The influence of differing rates of increase of the atmospheric CO 2 concentration on the climatic response is investigated using a coupled ocean–atmosphere model. Five transient integrations are performed each using a different constant exponential rate of CO 2 increase ranging from 4 % yr �1 to 0.25 % yr �1. By the time of CO 2 doubling, the surface air temperature response in all the transient integrations is locally more than 50 % and globally more than 35 % of the equilibrium response. The land–sea contrast in the warming, which is evident in the equilibrium results, is larger in all the transient experiments. The land–sea difference in the response increases with the rate of increase in atmospheric CO 2 concentration. The thermohaline circulation (THC) weakens in response to increasing atmospheric CO 2 concentration in all the transient integrations, confirming earlier work. The results also indicate that the slower the rate of increase, the larger the weakening of the THC by the time of doubling. Two of the transient experiments are continued beyond the time of CO 2 doubling with the CO 2 concentration maintained at that level. The amount of weakening of the THC after the CO 2 stops increasing is smaller in the experiment with the slower rate of CO 2 increase, indicating that the coupled system has more time to adjust to the forcing when the rate of CO 2 increase is slower. After a period of slow overturning, the THC gradually recovers and eventually regains the intensity found in the control integration, so that the equilibrium

Estimating the mean and the covariance matrix of an incomplete dataset and filling in missing values with imputed values is generally a nonlinear problem, which must be solved iteratively. The expectation maximization (EM) algorithm for Gaussian data, an iterative method both for the estimation of mean values and covariance matrices from incomplete datasets and for the imputation of missing values, is taken as the point of departure for the development of a regularized EM algorithm. In contrast to the conventional EM algorithm, the regularized EM algorithm is applicable to sets of climate data, in which the number of variables typically exceeds the sample size. The regularized EM algorithm is based on iterated analyses of linear regressions of variables with missing values on variables with available values, with regression coefficients estimated by ridge regression, a regularized regression method in which a continuous regularization parameter controls the filtering of the noise in the data. The regularization parameter is determined by generalized cross-validation, such as to minimize, approximately, the expected mean squared error of the imputed values. The regularized EM algorithm can estimate, and exploit for the imputation of missing values, both synchronic and diachronic covariance matrices, which may contain information on spatial covariability, stationary temporal covariability, or cyclostationary temporal covariability. A test of the regularized EM algorithm with simulated surface temperature data demonstrates that the algorithm is applicable to typical sets of climate data and that it leads to more accurate estimates of the missing values than a conventional non-iterative imputation technique.

In this report, global coupled ocean–atmosphere models are used to explore possible mechanisms for observed decadal variability and trends in Pacific Ocean SSTs over the past century. The leading mode of internally generated decadal (�7 yr) variability in the model resembles the observed decadal variability in terms of pattern and amplitude. In the model, the pattern and time evolution of tropical winds and oceanic heat content are similar for the decadal and ENSO timescales, suggesting that the decadal variability has a similar ‘‘delayed oscillator’ ’ mechanism to that on the ENSO timescale. The westward phase propagation of the heat content anomalies, however, is slower and centered slightly farther from the equator (�12 � vs 9�N) for the decadal variability. Cool SST anomalies in the midlatitude North Pacific during the warm tropical phase of the decadal variability are induced in the model largely by oceanic advection anomalies. An index of observed SST over a broad triangular region of the tropical and subtropical Pacific indicates a warming rate of �0.41�C (100 yr) �1 since 1900, �1.2�C (100 yr) �1 since 1949, and �2.9�C (100 yr) �1 since 1971. All three warming trends are highly unusual in terms of their duration, with occurrence rates of less than 0.5 % in a 2000-yr simulation of internal climate variability using a low-resolution model. The most unusual is the trend since 1900 (96-yr duration): the longest simulated duration of a trend of this magnitude is 85 yr. This

To understand the role of water vapor feedback in unperturbed surface temperature variability, a version of the Geophysical Fluid Dynamics Laboratory coupled ocean–atmosphere model is integrated for 1000 yr in two configurations, one with water vapor feedback and one without. For all spatial scales, the model with water vapor feedback has more low-frequency (timescale � 2 yr) surface temperature variability than the one without. Thus water vapor feedback is positive in the context of the model’s unperturbed variability. In addition, water vapor feedback is more effective the longer the timescale of the surface temperature anomaly and the larger its spatial scale. To understand the role of water vapor feedback in global warming, two 500-yr integrations were also performed in which CO2 was doubled in both model configurations. The final surface global warming in the model with water vapor feedback is 3.38�C, while in the one without it is only 1.05�C. However, the model’s water vapor feedback has a larger impact on surface warming in response to a doubling of CO 2 than it does on internally generated, low-frequency, global-mean surface temperature anomalies. Water vapor feedback’s strength therefore depends on the type of temperature anomaly it affects. The authors found that the degree to which a surface temperature anomaly penetrates into the troposphere is a critical factor in determining the effectiveness of its

This study compares the variability of surface air temperature in three long coupled ocean–atmosphere general circulation model integrations. It is shown that the annual mean climatology of the surface air temperatures (SAT) in all three models is realistic and the linear trends over the 1000-yr integrations are small over most areas of the globe. Second, although there are notable differences among the models, the models ’ SAT variability is fairly realistic on annual to decadal timescales, both in terms of the geographical distribution and of the global mean values. A notable exception is the poor simulation of observed tropical Pacific variability. In the HadCM2 model, the tropical variability is overestimated, while in the GFDL and HAM3L models, it is underestimated. Also, the ENSO-related spectral peak in the globally averaged observed SAT differs from that in any of the models. The relatively low resolution required to integrate models for long time periods inhibits the successful simulation of the variability in this region. On timescales longer than a few decades, the largest variance in the models is generally located near sea ice margins in high latitudes, which are also regions of deep oceanic convection and variability related to variations in the thermohaline circulation. However, the exact geographical location of these maxima varies from model to model. The preferred patterns of interdecadal variability that are common to all three coupled models can be isolated by computing empirical orthogonal functions (EOFs) of

Many climate models predict that anthropogenic greenhouse gas emissions may cause a threshold response of the North Atlantic meridional overturning circulation (MOC). These model predictions are,

The process of baroclinic equilibration in the atmosphere is investigated using a high-resolution two-layer quasigeostrophic model in a �-plane channel. One simple channel geometry is investigated for which only two zonal waves are initially unstable, with the shorter being linearly more unstable but nonlinearly less effective. It is discovered that the mechanism of nonlinear baroclinic adjustment, formerly proposed by Cehelsky and Tung, including a nonlinear wavenumber selection process, can explain the equilibration at all levels of forcing for this case. At small forcings the most unstable wave dominates the heat flux, consistent with the quasi-linear equilibration of Stone’s simple baroclinic adjustment. At high forcings the longer, less unstable wave dominates, and the equilibration involves both quasi-linear dynamics by this dominant wave and nonlinear transfer from the shorter to the longer wave. For intermediate forcings there is a transition between the low and high regimes; no single wave dominates. At every forcing except in the intermediate regime there is critical equilibration by the dominant wave. For intermediate forcings, the model equilibrates at a value between the critical shear of the two waves. The wavenumber selection process involves a threshold of heat transport for each wave. Above this, the amplitude of the wave would be so large as to cause itself to break and saturate. The shorter wave’s threshold occurs at moderate forcings, at which point it relinquishes dominance to the longer wave. A method for calculating these thresholds is proposed, which involves only robust features of the equilibrium. 1.

Surface air temperatures from a 1000-yr integration of a coupled atmosphere–ocean model with constant forcing are analyzed by using a method that decomposes temperature variations into a component associated with a characteristic spatial structure and a residual. The structure function obtained from the coupled model output is almost identical to the so-called cold ocean–warm land (COWL) pattern based on observations, in which above-average spatial mean temperature is associated with anomalously cold oceans and anomalously warm land. This pattern features maxima over the high-latitude interiors of Eurasia and North America. The temperature fluctuations at the two continental centers exhibit almost no temporal correlation with each other. The temperature variations at the individual centers are related to teleconnection patterns in sea level pressure and 500-mb height that are similar to those identified in previous observational and modeling studies. As in observations, variations in the polarity and amplitude of this structure function are an important source of spatially averaged surface air temperature variability. Results from parallel integrations of models with more simplified treatments of the ocean confirm that the contrast in thermal inertia between land and ocean is the primary factor for the existence of the COWL pattern, whereas dynamical air–sea interactions do not play a significant role. The internally generated variability in

Two coupled atmosphere–ocean general circulation models developed at GFDL show differing stability properties of the Atlantic thermohaline circulation (THC) in the Coupled Model Intercomparison Project/ Paleoclimate Modeling Intercomparison Project (CMIP/PMIP) coordinated “water-hosing ” experiment. In contrast to the R30 model in which the “off ” state of the THC is stable, it is unstable in the CM2.1. This discrepancy has also been found among other climate models. Here a comprehensive analysis is performed to investigate the causes for the differing behaviors of the THC. In agreement with previous work, it is found that the different stability of the THC is closely related to the simulation of a reversed thermohaline circulation (RTHC) and the atmospheric feedback. After the shutdown of the THC, the RTHC is well developed and stable in R30. It transports freshwater into the subtropical North Atlantic, preventing the recovery of the salinity and stabilizing the off mode of the THC. The flux adjustment is a large term in the water budget of the Atlantic Ocean. In contrast, the RTHC is weak and unstable in CM2.1. The atmospheric feedback associated with the southward shift of the Atlantic ITCZ is much more significant. The oceanic freshwater convergence into the subtropical North Atlantic cannot completely compensate for the evaporation, leading to the recovery of the THC in CM2.1. The rapid salinity recovery in the subtropical North

The climate response to idealized changes in the atmospheric CO 2 concentration by the new GFDL climate model (CM2) is documented. This new model is very different from earlier GFDL models in its