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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]

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]

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]

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]

The variation of near-surface air temperature anomalies in Africa between 1979 and 2010 is investigated primarily using Microwave Sounding Unit (MSU) total lower-tropospheric temperature data from the Remote Sensing Systems (RSS) and the University of Alabama in Huntsville (UAH) datasets. Significant increasing temperature trends were found in each of the following regions examined: all of Africa, Northern Hemisphere Africa, Southern Hemisphere Africa, tropical Africa, and subtropical Africa. Considering the months June--August, regions in both North and South Africa saw significantly warmer temperatures in the most recent period 1995--2010 than in the period 1979--94. However, for the months December--February, the significant warming was concentrated in the north of Africa. When the two most recent decades are compared with the period 1979--90, warming is observed over these same regions and is concentrated in the most recent decade, from 2001 to 2010. The results presented here indicate that the climate change over Africa is likely not predominantly a result of variations in the El Niñño--Southern Oscillation (a teleconnection that has been previously shown to affect climate in some parts of Africa). Instead the climate changes likely occur owing to other natural variability of the climate and/or may be a result of human activity. However, even without ascertaining the specific causes, the most important finding in this work is to demonstrate that a significant rise in African temperatures occurred between 1979 and 2010. [ABSTRACT FROM AUTHOR]

The role of atmospheric circulations, yielding extremely cold summer and wet winter seasons, in the development of perennial snow cover over the inception region of the Laurentide Ice Sheet is investigated using the Community Land Model, version 3 (CLM3) with bias-corrected 40-yr ECMWF Re-Analysis (ERA-40) idealized atmospheric forcing. Potential contribution of changes in frequency of these extremes under contemporary and Eemian (116 kyr BP) conditions is also examined by adjusting the atmospheric forcing. The results confirm that colder atmospheric temperatures during the melt season are more important than extreme amounts of winter snowfall. Increases in frequency of extremely cold and persistent summer air temperatures in the contemporary climate do not produce perennial snow. An additional cooling of 4°C together with adjustments for Eemian incident radiation is required for perennial snow to start growing around Hudson Bay. Deeper snow is found over the Labrador–Ungava area, close to the North Atlantic Ocean moisture sources, compared to the Keewatin area. These areas are in agreement with the locations of the Laurentide Ice Sheet domes found from free gravity analysis. Starting from the warm present-day atmosphere a 25% decrease in summer insolation is required for CLM3 to develop perennial snow. This suggests that cooling resulting from modest decreases in local insolation in response to Milankovitch radiation forcing was insufficient for inception at 116 kyr BP. Remote cooling or local feedbacks that amplify the impact of the modest insolation reductions are required. A large-scale atmospheric cooling appears to have played a decisive role in inception. [ABSTRACT FROM AUTHOR]

Simple equations are developed to express regional climate changes for the twenty-first century and associated uncertainty in terms of the global temperature change (GTC) without a dependence on the underlying emission pathways. The equations are applied to regional temperature and precipitation changes over different regions of the world, and relevant parameters are calculated using the latest multimodel ensemble of global climate change simulations. Examples are also shown of how to use the equations to develop probability density functions (PDFs) of regional climate change based on PDFs of GTC. The main advantage of these equations is that they can be used to estimate regional changes from GTC obtained either from simple and intermediate complexity models or from target CO2 stabilization concentrations. [ABSTRACT FROM AUTHOR]

Dynamical effects of convective momentum transports (CMT) on global climate simulations are investigated using the NCAR Community Climate Model version 3 (CCM3). To isolate the dynamical effects of the CMT, an experimental setup is proposed in which all physical parameterizations except for the deep convection scheme are replaced with idealized forcing. The CMT scheme is incorporated into the convection scheme to calculate the CMT forcing, which is used to force the momentum equations, while convective temperature and moisture tendencies are not passed into the model calculations in order to remove the physical feedback between convective heating and wind fields. Excluding the response of complex physical processes, the model with the experimental setup contains a complete dynamical core and the CMT forcing. Comparison between two sets of 5-yr simulations using this idealized general circulation model (GCM) shows that the Hadley circulation is enhanced when the CMT forcing is included, in agreement with previous studies that used full GCMs. It suggests that dynamical processes make significant contributions to the total response of circulation to CMT forcing in the full GCMs. The momentum budget shows that the Coriolis force, boundary layer friction, and nonlinear interactions of velocity fields affect the responses of zonal wind field, and the adjustment of circulation follows an approximate geostrophic balance. The adjustment mechanism of meridional circulation in response to ageostrophic CMT forcing is examined. It is found that the strengthening of the Hadley circulation is an indirect response of the meridional wind to the zonal CMT forcing through the Coriolis effect, which is required for maintaining near-geostrophic balance. [ABSTRACT FROM AUTHOR]

An examination of five temperature and five precipitation extreme indicators reveals an increase in both temperature and precipitation extremes over the 1926–2000 period in the northeast United States, with most of this increase occurring over the past four decades. Empirical orthogonal function (EOF) analysis of winter frost days (FD) and warm nights (TN90) and also winter consecutive dry days (CDD) and very wet days (R95T) over the 1950–2000 period reveals that some of the variability associated with changes in these extremes may be explained by variations in the Arctic Oscillation (AO), El Niño–Southern Oscillation (ENSO), and Pacific–North American (PNA) pattern. The most prominent feature of these results was the high correlation between the leading EOF of frost days and warm nights and the AO. Winter composites of temperature and precipitation extreme indicators were examined for different phases of the AO and ENSO during the 1926–2000 period. Overall, the AO is a better predictor of winter warm nights, while the ENSO is a better predictor of consecutive dry days in the northeast United States. [ABSTRACT FROM AUTHOR]

In this study the direct and diffuse solar radiation changes are estimated, and they contribute to the understanding of the observed global dimming and the more recent global brightening during the industrial era. Using a multistream radiative transfer model, the authors calculate the impact of changes in ozone, NO2, water vapor, CH4, CO2, direct and indirect aerosol effects, contrails, and aviation-induced cirrus on solar irradiances at the surface. The results show that dimming is most pronounced in central Africa, Southeast Asia, Europe, and northeast America. Human activity during the industrial era is calculated and accounts for a decrease in direct solar radiation at the surface of up to 30 W m-2 (30%–40%) and an increase in diffuse solar radiation of up to 20 W m-2. The physical processes that lead to the changes in direct and diffuse solar radiation are found to be remarkably different and the authors explain which mechanisms are responsible for the observed changes. [ABSTRACT FROM AUTHOR]

The atmospheric response to a North Pacific subsurface oceanic temperature anomaly is studied in a coupled ocean–atmosphere general circulation model using a combined dynamical and statistical approach, with the focus on the evolution at seasonal and longer time scales. The atmospheric response is first assessed dynamically with an ensemble coupled experiment. The atmospheric response is found to exhibit a distinct seasonal evolution and a significant long-term response. The oceanic temperature anomaly reemerges each winter to force the atmosphere through an upward heat flux, forcing a clear seasonal atmospheric response locally over the Aleutian low and downstream over the North America/North Atlantic Ocean and the Arctic regions. The atmospheric response is dominated by the early winter response with a warm SST-equivalent barotropic ridge and a wave train downstream. Starting in later winter, the atmospheric response weakens significantly and remains weak throughout the summer. The seasonal response of the atmosphere is then assessed statistically from the control simulation. It is found that the major features of the seasonal response, especially the strong warm SST–ridge response in early winter, are crudely consistent between the dynamical and statistical assessments. The statistical assessment is finally applied to the observation, which also suggests a strong seasonal atmospheric response locally over the North Pacific dominated by a warm SST–ridge response in early winter. One important conclusion is that the atmospheric response becomes more significant at annual and longer time scales, with the signal/noise ratio increasing up to 4 times from the monthly to the 4-yr mean response. This increased signal/noise ratio is caused by a much faster reduction of the atmospheric internal variability toward longer time scales than that of the response signal. The slow decrease of the response signal is due to the long persistence associated with the subsurface ocean. This suggests that the subsurface extratropical oceanic variability could have a much stronger impact on the extratropical atmosphere (and climate variability) at interannual–interdecadal time scales than at monthly–seasonal time scales. [ABSTRACT FROM AUTHOR]

It is argued that simulations of the twentieth century performed with coupled global climate models with specified historical changes in external radiative forcing can be interpreted as climate hindcasts. A simple Bayesian method for postprocessing such simulations is described, which produces probabilistic hindcasts of interdecadal temperature changes on large spatial scales. Hindcasts produced for the last two decades of the twentieth century are shown to be skillful. The suggestion that skillful decadal forecasts can be produced on large regional scales by exploiting the response to anthropogenic forcing provides additional evidence that anthropogenic change in the composition of the atmosphere has influenced the climate. In the absence of large negative volcanic forcing on the climate system (which cannot presently be forecast), it is predicted that the global mean temperature for the decade 2000–09 will lie above the 1970–99 normal with a probability of 0.94. The global mean temperature anomaly for this decade relative to 1970–99 is predicted to be 0.35°C with a 5%–95% confidence range of 0.21°–0.48°C. [ABSTRACT FROM AUTHOR]

The ability of coupled GCMs to correctly simulate the climatology and a prominent mode of variability of the West African monsoon is evaluated, and the results are used to make informed decisions about which models may be producing more reliable projections of future climate in this region. The integrations were made available by the Program for Climate Model Diagnosis and Intercomparison for the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. The evaluation emphasizes the circulation characteristics that support the precipitation climatology, and the physical processes of a “rainfall dipole” variability mode that is often associated with dry conditions in the Sahel when SSTs in the Gulf of Guinea are anomalously warm. Based on the quality of their twentieth-century simulations over West Africa in summer, three GCMs are chosen for analysis of the twenty-first century integrations under various assumptions about future greenhouse gas increases. Each of these models behaves differently in the twenty-first-century simulations. One model simulates severe drying across the Sahel in the later part of the twenty-first century, while another projects quite wet conditions throughout the twenty-first century. In the third model, warming in the Gulf of Guinea leads to more modest drying in the Sahel due to a doubling of the number of anomalously dry years by the end of the century. An evaluation of the physical processes that cause these climate changes, in the context of the understanding about how the system works in the twentieth century, suggests that the third model provides the most reasonable projection of the twenty-first-century climate. [ABSTRACT FROM AUTHOR]

Climate models used to produce global warming scenarios exhibit widely diverging responses of the thermohaline circulation (THC). To investigate the mechanisms responsible for this variability, a regional Atlantic Ocean model driven with forcing diagnosed from two coupled greenhouse gas simulations has been employed. One of the coupled models (MPI) shows an almost constant THC, the other (GFDL) shows a declining THC in the twenty-first century. The THC evolution in the regional model corresponds rather closely to that of the respective coupled simulation, that is, it remains constant when driven with the forcing from the MPI model, and declines when driven with the GFDL forcing. These findings indicate that a detailed representation of ocean processes in the region covered by the Atlantic model may not be critical for the simulation of the overall THC changes in a global warming scenario, and specifically that the coupled model’s rather coarse representation of water mass formation processes in the subpolar North Atlantic is unlikely to be the primary cause for the large differences in the THC evolution. Sensitivity experiments have confirmed that a main parameter governing the THC response to global warming is the density of the intermediate waters in the Greenland–Iceland–Norwegian Seas, which in turn influences the density of the North Atlantic Deep Water, whereas changes in the air–sea heat and freshwater fluxes over the subpolar North Atlantic are only of moderate importance, and mainly influence the interannual–decadal variability of THC. Finally, as a consequence of changing surface fluxes, the Labrador Sea convection ceases by about 2030 under both forcings (i.e., even in a situation where the overall THC is stable) indicating that the eventual breakdown of the convection is likely but need not coincide with substantial THC changes. [ABSTRACT FROM AUTHOR]

Climate model simulations of the latter part of the twentieth century indicate a warming of the troposphere that is equal to or larger than the warming at the surface, while satellite observations from the Microwave Sounding Unit (MSU) indicate little warming of the troposphere relative to surface observations. Recently, Fu et al. proposed a new approach to retrieving free tropospheric temperature trends from MSU data that better accounts for stratospheric cooling, which contaminates the tropospheric signal and leads to a smaller trend in tropospheric warming. In this study, climate model simulations are used as a self-consistent dataset to test these retrieval algorithms. The two methods of retrieving tropospheric temperature trends are applied to three climate model simulations of the twentieth century. The Fu et al. algorithm is found to be in very good agreement with the model-simulated tropospheric warming, indicating that it accurately accounts for cooling from the lower stratosphere. [ABSTRACT FROM AUTHOR]

A number of statistical downscaling models are applied to the Canadian Climate Centre general circulation model (CCCM) outputs to provide climate change estimates for local daily surface temperature at a network of 39 stations in central and western Europe. Several different linear downscaling methods (multiple linear regression of gridded values, multiple linear regression of principal components, canonical correlation analysis) are applied to a number of sets of predictors (500- and 1000-hPa heights, 850-hPa temperature, 1000–500-hPa thickness, and their combinations) defined on a grid over the Euro–Atlantic domain. The temperature change estimates are shown to vary widely among the methods as well as among the predictors, both in their areal mean, spatial pattern, and elevation dependence in the Alpine region. The most counterintuitive result is the dependence of the estimated warming on the number of principal components (PCs) of predictors: the larger the number of PCs, the higher the warming. The mechanisms of these dependencies are identified and discussed. In particular, the necessity to include among predictors the variables able to describe the radiation-induced changes, not only the circulation-induced ones, is underlined. For this reason, the use of sea level pressure or 1000-hPa heights as the only predictor in statistical downscaling leads to unrealistically low temperature change estimates. The main problem in applications of statistical downscaling to estimation of climate change appears to be that downscaling models are fitted predominantly to a short-term variability, but the focus in studies of future climate change is on variations on long-term (decadal) time scales. [ABSTRACT FROM AUTHOR]