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John P. Iselin and William J. Gutowski Jr.

Abstract

The STORM-FEST (Fronts Experiment Systems Test) rawinsonde data were analyzed to determine the abundance and characteristics of moist layers within the troposphere. A moist layer was defined as a local maximum in relative humidity with lower relative humidity air above and below. Moist layers under the criteria occur in over half the soundings with an average location between 600 and 500 mb and an average thickness of approximately 120 mb. The layers also appeared to be more nearly aligned with isentropic, rather than isobaric, surfaces. Compositing of relative humidity profiles with a layer at approximately the same level showed an increase in lapse rate at the top of moist layers indicating that the layers are contained by dynamic mechanisms. In addition, there was no diurnal cycle to the characteristics of the layers. These factors suggest a close relationship between the layers and large-scale dynamics. An examination of spatial continuity suggests a horizontal scale of a few hundred kilometers. Their appearance poses a challenge for numerical modeling of atmospheric water vapor. Furthermore, limitations of the two types of rawinsonde instruments used in STORM-FEST are apparent in some characteristics of the layers, thus indicating instrumentation challenges posed by these structures for observing the atmospheric branch of the hydrological cycle.

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John P. Iselin, William J. Gutowski, and Joseph M. Prusa

Abstract

A dynamic grid adaptation (DGA) technique is used to numerically simulate tracer transport at meso- and regional scales. A gridpoint redistribution scheme is designed to maximize heuristic characteristics of a “good” grid. The advective solver used in conjunction with the DGA is the multidimensional positive definite advection transport algorithm (MPDATA). The DGA results for regional tracer transport are compared against results generated using the leapfrog as well as MPDATA advection schemes with uniformly spaced, static grids. Wind fields for all tracer transport algorithms are provided by the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5). A mesoscale-sized test case with idealized initial condition and wind field clearly shows qualitatively and quantitatively the advantage of using the dynamic adaptive grid, which is a marked reduction in numerical error. These results are further corroborated by more realistic test cases that used NCEP–NCAR reanalysis data from 6–11 March 1992 to set initial and boundary conditions for (i) a mesoscale-sized, 24-h simulation with an idealized initial tracer field, and (ii) a regional, 5-day simulation with water vapor field initialized from the reanalysis data but then treated as a passive tracer. A result of interest is that MPDATA substantially outperforms the leapfrog method with fourth-order artificial dissipation (central to MM5) in all of our test cases. We conclude that with dynamic grid adaptation, results with approximately the same accuracy as a uniform grid may be obtained using only a quarter of the grid points of the uniform grid MPDATA simulations. Compared to results generated using the leapfrog method on a uniform grid, the DGA does even better.

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John P. Iselin, Joseph M. Prusa, and William J. Gutowski

Abstract

A dynamic grid adaptation (DGA) scheme is developed using various combinations of the multidimensional positive definite advection transport algorithm (MPDATA) to show the applicability of DGA with the MPDATA scheme to solve advection problems. A one-dimensional model is used to show the effects of varying the number of grid points and the parameters that control the grid redistribution scheme, to determine a stability criteria for the scheme and to investigate the effect of several MPDATA options. A two-dimensional model is used to show the applicability of the scheme in multiple dimensions and to illustrate the effects of DGA in combination with MPDATA options. Diffusion errors are reduced by more than 90% using DGA when compared to static, uniformly spaced grid computations. Phase errors are reduced using certain MPDATA options by more than 25%.

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