Search

Models are attractive tools to deepen the understanding of atmospheric and climate processes. In practice, such investigations often involve numerical experiments that switch on or off individual factors (such as latent heating, nonlinear coupling, or some climate forcing). However, as in general many factors can be considered, the analysis of these experiments is far from straightforward. In particular, as pointed out in an influential study on factor separation by Stein and Alpert, the analysis will often require the consideration of nonlinear interaction terms. In the current paper an alternative factor separation methodology is proposed and analyzed. Unlike the classical method, sequential factor separation (SFS) does not involve the derivation of the interaction terms but, rather, provides some uncertainty measure that addresses the quality of the separation. The main advantage of the proposed methodology is that in the case of n factors it merely requires 2 n simulations (rather than 2 n for the classical analysis). The paper provides an outline of the methodology, a detailed mathematical analysis, and a theoretical intercomparison against the classical methodology. In addition, an example and an intercomparison using regional climate model experiments with n = 3 factors are presented. The results relate to the Mediterranean amplification and demonstrate that-at least in the particular example considered-the two methodologies yield almost identical results and that the SFS is rather insensitive with respect to design choices. [ABSTRACT FROM AUTHOR]

This paper presents a novel method based on the application of interpolation techniques to the multicomponent aerosol–cloud parameterization for global climate modeling. Quantifying the aerosol indirect effect still remains a difficult task, and thus developing parameterizations for general circulation models (GCMs) of the microphysics of clouds and their interactions with aerosols is a major challenge for climate modelers. Three aerosol species are considered in this paper—namely sulfate, sea salt, and biomass smoke—and a detailed microphysical chemical parcel model is used to obtain a dataset of points relating the cloud droplet number concentration (CDNC) to the three aerosol input masses. The resulting variation of CDNC with the aerosol mass has some nonlinear features that require a complex but efficient parameterization to be easily incorporated into GCMs. In bicomponent systems, simple interpolation techniques may be sufficient to relate the CDNC to the aerosol mass, but with increasing components, simple methods fail. The parameterization technique proposed in this study employs either the modified Shepard interpolation method or the Hardy multiquadrics interpolation method, and the numerical results obtained show that both methods provide realistic results for a wide range of aerosol mass loadings. This is the first application of these two interpolation techniques to aerosol–cloud interaction studies. [ABSTRACT FROM AUTHOR]

The aim of the paper is to investigate the question of how a changing climate influences the spreading of pollutants on continental and global scales. For characterizing the spreading, a measure of chaotic systems, called topological entropy, is used. This quantity describes the exponential stretching of pollutant clouds and, therefore, is related to the predictability and the complexity of the structure of a pollutant cloud. For the dispersion simulations the ERA-Interim database is used from 1979 to 2015. The simulations demonstrate that during this period the mean topological entropy slightly increases: the length of an initially line-like pollutant cloud advected for 10 (30) days in the atmosphere becomes 20%–65% (200%–400%) longer by the 2010s than in the 1980s. The mean topological entropy is found to be strongly correlated with the mean of the absolute value of the relative vorticity and only weakly linked to the mean temperature. [ABSTRACT FROM AUTHOR]

Midlatitude storm tracks shift in response to climate change and natural climate variations such as El Niño, but the dynamical mechanisms controlling these shifts are not well established. This paper develops an energy balance model that shows how shifts of the Hadley cell terminus and changes of the meridional energy flux out of the Hadley cell can drive shifts of storm tracks, identified as extrema of the atmospheric meridional eddy energy flux. The distance between the Hadley cell terminus and the storm tracks is primarily controlled by the energy flux out of the Hadley cell. Because tropical forcings alone can modify the Hadley cell terminus, they can also shift extratropical storm tracks, as demonstrated through simulations with an idealized GCM. Additionally, a strengthening of the meridional temperature gradient at the terminus and hence of the energy flux out of the Hadley cell can reduce the distance between the Hadley cell terminus and the storm tracks, enabling storm-track shifts that do not parallel shifts of the Hadley cell terminus. Thus, with the aid of the energy balance model and supporting GCM simulations, a closed theory of storm-track shifts emerges. [ABSTRACT FROM AUTHOR]

The aim of the paper is to investigate the question of how a changing climate influences the spreading of pollutants on continental and global scales. For characterizing the spreading, a measure of chaotic systems, called topological entropy, is used. This quantity describes the exponential stretching of pollutant clouds and, therefore, is related to the predictability and the complexity of the structure of a pollutant cloud. For the dispersion simulations the ERA-Interim database is used from 1979 to 2015. The simulations demonstrate that during this period the mean topological entropy slightly increases: the length of an initially line-like pollutant cloud advected for 10 (30) days in the atmosphere becomes 20%-65% (200%-400%) longer by the 2010s than in the 1980s. The mean topological entropy is found to be strongly correlated with the mean of the absolute value of the relative vorticity and only weakly linked to the mean temperature. [ABSTRACT FROM AUTHOR]

This paper introduces the average predictability time (APT) for characterizing the overall predictability of a system. APT is the integral of a predictability measure over all lead times. The underlying predictability measure is based on the Mahalanobis metric, which is invariant to linear transformation of the prediction variables and hence gives results that are independent of the (arbitrary) basis set used to represent the state. The APT is superior to some integral time scales used to characterize the time scale of a random process because the latter vanishes in situations when it should not, whereas the APT converges to reasonable values. The APT also can be written in terms of the power spectrum, thereby clarifying the connection between predictability and the power spectrum. In essence, predictability is related to the width of spectral peaks, with strong, narrow peaks associated with high predictability and nearly flat spectra associated with low predictability. Closed form expressions for the APT for linear stochastic models are derived. For a given dynamical operator, the stochastic forcing that minimizes APT is one that allows transformation of the original stochastic model into a set of uncoupled, independent stochastic models. Loosely speaking, coupling enhances predictability. A rigorous upper bound on the predictability of linear stochastic models is derived, which clarifies the connection between predictability at short and long lead times, as well as the choice of norm for measuring error growth. Surprisingly, APT can itself be interpreted as the “total variance” of an alternative stochastic model, which means that generalized stability theory and dynamical systems theory can be used to understand APT. The APT can be decomposed into an uncorrelated set of components that maximize predictability time, analogous to the way principle component analysis decomposes variance. Part II of this paper develops a practical method for performing this decomposition and applies it to meteorological data. [ABSTRACT FROM AUTHOR]

Results are presented from a large set of large-eddy simulations of a class of unsteady vortex evolution that may sometimes play a role in tornadogenesis or tornado variability. Beginning with a high-swirl parent vortex with an excess of low-swirl flow through the surface/corner/core region, perturbation of the low-swirl near-surface inflow at a large radius can trigger a subsequent dynamic “corner flow collapse” producing dramatic near-surface intensification relative to conditions aloft of an order of magnitude or more in velocity scale. This paper presents a more detailed treatment of the physics and simulation of corner flow collapse, expanding upon the presentation given in a companion paper treating near-surface vortex intensification more generally for both steady and unsteady conditions. The basic scaling of the onset, intensification, structure, and duration of the phenomenon is explored as a function of some of the dominant physical parameters involved. A dimensionless rate of change of the low-swirl flux through the surface/corner flow during the process is identified as a critical governing parameter. Given the mode of triggering near the surface at large radii, the large intensification that can result, and the sensitivity to some of the parameters involved, corner flow collapse may provide a mechanism by which the rear-flank downdraft can promote tornadogenesis and help explain why seemingly similar conditions sometimes produce intense tornadoes and other times do not. [ABSTRACT FROM AUTHOR]

This paper examines the nature and robustness of internal stratospheric variability, namely the variability resulting from the internal dynamics of the stratosphere itself, as opposed to that forced by external sources such as the natural variability of the free troposphere. Internal stratospheric variability arises from the competing actions of radiative forcing, which under perpetual winter conditions strengthens the polar vortex, and planetary wave breaking, which weakens it. The results from a stratosphere-only model demonstrate that strong internal stratospheric variability, consisting of repeated sudden warming-type events, exists over a wide range of realistic radiative and wave forcing conditions, and is largely independent of other physical and numerical parameters. In particular, the coherent form of the variability persists as the number of degrees of freedom is increased, and is therefore not an artifact of severe model truncation. Various diagnostics, including three-dimensional representations of the potential vorticity, illustrate that the variability is determined by the vertical structure of the vortex and the extent to which upward wave propagation is favored or inhibited. In this paper, the variability arising from purely internal stratosphere dynamics is isolated by specifying thermal and wave forcings that are completely time independent. In a second paper, the authors investigate the relative importance of internal and external variability by considering time-dependent wave forcing as a simple representation of tropospheric variability. [ABSTRACT FROM AUTHOR]

Arctic climate change in winter is tightly linked to changes in the strength of surface temperature inversions, which occur frequently in the present climate as Arctic air masses form during polar night. Recent work proposed that, in a warmer climate, increasing low-cloud optical thickness of maritime air advected over high-latitude landmasses during polar night could suppress the formation of Arctic air masses, amplifying winter warming over continents and sea ice. But this mechanism was based on single-column simulations that could not assess the role of fractional cloud cover change. This paper presents two-dimensional cloud-resolving model simulations that support the single-column model results: low-cloud optical thickness and duration increase strongly with initial air temperature, slowing the surface cooling rate as the climate is warmed. The cloud-resolving model cools less at the surface than the single-column model, and the sensitivity of its cooling to warmer initial temperatures is also higher, because it produces cloudier atmospheres with stronger lower-tropospheric mixing and distributes cloud-top cooling over a deeper atmospheric layer with larger heat capacity. Resolving larger-scale cloud turbulence has the greatest impact on the microphysics schemes that best represent general observed features of mixed-phase clouds, increasing their sensitivity to climate warming. These findings support the hypothesis that increasing insulation of the high-latitude land surface by low clouds in a warmer world could act as a strong positive feedback in future climate change and suggest studying Arctic air formation in a three-dimensional climate model. [ABSTRACT FROM AUTHOR]

Studies have suggested that the persistence in the meridional vacillation of the midlatitude jet (i.e., annular mode time scale) in comprehensive climate models is related to the model biases in climatological jet latitude, with important implications for projections of future climates and midlatitude weather events. Through the use of the recently developed finite-amplitude wave activity formalism and feedback quantifying techniques, this paper has quantified the role of barotropic and baroclinic eddy feedbacks in annular mode time scales using an idealized dry atmospheric model. The eddy-mean flow interaction that characterizes the persistent anomalous state of the midlatitude jet depends on processes associated with the lower-tropospheric source of vertically propagating Rossby waves, baroclinic mechanisms, and processes associated with upper-tropospheric wave propagation and breaking, barotropic mechanisms. A variety of climate change-like thermal forcings are used to generate a range of meridional shifts in the midlatitude eddy-driven jet. The idealized model shows a reduction in annular mode time scale associated with an increase in jet latitude, similar to comprehensive climate models. This decrease in time scale can be attributed to a similar decrease in the strength of the barotropic eddy feedback, which, in the positive phase of the annular mode, is characterized by anomalous potential vorticity (PV) mixing on the equatorward flank of the climatological jet. The decrease in subtropical PV mixing is, in turn, associated with a stronger subtropical jet as the eddy-driven jet is more distant from the subtropics. These results highlight the importance of subtropical eddy-mean flow interactions for the persistence of an eddy-driven jet. [ABSTRACT FROM AUTHOR]

The paper demonstrates that sudden stratospheric warmings (SSWs) can be simulated in an ensemble of dry dynamical cores that miss the typical SSW forcing mechanisms like moist processes, land-sea contrasts, or topography. These idealized general circulation model (GCM) simulations are driven by a simple Held-Suarez-Williamson (HSW) temperature relaxation and low-level Rayleigh friction. In particular, the four dynamical cores of NCAR's Community Atmosphere Model, version 5 (CAM5), are used, which are the semi-Lagrangian (SLD) and Eulerian (EUL) spectral-transform models and the finite-volume (FV) and the spectral element (SE) models. Three research themes are discussed. First, it is shown that SSW events in such idealized simulations have very realistic flow characteristics that are analyzed via the SLD model. A single vortex-split event is highlighted that is driven by wavenumber-1 and -2 wave-mean flow interactions. Second, the SLD simulations are compared to the EUL, FV, and SE dynamical cores, which sheds light on the impact of the numerical schemes on the circulation. Only SLD produces major SSWs, while others only exhibit minor stratospheric warmings. These differences are caused by SLD's more vigorous wave-mean flow interactions in addition to a warm pole bias, which leads to relatively weak polar jets in SLD. Third, it is shown that tropical quasi-biennial oscillation (QBO)-like oscillations and SSWs can coexist in such idealized HSW simulations. They are present in the SLD dynamical core that is used to analyze the QBO-SSW interactions via a transformed Eulerian-mean (TEM) analysis. The TEM results provide support for the Holton-Tan effect. [ABSTRACT FROM AUTHOR]

This paper addresses the effect of interannual variability in jet stream orientation on weather systems over the North Atlantic basin (NAB). The observational analysis relies on 65 yr of NCEP-NCAR reanalysis (1948-2012). The total daily kinetic energy of the geostrophic wind (GTKE) is taken as a measure of storm activity over the North Atlantic. The NAB is partitioned into four rectangular regions, and the winter average of GTKE is calculated for each quadrant. The spatial GTKE average over all four quadrants shows striking year-to-year variability and is strongly correlated with the North Atlantic Oscillation (NAO). The GTKE strength in the northeast quadrant is closely related to the diffluence angle of the jet stream in the northwest quadrant. To gain insight into the relationship between the diffluence angle and its downstream impact, a quasigeostrophic baroclinic model is used. The results show that an initially zonal jet persists at its initial latitude over 30 days or longer, while a tilted jet propagates meridionally according to the Rossby wave group velocity, unless kept stationary by external forcing. A Gulf Stream-like narrow sea surface temperature (SST) front provides the requisite forcing for an analytical steady-state solution to this problem. This SST front influences the atmospheric jet in the northwest quadrant: it both strengthens the jet and tilts it northward at higher levels, while its effect is opposite at lower levels. Reanalysis data confirm these effects, which are consistent with thermal wind balance. The results suggest that the interannual variability found in the GTKE may be caused by intrinsic variability of the thermal Gulf Stream front. [ABSTRACT FROM AUTHOR]

This paper studies operators inspired by the fluctuation-dissipation theorem that consider the seasonality (nonstationarity) of the climate system under conditions of limited sample size relevant to application of the method to observational records. The approach is used to predict the steady-state response of an atmospheric general circulation model to localized temperature perturbations. A seasonal operator nominally requires a much larger data sample than a stationary operator; the authors study some strategies to overcome this. First, two methods for approximating the seasonality of the system are examined. Second, an alternative 'transpose approach' to the standard dimension reduction is considered that is more efficient and accurate for small sample sizes and additionally enables the use of a kernel, which provides a convenient way to incorporate prior physical understanding into the operator. All operators show considerable skill in predicting seasonal responses for a variety of variables (temperature, winds, rainfall, and cloud cover) and better skill in predicting the annual-mean ones. A comparison of these predictions to ones done on the same system with temporally fixed boundary conditions shows unexpectedly that skill is, if anything, improved by the presence of a seasonal cycle. The authors suggest that the extra complexity due to a seasonal system is outweighed by the added information due to the seasonal forcing and the effect of seasonality in smoothing out prediction errors. [ABSTRACT FROM AUTHOR]

The probabilistic bulk convection model (PBCM) developed in a companion paper is here extended to shallow nonprecipitating convection. The PBCM unifies the clear-sky and shallow convection boundary layer regimes by obtaining mixed-layer growth, cloud fraction, and convective inhibition from a single parameterization based on physical principles. The evolution of the shallow convection PBCM is based on the statistical distribution of the surface thermodynamic state of convective plumes. The entrainment velocity of the mixed layer is related to the mass flux of the updrafts overshooting the dry inversion capping the mixed layer. The updrafts overcoming the convective inhibition generate active cloud-base mass flux, which is the boundary condition for the shallow cumulus scheme. The subcloud-layer entrainment velocity is directly coupled to the cloud-base mass flux through the distribution of vertical velocity and fractional cover of the updrafts. Comparisons of the PBCM against large-eddy simulations from the Barbados Oceanographic and Meteorological Experiment (BOMEX) and from the Southern Great Plains Atmospheric Radiation Measurement Program (ARM) facility demonstrate good agreement in terms of thermodynamic structure, cloud-base mass flux, and cloud top. The equilibrium between the cloud-base mass flux and rate of growth of the mixed layer determines the equilibrium convective inhibition and cloud cover. This process is an important new insight on the coupling between the mixed-layer and cumulus dynamics. Given its relative simplicity and transparency, the PBCM represents a powerful tool for developing process-based understanding and intuition about the physical processes involved in boundary layer-convection interactions, as well as a test bed for diagnosing and validating shallow convection parameterizations. [ABSTRACT FROM AUTHOR]

The paper describes a convection parameterization employing a new formulation of the quasi-equilibrium closure hypothesis of Arakawa and Schubert. The scheme models a full spectrum of different cumulus clouds and its evolution within one time step of the host global climate model. Each cloud is simulated using a one-dimensional Lagrangian entraining parcel model, which includes mixed phase microphysics and vertical velocity. Hence, the model delivers explicit information on distribution of vertical velocities, precipitation intensities, cloud heights, and cloud coverage. The parameterization is evaluated in the ECHAM single-column model for midlatitude summer and tropical convection. Results show an improved temporal distribution, including the diurnal cycle, of convective heating and moistening in comparison to the Tiedtke--Nordeng scheme, which is the standard convection parameterization within ECHAM. The amount and temporal distribution of precipitation are clearly improved compared with the original parameterization. The convective cloud field model (CCFM) does not produce spurious convection events occurring with the standard parameterization. [ABSTRACT FROM AUTHOR]

Optically thin cirrus play a key role in the earth’s radiation budget and global climate change. Their radiative effects depend critically on the thin cirrus optical and microphysical properties. In this paper, inhomogeneous hexagonal monocrystals (IHMs), which consist of a pure hexagon with spherical air bubble or aerosol inclusions, are applied to calculate the single-scattering properties of individual ice crystals. The multiangular polarized characteristics of optically thin cirrus for the 0.865- and 1.38- μm spectral bands are simulated on the basis of an adding–doubling radiative transfer program. The sensitivity of total and polarized reflectance at the top of the atmosphere (TOA) to different aerosol, cirrus, and surface parameters is studied. A new sensitivity index is introduced to further quantify the sensitivity study. The TOA polarized reflectance measured by the Polarization and Directionality of the Earth’s Reflectance (POLDER) instruments is compared to simulated TOA total and polarized reflectance. The test results are reasonable, although small deviations caused by the change of aerosol properties and thin cirrus optical thickness do exist. Finally, on the basis of the sensitivity study, a conceptual approach is suggested to simultaneously retrieve thin cirrus clouds’ optical thickness, ice particle shape, and the underlying aerosol optical thickness using the TOA total and polarized reflectance of the 0.865- and 1.38- μm spectral bands measured at multiple viewing angles. [ABSTRACT FROM AUTHOR]

This paper proposes a new method for diagnosing predictability on multiple time scales without time averaging. The method finds components that maximize the average predictability time (APT) of a system, where APT is defined as the integral of the average predictability over all lead times. Basing the predictability measure on the Mahalanobis metric leads to a complete, uncorrelated set of components that can be ordered by their contribution to APT, analogous to the way principal components decompose variance. The components and associated APTs are invariant to nonsingular linear transformations, allowing variables with different units and natural variability to be considered in a single state vector without normalization. For prediction models derived from linear regression, maximizing APT is equivalent to maximizing the sum of squared multiple correlations between the component and the time-lagged state vector. The new method is used to diagnose predictability of 1000-hPa zonal velocity on time scales from 6 h to decades. The leading predictable component is dominated by a linear trend and presumably identifies a climate change signal. The next component is strongly correlated with ENSO indices and hence is identified with seasonal-to-interannual predictability. The third component is related to annular modes and presents decadal variability as well as a trend. The next few components have APTs exceeding 10 days. A reconstruction of the tropical zonal wind field based on the leading seven components reveals eastward propagation of anomalies with time scales consistent with the Madden–Julian oscillation. The remaining components have time scales less than a week and hence are identified with weather predictability. The detection of predictability on these time scales without time averaging is possible by virtue of the fact that predictability on different time scales is characterized by different spatial structures, which can be optimally extracted by suitable projections. [ABSTRACT FROM AUTHOR]

The low-frequency response to changes in external forcing for the climate system is a fundamental issue. In two recent papers the authors developed a new blended response algorithm for predicting the response of a nonlinear chaotic forced-dissipative system to small changes in external forcing. This new algorithm is based on the fluctuation–dissipation theorem and combines the geometrically exact general response formula using integration of a linear tangent model at short response times and the classical quasi-Gaussian response algorithm at longer response times. This algorithm overcomes the inherent numerical instability in the geometric formula arising because of positive Lyapunov exponents at longer times while removing potentially large systematic errors from the classical quasi-Gaussian approximation at moderate times. Here the new blended method is tested on the low-frequency response for a T21 barotropic truncation on the sphere with realistic topography in two dynamical regimes corresponding to the mean climate behavior at 300- and 500-hPa geopotential height. The 300-hPa regime has robust strongly mixing behavior with a nearly Gaussian equilibrium state distribution, whereas the 500-hPa regime is weakly chaotic with slowly decaying time autocorrelation functions and strongly non-Gaussian climatology. It is found that the blended response algorithm has significant skill beyond the classical quasi-Gaussian algorithm for the response of the climate mean state and its variance. Additionally, the predicted response of the T21 barotropic model in the lowfrequency regime for these functionals does not seem to be affected by the model's structural instability. Thus, the results here suggest the use of the fluctuation–dissipation theorem–based blended response algorithm for more complex nonlinear geophysical models. [ABSTRACT FROM AUTHOR]

This paper examines feedbacks between the radiative heating of clouds and convection in the context of numerical radiative–convective equilibrium experiments conducted using both 2D and 3D versions of a cloud-resolving model. The experiments are conducted on a large domain, and equilibria develop as juxtaposed regions of dry and moist air that are connected and sustained by circulations between them. The scales of such variability are large and differ significantly between the 2D and 3D versions of the experiments. Three sensitivity experiments were conducted which, when compared to the control experiment, provide insight into the relative influences of cloud–radiation feedback mechanisms on the equilibrium state achieved. It emerges from the experiments conducted that radiation feedbacks operate via two main pathways, with the radiative heating by high clouds being the governing process of both. The predominant bimodal nature of the moist equilibrium is established by gradients in radiative heating that, in turn, are determined by high cloud differences between wet and dry regions that, in turn, are controlled by convection. Convection, on the other hand, is also influenced by the localized effects of cloud radiative heating by these extended layers of high clouds. The results of the experiments demonstrate how high cloud radiative heating, which is a by-product of the convection itself, provides a feedback that acts to regulate the high clouds produced in the wet convective areas of the equilibrium. [ABSTRACT FROM AUTHOR]

A baroclinic model of intermediate complexity for the atmospheric jet at middle latitudes is used as a stochastic generator of atmosphere-like time series. In this case, time series of the total energy of the system are considered. Statistical inference of extreme values is applied to sequences of yearly maxima extracted from the time series in the rigorous setting provided by extreme value theory. The generalized extreme value (GEV) family of distributions is used here as a basic model, both for its qualities of simplicity and its generality. Several physically plausible values of the parameter TE, which represents the forced equator-to-pole temperature gradient and is responsible for setting the average baroclinicity in the atmospheric model, are used to generate stationary time series of the total energy. Estimates of the three GEV parameters—location, scale, and shape—are inferred by maximum likelihood methods. Standard statistical diagnostics, such as return level and quantile–quantile plots, are systematically applied to assess goodness-of-fit. The GEV parameters of location and scale are found to have a piecewise smooth, monotonically increasing dependence on TE. The shape parameter also increases with TE but is always negative, as is required a priori by the boundedness of the total energy. The sensitivity of the statistical inferences is studied with respect to the selection procedure of the maxima: the roles occupied by the length of the sequences of maxima and by the length of data blocks over which the maxima are computed are critically analyzed. Issues related to model sensitivity are also explored by varying the resolution of the system. The method used in this paper is put forward as a rigorous framework for the statistical analysis of extremes of observed data, to study the past and present climate and to characterize its variations. [ABSTRACT FROM AUTHOR]

The fluctuation–dissipation theorem (FDT) states that for systems with certain properties it is possible to generate a linear operator that gives the response of the system to weak external forcing simply by using covariances and lag-covariances of fluctuations of the undisturbed system. This paper points out that the theorem can be shown to hold for systems with properties very close to the properties of the earth’s atmosphere. As a test of the theorem’s applicability to the atmosphere, a three-dimensional operator for steady responses to external forcing is constructed for data from an atmospheric general circulation model (AGCM). The response of this operator is then compared to the response of the AGCM for various heating functions. In most cases, the FDT-based operator gives three-dimensional responses that are very similar in structure and amplitude to the corresponding GCM responses. The operator is also able to give accurate estimates for the inverse problem in which one derives the forcing that will produce a given response in the AGCM. In the few cases where the operator is not accurate, it appears that the fact that the operator was constructed in a reduced space is at least partly responsible. As an example of the potential utility of a response operator with the accuracy found here, the FDT-based operator is applied to a problem that is difficult to solve with an AGCM. It is used to generate an influence function that shows how well heating at each point on the globe excites the AGCM’s Northern Hemisphere annular mode (NAM). Most of the regions highlighted by this influence function, including the Arctic and tropical Indian Ocean, are verified by AGCM solutions as being effective locations for stimulating the NAM. [ABSTRACT FROM AUTHOR]

The leading mode of interannual variability of the midwinter Pacific storm track is such that the storm track is weaker during the winters when the Pacific jet is strong, and stronger when the jet is weak. In this paper, experiments are conducted using a stationary wave model as well as an idealized global circulation model to explore the roles of anomalous tropical heating and eddy fluxes in forcing the observed Pacific jet anomalies. It is found that enhanced tropical heating over the region 60°E to the date line, 25°S to 25°N, acts to force a stronger and narrower Pacific jet. On average, tropical heating may account for about one-third of the strong jet anomaly, but there is significant year-to-year variability. Moreover, tropical heating does not appear to contribute to the weak jet anomaly. Much of the Pacific jet anomalies are forced by anomalous eddy fluxes. By examining the regional contributions from the Pacific, the Atlantic, and Asia, it is found that local eddy feedback over the Pacific only acts to force part of the stationary anomaly, while much of the signal is forced by remote eddy forcings from the Atlantic and Asia. Since significant parts of the jet anomalies are forced by anomalous tropical heating and remote eddy fluxes, it is concluded that the observed Pacific jet/storm-track variability is not a pure local wave–mean flow interaction mode internal to the Pacific basin. Both stationary wave model diagnostics and idealized global circulation model experiments suggest that stronger eddy activity over the Atlantic may force a weaker Pacific jet and stronger Pacific eddies. On the other hand, changes in eddy activity over the Pacific may also act to force changes in the Atlantic storm track. There are also indications that tropical heating anomalies may force a simultaneous weakening of both storm tracks. These possibilities may be some of the factors behind the observed significant correlation between the Pacific and Atlantic storm tracks and should be further explored in more realistic GCM experiments. [ABSTRACT FROM AUTHOR]

In this paper, a nonlinear dry model, forced by fixed radiative forcing alone, has been constructed to simulate the Northern Hemisphere winter storm tracks. A procedure has been devised to iterate the radiative equilibrium temperature profile such that at the end of the iterations the model climate closely resembles the desired target climate. This iterative approach is applied to simulate the climatological storm tracks in January. It is found that, when the three-dimensional temperature distribution in the model resembles the observed distribution, the model storm tracks are much too weak. It is hypothesized that this is due to the fact that eddy development is suppressed in a dry atmosphere, owing to the lack of latent heat release in the ascending warm air. To obtain storm tracks with realistic amplitudes, the static stability of the target climate is reduced to simulate the enhancement in baroclinic energy conversion due to latent heat release. With this modification, the storm tracks in the model simulation closely resemble those observed except that the strength of the Atlantic storm track is slightly weaker than observed. The model, when used as a forecast model, also gives high-quality forecasts of the evolution of observed eddies. The iterative approach is applied to force the model to simulate climate anomalies associated with ENSO and the interannual variations of the winter Pacific jet stream/storm tracks. The results show that the model not only succeeds in simulating the climatology of storm tracks, but also produces realistic simulations of storm track anomalies when the model climate is forced to resemble observed climate anomalies. An extended run of the control experiment is conducted to generate monthly mean flow and storm track statistics. These statistics are used to build a linear statistical model relating storm track anomalies to mean flow anomalies. This model performs well when used to hindcast observed storm track anomalies based on observed mean flow anomalies, showing that the storm track/mean flow covariability in the model is realistic and that storm track distribution is not sensitive to the exact form of the applied forcings. [ABSTRACT FROM AUTHOR]

Aerosol size is still a poorly constrained quantity in general circulation models (GCMs). By using the modal radii of the coarse and fine mode retrieved from 103 stations in the Aerosol Robotic Network (AERONET) and the fine mode aerosol optical depth fraction derived from both the Moderate Resolute Imaging Spectroradiometer (MODIS) Terra and AERONET, a globally and monthly averaged aerosol size distribution dataset was computed assuming internally mixed aerosols. Different methods were employed in creating the size distribution datasets that were input to the ECHAM4 climate model giving a globally averaged aerosol optical depth (AOD) at 500 nm that ranged from 0.11 to 0.20 depending on the method. This translates into a globally averaged direct aerosol top-of-atmosphere forcing range from -1.6 to -3.9 W m-2. Reducing the uncertainty in the aerosol sizes is important when using AOD to validate models since mass burden errors can then be assumed to be the main AOD error source. This paper explores a procedure that can help achieve this goal. [ABSTRACT FROM AUTHOR]

Interactions between deep tropical clouds over the western Pacific warm pool and the larger-scale environment are key to understanding climate change. Cloud models are an extremely useful tool in simulating and providing statistical information on heat and moisture transfer processes between cloud systems and the environment, and can therefore be utilized to substantially improve cloud parameterizations in climate models. In this paper, the Goddard Cumulus Ensemble (GCE) cloud-resolving model is used in multiday simulations of deep tropical convective activity over the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE). Large-scale temperature and moisture advective tendencies, and horizontal momentum from the TOGA COARE Intensive Flux Array region, are applied to the GCE version that incorporates cyclical boundary conditions. Sensitivity experiments show that the horizontal extent (size) of the domain produces the largest response to domain-mean temperature and moisture deviations, as well as cloudiness, in comparison with grid horizontal or vertical resolution, and advection scheme. It is found that a domain size of at least 512 km is needed to adequately contain the convective cloud features and to replicate both the eastward and westward movements of the observed precipitating systems. The control experiment shows that the atmospheric heating and moistening is primarily a response to cloud latent processes of condensation/evaporation, and deposition/ sublimation. Air-sea exchange of heat and moisture is found to be of secondary importance, while the net radiational heating-cooling is small except above cloud tops. A convective-stratiform breakdown of the precipitating systems shows that while 55% of the total rainfall occurs in convective regions, 90% of the total rainfall coverage occurs in stratiform regions. The simulated rainfall and atmospheric heating and moistening rates agree very well with observations, and... [ABSTRACT FROM AUTHOR]

A thermodynamic analysis is presented of an overturning circulation simulated by two cloud-resolving models, coupled by a weak temperature gradient parameterization. Taken together, they represent two separated regions over different sea surface temperatures, and the coupling represents an idealized large-scale circulation such as the Walker circulation. It is demonstrated that a thermodynamic budget linking net heat input to the generation of mechanical energy can be partitioned into contributions from the large-scale interaction between the two regions, as represented by the weak temperature gradient approximation, and from convective motions in the active warm region and the suppressed cool region. Model results imply that such thermodynamic diagnostics for the aggregate system are barely affected by the strength of the coupling, even its introduction, or by the SST contrast between the regions. This indicates that the weak temperature gradient parameterization does not introduce anomalous thermodynamic behavior. We find that the vertical kinetic energy associated with the large-scale circulation is more than three orders of magnitude smaller than the typical vertical kinetic energy in each region. However, even with very weak coupling circulations, the contrast between the thermodynamic budget terms for the suppressed and active regions is strong and is relatively insensitive to the degree of the coupling. Additionally, scaling arguments are developed for the relative values of the terms in the mechanical energy budget. [ABSTRACT FROM AUTHOR]

Presents information on field experiments while focusing on global change and regional climate experiments with atmospheric numerical models which rely on the parameterization of the surface boundary. Evaluation of its impact on society and agriculture; Purpose of the present paper; Discussion of the interaction between vegetation and soil models.

The Suite of Community Radiative Transfer Codes Based on Edwards and Slingo (SOCRATES) offline radiative transfer code is used to investigate the magnitude and structure of the instantaneous radiative forcing kernels (IRFKs) for five major greenhouse gases (GHGs; CO2, CH4, N2O, CFC-11, and O3). All gases produce IRFKs that peak in the tropical upper troposphere. In addition to differences in spectroscopic intensities and the position of absorption features relative to the peak of the Planck function for Earth’s temperature, the variation in current background concentration of gases substantially affects the IRFK magnitudes. When the background concentration of CO2 is reduced from parts per million to parts per trillion levels, the peak magnitude of the IRFK increases by a factor of 642. When all gases are set to parts per trillion concentrations in the troposphere, the peak IRFK magnitudes are 1.0, 3.0, 3.1, 58, and 75Wm-2 ppmv-1 (100 hPa)-1 for CH4, CO2, N2O, O3, and CFC-11, respectively. The altitude of the IRFK maximum also differs, with the maximum for CFC-11 and water vapor occurring above 100 hPa whereas the other gases peak near 150–200 hPa. Overlap with water vapor absorption decreases the magnitude of the IRFKs for all of the GHGs, particularly in the lower-to-middle troposphere, but it does not strongly affect the peak IRFK altitude. Cloud radiative effects reduce the magnitude of the IRFK for CO2 by around 10%–20% in the upper troposphere. The use of IRFKs to estimate instantaneous radiative forcing is found to be accurate for small-amplitude perturbations but becomes inaccurate for large-amplitude changes (e.g., a doubling) for gases with a higher atmospheric optical depth. [ABSTRACT FROM AUTHOR]

There is ongoing interest in the global entropy production rate as a climate diagnostic and predictor, but progress has been limited by ambiguities in its definition; different conceptual boundaries of the climate system give rise to different internal production rates. Three viable options are described, estimated, and investigated here, two--the material and the total radiative (here ''planetary'') entropy production rates--that are well established and a third that has only recently been considered but appears very promising. This new option is labeled the ''transfer'' entropy production rate and includes all irreversible processes that transfer heat within the climate, radiative, andmaterial, but not those involved in the exchange of radiation with space. Estimates in three model climates put the material rate in the range 27-48mWm-2K-1, the transfer rate at 67-76mWm-2K-1, and the planetary rate at 1279-1312mWm22K21. The climate relevance of each rate is probed by calculating their responses to climate changes in a simple radiative-convective model. An increased greenhouse effect causes a significant increase in the material and transfer entropy production rates but has no direct impact on the planetary rate. When the same surface temperature increase is forced by changing the albedo instead, the material and transfer entropy production rates increase less dramatically and the planetary rate also registers an increase. This is pertinent to solar radiation management as it demonstrates the difficulty of reversing greenhouse gas-mediated climate changes by albedo alterations. It is argued that the transfer perspective has particular significance in the climate system and warrants increased prominence. [ABSTRACT FROM AUTHOR]

Tropical precipitation extremes are expected to strengthen with warming, but quantitative estimates remain uncertain because of a poor understanding of changes in convective dynamics. This uncertainty is addressed here by analyzing idealized convection-permitting simulations of radiative–convective equilibrium in long-channel geometry. Across a wide range of climates, the thermodynamic contribution to changes in instantaneous precipitation extremes follows near-surface moisture, and the dynamic contribution is positive and small but is sensitive to domain size. The shapes of mass flux profiles associated with precipitation extremes are determined by conditional sampling that favors strong vertical motion at levels where the vertical saturation specific humidity gradient is large, and mass flux profiles collapse to a common shape across climates when plotted in a moisture-based vertical coordinate. The collapse, robust to changes in microphysics and turbulence schemes, implies a thermodynamic contribution that scales with near-surface moisture despite substantial convergence aloft and allows the dynamic contribution to be defined by the pressure velocity at a single level. Linking the simplified dynamic mode to vertical velocities from entraining plume models reveals that the small dynamic mode in channel simulations (≲ 2% K−1) is caused by opposing height dependences of vertical velocity and density, together with the buffering influence of cloud-base buoyancies that vary little with surface temperature. These results reinforce an emerging picture of the response of extreme tropical precipitation rates to warming: a thermodynamic mode of about 7% K−1 dominates, with a minor contribution from changes in dynamics. [ABSTRACT FROM AUTHOR]

The tropical tropospheric temperature is close to but typically cooler than that of the moist adiabat. The negative temperature deviation from the moist adiabat manifests a C-shape profile and is projected to increase and stretch upward under warming in both comprehensive climate models and idealized radiative–convective equilibrium (RCE) simulations. The increased temperature deviation corresponds to a larger convective available potential energy (CAPE) under warming. The extreme convective updraft velocity in RCE increases correspondingly but at a smaller fractional rate than that of CAPE. A conceptual model for the tropical temperature deviation and convective updraft velocities is formulated to understand these features. The model builds on the previous zero-buoyancy model but replaces the bulk zero-buoyancy plume by a spectrum of entraining plumes that have distinct entrainment rates and are positively buoyant until their levels of neutral buoyancy. Besides the negative temperature deviation and its increasing magnitude with warming, this allows the spectral plume model to further predict the C-shape profile as well as its upward stretch with warming. By representing extreme convective updrafts as weakly entraining plumes, the model is able to reproduce the smaller fractional increase in convective velocities with warming as compared to that of CAPE. The smaller fractional increase is mainly caused by the upward stretch in the temperature deviation profile with warming, which reduces the ratio between the integrated plume buoyancy and CAPE. The model thus provides a useful tool for understanding the tropical temperature profile and convective updraft velocities. [ABSTRACT FROM AUTHOR]

Many subgrid-scale (SGS) parameterizations in climate models contain empirical parameters and are thus data dependent. In particular, it is not guaranteed that the SGS parameterization still helps the model to produce the correct climate projection in the presence of an external perturbation (e.g., because of climate change). Therefore, a climate dependence of tuning parameters is proposed, using the fluctuation–dissipation theorem (FDT). The FDT provides an estimation of the changes in the statistics of a system, caused by a small external forcing. These estimations are then used to update the SGS parameterization. This procedure is tested for a toy atmosphere given by a quasigeostrophic three-layer model (QG3LM). We construct a low-order climate model for this toy atmosphere, based on a reduced number of its empirical orthogonal functions (EOFs), equipped with either an empirical deterministic or an empirical stochastic SGS parameterization. External forcings are considered that are either a local anomalous heat source in the extratropics or a global dynamical forcing represented by individual EOF patterns. A quasi-Gaussian variant of the FDT is able to successfully update the SGS parameterization leading to an improvement in both amplitude and correlation between the low-order climate model and the QG3LM, in case of a perturbed system. The stochastic closure exhibits nearly no improvement compared to the deterministic parameterization. The application of a more sophisticated non-Gaussian FDT algorithm (i.e., the blended short-time/quasi-Gaussian FDT) yields only marginal improvement over the simple quasi-Gaussian FDT. [ABSTRACT FROM AUTHOR]

Stagnation weather affects atmospheric diffusion ability, and hence causes the occurrence of haze events, which have been happening frequently in northern China (NC). This work puts forward an air stagnation index (ASITS) to characterize the stagnation weather in NC, in which the processes of ventilation, vertical diffusion, and wet deposition potency are concerned. ASITS can be applied to analyze air stagnation conditions with daily to monthly time scale. It is shown that the ASITS and particulate matter smaller than 2.5 μm in diameter (PM2.5) concentrations own similar lognormal probability distribution functions on both daily and monthly time scales. And the correlation analyses between the ASITS and PM2.5 concentrations indicate that the ASITS can reflect the monthly and daily variations in PM2.5 concentrations in NC. In addition, ASITS could be used as a leading predictor of haze events since correlation coefficients of ASITS leading PM2.5 concentrations by 1 day were significant and were larger than simultaneous correlation coefficients in almost all areas in NC. The robust relationship between ASITS and PM2.5 concentrations exists possibly because the index can reflect the activities of synoptic systems. ASITS could be a useful statistical indicator for variations in PM2.5 concentrations and haze events, and a good tool in analyzing the relationship between climate change and long-term variations in haze in NC. [ABSTRACT FROM AUTHOR]

Large-scale tracer transport in the upper troposphere and lower stratosphere (UTLS) is investigated using simulations of the Whole Atmosphere Community Climate Model (WACCM) over the period 1955–2099. The analyses are based on e90, an artificial passive tracer with constant emissions and atmospheric loss rates. The separate contributions of advection by the residual circulation, eddy mixing, and subgrid convection to total transport are explicitly evaluated. The results highlight distinct large-scale transport regimes in the tropics, characterized by efficient vertical tracer transport, and the extratropics, dominated by isentropic mixing. One novel result is the important role of vertical eddy mixing in the tropical upper troposphere. It is shown that interannual variability in e90 is largely driven by El Niño–Southern Oscillation and the quasi-biennial oscillation. The long-term trends emphasize a strong impact of a rising tropopause with climate change on UTLS dynamics and tracer transport. The analyses directly attribute the e90 trends to changes in the different transport components. Stronger residual circulation in the future leads to increased tracer concentrations in the tropical lower stratosphere. Enhanced eddy mixing increases e90 in the extratropical lowermost stratosphere, linked to an upward shift of wave dissipation tied to the tropopause rise. In the troposphere, reduced concentrations in the future are due to weaker convective transport out of the boundary layer and weaker extratropical isentropic eddy mixing. [ABSTRACT FROM AUTHOR]

A conceptual bulk model for a dry, convective boundary layer with prescribed horizontally homogeneous and heterogeneous low-level radiative cooling rates is developed. For horizontally homogeneous radiative cooling, the response of the system to varying its prescribed parameters is explored and formulated in terms of nondimensional parameters. Large-eddy simulations with prescribed radiative cooling rates match the results of the bulk model well. It is found that, depending on the strength of the surface coupling, the height of the boundary layer (BL) either increases or decreases in response to increasing radiative BL cooling. Another property of the system is that, for increasing surface temperature, the BL temperature decreases if the prescribed radiative BL cooling rates are strong. This counterintuitive behavior is caused by the formulation of the entrainment rate at the inversion. Heterogeneous radiative BL cooling is found to cause a circulation induced by pressure deviations between the area of weak radiative BL cooling and the area of strong radiative BL cooling. Including the feedback of the induced circulation on the BL in a two-column model leads to a modified equilibrium state, in which a weakened horizontal BL flow of about 1 m s−1 is maintained for differences in radiative BL cooling rates larger than 1 K day−1. Such a circulation strength is comparable to a shallow circulation caused by surface temperature differences of a few kelvins. Spatial differences in radiative BL cooling should therefore be considered as a first-order effect for the formation of shallow circulations. [ABSTRACT FROM AUTHOR]

The Front Rangemountain-plain circulation (FRMC) is a large-scale diurnally driven wind systemthat occurs east of the Colorado Rocky Mountains in the United States and affects the weather both in the Rocky Mountains and Great Plains. As the climate warms, the snow albedo feedback will amplify the warming response in the Rocky Mountains during the spring, increasing the thermal contrast that drives the FRMC. In this study, the authors perform a 7-yr pseudo-global warming (PGW) regional climate change experiment along with an idealized PGW ''fixed albedo'' experiment to test the sensitivity of the FRMC to the snow albedo feedback (SAF). The authors find a mean increase in the springtime FRMC strength in the PGW experiment that is primarily driven by the snow albedo feedback. Furthermore, interannual variability of changes in FRMC strength is strongly influenced by interannual variability in the SAF. An additional case study experiment configured with a much higher resolution is performed to examine the finescale details of how the SAF and the FRMC interact. This experiment includes a passive tracer to investigate subsequent impacts on pollution transport. The case study reveals that loss of snow cover causes an increase in the strength of the FRMC. Advection by the strengthened FRMC increases the concentration of tracers emitted over the Great Plains in the boundary layer over the Front Range mountains. [ABSTRACT FROM AUTHOR]

Organized rainstorms and their associated overturning circulations can self-emerge over an ocean surface with uniform temperature in cloud-resolving simulations. This phenomenon is referred to as convective selfaggregation. Convective self-aggregation is argued to be an important building block for tropical weather systems and may help regulate tropical atmospheric humidity and thereby tropical climate stability. Here the author presents a boundary layer theory for the horizontal scale λ of 2D (x, z) convective self-aggregation by considering both the momentum and energy constraints for steady circulations. This theory suggests that λ scales with the product of the boundary layer height h and the square root of the amplitude of density variation between aggregated moist and dry regions in the boundary layer, and that this density variation mainly arises from the moisture variation due to the virtual effect of water vapor. This theory predicts the following: 1) the order of magnitude of λ is ~2000 km, 2) the aspect ratio of the boundary layer λ/h increases with surface warming, and 3) λ decreases when the virtual effect of water vapor is disabled. These predictions are confirmed using a suite of cloud-resolving simulations spanning a wide range of climates. [ABSTRACT FROM AUTHOR]

Large-scale tracer transport in the upper troposphere and lower stratosphere (UTLS) is investigated using simulations of the Whole Atmosphere Community Climate Model (WACCM) over the period 1955-2099. The analyses are based on e90, an artificial passive tracer with constant emissions and atmospheric loss rates. The separate contributions of advection by the residual circulation, eddy mixing, and subgrid convection to total transport are explicitly evaluated. The results highlight distinct large-scale transport regimes in the tropics, characterized by efficient vertical tracer transport, and the extratropics, dominated by isentropic mixing. One novel result is the important role of vertical eddy mixing in the tropical upper troposphere. It is shown that interannual variability in e90 is largely driven by El Niño-Southern Oscillation and the quasi-biennial oscillation. The long-term trends emphasize a strong impact of a rising tropopause with climate change on UTLS dynamics and tracer transport. The analyses directly attribute the e90 trends to changes in the different transport components. Stronger residual circulation in the future leads to increased tracer concentrations in the tropical lower stratosphere. Enhanced eddy mixing increases e90 in the extratropical lowermost stratosphere, linked to an upward shift of wave dissipation tied to the tropopause rise. In the troposphere, reduced concentrations in the future are due to weaker convective transport out of the boundary layer and weaker extratropical isentropic eddy mixing. [ABSTRACT FROM AUTHOR]

The parameterization of orographic drag processes in atmospheric models remains uncertain because of a lack of observational and theoretical constraints on their formulation and free parameters. While previous studies have demonstrated that parameterized orographic drag acting near the surface has a significant impact on the atmospheric circulation, this work follows a more systematic approach to investigate its impacts on the large-scale circulation and the circulation response to climate change. A set of experiments with a comprehensive atmospheric general circulation model is used to ascertain the range of climatological circulations that may arise from parameter uncertainty. It is found that the Northern Hemisphere (NH) wintertime stationary wave field is strongly damped over the North Pacific (NP) and amplified over the North Atlantic (NA) as a result of increased low-level parameterized orographic drag, both of which are shown to be conducive to higher-latitude westerlies. A comparison with the stationary wave field presented in other studies suggests that the too-zonal NA jet and equatorward NP jet biases that are prevalent in climate models may be at least partly due to their representation of orographic drag. The amplitude of the stationary wave response to climate change across the experiments is shown to scale with the magnitude of low-level parameterized orographic drag through its influence on the present-day climatological stationary wave amplitudes over different sectors of the NH, which is consistent with linear stationary wave theory. This work highlights the importance of fidelity in a model's basic state for regional climate change projections. [ABSTRACT FROM AUTHOR]

A new approach for treating organized convection in global climate models (GCMs) referred to as multiscale coherent structure parameterization (MCSP) introduces physical and dynamical effects of organized convection that are missing from contemporary parameterizations. The effects of vertical shear are approximated by a nonlinear slantwise overturning model based on Lagrangian conservation principles. Simulation of the April 2009 Madden-Julian oscillation event during the Year of Tropical Convection (YOTC) over the Indian Ocean using the Weather Research and Forecasting (WRF) Model at 1.3-km grid spacing identifies self-similar properties for squall lines, MCSs, and superclusters embedded in equatorial waves. The slantwise overturning model approximates this observed self-similarity. The large-scale effects of MCSP are examined in two categories of GCM. First, large-scale convective systems simulated in an aquaplanet model are approximated by slantwise overturning with attention to convective momentum transport. Second, MCSP is utilized in the Community Atmosphere Model, version 5.5 (CAM5.5), as tendency equations for second-baroclinic heating and convective momentum transport. The difference between MCSP and CAM5.5 is a direct measure of the global effects of organized convection. Consistent with TRMM measurements, the MCSP generates large-scale precipitation patterns in the tropical warm pool and the adjoining locale; improves precipitation in the intertropical convergence zone (ITCZ), South Pacific convergence zone (SPCZ), and Maritime Continent regions; and affects tropical wave modes. In conclusion, the treatment of organized convection by MCSP is salient for the next generation of GCMs. [ABSTRACT FROM AUTHOR]

Zonal-mean storm-track shifts in response to perturbations in climate occur even in idealized simulations of dry atmospheres with axisymmetric forcing. Nonetheless, a generally accepted theory of the mechanisms controlling the storm-track shifts is still lacking. Here, mean available potential energy (MAPE), a general measure of baroclinicity that is proportional to the square of the Eady growth rate, is used to understand storm-track shifts. It is demonstrated that, in dry atmospheres, the eddy kinetic energy (EKE) in a storm track is linearly related to the mean available potential energy, relative to a local reference state, and that maxima of the two are generally collocated in latitude. Changes in MAPE with climate are then decomposed into components. It is shown that in simulations of dry atmospheres, changes in the latitude of maximum MAPE are dominated by changes in near-surface meridional temperature gradients. By contrast, changes in the magnitude of MAPE are primarily determined by changes in static stability and in the depth of the troposphere. A theory of storm-track shifts may build upon these findings and primarily needs to explain changes in near-surface meridional temperature gradients. The terminus of the Hadley circulation often shifts in tandem with storm tracks and is hypothesized to play an important role in triggering the storm-track shifts seen in this idealized dry context, especially in simulations where increases only in the convective static stability in the deep tropics suffice to shift storm tracks poleward. [ABSTRACT FROM AUTHOR]

The authors use a quasigeostrophic (QG) two-layer model to examine how eddies modify the meridional asymmetry of a zonal jet. The initial asymmetry is introduced in the model's 'radiative equilibrium state' and is intended to mimic a radiatively forced poleward jet shift simulated by climate models. The calculations show that the initial 'poleward' jet shift in the two-layer model is amplified by eddy potential vorticity fluxes. This eddy-accentuation effect is greater as the baroclinicity of the equilibrium state is reduced, suggesting that seasonal variations in baroclinicity may help explain observed and modeled jet-shift sensitivity to season. The eddy-accentuated jet shift from the corresponding radiative equilibrium state is more clearly visible in the slowly varying, eddy-free reference state of Nakamura and Zhu. This reference state formally responds only to nonadvective, nonconservative processes, but ultimately arises from the advective eddy fluxes. The implication is that fast eddies are capable of driving a slowly varying jet shift, which may be balanced by nonconservative processes such as radiative heating/cooling. [ABSTRACT FROM AUTHOR]

Accurate uncertainty quantification for the mean and variance about forced responses to general external perturbations in the climate system is an important subject in understanding Earth's atmosphere and ocean in climate change science. A low-dimensional reduced-order method is developed for uncertainty quantification and capturing the statistical sensitivity in the principal model directions with largest variability and in various regimes in two-layer quasigeostrophic turbulence. Typical dynamical regimes tested here include the homogeneous flow in the high latitudes and the anisotropic meandering jets in the low latitudes and/or midlatitudes. The idea in the reduced-order method is from a self-consistent mathematical framework for general systems with quadratic nonlinearity, where crucial high-order statistics are approximated by a systematic model calibration procedure. Model efficiency is improved through additional damping and noise corrections to replace the expensive energy-conserving nonlinear interactions. Model errors due to the imperfect nonlinear approximation are corrected by tuning the model parameters using linear response theory with an information metric in a training phase before prediction. Here a statistical energy principle is adopted to introduce a global scaling factor in characterizing the higher-order moments in a consistent way to improve model sensitivity. The reduced-order model displays uniformly high prediction skill for the mean and variance response to general forcing for both homogeneous flow and anisotropic zonal jets in the first 102 dominant low-wavenumber modes, where only about 0.15% of the total spectral modes are resolved, compared with the full model resolution of 2562 horizontal modes. [ABSTRACT FROM AUTHOR]

Over the past decade, the number of studies that investigate aerosol-cloud interactions has increased considerably. Although tremendous progress has been made to improve the understanding of basic physical mechanisms of aerosol-cloud interactions and reduce their uncertainties in climate forcing, there is still poor understanding of 1) some of the mechanisms that interact with each other over multiple spatial and temporal scales, 2) the feedbacks between microphysical and dynamical processes and between local-scale processes and large-scale circulations, and 3) the significance of cloud-aerosol interactions on weather systems as well as regional and global climate. This review focuses on recent theoretical studies and important mechanisms on aerosol-cloud interactions and discusses the significances of aerosol impacts on radiative forcing and precipitation extremes associated with different cloud systems. The authors summarize the main obstacles preventing the science from making a leap-for example, the lack of concurrent profile measurements of cloud dynamics, microphysics, and aerosols over a wide region on the observation side and the large variability of cloud microphysics parameterizations resulting in a large spread of modeling results on the modeling side. Therefore, large efforts are needed to escalate understanding. Future directions should focus on obtaining concurrent measurements of aerosol properties and cloud microphysical and dynamic properties over a range of temporal and spatial scales collected over typical climate regimes and closure studies, as well as improving understanding and parameterizations of cloud microphysics such as ice nucleation, mixed-phase properties, and hydrometeor size and fall speed. [ABSTRACT FROM AUTHOR]

Aerosols contribute to Earth's radiative budget both directly and indirectly, and large uncertainties remain in quantifying aerosol effects on climate. Variability in aerosol distribution and properties, as might result from changing emissions and transport processes, must be characterized. In this study, variations in aerosol loading across the eastern seaboard of the United States and the North Atlantic Ocean during 2002 to 2012 are analyzed to examine the impacts of anthropogenic emission control measures using monthly mean data from MODIS, AERONET, and IMPROVE observations and Goddard Chemistry Aerosol Radiation and Transport (GOCART) model simulation. MODIS observes a statistically significant negative trend in aerosol optical depth (AOD) over the midlatitudes (−0.030 decade−1). Correlation analyses with surface AOD from AERONET sites in the upwind region combined with trend analysis from GOCART component AOD confirm that the observed decrease in the midlatitudes is chiefly associated with anthropogenic aerosols that exhibit significant negative trends from the eastern U.S. coast extending over the western North Atlantic. Additional analysis of IMPROVE surface PM2.5 observations demonstrates statistically significant negative trends in the anthropogenic components with decreasing mass concentrations over the eastern United States. Finally, a seasonal analysis of observational datasets is performed. The negative trend seen by MODIS is strongest during spring (MAM) and summer (JJA) months. This is supported by AERONET seasonal trends and is identified from IMPROVE seasonal trends as resulting from ammonium sulfate decreases during these seasons. [ABSTRACT FROM AUTHOR]

The GFDL hurricane modeling system, initiated in the 1970s, has progressed from a research tool to an operational system over four decades. This system is still in use today in research and operations, and its evolution will be briefly described. This study used an idealized version of the 2014 GFDL model to test its sensitivity across a wide range of three environmental factors that are often identified as key factors in tropical cyclone (TC) evolution: SST, atmospheric stability (upper-air thermal anomalies), and vertical wind shear (westerly through easterly). A wide range of minimum central pressure intensities resulted (905-980 hPa). The results confirm that a scenario (e.g., global warming) in which the upper troposphere warms relative to the surface will have less TC intensification than one with a uniform warming with height. The TC rainfall is also investigated for the SST-stability parameter space. Rainfall increases for combinations of SST increase and increasing stability similar to global warming scenarios, consistent with climate change TC downscaling studies with the GFDL model. The forecast system's sensitivity to vertical shear was also investigated. The idealized model simulations showed weak disturbances dissipating under strong easterly and westerly shear of 10 m s−1. A small bias for greater intensity under easterly sheared versus westerly sheared environments was found at lower values of SST. The impact of vertical shear on intensity was different when a strong vortex was used in the simulations. In this case, none of the initial disturbances weakened, and most intensified to some extent. [ABSTRACT FROM AUTHOR]

A linear response function (LRF) determines the mean response of a nonlinear climate system to weak imposed forcings, and an eddy flux matrix (EFM) determines the eddy momentum and heat flux responses to mean-flow changes. Neither LRF nor EFM can be calculated from first principles owing to the lack of a complete theory for turbulent eddies. Here the LRF and EFM for an idealized dry atmosphere are computed by applying numerous localized weak forcings, one at a time, to a GCM with Held-Suarez physics and calculating the mean responses. The LRF and EFM for zonally averaged responses are then constructed using these forcings and responses through matrix inversion. Tests demonstrate that LRF and EFM are fairly accurate. Spectral analysis of the LRF shows that the most excitable dynamical mode, the neutral vector, strongly resembles the model's annular mode. The framework described here can be employed to compute the LRF and EFM for zonally asymmetric responses and more complex GCMs. The potential applications of the LRF and EFM constructed here are (i) forcing a specified mean flow for hypothesis testing, (ii) isolating/quantifying the eddy feedbacks in complex eddy-mean flow interaction problems, and (iii) evaluating/improving more generally applicable methods currently used to construct LRFs or diagnose eddy feedbacks in comprehensive GCMs or observations. As an example for (iii), in Part II, the LRF is also computed using the fluctuation-dissipation theorem (FDT), and the previously calculated LRF is exploited to investigate why FDT performs poorly in some cases. It is shown that dimension reduction using leading EOFs, which is commonly used to construct LRFs from the FDT, can significantly degrade the accuracy owing to the nonnormality of the operator. [ABSTRACT FROM AUTHOR]

A dry atmospheric general circulation model is forced with large-scale, Gaussian orography in an attempt to isolate a regime in which the model responds linearly to orographic forcing and then to study the departures from linearity as the orography is increased in amplitude. In contrast to previous results, which emphasized the meridional propagation of orographically forced stationary waves, using the standard Held-Suarez (H-S) control climate, it is found that the linear regime is characterized by a meridionally trapped, zonally propagating wave. Meridionally trapped waves of this kind have been seen in other contexts, where they have been termed 'circumglobal waves.' As the height of the orography is increased, the circumglobal wave coexists with a meridionally propagating wave and for large-enough heights the meridionally propagating wave dominates the response. A barotropic model on a sphere reproduces this trapped wave in the linear regime and also reproduces the transition to meridional propagation with increasing amplitude. However, mean-flow modification by the stationary waves is very different in the two models, making it difficult to argue that the transitions have the same causes. When adding asymmetry across the equator to the H-S control climate and placing the orography in the cooler hemisphere, it becomes harder to generate trapped waves in the GCM and the trapping becomes sensitive to the shape of the orography. The barotropic model overestimates the trapping in this case. These results suggest that an improved understanding of the role of circumglobal waves will be needed to understand the stationary wave field and its sensitivity to the changes in the zonal-mean climate. [ABSTRACT FROM AUTHOR]

The equatorward shift of the zonal-mean midlatitude tropospheric jet following a stratospheric sudden warming in a comprehensive stratosphere-resolving model is found to be well quantified by the simple model of tropospheric eddy feedbacks proposed by Lorenz and Hartmann. This permits a decomposition of the shift into a component driven by the stratospheric anomalies and a component driven by tropospheric feedbacks. This is done by extending the simple model to include three effective forcing mechanisms by which the stratosphere may influence the tropospheric jet. These include 1) the zonally symmetric adjustments associated with the mean meridional circulation and the direct influence of the stratospheric anomalies on 2) the tropospheric synoptic-scale or 3) the tropospheric planetary-scale eddies. Although the anomalous tropospheric winds are primarily maintained against surface friction by the synoptic-scale eddies, this response can be entirely attributed to the eddy feedback term. The response of the planetary-scale eddies, in contrast, can be directly attributed to the stratosphere. The zonally symmetric tropospheric circulation associated with downward control is found to play little role in driving the tropospheric response. The prospects of applying this methodology to reanalysis data are also considered, but statistical limitations and the relatively weak projection of the vertically integrated composite wind anomalies onto the leading EOF preclude any conclusions from being drawn. [ABSTRACT FROM AUTHOR]