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Two widely used approaches for parameterizing tracer transport based on convective mass fluxes are the plume ensemble formulation (PEF) and the bulk formulation (BF). Here the behavior of these two is contrasted for the specific case in which the BF airmass fluxes are derived as a direct simplification of an explicit PEF. Relative to the PEF, the BF has a greater rate of entrainment of midtropospheric air into the parcels that reach the highest altitudes, and thus is expected to compute less efficient transport of surface-layer tracers to the upper troposphere. In this study, this difference is quantified using a new algorithm for computing mass conserving, monotonic tracer transport for both the BF and PEF, along with a technique for decomposing a bulk mass flux profile into a set of consistent, discrete plumes for use in the PEF. Runs with a 3D global chemistry transport model (MATCH) show that the BF is likely to be an adequate approximation for most tracers with lifetimes of a week or longer. However, for short-lived tracers (lifetimes of a couple days or less) the BF results in significantly less efficient transport to the upper troposphere than the PEF, with differences exceeding 30% on a monthly zonal mean basis. Implications of these results for tropospheric chemistry are discussed.

A parameterization for specifying subgrid-scale cloud distributions in atmospheric models is developed. The fractional area of a grid-scale column in which clouds from two levels overlap (i.e., the cloud overlap probability) is described in terms of the correlation between horizontal cloudiness functions in the two levels. Cloud distributions that are useful for radiative transfer and cloud microphysical calculations are then determined from cloud fraction at individual model levels and a decorrelation depth. All pair-wise overlap probabilities among cloudy levels are obtained from the cloudiness correlations. However, those probabilities can overconstrain the determination of the cloud distribution. It is found that cloud fraction in each level along with the overlap probabilities among nearest neighbor cloudy levels is sufficient to specify the full cloud distribution. The parameterization has both practical and interpretative advantages over existing parameterizations. The parameterized cloud fields are consistent with physically meaningful distributions at arbitrary vertical resolution. In particular, bulk properties of the distribution, such as total cloud fraction and radiative fluxes calculated from it, approach asymptotic values as the vertical resolution increases. Those values are nearly obtained once the cloud distribution is resolved; that is, if the thickness of cloudy levels is less than one half of the decorrelation depth. Furthermore, the decorrelation depth can, in principle, be specified as a function of space and time, which allows one to construct a wide range of cloud distributions from any given vertical profile of cloud fraction. The parameterization is combined with radiative transfer calculations to examine the sensitivity of radiative fluxes to changes of the decorrelation depth. Calculations using idealized cloud distributions display strong sensitivities (~50 W [m.sup.-2]) to changes of decorrelation depth. Those sensitivities arise primarily from the sensitivity of total cloud fraction to that parameter. Radiative fluxes calculated from a version of the National Center for Atmospheric Research Community Climate Model (CCM) show only a small sensitivity. The reason for this small sensitivity is traced to the propensity of CCM to produce overcast conditions within individual model levels. Thus, in order for the parameterization to be fully useful, it is necessary that other cloud parameterizations in the atmospheric model attain a threshold of realism.

The effective radiative forcing of anthropogenic aerosols (ERFaer) is an important measure of the anthropogenic aerosol effects simulated by a global climate model. Here we analyze ERFaer simulated by the E3SMv1 atmosphere model using both century-long free-running atmosphere-land simulations and short nudged simulations. We relate the simulated ERFaer to characteristics of the aerosol composition and optical properties, and evaluate the relationships between key aerosol and cloud properties. In terms of historical changes from the year 1870 to 2014, our results show that the global mean anthropogenic aerosol burden and optical depth increase during the simulation period as expected, but the regional averages show large differences in the temporal evolution. The largest regional differences are found in the emission-induced evolution of the burden and optical depth of the sulfate aerosol: a strong decreasing trend is seen in the Northern Hemisphere high-latitude region after around 1970, while a continued increase is simulated in the tropics. Consequently, although the global mean anthropogenic aerosol burden and optical depth increase from 1870 to 2014, the ERFaer magnitude does not increase after around year 1970. The relationships between key aerosol and cloud properties (relative changes between preindustrial and present-day conditions) also show evident changes after 1970, diverging from the linear relationships exhibited for the period from 1870 to 2014. The ERFaer in E3SMv1 is relatively large compared to the recently published multi-model estimates; the primary reason is the large indirect aerosol effect (i.e., through aerosol-cloud interactions). Compared to other models, E3SMv1 features a stronger sensitivity of the cloud droplet effective radius to changes in the cloud droplet number concentration. Large sensitivity is also seen in the liquid cloud optical depth, which is determined by changes in both the effective radius and liquid water path. Aerosol-induced changes in liquid and ice cloud properties in E3SMv1 are found to have a strong correlation, as the evolution of anthropogenic sulfate aerosols affects both the liquid cloud formation and the homogeneous ice nucleation in cirrus clouds. The ERFaer estimates in E3SMv1 for the shortwave and longwave components are sensitive to the parameterization changes in both liquid and ice cloud processes. When the parameterization of ice cloud processes is modified, the top-of-atmosphere forcing changes in the shortwave and longwave components largely offset each other, so the net effect is negligible. This suggests that, to reduce the magnitude of the net ERFaer, it would be more effective to reduce the anthropogenic aerosol effect through liquid or mixed-phase clouds. [ABSTRACT FROM AUTHOR]

How the surface boundary heating (sea surface temperature) and cumulus adjustment process affect the location, structure, energetics, and dynamics of the intertropical convergence zones (ITCZs) is investigated. A series of experiments is performed with a general circulation model where the lower boundary is specified to be water at a fixed sea surface temperature (SST), an aqua planet. All experiments are run using equinoctal insolation with no longitudinal variation in SST. Two different convective parameterization schemes (Kuo and moist convective adjustment) and several different zonally symmetric SST distributions are used in these experiments. The location of the ITCZ is found to be sensitive to the convective parameterization scheme and the SST distribution. The model with the moist convective adjustment scheme produces an ITCZ over the tropical SST maximum, even under conditions where the SST gradient is weak. By contrast, the model with the Kuo convective parameterization is not as sensitive to SST distribution: the model with the Kuo scheme yields two ITCZs straddling the equator at approximately 7 degrees latitude for a wide variety of SST distributions, including when the warmest water is located on the equator. The location of the ITCZ affects the structure and strength of both the time-mean Hadley cells and the subtropical jets. Furthermore, the equatorial wave spectrum is strongly influenced by the type of cumulus parameterization scheme used. The 'convective characteristics' for each parameterization scheme are presented in detail to elucidate the influence of the large-scale environment on convection.

Numerical models used in weather and climate prediction take into account a comprehensive set of atmospheric processes such as the resolved and unresolved fluid dynamics, radiative transfer, cloud and aerosol life cycles, and mass or energy exchanges with the Earth's surface. In order to identify model deficiencies and improve predictive skills, it is important to obtain process-level understanding of the interactions between different processes. Conditional sampling and budget analysis are powerful tools for process-oriented model evaluation, but they often require tedious ad hoc coding and large amounts of instantaneous model output, resulting in inefficient use of human and computing resources. This paper presents an online diagnostic tool that addresses this challenge by monitoring model variables in a generic manner as they evolve within the time integration cycle. The tool is convenient to use. It allows users to select sampling conditions and specify monitored variables at run time. Both the evolving values of the model variables and their increments caused by different atmospheric processes can be monitored and archived. Online calculation of vertical integrals is also supported. Multiple sampling conditions can be monitored in a single simulation in combination with unconditional sampling. The paper explains in detail the design and implementation of the tool in the Energy Exascale Earth System Model (E3SM) version 1. The usage is demonstrated through three examples: a global budget analysis of dust aerosol mass concentration, a composite analysis of sea salt emission and its dependency on surface wind speed, and a conditionally sampled relative humidity budget. The tool is expected to be easily portable to closely related atmospheric models that use the same or similar data structures and time integration methods. [ABSTRACT FROM AUTHOR]

A novel decomposition of the ocean heat energy that contributes to sea ice melt and growth (ocean‐ice and frazil heat) into components that are driven by surface heat flux and ocean circulation changes is used to isolate the evolving roles of the atmosphere and ocean in the Arctic sea ice loss from CO2 increases. A sea ice volume budget analysis is used to separate the impacts of the anomalous frazil/ocean‐ice heat from those of atmosphere‐ice heat on the evolving Arctic sea ice volume. The role of atmosphere‐ocean coupling in augmenting or curtailing the atmosphere‐ and ocean‐driven sea ice losses is further isolated by comparing the ice volume budget and the anomalous frazil/ocean‐ice heat components in partially and fully coupled experiments. Atmosphere‐ice heat fluxes drive most of Arctic sea ice loss in the first decade following CO2 increase by increasing the sea ice top face melt in summer, while ocean circulation changes drive the loss over the longer term through the anomalous increase of heat transport into the Arctic, which drive decreases in frazil ice growth and sea ice extent in winter. Atmosphere‐ocean coupling in the subpolar Atlantic further supports a negative feedback that attenuates the ocean‐driven sea ice losses over time; by accelerating the weakening of the Atlantic meridional overturning circulation, it causes a large cooling of the subpolar Atlantic and attenuation of the anomalous heat transport into the Arctic in winter, allowing for a seasonal Arctic sea ice in the fully coupled experiment, while the Arctic completely becomes ice free in the partially coupled experiment. Plain Language Summary: The interactions between the atmosphere, ocean, and sea ice are disentangled in order to isolate their individual roles in driving Arctic sea ice losses and how these roles change over time. We introduce a new decomposition of the ocean heat that contributes to melting and growing sea ice into parts that are caused by changes in the surface heat input into the ocean and ocean circulation. We analyze the contributions of the ocean heat and atmosphere heat to the overall Arctic sea ice volume changes, both in an experiment where a two‐way interaction between the atmosphere and ocean is allowed and in another where this two‐way interaction is not allowed. Our results suggest that the atmosphere causes most of Arctic sea ice loss (within a decade) by increasing sea ice top face melt, while the ocean causes the long‐term sea ice changes in the Arctic by decreasing winter bottom face growth. The interactions between the atmosphere and ocean further enhance the ocean circulation weakening and surface cooling in the subpolar Atlantic and thereby stop the winter heat transport increase into the Arctic and eventually curtail the ocean‐driven sea ice loss and prevent the total loss of Arctic sea ice. Key Points: A novel decomposition isolates how ocean surface heating, circulation changes, and air‐sea interactions drive sea ice loss from CO2 increasesAtmosphere changes determine Arctic sea ice loss within the first decade; ocean circulation changes drive longer term ice lossesAtmosphere‐ocean coupling feedbacks on ocean circulation change in the subpolar Atlantic stabilizes Arctic sea ice loss in the long term [ABSTRACT FROM AUTHOR]

Quantifying teleconnections and discovering new ones is a complex, difficult process. Using transfer functions, we introduce a new method of identifying teleconnections in climate models on arbitrary timescales. We validate this method by perturbing temperature in the Nino3.4 region in a climate model. Temperature and precipitation responses in the model match known El Nino-Southern Oscillation (ENSO)-like teleconnection features, consistent with modes of tropical variability. Perturbing the Nino3.4 region results in temperature responses consistent with the Pacific Meridional Mode, the Pacific Decadal Oscillation, and the Indian Ocean Dipole, all of which have strong ties to ENSO. Some precipitation features are also consistent with these modes of variability, although because precipitation is noisier than temperature, obtaining robust responses is more difficult. While much work remains to develop this method further, transfer functions show promise in quantifying teleconnections or, perhaps, identifying new ones. [ABSTRACT FROM AUTHOR]