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Ross Heikes
and
David A. Randall

Abstract

The streamfunction-velocity potential form of shallow-water equations, implemented on a spherical geodesic grid, offers an attractive solution to many of the problems associated with fluid-flow simulations in a spherical geometry. Here construction of a new type of spherical geodesic grid is outlined, and discretization of the equations is explained. The model is subjected to the NCAR suite of seven test cases for shallow-water models.

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Ross Heikes
and
David A. Randall

Abstract

The finite-difference scheme for the Laplace and flux-divergence operators described in the companion paper (Part I) is consistent when applied on a grid consisting of perfect hexagons. The authors describe a necessary and sufficient condition for this finite-difference scheme to be consistent when applied on a grid consisting of imperfect hexagons and pentagons, and present an algorithm for generating a spherical geodesic grid on a sphere that guarantees that this condition is satisfied. Also, the authors qualitatively describe the error associated with the operators and estimate their order of accuracy when applied on the new grid.

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Ross Gunn
and
Paul A. Allee
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A. N. Ross
,
A. M. Tompkins
, and
D. J. Parker

Abstract

Gravity-current models have been used for many years to describe the cold pools of low-level air that are generated by cumulonimbus precipitation. More recently, it has been realized that surface fluxes of heat and water vapor can be important in modifying these flows, through turbulent mixing of buoyancy by convection, and through direct modification of the cold pool buoyancy. In this paper, simple models describing the role of surface fluxes in depleting the negative buoyancy of a gravity current and the consequences of this for the flow dynamics are discussed.

It is pointed out that the depletion of cold pool buoyancy by surface fluxes is analogous to the depletion of buoyancy in a turbidity current through particle sedimentation, and in one regime of parameter values the analogy is exact. This analogy allows one to use simple flow models that have been tested extensively against laboratory experiments on turbidity currents. A simple “box model” and a more sophisticated shallow water model are each developed. It is shown how these models can give relatively simple expressions for cold pool “runout length” and buoyancy distributions. These runout lengths compare well with maximum cold pool sizes previously observed in cloud-resolving model simulations of unorganized tropical deep convection.

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Allan Frei
,
Ross Brown
,
James A. Miller
, and
David A. Robinson

Abstract

Eighteen global atmospheric general circulation models (AGCMs) participating in the second phase of the Atmospheric Model Intercomparison Project (AMIP-2) are evaluated for their ability to simulate the observed spatial and temporal variability in snow mass, or water equivalent (SWE), over North America during the AMIP-2 period (1979–95). The evaluation is based on a new gridded SWE dataset developed from objective analysis of daily snow depth observations from Canada and the United States with snow density estimated from a simple snowpack model. Most AMIP-2 models simulate the seasonal timing and the relative spatial patterns of continental-scale SWE fairly well. However, there is a tendency to overestimate the rate of ablation during spring, and significant between-model variability is found in every aspect of the simulations, and at every spatial scale analyzed. For example, on the continental scale, the peak monthly SWE integrated over the North American continent in AMIP-2 models varies between ±50% of the observed value of ∼1500 km3. The volume of water in the snowpack, and the magnitudes of model errors, are significant in comparison to major fluxes in the continental water balance. It also appears that the median result from the suite of models tends to do a better job of estimating climatological mean features than any individual model. Year-to-year variations in large-scale SWE are only weakly correlated to observed variations, indicating that sea surface temperatures (specified from observations as boundary conditions) do not drive interannual variations of SWE in these models. These results have implications for simulations of the large-scale hydrologic cycle and for climate change impact assessments.

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Ross P. Heikes
,
David A. Randall
, and
Celal S. Konor

Abstract

This paper discusses the generation of icosahedral hexagonal–pentagonal grids, optimization of the grids, how optimization affects the accuracy of finite-difference Laplacian, Jacobian, and divergence operators, and a parallel multigrid solver that can be used to solve Poisson equations on the grids. Three different grid optimization methods are compared through an error convergence analysis. The optimization process increases the accuracy of the operators. Optimized grids up to 1-km grid spacing over the earth have been created. The accuracy, performance, and scalability of the multigrid solver are demonstrated.

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Mary McRae
,
Ross A. Lee
,
Scott Steinschneider
, and
Frank Galgano
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Luke J. LeBel
,
Brian H. Tang
, and
Ross A. Lazear

Abstract

The complex terrain at the intersection of the Mohawk and Hudson valleys of New York has an impact on the development and evolution of severe convection in the region. Specifically, previous research has concluded that terrain-channeled flow in the Mohawk and Hudson valleys likely contributes to increased low-level wind shear and instability in the valleys during severe weather events such as the historic 31 May 1998 event that produced a strong (F3) tornado in Mechanicville, New York. The goal of this study is to further examine the impact of terrain channeling on severe convection by analyzing a high-resolution WRF Model simulation of the 31 May 1998 event. Results from the simulation suggest that terrain-channeled flow resulted in the localized formation of an enhanced low-level moisture gradient, resembling a dryline, at the intersection of the Mohawk and Hudson valleys. East of this boundary, the environment was characterized by stronger low-level wind shear and greater low-level moisture and instability, increasing tornadogenesis potential. A simulated supercell intensified after crossing the boundary, as the larger instability and streamwise vorticity of the low-level inflow was ingested into the supercell updraft. These results suggest that terrain can have a key role in producing mesoscale inhomogeneities that impact the evolution of severe convection. Recognition of these terrain-induced boundaries may help in anticipating where the risk of severe weather may be locally enhanced.

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Daniel Gombos
,
Ross N. Hoffman
, and
James A. Hansen

Abstract

Ensemble regression (ER) is a simple linear inverse technique that uses correlations from ensemble model output to make inferences about dynamics, models, and forecasts. ER defines a multivariate regression operator in the principal component subspaces of ensemble forecasts and analyses of atmospheric fields. ER uses the ensemble members of a predictor and a predictand field as training samples to compute the ensemble anomaly (with respect to the ensemble mean of the predictand field) with which a dynamically relevant ensemble anomaly (with respect to the ensemble mean of the predictor field) is linearly related. Specifically, an ER operator defined by the Japan Meteorological Agency’s ensemble forecast 500-hPa geopotential height and 1000-hPa potential vorticity is used to show that Supertyphoon Sepat’s (2007) track strongly covaried with the position and strength of the antecedent steering subtropical high to its northeast and the trough to its northwest. The case study illustrates how ER can identify, in real time, the dynamical processes that are particularly relevant for operational forecasters to make specific forecasting decisions and can help researchers to infer physical relationships from multivariate statistical sensitivities.

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Robert S. Ross
,
T. N. Krishnamurti
,
S. Pattnaik
, and
A. Simon

Abstract

This paper provides an understanding of essential differences between developing and nondeveloping African easterly waves, which was a major goal of NAMMA, NASA’s field program in the eastern Atlantic, which functioned as an extension of the African Monsoon Multidisciplinary Analysis (AMMA) program during 2006.

Three NAMMA waves are studied in detail using FNL analysis: NAMMA wave 2, which developed into Tropical Storm Debby; NAMMA wave 7, which developed into Hurricane Helene; and NAMMA wave 4, which did not develop within the NAMMA domain. Diagnostic calculations are performed on the analyzed fields using energy transformation equations and the isentropic potential vorticity equation.

The results show that the two developing waves possess clear and robust positive barotropic energy conversion in conjunction with positive diabatic heating that includes a singular burst of heating at a particular time in the wave’s history. This positive barotropic energy conversion is facilitated in waves that have a northeast–southwest tilt to the trough axis and a wind maximum to the west of this axis. The nondeveloping wave is found to have the same singular burst of diabatic heating at one point in its history, but development of the wave does not occur due to negative barotropic energy conversion. Such conversion is facilitated by a northwest–southeast tilt to the trough axis and a wind maximum to the east of this axis.

The conclusions about wave development and nondevelopment formulated in this research are viewed as important and significant, but they require additional testing with detailed observational- and numerical-based studies.

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