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Time series of stratospheric climate variables are used to derive master equations in the discretized phase space spanned by three variables. The empirical master equation (EME) predicts the probability density function (PDF) in this phase space. The numerical properties of EMEs have been investigated in the first part of this paper using synthetic time series. In this part of the paper, the time series consist of normalized and deseasonalized daily and zonally averaged meteorologically relevant quantities obtained from the 40-yr ECMWF Re-Analysis (ERA-40) and observations. One EME reproduces the climatological features of the quasi-biennial oscillation (QBO) of stratospheric equatorial zonal wind including the probabilistic character of transitions between phases. Also, the Arctic stratosphere at 10 hPa is about 2 K warmer during the easterly phase of the QBO than during the westerly phase. Another EME including a time series of the solar radio flux at 10.7 cm hints that the relationship between the QBO and the temperature in the Arctic stratosphere is shifted toward warmer (colder) states by about 1 K during periods of high (low) solar activity. Finally, an EME is derived from time series of variables highly correlated with the northern annular mode (NAM). The EME shows that NAM anomalies in the middle stratosphere propagate into the lower stratosphere and then into the lower troposphere with a time scale of about two and four weeks, respectively. The influence of strong tropospheric NAM anomalies is confined to the lower stratosphere. [ABSTRACT FROM AUTHOR]

This paper examines the structure and variability of the moisture field in the tropical marine boundary layer (TMBL) as defined by Bragg scattering layers (BSLs) observed with S-band radar. Typically, four to five BSLs were present in the TMBL, including the transition layer at the top of the surface-based mixed layer. The transition-layer depth (~350 m) exhibited a weak diurnal cycle because of changes in the mixed-layer depth. BSLs and the 'clear' layers between them each had a median thickness of about 350 m and a lifetime over the radar of 8.4 h, with about 25% having lifetimes longer than 20 h. More (fewer) BSLs were present when surface winds had a more southerly (northerly) component. Both BSLs and clear layers increased in depth with increasing rain rates, with the rainiest days producing layers that were about 100 m thicker than those on the driest days. The analyses imply that the relative humidity (RH) field in the TMBL exhibits layering on scales observable by radar. Satellite and wind profiler measurements show that the layered RH structure is related, at least in part, to detraining cloudy air. Based on analyses in this series of papers, a revised conceptual model of the TMBL is presented that emphasizes moisture variability and incorporates multiple moist and dry layers and a higher TMBL top. The model is supported by comparing BSL tops with satellite-derived cloud tops. This comparison suggests that the layered RH structure is related, in part, to cloud detrainment at preferred altitudes within the TMBL. The potential ramifications of this change in TMBL conceptualization on modeling of the TMBL are discussed. [ABSTRACT FROM AUTHOR]

In the atmospheric sciences, master equations are mainly used in a discrete time approximation to provide forecasts of the probability density function in a discretized phase space spanned by a few climate variables. The coefficients of an empirical master equation (EME) are estimated from the relative frequencies of transitions observed in time series of the variables. The quality of an EME depends on, among other things, the length and time resolution of the available time series. In this part of the paper, these dependencies are studied on the basis of data from the three-component Lorenz model with additional white noise forcing. Thus, time series of almost any length and time resolution can be generated easily, and probability density forecasts can be compared directly with the evolution of an ensemble of points. Useful results are obtained by partitioning the phase space into several hundred cells of equal grid size. The authors find that a threshold length of the time series exists beyond which improvements in the performance of the EME are hard to detect. It is even more surprising that the performance deteriorates with reduction of the time step. This is due to an increase in numerical diffusion. The choice of the dimensionality and the selection of the variables of the EME are very important. The results of this part of the paper provide useful guidelines for any application of the EME in the atmospheric sciences and elsewhere. The second part of the paper illustrates the usefulness of these guidelines through applications to stratospheric dynamics. [ABSTRACT FROM AUTHOR]

This paper gives an introduction to the connection between predictability and information theory, and derives new connections between these concepts. A system is said to be unpredictable if the forecast distribution, which gives the most complete description of the future state based on all available knowledge, is identical to the climatological distribution, which describes the state in the absence of time lag information. It follows that a necessary condition for predictability is for the forecast and climatological distributions to differ. Information theory provides a powerful framework for quantifying the difference between two distributions that agrees with intuition about predictability. Three information theoretic measures have been proposed in the literature: predictive information, relative entropy, and mutual information. These metrics are discussed with the aim of clarifying their similarities and differences. All three metrics have attractive properties for defining predictability, including the fact that they are invariant with respect to nonsingular linear transformations, decrease monotonically in stationary Markov systems in some sense, and are easily decomposed into components that optimize them (in certain cases). Relative entropy and predictive information have the same average value, which in turn equals the mutual information. Optimization of mutual information leads naturally to canonical correlation analysis, when the variables are joint normally distributed. Closed form expressions of these metrics for finite dimensional, stationary, Gaussian, Markov systems are derived. Relative entropy and predictive information differ most significantly in that the former depends on the “signal to noise ratio” of a single forecast distribution, whereas the latter does not. Part II of this paper discusses the extension of these concepts to imperfect forecast models. [ABSTRACT FROM AUTHOR]

The moist-air entropy can be used to analyze and better understand the general circulation of the atmosphere or convective motions. Isentropic analyses are commonly based on studies of different equivalent potential temperatures, all of which are assumed to fully represent the entropy of moist air. It is, however, possible to rely either on statistical physics or the third law of thermodynamics when defining and computing the absolute entropy of moist air and to study the corresponding third-law potential temperature, which is different from the previous ones. The third law assumes that the entropy for the most stable crystalline state of all substances is zero when approaching absolute zero temperature. This paper shows that the way all these moist-air potential temperatures are defined has a large impact on (i) the plotting of the isentropes for a simulation of Hurricane Dumile, (ii) the changes in moist-air entropy computed for a steam cycle defined for this hurricane, (iii) the analyses of isentropic streamfunctions computed for this hurricane, and (iv) the computations of the heat input, the work function, and the efficiency defined for this steam cycle. The moist-air entropy is a state function and the isentropic analyses must be completely determined by the local moist-air conditions. The large differences observed between the different formulations of moist-air entropy are interpreted as proof that the isentropic analyses of moist-air atmospheric motions must be achieved by using the third-law potential temperature defined from general thermodynamics. [ABSTRACT FROM AUTHOR]

In Part I of this two-part paper, a formulation was developed to treat fragmentation in ice-ice collisions. In the present Part II, the formulation is implemented in two microphysically advanced cloud models simulating a convective line observed over the U.S. high plains. One model is 2D with a spectral bin microphysics scheme. The other has a hybrid bin-two-moment bulk microphysics scheme in 3D. The case consists of cumulonimbus cells with cold cloud bases (near 0°C) in a dry troposphere. Only with breakup included in the simulation are aircraft observations of particles with maximum dimensions >0.2 mm in the storm adequately predicted by both models. In fact, breakup in ice-ice collisions is by far the most prolific process of ice initiation in the simulated clouds (95%-98% of all nonhomogeneous ice), apart from homogeneous freezing of droplets. Inclusion of breakup in the cloud-resolving model (CRM) simulations increased, by between about one and two orders of magnitude, the average concentration of ice between about 0° and −30°C. Most of the breakup is due to collisions of snow with graupel/hail. It is broadly consistent with the theoretical result in Part I about an explosive tendency for ice multiplication. Breakup in collisions of snow (crystals >~1 mm and aggregates) with denser graupel/hail was the main pathway for collisional breakup and initiated about 60%-90% of all ice particles not from homogeneous freezing, in the simulations by both models. Breakup is predicted to reduce accumulated surface precipitation in the simulated storm by about 20%-40%. [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]

In the third part of the 'Cellular Statistical Models of Broken Cloud Fields' series the cloud statistics formalism developed in the first two parts is interpreted in terms of the theory of Markov processes. The master matrix introduced in this study is a unifying generalization of both the cloud fraction probability distribution function (PDF) and the Markovian transition probability matrix. To illustrate the new concept, the master matrix is used for computation of the moments of the cloud fraction PDF-in particular, the variance-which until now has not been analytically derived in the framework of the authors' previous work. This paper also serves as a bridge to the proposed future studies of the effects of sampling and averaging on satellite-based cloud masks. [ABSTRACT FROM AUTHOR]

Elevated heating of the atmosphere by large plateaus has been argued to influence regional climate in Asia and other regions, but the mechanisms that cause the troposphere to equilibrate at warmer temperatures over elevated terrain are not well understood. This paper quantitatively describes the physics that controls temperatures over elevated terrain in radiative-convective equilibrium (RCE). First, a cloud-system-resolving model (CSRM) is used to simulate RCE states over surfaces with various elevations. Then, a theory for the influence of surface elevation on temperatures in RCE is presented. Together with offline radiative transfer calculations, this theory is used to quantitatively attribute the magnitude of the elevated heating effect to top-of-atmosphere radiative flux changes caused by decreases in longwave absorption, shortwave scattering, and the moist lapse rate that occur as surface pressure drops. Sensitivity functions obtained through these offline calculations suggest that elevated heating is weaker in warmer climates, and additional CSRM simulations support this hypothesis. Under certain circumstances, even the sign of the elevated heating effect can change to produce cooler temperatures at a given pressure level as the surface is lifted in RCE. [ABSTRACT FROM AUTHOR]

This paper focuses on two shortcomings of radiative transfer codes commonly used in climate models. The first aspect concerns the partitioning of solar versus infrared spectral energy. In most climate models, the solar spectrum comprises wavelengths less than 4 μm with all incoming solar energy deposited in that range. In reality, however, the solar spectrum extends into the infrared, with about 12 W m−2 in the 4–1000- μm range. In this paper a simple method is proposed wherein the longwave radiative transfer equation with solar energy input is solved. In comparison with the traditional method, the new solution results in more solar energy absorbed in the atmosphere and less at the surface. As mentioned in a recent intercomparison of the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) and line-by-line (LBL) radiation models, most climate model radiation schemes neglect shortwave absorption by methane. However, the shortwave radiative forcing at the surface due to CH4 since the preindustrial period is estimated to exceed that due to CO2. The authors show that the CH4 shortwave effect can be included in a correlated k-distribution model, with the additional flux being accurately simulated in comparison with LBL models. Ten-year GCM simulations are presented, showing the detailed climatic effect of these changes in radiation treatment. It is demonstrated that the inclusion of solar flux in the infrared range produces a significant amount of extra warming in the atmosphere, specifically (i) in the tropical stratosphere where the warming can exceed 1 K day−1, and (ii) near the tropical tropopause layer. Additional GCM simulations show that inclusion of CH4 in the shortwave calculations also produces a warming of the atmosphere and a consequent reduction of the upward flux at the top of the atmosphere. [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]

In this paper, the north–south variability of westerly jet anomalies during the two phases of the North Atlantic Oscillation (NAO) is examined in a theoretical model. It is found that the north–south variability of the zonal mean westerly anomaly results from the interaction between the eddy-driven anomalous stationary waves with a dipole meridional structure (NAO anomalies) and topographically induced climatological stationary waves with a monopole structure, which is dependent upon the phase of the NAO. The westerly jet anomaly tends to shift northward during the positive NAO phase but southward during the negative phase. Synoptic-scale eddies tend to maintain westerly jet anomalies through the excitation of NAO anomalies, but the climatological stationary wave and its position relative to the eddy-driven anomalous stationary wave appear to dominate the north–south shift of westerly jet anomalies. On the other hand, it is shown that when the climatological stationary wave ridge is located downstream of the eddy-driven anomalous stationary wave, the storm track modulated by the NAO pattern splits into two branches for the negative phase, in which the northern branch is generally stronger than the southern one. However, the southern one can be dominant as the relative position between anomalous and climatological stationary waves is within a moderate range. The storm track for the positive phase tends to drift northeastward when there is a phase difference between the NAO anomaly and climatological stationary wave ridge downstream. Thus, it appears that the relationship between the NAO jets and storm tracks can be clearly seen from the present theoretical model. [ABSTRACT FROM AUTHOR]

This paper investigates the relationship between large-scale dynamics, water vapor, and organized convection over West Africa. Making use of a simplified condensation hypothesis, a back-trajectory model fed by NCEP-analyzed winds is used to reconstruct the midtropospheric humidity field over Africa during July to August 1992. The approach documents both the moisture content and the origin of the air masses. Meteosat satellite infrared imagery is used to characterize the convective systems. A case study analysis reveals that very dry air patches (RH < 5%) are located in the immediate midtropospheric environment of a typical squall line. Such dry-air structures are shown to originate in the upper levels (200–250 hPa) on the anticyclonic side of the polar jet stream at 50°N. Focusing on the Sahel region, dry events are isolated using the time series of the 500-hPa relative humidity distribution during the monsoon period. These dry events are shown to be composed of extratropical air. Composite analysis of the convective activity indicator exhibits a strong positive association between dry intrusions and convection on the eastern side of the Sahelian region. Organized convective systems that are fast moving and long lasting are more likely over this region when a dry intrusion is present. This coincides with the well-established theory that midtropospheric dry air, when combined with sufficient wind shear, can maintain and intensify previously triggered deep convection through rain evaporation that feeds the cold pools, especially within squall lines. This paper suggests that the extratropical dry-air intrusions modulate the occurrence and duration of convective systems and, therefore, the mode of variability of rainfall over West Africa during the monsoon. [ABSTRACT FROM AUTHOR]

Multiple linear regression models with nonlinear power terms may be applied to find relationships between interacting wave modes that may be characterized by different frequencies. Such regression techniques have been explored in other disciplines, but they have not been used in the analysis of atmospheric circulations. In this study, such a model is developed to predict anomalies of westward-moving intraseasonal precipitable water by utilizing the first through fourth powers of a time series of outgoing longwave radiation that is filtered for eastward propagation and for the temporal and spatial scales of the tropical intraseasonal oscillations. An independent and simpler compositing method is applied to show that the results of this multiple linear regression model provide a better description of the actual relationships between eastward- and westward-moving intraseasonal modes than a regression model that includes only the linear predictor. A statistical significance test is applied to the coefficients of the multiple linear regression model, and they are found to be significant over broad regions of the Tropics. Correlations between the predictors are shown to not significantly influence results for this case. Results show that this regression model reveals physical relationships between eastward- and westward-moving intraseasonal modes. The physical interpretation of these regression relationships is given in a companion paper. [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]

Conditional Markov chain (CMC) models have proven to be promising building blocks for stochastic convection parameterizations. In this paper, it is demonstrated how two different CMC models can be used as mass flux closures in convection parameterizations. More specifically, the CMC models provide a stochastic estimate of the convective area fraction that is directly proportional to the cloud-base mass flux. Since, in one of the models, the number of CMCs decreases with increasing resolution, this approach makes convection parameterizations scale aware and introduces stochastic fluctuations that increase with resolution in a realistic way. Both CMC models are implemented in a GCM of intermediate complexity. It is shown that with the CMC models, trained with observational data, it is possible to improve both the subgrid-scale variability and the autocorrelation function of the cloud-base mass flux as well as the distribution of the daily accumulated precipitation in the tropics. Hovmöller diagrams and wavenumber-frequency diagrams of the equatorial precipitation indicate that, in this specific GCM, convectively coupled equatorial waves are more sensitive to the mean cloud-base mass flux than to stochastic fluctuations. A smaller mean mass flux tends to increase the power of the simulated MJO and to diminish equatorial Kelvin waves. [ABSTRACT FROM AUTHOR]

This paper investigates the connection between the delay in the final breakdown of the stratospheric polar vortex, the stratospheric final warming (SFW), and Southern Hemisphere climate trends. The authors first analyze Interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-Interim) and three climate model outputs with different climate forcings. Climate trends appear when there is a delay in the timing of SFWs. When regressed onto the SFW dates (which reflect the anomaly when the SFW is delayed for one standard deviation of its onset dates), the anomaly pattern bears a resemblance to the observed climate trends, for all the model outputs, even without any trends. This suggests that the stratospheric and tropospheric circulations are organized by the timing of SFWs in both the interannual time scale and climate trends because of external forcings. The authors further explore the role of the SFW using a simplified dynamical model in which the ozone depletion is mimicked by a springtime polar stratospheric cooling. The responses of zonal-mean atmospheric circulation, including zonal wind, temperature, and poleward edge of the Hadley cell and the Ferrel cell, are similar to the observed climate trends. The authors divide the years into those in which the SFW is delayed and those in which it is not. The responses for the years in which the SFW is delayed are very similar to the overall response, while the stratosphere is only characterized by the localized cooling for those years in which the SFW is not delayed, with no subsequent downward influence into the troposphere. This suggests that, in order to affect the troposphere, ozone depletion must first delay the SFW so as to induce a deep response in planetary wave drag and the associated eddy-driven circulation. [ABSTRACT FROM AUTHOR]

This paper discusses the sensitivity of the horizontal and vertical scales of extratropical eddies when criticality is varied in a dry, primitive-equation, general circulation model. Criticality is a measure of extratropical isentropic slope and when defined appropriately its value is often close to 1 for Earth's climate. The model is forced by a Newtonian relaxation of temperature to a prescribed temperature profile, and criticality is increased by increasing the thermal relaxation rate on the mean flow. When criticality varies near 1, it is shown that there exists a weakly nonlinear regime in which the eddy scale increases with criticality without involving an inverse cascade, while at the same time the Rossby radius may in fact decrease. The quasigeostrophic instability of the Charney problem is revisited. It is demonstrated that both the horizontal and vertical scales of the most unstable wave depend on criticality, and simple estimates for the two scales are obtained. The authors reconcile the opposite trends of the eddy scale and Rossby radius and obtain an estimate for the eddy scale in terms of the Rossby radius and criticality that is broadly consistent with simulations. [ABSTRACT FROM AUTHOR]

Diurnal variations of the Great Plains low-level jet (GPLLJ) and vertical motions have been related to the development of summer precipitation individually, but their underlying connection and consequences for the nocturnal and afternoon precipitation peaks are less discussed. This paper examines how together they help explain the spatial pattern of the frequency of summer convective precipitation over the Great Plains. A one-layer linearized boundary layer model is used to reproduce the diurnal cycle of the GPLLJ. Its periodic rising and sinking motions compare favorably with those of the North American Regional Reanalysis (NARR) climatology. Its development of rising motion is also consistent with the enhanced occurrence of nocturnal convective precipitation over the central and eastern Great Plains (90°-100°W) and afternoon maximum over the western Great Plains (100°-105°W). The diurnal phasing of the vertical motions can be captured by the model only if the diurnal oscillation of the jet is forced by both near surface geopotential gradients and friction with observed diurnal variability. The diurnal variation of the vertical velocity (or boundary layer convergence and divergence) is explained by local vorticity balance; that is, following the diurnal oscillation of the jet, the zonal gradient of the meridional wind oscillates and, thus, relative vorticity and its tendency. The slowing down of the jet after midnight decreases the anticyclonic (cyclonic) vorticity and consequently gives a positive (negative) vorticity tendency to the east (west) of the jet core; anomalous rising (sinking) motions occur to balance these positive (negative) vorticity tendencies. The pattern reverses when the jet is relatively weak. [ABSTRACT FROM AUTHOR]

A new bulk model of the convective boundary layer, the probabilistic bulk convection model (PBCM), is presented. Unlike prior bulk approaches that have modeled the mixed-layer-top buoyancy flux as a constant fraction of the surface buoyancy flux, PBCM implements a new mixed-layer-top entrainment closure based on the mass flux of updrafts overshooting the inversion. This mass flux is related to the variability of the surface state (potential temperature θ and specific humidity q) of an ensemble of updraft plumes. The authors evaluate the model against observed clear-sky weak and strong inversion cases and show that PBCM performs well. The height, state, and timing of the boundary layer growth are accurately reproduced. Sensitivity studies are performed highlighting the role of the main parameters (surface variances, lateral entrainment). The model is weakly sensitive to the exact specification of the variability at the surface and is most sensitive to the lateral entrainment of environmental air into the rising plumes. Apart from allowing time-dependent top-of-the-boundary-layer entrainment rates expressed in terms of surface properties, which can be observed in situ, PBCM naturally takes into account the transition to the shallow convection regime, as described in a companion paper. Thus, PBCM represents an important step toward a unified framework bridging parameterizations of mixed-layer entrainment velocity in both clear-sky and moist convective boundary layers. [ABSTRACT FROM AUTHOR]

This paper presents a simple analytical framework for the dynamic response of cirrus to a local radiative flux convergence, expressible in terms of three independent modes of cloud evolution. Horizontally narrow and tenuous clouds within a stable environment adjust to radiative heating by ascending gradually across isentropes while spreading sufficiently fast that isentropic surfaces stay nearly flat. Alternatively, optically dense clouds experience very concentrated heating, and if they are also very broad, they develop a convecting mixed layer. Along-isentropic spreading still occurs, but in the form of turbulent density currents rather than laminar flows. A third adjustment mode relates to evaporation, which erodes cloudy air as it lofts, regardless of its optical density. The dominant mode is determined from two dimensionless numbers, whose predictive power is shown in comparisons with high-resolution numerical cloud simulations. The power and simplicity of the approach hints that fast, subgrid-scale radiative-dynamic atmospheric interactions might be efficiently parameterized within slower, coarse-grid climate models. [ABSTRACT FROM AUTHOR]

This paper presents a new method for representing the important effects of horizontal radiation transport through cloud sides in two-stream radiation schemes. Ordinarily, the radiative transfer equations are discretized separately for the clear and cloudy regions within each model level, but here terms are introduced that represent the exchange of radiation laterally between regions and the resulting coupled equations are solved for each layer. This approach may be taken with both the direct incoming shortwave radiation, which is governed by Beer's law, and the diffuse shortwave and longwave radiation, governed by the two-stream equations. The rate of lateral exchange is determined by the area of cloud 'edge.' The validity of the method is demonstrated by comparing with rigorous 3D radiative transfer calculations in the literature for two cloud types in which the 3D effect is strong, specifically cumulus and aircraft contrails. The 3D effect on shortwave cloud radiative forcing varies between around −25% and around +100%, depending on solar zenith angle. Even with an otherwise very simplistic representation of the cloud, the new scheme exhibits good agreement with the rigorous calculations in the shortwave, opening the way for efficient yet accurate representation of this important effect in climate models. [ABSTRACT FROM AUTHOR]

In this paper the authors exploit two equivalent formulations of the average rate of material entropy production in the climate system to propose an approximate splitting between contributions due to vertical and eminently horizontal processes. This approach is based only on 2D radiative fields at the surface and at the top of atmosphere. Using 2D fields at the top of atmosphere alone, lower bounds to the rate of material entropy production and to the intensity of the Lorenz energy cycle are derived. By introducing a measure of the efficiency of the planetary system with respect to horizontal thermodynamic processes, it is possible to gain insight into a previous intuition on the possibility of defining a baroclinic heat engine extracting work from the meridional heat flux. The approximate formula of the material entropy production is verified and used for studying the global thermodynamic properties of climate models (CMs) included in the Program for Climate Model Diagnosis and Intercomparison (PCMDI)/phase 3 of the Coupled Model Intercomparison Project (CMIP3) dataset in preindustrial climate conditions. It is found that about 90%% of the material entropy production is due to vertical processes such as convection, whereas the large-scale meridional heat transport contributes to only about 10%% of the total. This suggests that the traditional two-box models used for providing a minimal representation of entropy production in planetary systems are not appropriate, whereas a basic-but conceptually correct-description can be framed in terms of a four-box model. The total material entropy production is typically 55 mW m−2 K−1, with discrepancies on the order of 5%%, and CMs' baroclinic efficiencies are clustered around 0.055. The lower bounds on the intensity of the Lorenz energy cycle featured by CMs are found to be around 1.0-1.5 W m−2, which implies that the derived inequality is rather stringent. When looking at the variability and covariability of the considered thermodynamic quantities, the agreement among CMs is worse, suggesting that the description of feedbacks is more uncertain. The contributions to material entropy production from vertical and horizontal processes are positively correlated, so that no compensation mechanism seems in place. Quite consistently among CMs, the variability of the efficiency of the system is a better proxy for variability of the entropy production due to horizontal processes than that of the large-scale heat flux. The possibility of providing constraints on the 3D dynamics of the fluid envelope based only on 2D observations of radiative fluxes seems promising for the observational study of planets and for testing numerical models. [ABSTRACT FROM AUTHOR]

During boreal summer, both the monsoon trough and the equatorial Indian Ocean (EIO) receive intense climatological precipitation. At various time scales, EIO sea surface temperature (SST) and/or precipitation variations interact with rainfall along the trough. For instance, during July–August in strong Indian Ocean dipole/zonal mode (IODZM) years, EIO experiences below-normal rainfall while regions along the monsoon trough receive above-normal rainfall. A lack of spatial coherency between SST and precipitation variations is noted in both regions. This paper posits the hypothesis that interaction between equatorial waves and moist physics is important in determining precipitation anomalies over these regions and in setting up the teleconnection. The hypothesis is tested using a linear baroclinic model (LBM). IODZM-related SST anomalies derived from multicentury integrations of the Geophysical Fluid Dynamics Laboratory coupled model (GFDL CM2.1) are used to force the LBM. Consistent with observations and CM2.1 composites of strong IODZM events, steady-state LBM solutions simulate zonally oriented negative (positive) precipitation anomalies over the EIO (along the monsoon trough). To identify the processes simulated in the LBM, moisture and moist static energy budgets are examined. Over both regions, analyses reveal that moisture advection contributes the most to the LBM budget, with advection of climatological moisture by the anomalous wind being the principal factor. Specifically, in response to cold SST anomalies in the EIO, moist stability due to surface fluxes increases, giving rise to below-normal rainfall. These conditions produce anomalous anticyclonic circulation as a Rossby wave response in the lower troposphere. Over the central-eastern EIO, this anomalous circulation advects climatological air of lower moisture content from the subtropics. In addition, advection of anomalous moisture by both climatological and anomalous wind results in anomalous dry conditions over the entire EIO. In contrast, anomalous divergent circulations that emanate from the EIO advect climatological air of higher moisture content from the equatorial region, amplifying rainfall along the monsoon trough. Consequently, the two regions are connected by a thermally driven overturning meridional circulation. Budget diagnostics performed with CM2.1 composites and the ECMWF interim reanalysis for observed IODZM events support the hypothesis. The results here imply that in coupled models, realistic representation of the basic state and details of the moist processes are necessary for successful monsoon prediction. [ABSTRACT FROM AUTHOR]

This paper presents the extension of the eddy diffusivity mass flux (EDMF) framework for turbulent transport into the statistical modeling of boundary layer clouds. The advection–diffusion decomposition that defines EDMF is projected onto the turbulent distribution as used in the statistical cloud model. Each EDMF component is thus assigned its own independent probability density function (PDF), resulting in an updraft PDF and a diffusive PDF. This double PDF system is configured and integrated in conserved variable space, with the position and orientation of each PDF determined by its unique nature. The parameterization of the associated updraft/diffusion decomposition of variance introduces close ties to the transport scheme; whereas the grid box mean variance is reconstructed using a prognostic variance budget, the variance of the updraft component is parameterized as a function of the spread among various resolved model updrafts. Individual model components and the scheme as a whole are evaluated in detail against large-eddy simulations of a number of prototype subtropical trade wind cases. The results show that various structures in cloud fraction, condensate, and variance are reproduced. The diffusive PDF acts to represent stratiform clouds; the advective PDF represents cumuliform clouds in conditionally unstable layers. This allows representation of complex scenarios in which both cloud forms occur, such as the transitional trade wind regime featuring cumulus rising into stratocumulus. [ABSTRACT FROM AUTHOR]

The present paper examines ways in which the seasonal cycle influences the evolution of El Niño in the tropical Pacific. The following hypotheses and associated physical mechanisms are investigated: (i) Hypothesis 1 (H1)—the seasonal warming of the cold tongue early in the calendar year (January–April) favors the initial growth of an event; (ii) hypothesis 2 (H2)—during an event, the warm surface waters migrating in the western basin from the Southern to the Northern Hemisphere during the northern spring (April–May) trigger enhanced convection along the equator, which contributes to reinforce the event; and (iii) hypothesis 3 (H3)—the warm surface waters returning in the western basin from the Northern to the Southern Hemisphere toward the end of the calendar year (November–January) favor the demise of ongoing events. Hypothesis-validation experiments are performed with a coupled atmosphere–ocean general circulation model (CGCM)—the tropical Pacific version of the University of California, Los Angeles (UCLA) CGCM. The anomaly-coupling technique is applied, in which the simulated seasonal cycle and interannual variability can be separated and artificially modified to highlight the aspect targeted for examination, thus allowing for comparisons of simulations in which seasonal conditions in the CGCM’s atmospheric component are either fixed or time varying. The results obtained in the experiments are supportive of hypotheses H1 and H3. No supportive evidence is found for the validity of hypothesis H2. [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 presents an extension of the recently developed method for simultaneous dimension reduction and metastability analysis of high-dimensional time series. The modified approach is based on a combination of ensembles of hidden Markov models (HMMs) with state-specific principal component analysis (PCA) in extended space (guaranteeing that the overall dynamics will be Markovian). The main advantage of the modified method is its ability to deal with the gaps in the high-dimensional observation data. The proposed method allows for (i) the separation of the data according to the metastable states, (ii) a hierarchical decomposition of these sets into metastable substates, and (iii) calculation of the state-specific extended empirical orthogonal functions simultaneously with identification of the underlying Markovian dynamics switching between those metastable substates. The authors discuss the introduced model assumptions, explain how the quality of the resulting reduced representation can be assessed, and show what kind of additional insight into the underlying dynamics such a reduced Markovian representation can give (e.g., in the form of transition probabilities, statistical weights, mean first exit times, and mean first passage times). The performance of the new method analyzing 500-hPa geopotential height fields [daily mean values from the 40-yr ECMWF Re-Analysis (ERA-40) dataset for a period of 44 winters] is demonstrated and the results are compared with information gained from a numerically expensive but assumption-free method (Wavelets–PCA), and the identified metastable states are interpreted w.r.t. the blocking events in the atmosphere. [ABSTRACT FROM AUTHOR]

The kinetic equation of stochastic condensation for cloud drop size spectra is extended to account for crystalline clouds and also to include the accretion–aggregation process. The size spectra are separated into small and large size fractions that correspond to cloud drops (ice) and rain (snow). In Part I of this two-part paper, analytical solutions are derived for the small-size fractions of the spectra that correspond to cloud drops and cloud ice particles that can be identified with cloud liquid water or cloud ice water content, and used in bulk microphysical schemes employed in cloud and climate models. Solutions for the small-size fraction have the form of generalized gamma distributions. Simple analytical expressions are found for parameters of the gamma distributions that are functions of quantities that are available in cloud and climate models: liquid or ice water content and its vertical gradient, mean particle radius or concentration, and supersaturation or vertical velocities. Equations for the gamma distribution parameters provide an explanation of the dependence of the observed spectra on atmospheric dynamics, cloud temperature, and cloud liquid water or ice water content. The results are illustrated with example calculations for a crystalline cloud. The analytical solutions and expressions for the parameters presented here can be used for parameterization of the small-size fraction size spectra in liquid and crystalline clouds and related quantities (e.g., optical properties, lidar, and radar reflectivities). [ABSTRACT FROM AUTHOR]

This paper presents statistical analyses of possible associations between major stratospheric sudden warming (SSW) and tropospheric blocking events in the Northern Hemisphere (NH) with 49 yr of NCEP–NCAR reanalysis data from 1957/58 to 2005/06. Using a random shuffling or “bootstrap” method, these analyses explore two hypotheses claiming that blocking events occur preferentially and last longer in association with SSWs (pre- and post-SSW periods are considered separately). In the shuffling method, the defined SSWs are randomly redistributed to evaluate the statistical significance of linked cases in the original data. The author’s analyses generally do not support either hypothesis for the pre- or post-SSW period when treating the SSW events all together, suggesting that such associations are not dominant modes of coupling. [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]

In this fifth of a series of papers describing the extended-time high cloud observation program from the University of Utah Facility for Atmospheric Remote Sensing, the structural properties of cirrus clouds over Salt Lake City, Utah, are examined. Wavelet analysis is applied to a 10-yr record of cirrus cloud ruby (0.694 μm) lidar backscatter data as a function of cloud height in order to study the presence of periodic cloud structures, such as the signatures of Kelvin–Helmholtz instabilities, cirrus mammata, and uncinus cells (all with length scales of ∼1–10 km), as well as mesoscale cloud organizations generally believed to be induced by gravity waves. About 8.4% of the data display structures after passing a 95% confidence level test, but an 80% confidence level, which seems better able to resolve structures spread over long periods, yields 16.4%. The amount of identified cloud structures does not change significantly with length scale from 0.2 to 200 km, although the frequency of mesoscale cloud structures tends to increase as length scales increase. The middle-to-lower portion of cirrus clouds contains the most identified cloud structures, which seems related to the mesoscale organization of fall streaks from cloud-top-generating cells. The variability of cirrus cloud optical depth τ (defined by the standard deviation over mean τ) derived from a combined lidar and infrared radiometer (LIRAD) analysis is shown to be largely independent of τ. Because visual examination of the lidar displays also indicates that few cirrus layers can be considered horizontally homogeneous over our typical 3-h lidar data collection period, the authors conclude that the clouds in their sample are inherently inhomogeneous even though most cirrus structures are not revealed as periodic by wavelet analysis. [ABSTRACT FROM AUTHOR]

Katabatic winds on ice sheets and glaciers are buoyancy-driven flows, much like turbidity currents in the ocean. These winds are driven by radiative cooling of the ice surface and are not resolved by the typical horizontal and vertical discretization of general circulation models; therefore, a parameterization of their magnitude is desirable. In this paper, it is shown that the simplest such parameterization, based on the classical Prandtl model of slope winds, is physically inadmissible, and an improved model, which removes this irregularity, is presented. It is also shown that the improved model allows favorable comparison with both observations and regional numerical models. [ABSTRACT FROM AUTHOR]

This paper provides a unified perspective on the dynamics of hurricane- and monsoonlike vortices by identifying them as specific limiting cases of a more general flow system. This more general system is defined as stationary axisymmetric balanced flow of a stably stratified non-Boussinesq atmosphere on the f plane. The model is based on the primitive equations assuming gradient wind balance in the radial momentum equation. The flow is forced by heating in the vortex center, which is implemented as relaxation toward a specified equilibrium temperature Te. The flow is dissipated through surface friction, and it is assumed to be almost inviscid in the interior. The heating is assumed supercritical, which means that Te does not allow a regular thermal equilibrium solution with zero surface wind, and which gives rise to a cross-vortex secondary circulation. Numerical solutions are obtained using time stepping to a steady state, where at each step the Eliassen secondary circulation is diagnosed as part of the solution strategy. Reality and regularity of the solution is discussed, putting this work in relation to previous work. Scaling analysis suggests that for a given geometry, essential vortex properties are controlled by the ratio F = αT/cD, where αT is the rate of thermal relaxation and cD quantifies the strength of surface friction for a given surface wind. For large F, the temperature is close to Te and the vortex shows properties that can be associated with a hurricane including strong cyclonic surface winds. On the other hand, for small F, the vortex shows properties that can be associated with a monsoon; that is, the surface winds are small and the secondary circulation keeps the temperature significantly away from Te. The scaling analysis is verified by numerical solutions spanning a wide range of the parameter space. It is shown how the two limiting cases correspond with the respective approximate semianalytical theories presented previously. The results imply an important role of αT for hurricane formation. [ABSTRACT FROM AUTHOR]

A successful description of a convective boundary layer requires that the model employed takes into account the nonlocal nature of turbulent convection. In this paper new third-order moments (TOMs) are presented and tested. Numerical solutions are obtained using mean flow components and second-order moments as input. The problem of the turbulent damping of the TOMs is considered. The terms in the dynamic equations responsible for the unphysical growth of the TOMs are parameterized, taking into account their dependence on the integral length scale vertical profile. The calculated profiles are presented and tested against large-eddy simulation data and aircraft measurements. In both cases the results compare favorably. [ABSTRACT FROM AUTHOR]

The interaction between synoptic eddy and low-frequency flow (SELF) has been recognized for decades to play an important role in the dynamics of the low-frequency variability of the atmospheric circulation. In this three-part study a linear framework with a stochastic basic flow capturing both the climatological mean flow and climatological measures of the synoptic eddy flow is proposed. Based on this linear framework, a set of linear dynamic equations is derived for the ensemble-mean eddy forcing that is generated by anomalous time-mean flows. By assuming that such dynamically determined eddy-forcing anomalies approximately represent the time-mean anomalies of the synoptic eddy forcing and by using a quasi-equilibrium approximation, an analytical nonlocal dynamical closure is obtained for the two-way SELF feedback. This linear closure, directly relating time-mean anomalies of the synoptic eddy forcing to the anomalous time–mean flow, becomes an internal part of a new linear dynamic system for anomalous time–mean flow that is referred to as the low-frequency variability of the atmospheric circulation in this paper. In Part I, the basic approach for the SELF closure is illustrated using a barotropic model. The SELF closure is tested through the comparison of the observed eddy-forcing patterns associated with the leading low-frequency modes with those derived using the SELF feedback closure. Examples are also given to illustrate an important role played by the SELF feedback in regulating the atmospheric responses to remote forcing. Further applications of the closure for understanding the dynamics of low-frequency modes as well as the extension of the closure to a multilevel primitive equation model will be given in Parts II and III, respectively. [ABSTRACT FROM AUTHOR]

Amidst stormy atmospheric circulation, there are prominent recurrent patterns of variability in the planetary circulation, such as the Antarctic Oscillation (AAO), Arctic Oscillation (AO) or North Atlantic Oscillation (NAO), and the Pacific–North America (PNA) pattern. The role of the synoptic eddy and low-frequency flow (SELF) feedback in the formation of these dominant low-frequency modes is investigated in this paper using the linear barotropic model with the SELF feedback proposed in Part I. It is found that the AO-like and AAO-like leading singular modes of the linear dynamical system emerge from the stormy background flow as the result of a positive SELF feedback. This SELF feedback also prefers a PNA-like singular vector as well among other modes under the climatological conditions of northern winters. A model with idealized conditions of basic mean flow and activity of synoptic eddy flow and a prototype model are also used to illustrate that there is a natural scale selection for the AAO- and AO-like modes through the positive SELF feedback. The zonal scale of the localized features in the Atlantic (southern Indian Ocean) for AO (AAO) is largely related to the zonal extent of the enhanced storm track activity in the region. The meridional dipole structures of AO- and AAO-like low-frequency modes are favored because of the scale-selective positive SELF feedback, which can be heuristically understood by the tilted-trough mechanism. [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]

The structure of westerly jets in a statistically steady state is investigated with both dry and moist models on the sphere. The dry model is forced with an idealized radiative equilibrium temperature profile that consists of a global-scale base profile plus both localized tropical heating and high-latitude cooling. The tropical heating controls the intensity of the subtropical jet, while the high-latitude cooling modulates the meridional width of the extratropical baroclinic zone. The jet structure is analyzed with a large number of dry model runs in which the tropical heating and high-latitude cooling rates are systematically varied. This parameter study shows that, in a regime with weak tropical heating and strong high-latitude cooling, the polar-front jet separates itself from the subtropical jet, forming a double-jet state. In contrast, if the tropical heating rate is greater than a certain value, a strong single jet emerges, indicating that the presence of one or two jets in a statistically steady state is dependent upon the relative values of both the tropical heating and the baroclinic zone width. A set of moist model runs is examined in which the moisture content is systematically varied. For a relatively small moisture content, the circulation prefers a double-jet state. However, for a moisture content that is greater than a certain threshold value, the two jets collapse into a single jet. With the aid of the aforementioned dry model results, an explanation for this nonlinear response exhibited by the moist model is provided. Based on the results of the dry and moist model calculations, this paper discusses various physical interpretations of the circulation responses to global warming presented in the literature. [ABSTRACT FROM AUTHOR]

One possible explanation for tropical sea surface temperature (SST) interannual variability is that it can be accurately described by a linear autoregressive model with damped coupled feedbacks and stochastic forcing. This autoregressive model can be viewed as a “null hypothesis” for tropical SST variability. This paper advances a new coupled general circulation model (CGCM) coupling strategy, called an interactive ensemble, as a method to test this null hypothesis. The design of the interactive ensemble procedure is to reduce the stochastic variability in the air–sea fluxes applied to the ocean component while retaining the deterministic component of the coupled feedbacks. The interactive ensemble procedure uses multiple realizations of the atmospheric GCM coupled to a single realization of the ocean GCM. The ensemble mean of the atmospheric GCM fluxes are applied to the ocean model thereby significantly reducing the variability due to internal atmospheric dynamics in the air–sea fluxes. If the null hypothesis is correct, the SST variability is reduced, and the autoregressive model defines how much the variability should be reduced. To test the null hypothesis, the interactive ensemble procedure is applied to a heuristic coupled model. Then the heuristic coupled model is used to interpret the CGCM interactive ensemble results with respect to (i) SST variance and (ii) how the amplitude of atmospheric internal dynamics depends on the evolving background SST anomaly. There are significant regions where the heuristic model fails to reproduce the CGCM results, suggesting that aspects of tropical Indo-Pacific variability in the CGCM cannot be explained by damped coupled feedbacks and stochastic forcing. These regions are largely coincident with regions of large convective anomalies. Surprisingly, significant regions were found in the tropical eastern Pacific where the variability due to internal ocean dynamics cannot be neglected. [ABSTRACT FROM AUTHOR]

The new double-moment microphysics scheme described in Part I of this paper is implemented into a single-column model to simulate clouds and radiation observed during the period 1 April–15 May 1998 of the Surface Heat Budget of the Arctic (SHEBA) and First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment–Arctic Clouds Experiment (FIRE–ACE) field projects. Mean predicted cloud boundaries and total cloud fraction compare reasonably well with observations. Cloud phase partitioning, which is crucial in determining the surface radiative fluxes, is fairly similar to ground-based retrievals. However, the fraction of time that liquid is present in the column is somewhat underpredicted, leading to small biases in the downwelling shortwave and longwave radiative fluxes at the surface. Results using the new scheme are compared to parallel simulations using other microphysics parameterizations of varying complexity. The predicted liquid water path and cloud phase is significantly improved using the new scheme relative to a single-moment parameterization predicting only the mixing ratio of the water species. Results indicate that a realistic treatment of cloud ice number concentration (prognosing rather than diagnosing) is needed to simulate arctic clouds. Sensitivity tests are also performed by varying the aerosol size, solubility, and number concentration to explore potential cloud–aerosol–radiation interactions in arctic stratus. [ABSTRACT FROM AUTHOR]

Recent theoretical studies, based on vortex Rossby wave (VRW) dynamics, have established the importance of the radial structure of the primary circulation in the response of tropical cyclone (TC)–like vortices to ambient vertical wind shear. Linear VRW theory suggests, in particular, that the degree of broadness of the primary circulation in the near-core region beyond the radius of maximum wind strongly influences whether a tilted TC vortex will realign and resist vertical shear or tilt over and shear apart. Fully nonlinear numerical simulations have verified that the vortex resiliency is indeed sensitive to the initial radial structure of the idealized vortex. This raises the question of how well the “true” nature of a TC’s primary circulation is represented by idealized vortices that are commonly used in some theoretical studies. In this paper the swirling wind structure of TCs is reexamined by utilizing flight-level observations collected from Atlantic and eastern Pacific storms during 1977–2001. Hundreds of radial profiles of azimuthal-mean tangential wind and relative vorticity are constructed from over 5000 radial flight leg segments and compared with some standard idealized vortex profiles. This analysis reaffirms that real TC structure in the near-core region is characterized by relatively slow tangential wind decay in conjunction with a skirt of significant cyclonic relative vorticity possessing a negative radial gradient. This broadness of the primary circulation is conspicuously absent in some idealized vortices used in theoretical studies of TC evolution in vertical shear. The relationship of the current findings to the problem of TC resiliency is discussed. [ABSTRACT FROM AUTHOR]

Offline atmospheric transport models are normally driven with meteorological analyses. However, subsequent analysis fields are dynamically not consistent with each other, because they are produced in independent data assimilation cycles that lack strong dynamical constraints between each other. In this paper, it is shown that when these data are used with Lagrangian transport models, spurious mixing results from the dynamic inconsistencies. As a consequence, quantities such as potential vorticity or specific humidity that tend to be conserved along trajectories are found to be significantly less well conserved when analysis data are used than when forecast data are used for the trajectory calculations. This leads, for instance, to enhanced stratosphere–troposphere exchange. It is also shown that the dispersion of initially neighboring particles occurs more rapidly with the analysis than with the forecast data. It is therefore concluded that small-scale tracer structures develop too quickly in Lagrangian models, due to the inconsistencies between the driving wind fields. [ABSTRACT FROM AUTHOR]

Because the land surface reflectance varies spatially, the atmospheric radiative transfer over land in clear-sky conditions is essentially three-dimensional. This is manifested through horizontal radiative fluxes that blur satellite images. It is important that the atmospheric blurring systematically increases the apparent brightness of the dark pixels. As a consequence, there are systematic biases in the satellite products of aerosol optical thickness and surface albedo over dark targets based on 1D theory, which may have a negative impact on climate research. Below, a new dark target method is presented for unbiased simultaneous retrieval of the aerosol model and optical thickness over land from Landsat Enhanced Thematic Mapper Plus (ETM+) data, based on 3D radiative transfer theory. The method automatically selects an aerosol model from a large set of candidate models using a statistical approach of the probability distribution function. The dark target method of aerosol retrieval in the blue and red bands relies on prediction of the surface reflectance in these bands from the shortwave infrared region (2.1–2.2 μm) based on the linear regression. In the Moderate Resolution Imaging Spectroradiometer (MODIS) algorithm, the regression coefficients are constants, whereas different studies indicate that they have seasonal and geographic variations. The work here shows that the accuracy of aerosol retrieval over land can be significantly increased based on ancillary information on the regional and seasonal distribution of the regression coefficients. This information, which is called surface climatology, can be derived globally around Aerosol Robotic Network (AERONET) sites, using AERONET aerosol and water vapor information for accurate atmospheric correction. This paper describes the developed method in application to Landsat data and its initial validation with AERONET measurements for a set of ETM+ images of the Washington–Baltimore area, and studies biases of 1D retrievals. [ABSTRACT FROM AUTHOR]

Prediction problems have been described by Lorenz as falling into two categories. Problems that depend on the initial condition, such as short- to medium-range weather forecasting, are described as “predictions of the first kind,” while problems that depend on boundary rather than initial conditions, such as, in many cases, the longer-term climatology, are referred to as predictions of the second kind. Both kinds of prediction will be affected by error in the model equations used to approximate the true system. In this paper, predictability over different timescales for the medium-dimensional Lorenz '96 systems is examined. Models are constructed for the purposes of optimizing both short-range prediction and climatological behavior, and studied over a range of forcings for which they show periodic, quasi-periodic, or chaotic behavior. It is shown that, for the models discussed here, there is a link between short- and long-range predictability, which is held independent of the effects of chaos. The role of stochastic terms is considered, and the possible implications for atmospheric or oceanographic modeling are discussed. [ABSTRACT FROM AUTHOR]

A systematic strategy for stochastic mode reduction is applied here to three prototype "toy" models with nonlinear behavior mimicking several features of low-frequency variability in the extratropical atmosphere. Two of the models involve explicit stable periodic orbits and multiple equilibria in the projected nonlinear climate dynamics. The systematic strategy has two steps: stochastic consistency and stochastic mode elimination. Both aspects of the mode reduction strategy are tested in an a priori fashion in the paper. In all three models the stochastic mode elimination procedure applies in a quantitative fashion for moderately large values of ∊ &ap; 0.5 or even ∊ &ap; 1, where the parameter ∊ roughly measures the ratio of correlation times of unresolved variables to resolved climate variables, even though the procedure is only justified mathematically for ∊ K 1. The results developed here provide some new perspectives on both the role of stable nonlinear structures in projected nonlinear climate dynamics and the regression fitting strategies for stochastic climate modeling. In one example, a deterministic system with 102 degrees of freedom has an explicit stable periodic orbit for the projected climate dynamics in two variables; however, the complete deterministic system has instead a probability density function with two large isolated peaks on the "ghost" of this periodic orbit, and correlation functions that only weakly "shadow" this periodic orbit. Furthermore, all of these features are predicted in a quantitative fashion by the reduced stochastic model in two variables derived from the systematic theory; this reduced model has multiplicative noise and augmented nonlinearity. In a second deterministic model with 101 degrees of freedom, it is established that stable multiple equilibria in the projected climate dynamics can be either relevant or completely irrelevant in the actual dynamics for the climate variable depending on the... [ABSTRACT FROM AUTHOR]

In the stratosphere, chemical tracers are drawn systematically from the equator to the pole. This observed Brewer-Dobson circulation is driven by wave drag, which in the stratosphere arises mainly from the breaking and dissipation of planetary-scale Rossby waves. While the overall sense of the circulation follows from fundamental physical principles, a quantitative theoretical understanding of the connection between wave drag and Lagrangian transport is limited to linear, small-amplitude waves. However, planetary waves in the stratosphere generally grow to a large amplitude and break in a strongly nonlinear fashion. This paper addresses the connection between stratospheric wave drag and Lagrangian transport in the presence of strong nonlinearity, using a mechanistic three-dimensional primitive equations model together with offline particle advection. Attention is deliberately focused on a weak forcing regime, such that sudden warmings do not occur and a quasi-steady state is reached, in order to examine this question in the cleanest possible context. Wave drag is directly linked to the transformed Eulerian mean (TEM) circulation, which is often used as a surrogate for mean Lagrangian motion. The results show that the correspondence between the TEM and mean Lagrangian velocities is quantitatively excellent in regions of linear, nonbreaking waves (i.e., outside the surf zone), where streamlines are not closed. Within the surf zone, where streamlines are closed and meridional particle displacements are large, the agreement between the vertical components of the two velocity fields is still remarkably good, especially wherever particle paths are coherent so that diabatic dispersion is minimized. However, in this region the meridional mean Lagrangian velocity bears little relation to the meridional TEM velocity, and reflects more the kinematics of mixing within and across the edges of the surf zone. The results from the mechanistic model are compared with those from... [ABSTRACT FROM AUTHOR]