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V. Balaji and Terry L. Clark

Abstract

Deep cumulus dynamics has often been treated as an initial value problem where the long time effect of surface energy fluxes are neglected. Initiation is often assumed to follow from a strong localized deformation of the flow field, which is elsewhere quiescent. In nature, however, the atmosphere is rarely found in an undisturbed condition just prior to the inception of deep growth. One likely cause of widespread motions is the natural modal response of the environment to surface energy fluxes which results in a field of disturbances. Evidence is presented in this paper for the possible existence of a class of solutions when deep convection is allowed to evolve in the context of a thermally forced field of shallow convection. This class of solutions is neglected when one visualizes the growth of severe local storms in term of buoyant bubbles in an otherwise tranquil atmosphere. Considering deep cumulus initiation as a field problem severely limits the concept of an isolated cloud. Individual clouds may owe much of their structure to the existence of, and interaction with, the field of thermally forced deep normal modes. The importance of the local forcing terms is demonstrated here through a numerical simulation of the evolution of deep and severe convection out of a locally forced shallow cloud field in the absence of large scale forcing.

When convection is initiated over the entire domain locally through thermal forcing at the ground, the modal solution first observed corresponds to the Rayleigh solution which consist of modes confined to the boundary-layer. However, solutions in the deep linear equations show that a second modal solution also exists. The dominance of this solution, which consists of deep modes of longer horizontal wavelength, is shown here to lead to deep convection.

While the contribution of local forcing terms to the overall energy budget may be negligible at the severe convective stage, the mechanism of initiation appears to influence the pattern of evolution even into the mature stage. At the stage of shallow cumulus, the well-known phenomenon of upshear cumulus development is observed. As clouds grow deeper, an interesting phenomenon of phase-decoupled modal solutions is observed:. the growth of clouds appears to decouple the boundary-layer horizontal motions in phase from the stable layer motions, an effect that cyclically enhances and suppresses cloud growth. A characteristic time may be computed, and average cloud longevity inferred. Finally; the interaction of a moving storm system in its severe stage with the boundary-layer modes appears to provide one explanation for the spatial and temporal distribution of new convective cells in a multicellular storm system.

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Olivier Pauluis, V. Balaji, and Isaac M. Held
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K. Aydin, T. A. Seliga, and V. Balaji

Abstract

A technique for the remote sensing of hail with an S-band dual linear polarization radar is described. The method employs a new hail signal HDR, which is derived from disdrometer measurements of raindrop size distributions. Experimental measurements, made in Colorado with the National Center for Atmospheric Research's (NCAR) CP-2 radar system, are used to demonstrate the technique in two major hailstorms.

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Olivier Pauluis, V. Balaji, and Isaac M. Held

Abstract

The frictional dissipation in the shear zone surrounding falling hydrometeors is estimated to be 2–4 W m−2 in the Tropics. A numerical model of radiative–convective equilibrium with resolved three-dimensional moist convection confirms this estimate and shows that the precipitation-related dissipation is much larger than the dissipation associated with the turbulent energy cascade from the convective scale. Equivalently, the work performed by moist convection is used primarily to lift water rather than generate kinetic energy of the convective airflow. This fact complicates attempts to use the entropy budget to derive convective velocity scales.

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Stephen M. Griffies, Ronald C. Pacanowski, Martin Schmidt, and V. Balaji

Abstract

This paper details a free surface method using an explicit time stepping scheme for use in z-coordinate ocean models. One key property that makes the method especially suitable for climate simulations is its very stable numerical time stepping scheme, which allows for the use of a long density time step, as commonly employed with coarse-resolution rigid-lid models. Additionally, the effects of the undulating free surface height are directly incorporated into the baroclinic momentum and tracer equations. The novel issues related to local and global tracer conservation when allowing for the top cell to undulate are the focus of this work. The method presented here is quasi-conservative locally and globally of tracer when the baroclinic and tracer time steps are equal. Important issues relevant for using this method in regional as well as large-scale climate models are discussed and illustrated, and examples of scaling achieved on parallel computers provided.

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V. Balaji, J-L. Redelsperger, and G. P. Klaassen

Abstract

Mesoscale cloud clusters are a frequently observed feature of the tropical atmosphere and are primarily responsible for the observed large-scale vertical mass flux. Given that the forcing for such convection comes from widely separated horizontal scales (boundary-layer motions on the scale of 1 km and weak ascent on a scale of over 1000 km), the persistent organization of cloud clusters into the scale 10–50 km presents an important problem.

In this article, Part I, two- and three-dimensional numerical simulations of convection under a capping inversion at 2 km are presented to demonstrate that the mechanism responsible for mesoscale organization of clouds requires neither deep convection nor large-scale forcing. The case study used as a basis for these simulations is one of several instances reported by LeMone and Meitin of mesoscale cloud bands during GATE Phase III. These observations are remarkable in that the cloud bands are shallow, yet possess a rather large horizontal periodicity in the range 15–30 km. The profile in this case is typical of the disturbed conditions of GATE Phase III, where the African easterly jet has undergone rotation due to a passing easterly wave trough. The result is a turning wind profile where the mean shear in the boundary layer is perpendicular to the shear in the lower troposphere, a case that leads to line organization. It is shown that mesoscale organization of the shallow cloud bands can be attributed to a mechanism where the scale selection is modified by the presence of deep gravity wave modes above the cloud layer. This particular case differs from earlier studies in that both trapped and propagating modes (each class possessing a distinct dominant horizontal scale) are excited in the free troposphere.

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D. Paradis, J-P. Lafore, J-L. Redelsperger, and V. Balaji

Abstract

A linearized version of a nonhydrostatic model is used to study the normal-mode selection and the structure of the African easterly waves in dry and moist environments associated with an idealized African easterly jet structure. The dry mode reproduces the principal observed characteristics of the lower troposphere, in particular the low-level ascent and convergence in the trough. A simple CISK-type parameterization improves the upper-level circulation. A budget of kinetic energy shows barotropic and baroclinic contributions and adequately reproduces the analysis of Norquist et al. The scale selection and the structure of the most unstable mode appears sensitive to the jet structure, in particular to the meridional and vertical shear. Several discrepancies between observations and these linear modes emphasize the importance of an accurate description of convection.

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S. Zhang, M. J. Harrison, A. T. Wittenberg, A. Rosati, J. L. Anderson, and V. Balaji

Abstract

As a first step toward coupled ocean–atmosphere data assimilation, a parallelized ensemble filter is implemented in a new stochastic hybrid coupled model. The model consists of a global version of the GFDL Modular Ocean Model Version 4 (MOM4), coupled to a statistical atmosphere based on a regression of National Centers for Environmental Prediction (NCEP) reanalysis surface wind stress, heat, and water flux anomalies onto analyzed tropical Pacific SST anomalies from 1979 to 2002. The residual part of the NCEP fluxes not captured by the regression is then treated as stochastic forcing, with different ensemble members feeling the residual fluxes from different years. The model provides a convenient test bed for coupled data assimilation, as well as a prototype for representing uncertainties in the surface forcing.

A parallel ensemble adjustment Kalman filter (EAKF) has been designed and implemented in the hybrid model, using a local least squares framework. Comparison experiments demonstrate that the massively parallel processing EAKF (MPPEAKF) produces assimilation results with essentially the same quality as a global sequential analysis. Observed subsurface temperature profiles from expendable bathythermographs (XBTs), Tropical Atmosphere Ocean (TAO) buoys, and Argo floats, along with analyzed SSTs from NCEP, are assimilated into the hybrid model over 1980–2002 using the MPPEAKF. The filtered ensemble of SSTs, ocean heat contents, and thermal structures converge well to the observations, in spite of the imposed stochastic forcings. Several facets of the EAKF algorithm used here have been designed to facilitate comparison to a traditional three-dimensional variational data assimilation (3DVAR) algorithm, for instance, the use of a univariate filter in which observations of temperature only directly impact temperature state variables. Despite these choices that may limit the power of the EAKF, the MPPEAKF solution appears to improve upon an earlier 3DVAR solution, producing a smoother, more physically reasonable analysis that better fits the observational data and produces, to some degree, a self-consistent estimate of analysis uncertainties. Hybrid model ENSO forecasts initialized from the MPPEAKF ensemble mean also appear to outperform those initialized from the 3DVAR analysis. This improvement stems from the EAKF’s utilization of anisotropic background error covariances that may vary in time.

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Dean N. Williams, V. Balaji, Luca Cinquini, Sébastien Denvil, Daniel Duffy, Ben Evans, Robert Ferraro, Rose Hansen, Michael Lautenschlager, and Claire Trenham

Abstract

Working across U.S. federal agencies, international agencies, and multiple worldwide data centers, and spanning seven international network organizations, the Earth System Grid Federation (ESGF) allows users to access, analyze, and visualize data using a globally federated collection of networks, computers, and software. Its architecture employs a system of geographically distributed peer nodes that are independently administered yet united by common federation protocols and application programming interfaces (APIs). The full ESGF infrastructure has now been adopted by multiple Earth science projects and allows access to petabytes of geophysical data, including the Coupled Model Intercomparison Project (CMIP)—output used by the Intergovernmental Panel on Climate Change assessment reports. Data served by ESGF not only include model output (i.e., CMIP simulation runs) but also include observational data from satellites and instruments, reanalyses, and generated images. Metadata summarize basic information about the data for fast and easy data discovery.

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Lakshmi Krishnamurthy, Gabriel A. Vecchi, Xiaosong Yang, Karin van der Wiel, V. Balaji, Sarah B. Kapnick, Liwei Jia, Fanrong Zeng, Karen Paffendorf, and Seth Underwood

Abstract

Unprecedented high-intensity flooding induced by extreme precipitation was reported over Chennai in India during November–December of 2015, which led to extensive damage to human life and property. It is of utmost importance to determine the odds of occurrence of such extreme floods in the future, and the related climate phenomena, for planning and mitigation purposes. Here, a suite of simulations from GFDL high-resolution coupled climate models are used to investigate the odds of occurrence of extreme floods induced by extreme precipitation over Chennai and the role of radiative forcing and/or large-scale SST forcing in enhancing the probability of such events in the future. The climate of twentieth-century experiments with large ensembles suggest that the radiative forcing may not enhance the probability of extreme floods over Chennai. Doubling of CO2 experiments also fails to show evidence for an increase of such events in a global warming scenario. Further, this study explores the role of SST forcing from the Indian and Pacific Oceans on the odds of occurrence of Chennai-like floods. Neither El Niño nor La Niña enhances the probability of extreme floods over Chennai. However, a warm Bay of Bengal tends to increase the odds of occurrence of extreme Chennai-like floods. In order to trigger a Chennai like-flood, a conducive weather event, such as a tropical depression over the Bay of Bengal with strong transport of moisture from a moist atmosphere over the warm Bay, is necessary for the intense precipitation.

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