Ocean dynamics is important closer to the coast, where upwelling acts partly as damping of the heat content changes and forces it to peak earlier than farther offshore. In a band farther to the southwest, locally wind-forced thermocline motions, which become shallower (deeper) in the warm (cool) season, partially cancel the effect of net surface heat fluxes, whose annual cycle is comparable to that in the region previously mentioned, producing a relatively small annual cycle of heat content. The local forcing appears to be associated with the annual meridional displacements of the South Pacific anticyclone. The annual cycle in SST is also relatively small, which is probably due to the changes in the temperature of the water entrained into the mixed layer associated with the thermocline motions, but also to a mixed layer deeper than that closer to the coast. [ABSTRACT FROM AUTHOR]

In an earlier paper by Verbitsky and Saltzman, a vertically integrated, high-resolution, nonlinearly viscous, nonisothermal ice sheet model was presented to calculate the “present-day” equilibrium regime of the Antarctic ice sheet. Steady-state solutions for the ice topography and thermodynamics, represented by the extent of the areas of basal melting, were shown to be in good agreement with both observations and results obtained from other three-dimensional thermodynamical equations. The solution for the basal temperature field of the West Antarctic Siple Coast produced areas at the pressure melting point separated by strips of frozen-to-bed ice, the structure of which looks very similar to ice streams A–E. Since the possible response of the Siple Coast basal temperature pattern to global warming and to associated changes in the snowfall rate is not obvious, a special sensitivity study was conducted. Results of such a study suggest that increased precipitation rate and associated intensification of ice advection can effectively “shut down” West Antarctic ice streams. [ABSTRACT FROM AUTHOR]

A thorough analysis of the stability of the uncoupled Rooth interhemispheric three-box model of thermohaline circulation (THC) is presented. The model consists of a northern high-latitude box, a tropical box, and a southern high-latitude box, which correspond to the northern, tropical, and southern Atlantic Ocean, respectively. Restoring boundary conditions are adopted for the temperature variables, and flux boundary conditions are adopted for the salinity variables. This paper examines how the strength of THC changes when the system undergoes forcings that are analogous to those of global warming conditions by applying the equilibrium state perturbations to the moisture and heat fluxes into the three boxes. In each class of experiments, using suitably defined metrics, the authors determine the boundary dividing the set of forcing scenarios that lead the system to equilibria characterized by a THC pattern similar to the present one from those that drive the system to equilibria with a reversed THC. Fast increases in the moisture flux into the northern high-latitude box are more effective than slow increases in leading the THC to a breakdown, while the increases of moisture flux into the southern high-latitude box strongly inhibit the breakdown and can prevent it, as in the case of slow increases in the Northern Hemisphere. High rates of heat flux increase in the Northern Hemisphere destabilize the system more effectively than low ones; increases in the heat fluxes in the Southern Hemisphere tend to stabilize the system. [ABSTRACT FROM AUTHOR]

Based on results from climate model simulations, many researchers have suggested that because of global warming, the sea surface temperature (SST) will likely increase, which will then lead to an increase in the intensity of tropical cyclones (TCs). This paper reports results of a study of the relationship between SST and observed typhoon activity (which is used as a proxy for the intensity of TCs averaged over a season) over the western North Pacific (WNP) for the past 40 yr. The average typhoon activity over a season is found to have no significant relationship with SST in the WNP but increases when the SST over the equatorial eastern Pacific Ocean is above normal. The mean annual typhoon activity is generally higher (lower) during an El Niño (La Niña) year. Such interannual variations of typhoon activity appear to be largely constrained by the large-scale atmospheric factors that are closely related to the El Niño–Southern Oscillation (ENSO) phenomenon. These large-scale dynamic and thermodynamic factors include low-level relative vorticity, vertical wind shear, and moist static energy. Such results are shown to be physically consistent with one another and with those from previous studies on the interannual variations of TC activity. The results emphasize the danger of drawing conclusions about future TC intensity based on current climate model simulations that are not designed to make such predictions. [ABSTRACT FROM AUTHOR]

A 63-station radiosonde network has been used for many years to estimate temperature variations and trends at the surface and in the 850-300-, 300-100-, and 100-50-mb layers of climate zones, both hemispheres, and the globe, but with little regard for the quality of individual station data. In this paper, nine tropical radiosonde stations in this network are identified as anomalous based on unrepresentatively large standard-error-of-regression values for 300-100-mb trends for the period 1958-2000. In the Tropics the exclusion of the 9 anomalous stations from the 63-station network for 1958-2000 results in a warming of the 300-100-mb layer rather than a cooling, a doubling of the warming of the 850-300-mb layer to a value of 0.13 K decade[SUP-1], and a greater warming at 850-300-mb than at the surface. The global changes in trend are smaller, but include a change to the same warming of the surface and the 850-300-mb layer during 1958-2000. The effect of the station exclusions is much less for 1979-2000, suggesting that most of the data problems are before this time. Temperature trends based on the 63-station network are compared with the Microwave Sounding Unit (MSU) and other radiosonde trends, and agreement is better after the exclusion of the anomalous stations. There is consensus that in the Tropics the troposphere has warmed slightly more than the surface during 1958-2000, but that there has been a warming of the surface relative to the troposphere during 1979-2000. Globally, the warming of the surface and the troposphere are essentially the same during 1958-2000, but during 1979-2000 the surface warms more than the troposphere. During the latter period the radiosondes indicate considerably more low-stratospheric cooling in the Tropics than does the MSU. [ABSTRACT FROM AUTHOR]

Emergent constraints are quantities that are observable from current measurements and have skill predicting future climate. This study explores 19 previously proposed emergent constraints related to equilibrium climate sensitivity (ECS; the global-average equilibrium surface temperature response to CO2 doubling). Several constraints are shown to be closely related, emphasizing the importance for careful understanding of proposed constraints. A new method is presented for decomposing correlation between an emergent constraint and ECS into terms related to physical processes and geographical regions. Using this decomposition, one can determine whether the processes and regions explaining correlation with ECS correspond to the physical explanation offered for the constraint. Shortwave cloud feedback is generally found to be the dominant contributor to correlations with ECS because it is the largest source of intermodel spread in ECS. In all cases, correlation results from interaction between a variety of terms, reflecting the complex nature of ECS and the fact that feedback terms and forcing are themselves correlated with each other. For 4 of the 19 constraints, the originally proposed explanation for correlation is borne out by our analysis. These four constraints all predict relatively high climate sensitivity. The credibility of six other constraints is called into question owing to correlation with ECS coming mainly from unexpected sources and/or lack of robustness to changes in ensembles. Another six constraints lack a testable explanation and hence cannot be confirmed. The fact that this study casts doubt upon more constraints than it confirms highlights the need for caution when identifying emergent constraints from small ensembles. [ABSTRACT FROM AUTHOR]

We develop a statistical method to assess CMIP6 simulations of large-scale surface temperature change during the historical period (1850–2014), considering all time scales, allowing for the different unforced variability of each model and the observations, observational uncertainty, and variable ensemble size. The generality of this method, and the fact that it incorporates information about the unforced variability, makes it a useful model assessment tool. We apply this method to the historical simulations of the CMIP6 multimodel ensemble. We use three indices that measure different aspects of large-scale surface air temperature change: global mean, hemispheric gradient, and a recently developed index that captures the sea surface temperature (SST) pattern in the tropics (SST#; see Fueglistaler and Silvers). We use the following observations: HadCRUT5 for the first two indices, and AMIPII and ERSSTv5 for SST#. In each case, we test the hypothesis that the model's forced response is compatible with the observations, accounting for unforced variability in both models and observations as well as measurement uncertainty. This hypothesis is accepted more often (75% of the models) for the hemispheric gradient than for the global mean, for which half of the models fail the test. The tropical SST pattern is poorly simulated in all models. Given that the tropical SST pattern can strongly modulate the relationship between energy imbalance and global-mean surface temperature anomalies on annual to decadal time scales (short-term feedback parameter), we suggest this should be a focus area for future improvements due to its potential implications for the global-mean temperature evolution in decadal time scales. [ABSTRACT FROM AUTHOR]

Volcanic aerosol forcing has previously been found to cause a weak global mean temperature response, as compared with CO2 radiative forcing of equal magnitude: its efficacy is supposedly low, but for reasons that are not fully understood. To investigate this, we perform idealized, time-invariant stratospheric sulfate aerosol forcing simulations with the MPI-ESM-1.2 and compare them with 0.5 × CO2 and 2 × CO2 runs. While the early decades of the aerosol forcing simulations are characterized by strong negative feedback (i.e., low efficacy), the feedback weakens on the decadal to centennial time scale. Although this effect is qualitatively also found in CO2-warming simulations, it is more pronounced for stratospheric aerosol forcing. The strong early and weak late cooling feedbacks compensate, leading to an equilibrium efficacy of approximately 1 in all simulations. The 0.5 × CO2 cooling simulations also exhibit strong feedback changes over time, albeit less than in the idealized aerosol forcing simulations. This suggests that the underlying cause for the feedback change is not exclusively specific to aerosol forcing. One critical region for the feedback differences between simulations with negative and positive radiative forcing is the tropical Indo-Pacific warm-pool region (30°S–30°N, 50°E–160°W). In the first decades of cooling, the temperature change in this region is stronger than the global average, whereas it is stronger outside it for 2 × CO2 warming. In cooling scenarios, this leads to an enhanced activation of the warm-pool region's strongly negative lapse-rate feedback. Significance Statement: Large volcanic eruptions can enhance the scattering aerosol layer in the stratosphere, which leads to a global cooling for a few years. Surprisingly, Earth has been found to cool less from radiative flux perturbations from stratospheric aerosol forcing, in comparison with how much it warms as a result of increases in CO2 concentration. We find that specific surface temperature change patterns after volcanic eruptions cause this effect. The temperature change in the tropical Indian and western Pacific Ocean determines how much global temperature change is needed to regain radiative equilibrium. Our findings contribute to understanding the climate response to volcanic eruptions and are relevant for understanding the mechanisms of climate change due to changes in CO2 concentration. [ABSTRACT FROM AUTHOR]

There are heated debates on the existence of the global warming slowdown during the early twenty-first century. Although efforts have been made to clarify or reconcile the controversy over this issue, it is not explicitly addressed, restricting the understanding of global temperature change particularly under the background of increasing greenhouse gas concentrations. Here, using extensive temperature datasets, we comprehensively reexamine the existence of the slowdown under all existing definitions during all decadal-scale periods spanning 1990–2017. Results show that the short-term linear trend–dependent definitions of slowdown make its identification severely suffer from the period selection bias, which largely explains the controversy over its existence. Also, the controversy is further aggravated by the significant impacts of the differences between various datasets on the recent temperature trend and the different baselines for measuring slowdown prescribed by various definitions. However, when the focus is shifted from specific periods to the probability of slowdown events, we find the probability is significantly higher in the 2000s than in the 1990s, regardless of which definition and dataset are adopted. This supports a slowdown during the early twenty-first century relative to the warming surge in the late twentieth century, despite higher greenhouse gas concentrations. Furthermore, we demonstrate that this decadal-scale slowdown is not incompatible with the centennial-scale anthropogenic warming trend, which has been accelerating since 1850 and never pauses or slows. This work partly reconciles the controversy over the existence of the warming slowdown and the discrepancy between the slowdown and anthropogenic warming. [ABSTRACT FROM AUTHOR]

A key goal of the 2015 Paris Climate Agreement is to keep global mean temperature change at 2°C and if possible under 1.5°C by the end of the century. To investigate the likelihood of achieving this target, we calculate the year of exceedance of a given global warming threshold (GWT) temperature across 32 CMIP6 models for Shared Socioeconomic Pathway (SSP) and radiative forcing combinations included in the Tier 1 ScenarioMIP simulations. Threshold exceedance year calculations reveal that a majority of CMIP6 models project warming beyond 2°C by the end of the century under every scenario or pathway apart from the lowest emission scenarios considered, SSP1–1.9 and SSP1–2.6, which is largely a function of the ScenarioMIP experiment design. The U.K. Earth System Model (UKESM1) ScenarioMIP projections are analyzed in detail to assess the regional and seasonal variations in climate at different warming levels. The warming signal emerging by midcentury is identified as significant and distinct from internal climate variability in all scenarios considered and includes warming summers in the Mediterranean, drying in the Amazon, and heavier Indian monsoons. Arctic sea ice depletion results in prominent amplification of warming and tropical warming patterns emerge that are distinct from interannual variability. Climate changes projected for a 2°C warmer world are in almost all cases exacerbated with further global warming (e.g., to a 4°C warmer world). Significance Statement: In this study, we look into changes occurring in climate due to global warming by analyzing data from the latest global climate models to see when the Earth will warm by 2° or 4°C, compared to preindustrial temperatures. We then use the UKESM1 climate model to identify regions on Earth where significant climate change is simulated in the future and discuss possible reasons for these changes. Simulations from this model also show that regions such as the Mediterranean, Amazon forests, and tropical countries are likely to see significant changes in climate impacting human lives. Future work to study the regional changes in greater detail will help us improve climate policies to protect society. [ABSTRACT FROM AUTHOR]

A comparison of three global reanalyses is conducted based on probability density functions of daily maximum and minimum temperature at 2-m and 1000-hPa levels. The three reanalyses compare very favorably in both maximum and minimum temperatures at 1000 hPa, in both the mean and the 99.7th and 0.3rd percentiles of both quantities in most regions. At 2 m, there are large and widespread differences in the mean and 99.7th percentiles in maximum temperature between the three reanalyses over land commonly exceeding ±5°C and regionally exceeding ±10°C. The 2-m minimum temperatures compare unfavorably between the three reanalyses over virtually all continental surfaces with differences exceeding ±10°C over widespread areas. It is concluded that the three reanalyses are generally interchangeable in 1000-hPa temperatures. The three reanalyses of 2-m temperatures are very different owing to the methods used to diagnose these quantities. At this time, the probability distribution functions of the 2-m temperatures from the three reanalyses are sufficiently different that either the 2-m air temperatures should not be used or all three products should be used independently in any application and the differences highlighted. [ABSTRACT FROM AUTHOR]

A simple technique is proposed for calculating global mean climate forcing from transient integrations of coupled atmosphere–ocean general circulation models (AOGCMs). This “climate forcing” differs from the conventionally defined radiative forcing as it includes semidirect effects that account for certain short time scale responses in the troposphere. First, a climate feedback term is calculated from reported values of 2 × CO2 radiative forcing and surface temperature time series from 70-yr simulations by 20 AOGCMs. In these simulations carbon dioxide is increased by 1% yr-1. The derived climate feedback agrees well with values that are diagnosed from equilibrium climate change experiments of slab-ocean versions of the same models. These climate feedback terms are associated with the fast, quasi-linear response of lapse rate, clouds, water vapor, and albedo to global surface temperature changes. The importance of the feedbacks is gauged by their impact on the radiative fluxes at the top of the atmosphere. Partial compensation is found between longwave and shortwave feedback terms that lessens the intermodel differences in the equilibrium climate sensitivity. There is also some indication that the AOGCMs overestimate the strength of the positive longwave feedback. These feedback terms are then used to infer the shortwave and longwave time series of climate forcing in twentieth- and twenty-first-century simulations in the AOGCMs. The technique is validated using conventionally calculated forcing time series from four AOGCMs. In these AOGCMs the shortwave and longwave climate forcings that are diagnosed agree with the conventional forcing time series within ∼10%. The shortwave forcing time series exhibit order of magnitude variations between the AOGCMs, differences likely related to how both natural forcings and/or anthropogenic aerosol effects are included. There are also factor of 2 differences in the longwave climate forcing time series, which may indicate problems with the modeling of well-mixed greenhouse gas changes. The simple diagnoses presented provides an important and useful first step for understanding differences in AOGCM integrations, indicating that some of the differences in model projections can be attributed to different prescribed climate forcing, even for so-called standard climate change scenarios. [ABSTRACT FROM AUTHOR]

The climate response to idealized changes in the atmospheric CO2 concentration by the new GFDL climate model (CM2) is documented. This new model is very different from earlier GFDL models in its parameterizations of subgrid-scale physical processes, numerical algorithms, and resolution. The model was constructed to be useful for both seasonal-to-interannual predictions and climate change research. Unlike previous versions of the global coupled GFDL climate models, CM2 does not use flux adjustments to maintain a stable control climate. Results from two model versions, Climate Model versions 2.0 (CM2.0) and 2.1 (CM2.1), are presented. Two atmosphere–mixed layer ocean or slab models, Slab Model versions 2.0 (SM2.0) and 2.1 (SM2.1), are constructed corresponding to CM2.0 and CM2.1. Using the SM2 models to estimate the climate sensitivity, it is found that the equilibrium globally averaged surface air temperature increases 2.9 (SM2.0) and 3.4 K (SM2.1) for a doubling of the atmospheric CO2 concentration. When forced by a 1% per year CO2 increase, the surface air temperature difference around the time of CO2 doubling [transient climate response (TCR)] is about 1.6 K for both coupled model versions (CM2.0 and CM2.1). The simulated warming is near the median of the responses documented for the climate models used in the 2001 Intergovernmental Panel on Climate Change (IPCC) Working Group I Third Assessment Report (TAR). The thermohaline circulation (THC) weakened in response to increasing atmospheric CO2. By the time of CO2 doubling, the weakening in CM2.1 is larger than that found in CM2.0: 7 and 4 Sv (1 Sv ≡ 106 m3 s-1), respectively. However, the THC in the control integration of CM2.1 is stronger than in CM2.0, so that the percentage change in the THC between the two versions is more similar. The average THC change for the models presented in the TAR is about 3 or 4 Sv; however, the range across the model results is very large, varying from a slight increase (+2 Sv) to a large decrease (-10 Sv). [ABSTRACT FROM AUTHOR]

Global warming projections show an anomalous temperature increase both at the Arctic surface and at lower latitudes in the upper troposphere. The Arctic amplification decreases the meridional temperature gradient, and simultaneously decreases static stability. These changes in the meridional temperature gradient and in the static stability have opposing effects on baroclinicity. The temperature increase at the upper tropospheric lower latitudes tends to increase the meridional temperature gradient and simultaneously increase static stability, which have opposing effects on baroclinicity as well. In this study, a dry idealized general circulation model with a modified Newtonian cooling scheme, which allows any chosen zonally symmetric temperature distribution to be simulated, is used to study the effect of Arctic amplification and lower-latitude upper-level warming on eddy activity. Due to the interplay between the static stability and meridional temperature gradient on atmospheric baroclinicity changes, and their opposing effect on atmospheric baroclinicity, it is found that both the Arctic amplification and lower-latitude upper-level warming could potentially lead to both decreases and increases in eddy activity, depending on the exact prescribed temperature modifications. Therefore, to understand the effect of global warming–like temperature trends on eddy activity, the zonally symmetric global warming temperature projections from state-of-the-art models are simulated. It is found that the eddy kinetic energy changes are dominated by the lower-latitude upper-level warming, which tends to weaken the eddy kinetic energy due to increased static stability. On the other hand, the eddy heat flux changes are dominated by the Arctic amplification, which tends to weaken the eddy heat flux at the lower levels. [ABSTRACT FROM AUTHOR]

Idealized experiments performed with the Community Atmospheric Model 5.3 indicate that the width and strength of the Hadley circulation (HC) are sensitive to the location of sea surface temperature (SST) increases. The HC edge shifts poleward in response to SST increases over the subtropical regions near and on the equatorward flank of the HC edge, and shifts equatorward in response to warming over the tropical area except for the western Pacific Ocean and Indian Ocean. The HC is strengthened in response to SST increases over the intertropical convergence zone (ITCZ) and is weakened in response to SST increases over the subsidence branch of the HC in the subtropics. Tropical SST increases off the ITCZ tend to weaken the HC in the corresponding hemisphere and strengthen the HC in the opposite hemisphere. These results could be used to explain the simulated HC changes induced by recent SST variations, and it is estimated that more than half of the SST-induced HC widening in 1980-2014 is caused by changes in the spatial pattern of SST. [ABSTRACT FROM AUTHOR]

Previous studies have outlined benefits of using multiple model platforms to make seasonal climate predictions. Here, reforecasts from five models included in the North American Multimodel Ensemble (NMME) project are utilized to determine skill in predicting Arctic sea ice extent (SIE) during 1982–2010. Overall, relative to the individual models, the multimodel average results in generally smaller biases and better correlations for predictions of total SIE and year-to-year (Y2Y), linearly, and quadratically detrended variability. Also notable is the increase in error for NMME predictions of total September SIE during the mid-1990s through 2000s. After 2000, observed September SIE is characterized by more significant negative trends and increased Y2Y variance, which suggests that recent sea ice loss is resulting in larger prediction errors. While this tendency is concerning, due to the possibility of models not accurately representing the changing trends in sea ice, the multimodel approach still shows promise in providing more skillful predictions of Arctic SIE over any individual model. [ABSTRACT FROM AUTHOR]

We investigated the scaling properties of two datasets of the observed near-surface global temperature data anomalies: the Met Office and the University of East Anglia Climatic Research Unit HadCRUT4 dataset and the NASA GISS Land–Ocean Temperature Index (LOTI) dataset. We used detrended fluctuation analysis of second-order (DFA2) and wavelet-based spectral (WTS) analysis to investigate and quantify the global pattern of scaling in two datasets and to better understand cyclic behavior as a possible underlying cause of the observed forms of scaling. We found that, excluding polar and parts of subpolar regions because of their substantial data inhomogeneity, the global temperature pattern is long-range autocorrelated. Our results show a remarkable heterogeneity in the long-range dynamics of the global temperature anomalies in both datasets. This finding is in agreement with previous studies. We additionally studied the DFA2 and the WTS behavior of the local station temperature anomalies and satellite-based temperature estimates and found that the observed diversity of global scaling can be attributed both to the intrinsic variability of data and to the methodology-induced variations that arise from deriving the global temperature gridded data from the original local sources. Finally, we found differences in global temperature scaling patterns of the two datasets and showed instances where spurious scaling is introduced in the global datasets through a spatial infilling procedure or the optimization of integrated satellite records. [ABSTRACT FROM AUTHOR]