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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2013

Understanding the Relationships Between Lightning, Cloud Microphysics, and Airborne Radar-derived Storm Structure During Hurricane Karl (2010)

This study explores relationships between lightning, cloud microphysics, and tropical cyclone (TC) storm structure in Hurricane Karl (16 September 2010) using data collected by the NASA DC-8 and Global Hawk (GH) aircraft during NASA's Genesis and Rapid Intensification Processes (GRIP) experiment. The research capitalizes on the unique opportunity provided by GRIP to synthesize multiple datasets from two aircraft and analyze the microphysical and kinematic properties of an electrified TC. Five coordinated flight legs through Karl by the DC-8 and GH are investigated, focusing on the inner-core region (within 50km of the storm center) where the lightning was concentrated and the aircraft were well coordinated. GRIP datasets are used to compare properties of electrified and nonelectrified inner-core regions that are related to the noninductive charging mechanism, which is widely accepted to explain the observed electric fields within thunderstorms. Three common characteristics of Karl's electrified regions are identified: 1) strong updrafts of 10-20ms21, 2) deep mixed-phase layers indicated by reflectivities.30 dBZ extending several kilometers above the freezing level, and 3) microphysical environments consisting of graupel, very small ice particles, and the inferred presence of supercooled water. These characteristics describe an environment favorable for in situ noninductive charging and, hence, TC electrification. The electrified regions in Karl's inner core are attributable to a microphysical environment that was conducive to electrification because of occasional, strong convective updrafts in the eyewall.

Cloud mircophysics↗
NASA NTRS2010

Improving the Representation of Snow Crystal Properties with a Single-Moment Mircophysics Scheme

Single-moment microphysics schemes are utilized in an increasing number of applications and are widely available within numerical modeling packages, often executed in near real-time to aid in the issuance of weather forecasts and advisories. In order to simulate cloud microphysical and precipitation processes, a number of assumptions are made within these schemes. Snow crystals are often assumed to be spherical and of uniform density, and their size distribution intercept may be fixed to simplify calculation of the remaining parameters. Recently, the Canadian CloudSat/CALIPSO Validation Project (C3VP) provided aircraft observations of snow crystal size distributions and environmental state variables, sampling widespread snowfall associated with a passing extratropical cyclone on 22 January 2007. Aircraft instrumentation was supplemented by comparable surface estimations and sampling by two radars: the C-band, dual-polarimetric radar in King City, Ontario and the NASA CloudSat 94 GHz Cloud Profiling Radar. As radar systems respond to both hydrometeor mass and size distribution, they provide value when assessing the accuracy of cloud characteristics as simulated by a forecast model. However, simulation of the 94 GHz radar signal requires special attention, as radar backscatter is sensitive to the assumed crystal shape. Observations obtained during the 22 January 2007 event are used to validate assumptions of density and size distribution within the NASA Goddard six-class single-moment microphysics scheme. Two high resolution forecasts are performed on a 9-3-1 km grid, with C3VP-based alternative parameterizations incorporated and examined for improvement. In order to apply the CloudSat 94 GHz radar to model validation, the single scattering characteristics of various crystal types are used and demonstrate that the assumption of Mie spheres is insufficient for representing CloudSat reflectivity derived from winter precipitation. Furthermore, snow density and size distribution characteristics are allowed to vary with height, based upon direct aircraft estimates obtained from C3VP data. These combinations improve the representation of modeled clouds versus their radar-observed counterparts, based on profiles and vertical distributions of reflectivity. These meteorological events are commonplace within the mid-latitude cold season and present a challenge to operational forecasters. This study focuses on one event, likely representative of others during the winter season, and aims to improve the representation of snow for use in future operational forecasts.

Molthan, Andrew L.↗