Dissertation on the relationships between convective storm kinematics, microphysics, and lightning

Fall 2000.Includes bibliographical references.Combined multiparameter radar, dual-Doppler, thermodynamic sounding, and lightning observations of 11 thunderstorms (6 from the mid-latitudes, 5 from the tropics) are presented. The thunderstorms span a wide spectrum of intensities, from weak monsoon-type to severe tornadic, and include both unicellular and multicellular convection. In general, the kinematically strongest storms featured lower production of negative cloud-to-ground lightning (typically 10 m s·1 and > 20 m s"1 ) and produced greater amounts of precipitation (both rain and hail). Otherwise, peak updrafts and vertical air mass fluxes were very similar between the two types of storms, and both types were linked by anomalously low production of negative CG lightning. It is suggested that PPCG storms may be caused by enhanced lower positive charge created by the larger volume of significant updrafts. Since both PPCG and low-CG storms are capable of being severe, anomalously low production of negative CG lightning (regardless of positive CG flash rate) may be a useful signature for use in the "nowcasting" of severe convection.Sponsored by the National Science Foundation grant ATM-9726464

Python-Based Scientific Analysis and Visualization of Precipitation Systems at NASA Marshall Space Flight Center

At NASA Marshall Space Flight Center (MSFC), Python is used several different ways to analyze and visualize precipitating weather systems. A number of different Pythonbased software packages have been developed, which are available to the larger scientific community. The approach in all these packages is to utilize preexisting Python modules as well as to be objectoriented and scalable. The first package that will be described and demonstrated is the Python Advanced Microwave Precipitation Radiometer (AMPR) Data Toolkit, or PyAMPR for short. PyAMPR reads geolocated brightness temperature data from any flight of the AMPR airborne instrument over its 25year history into a common data structure suitable for userdefined analyses. It features rapid, simplified (i.e., one line of code) production of quicklook imagery, including Google Earth overlays, swath plots of individual channels, and strip charts showing multiple channels at once. These plotting routines are also capable of significant customization for detailed, publicationready figures. Deconvolution of the polarizationvarying channels to static horizontally and vertically polarized scenes is also available. Examples will be given of PyAMPR's contribution toward realtime AMPR data display during the Integrated Precipitation and Hydrology Experiment (IPHEx), which took place in the Carolinas during MayJune 2014. The second software package is the Marshall MultiRadar/MultiSensor (MRMS) Mosaic Python Toolkit, or MMMPy for short. MMMPy was designed to read, analyze, and display threedimensional national mosaicked reflectivity data produced by the NOAA National Severe Storms Laboratory (NSSL). MMMPy can read MRMS mosaics from either their unique binary format or their converted NetCDF format. It can also read and properly interpret the current mosaic design (4 regional tiles) as well as mosaics produced prior to late July 2013 (8 tiles). MMMPy can easily stitch multiple tiles together to provide a larger regional or national picture of precipitating weather systems. Composites, horizontal and vertical crosssections, and combinations thereof are easily displayed using as little as one line of code. MMMPy can also write to the native MRMS binary format, and subsectioning of tiles (or multiple stitched tiles) is anticipated to be in place by the time of this meeting. Thus, MMMPy also can be used to power the creation of custom mosaics for targeted regional studies. Overlays of other data (e.g., lightning observations) are easily accomplished. Demonstrations of MMMPy, including the creation of animations, will be shown. Finally, Marshall has done significant work to interface Pythonbased analysis routines with the U.S. Department of Energy's PyART software package for radar data ingest, processing, and analysis. One example of this is the Python Turbulence Detection Algorithm (PyTDA), an MSFCbased implementation of the National Center for Atmospheric Research (NCAR) Turbulence Detection Algorithm (NTDA) for the purposes of convectivescale analysis, situational awareness, and forensic meteorology. PyTDA exploits PyART's radar data ingest routines and data model to rapidly produce aviationrelevant turbulence estimates from Doppler radar data. Work toward processing speed optimization and better integration within the PyART framework will be highlighted. Pythonbased analysis within the PyART framework is also being done for new research related to intercomparison of groundbased radar data with satellite estimates of ocean winds, as well as research on the electrification of pyrocumulus clouds

Geophysical Retrievals During OLYMPEX/RADEX Using the Advanced Microwave Precipitation Radiometer

The Olympic Mountains Experiment and Radar Definition Experiment (OLYMPEX/RADEX) took place Fall 2015 Spring 2016 in Washington, United States. The Advanced Microwave Precipitation Radiometer (AMPR) was flown on NASA ER-2 aircraft during science flights. This poster summarizes advancements in geophysical retrievals using AMPR data from OLYMPEX/RADEX. Calm ocean has low emissivity at microwave frequencies; wind creates foam increases emissivity. Liquid hydrometeors in atmosphere generally yield higher brightness temperature (T(sub b)) due to their higher reflectance. Effect of liquid hydrometeors depends highly on frequency resonance increases with increasing frequency, as does absorption (e.g., due to water vapor). Retrieve cloud liquid water (CLW), water vapor (WV), and 10-m wind speed (WS) using multiple T(sub b)

Tropical Processes Applications for CYGNSS

The Cyclone Global Navigation Satellite System (CYGNSS) is focused primarily on observing extreme winds in the inner core of tropical cyclones But... Named storms will occur in view of CYGNSS constellation for only a small percentage of the time on orbit And... Rapid-update, all-weather sampling of wind speeds has many other applications in Tropical Meteorology So... Many potential tropical processes applications for CYGNSS were identified in previous Workshop - Let's revisit some of these possibilities now that the mission is up

Analysis and Assimilation of CYGNSS Wind Data for Improved Tropical Convection Forecasts

No abstract availabl

Analysis and Modeling of Tropical Convection Observed by CYGNSS

No abstract availabl

Characteristics of Lightning Within Electrified Snowfall Events Using Total Lightning Measurements

No abstract availabl

Utilizing ISS Camera Systems for Scientific Analysis of Lightning Characteristics and Comparison with ISS-LIS and GLM

Video and still frame images from cameras aboard the International Space Station (ISS) are used to inspire, educate, and provide a unique vantage point from low-Earth orbit that is second to none; however, these cameras have overlooked capabilities for contributing to scientific analysis of the Earth and near-space environment. The goal of this project is to study how geo referenced video/images from available ISS camera systems can be useful for scientific analysis, using lightning properties as a demonstration

Validation of CYGNSS V2 Level 2 Winds

No abstract availabl