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Alexander I. Falkovich, Alexander P. Khain, and Isaac Ginis

Abstract

The interaction of binary tropical cyclones (TC) is investigated using a coupled TC-ocean movable nested-grid model. The model consists of an eight-layer atmospheric model in the sigma coordinate system and a three-layer primitive equation ocean model. There are five meshes in the TC model. The outermost domain (3840 km × 3840 km) is motionless. For the description of each TC in a TC pair, two telescopically nested meshes of finer resolution are used. The pair of the middle (1600 km × 1600 km) and innermost (800 km × 800 km) meshes move with the center of a corresponding TC. The space increments of the outermost domain and the middle and finest meshes are 160, 80, and 40 km. The oceanic domain contains 107 × 107 grid points, with the spatial increment of 40 km. In all numerical experiments a pair of equal strength axisymmetric vortices was located at different separation distances.

Experiments show that the rate of development of interacting TCs is different, mainly due to the difference in the velocities of TC movement. There is a “critical” separation distance between the centers of TCs, so that in case the separation distance is less than this critical value, attraction and merger of the TCs were observed. The critical separation distance depends on the structure of the vorticity field created by the binary TCs. Because of the changes in the structure of a TC during its life cycle the critical separation distance should also change. Two mechanisms related to the mutual vorticity advection and to the activity of irrotational velocity components seem to contribute to the attraction and repulsion of binary TCs.

The impact of the TC-ocean interaction on the evolution and trajectory of binary TCs is much stronger than in the case of a single TC. A decrease in TC strength is related not only to a TC response to seawater cooling caused by the TC itself but also to the crossing of the cold water wakes created both by the other TC and by the TC itself. A decrease in strength loads to a decrease in the mutual rotation velocity and, consequently, to a marked change in the trajectories of each of the interacting TCs. Changes in the structure of binary TCs caused by the TC-ocean interaction lead to an increase of the critical separation distance. Binary TCs cause seawater cooling over vast ocean areas and lead to the formation of a spotted sea surface temperature pattern.

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Barry H. Lynn, Alexander P. Khain, Jimy Dudhia, Daniel Rosenfeld, Andrei Pokrovsky, and Axel Seifert

Abstract

Considerable research investments have been made to improve the accuracy of forecasting precipitation systems in cloud-resolving, mesoscale atmospheric models. Yet, despite a significant improvement in model grid resolution and a decrease in initial condition uncertainty, the accurate prediction of precipitation amount and distribution still remains a difficult problem. Now, the development of a fast version of spectral (bin) microphysics (SBM Fast) offers significant potential for improving the description of precipitation-forming processes in mesoscale atmospheric models.

The SBM Fast is based on solving a system of equations for size distribution functions for water drops and three types of ice crystals (plates, columns, and dendrites), as well as snowflakes, graupel, and hail/frozen drops. Ice processes are represented by three size distributions, instead of six in the original SBM code. The SBM uses first principles to simulate microphysical processes such as diffusional growth and collision. A budget for aerosols is used to obtain the spectrum of condensation nuclei, which is used to obtain the initial drop spectrum. Hence, SBM allows one to take into account aerosol effects on precipitation, and corresponding cloud effects on the atmospheric aerosol concentration and distribution. SBM Fast has been coupled with the three-dimensional fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5), which allows SBM Fast to simulate microphysics within a realistic, time-varying mesoscale environment.

This paper describes the first three-dimensional SBM mesoscale model and presents results using 1-km resolution to simulate initial development of a cloud system over Florida on 27 July 1991. The focus is on initial cloud development along the west coast, just prior to sea-breeze formation. The results indicate that the aerosol concentration had a very important impact on cloud dynamics, microphysics, and rainfall.

Vertical cross sections of clouds obtained using SBM Fast are compared to those from a version of the “Reisner2” bulk-parameterization scheme that uses the Kessler autoconversion formula. The results show that this version of “Reisner2” produced vertically upright clouds that progressed very quickly from initial cloud formation to raindrop formation. In contrast, clouds obtained using SBM were relatively long lasting with greater production of stratiform clouds.

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Barry H. Lynn, Alexander P. Khain, Jimy Dudhia, Daniel Rosenfeld, Andrei Pokrovsky, and Axel Seifert

Abstract

Spectral (bin) microphysics (SBM) has been implemented into the three-dimensional fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5). The new model was used to simulate a squall line that developed over Florida on 27 July 1991. It is shown that SBM reproduces precipitation rate, rain amounts, and location, radar reflectivity, and cloud structure much better than bulk parameterizations currently implemented in MM5.

Sensitivity tests show the importance of (i) raindrop breakup, (ii) in-cloud turbulence, (iii) different aerosol concentrations, and (iv) inclusion of scavenging of aerosols. Breakup decreases average and maximum rainfall. In-cloud turbulence enhances particle drop collision rates and increases rain rates. A “continental” aerosol concentration produces a much larger maximum rainfall rate versus that obtained with “maritime” aerosol concentration. At the same time accumulated rain is larger with maritime aerosol concentration. The scavenging of aerosols by nucleating water droplets strongly affected the concentration of aerosols in the atmosphere.

The spectral (bin) microphysics mesoscale model can potentially be used for studies of specific phenomena such as severe storms, winter storms, tropical cyclones, etc. The more realistic reproduction of cloud structure than that obtained with bulk parameterization implies that the model will be more useful for remote sensing applications and in the development of advanced rain retrieval algorithms. The model can also simulate the effect of cloud seeding on rain production.

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