983 research outputs found

    History of the American Geophysical Union Atmospheric and Space Electricity Section

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    Atmospheric and Space Electricity (ASE) has been a part of the American Geophysical Union (AGU) since its initial founding and organization in 1919. John Fleming, who invented the vacuum tube, was the first Secretary of the AGU Terrestrial Magnetism and Atmospheric Electricity Section, and today has an AGU medal named after him. ASE played an important role in the post-World War II era of AGU, as a locus for scientific discussions regarding major ASE-related events, such as the Thunderstorm Project (19461949) and the 1969 Apollo 12 lightning incident. By the 1970s and 1980s, the ASE community was represented by the Committee on ASE (CASE) within the Atmospheric Sciences Section. CASE was able to bridge the gap between the fields of aeronomy and atmospheric science by sponsoring its own sessions and nominating AGU Fellow awardees. ASE business meetings at the AGU Fall and Spring Meetings lasted for hours, with anyone from the community presenting scientific ideas, field campaigns, and more - practically turning the business meeting into an ad hoc AGU session

    The black-white education-scaled test-score gap in grades k-7

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    We measure the black-white achievement gap from kindergarten through seventh grade on an interval scale created by tying each grade/test score combination to average eventual education. After correcting for various sources of test measurement error, some of which are unique to forward-looking scales, we find no racial component in the evolution of the achievement gap through the first eight years of schooling. Further, most, if not all, of the gap can be explained by socioeconomic differences. Our results suggest that the rising racial test gap in previous studies probably reflects excessive measurement error in testing in the early grades.Accepted manuscrip

    Relationship between storm structure and lightning activity in Colorado convection observed during STERO-A

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    November 1997.Includes bibliographical references.Concurrent measurements from the CSU-CHILL multiparameter Doppler radar, the ONERA VHF lightning interferometer, and the National Lightning Detection Network, obtained during Phase A of the Stratosphere-Troposphere Experiments: Radiation, Aerosols, Ozone (STERAO-A) field project, provided a unique data set with which to study the relationships between convective storm microphysics and associated lightning. Two events have been examined in detail: storms of 10 and 12 July 1996. Both storms underwent major organizational transitions during their lifetimes, identified by sharp changes in total lightning flash rates, dominant cloud-to-ground (CG) flash polarity, or dominant flash type (cloud-to-ground vs. intra-cloud). Both storms also featured relatively high intra-cloud (IC) flash rates. The 10 July 1996·storm evolved from a multicellular line to an intense unicellular storm. The unicellular stage was marked by a sharp peak in IC flash rate as identified by the interferometer. Cloud-to-ground flash rates were low throughout the storm’s lifetime. Small hail was produced during the entire observation period, suggesting storm updraft speeds were significant. The storm of 12 July evolved from an intense multicellular, hail­ producing storm to a weaker rainstorm. Before this transition, hail was being produced and the CG flash rates were low. After the transition, hail was no longer being produced and negative CG flash rates were significantly larger. Storm updraft speeds likely weakened during the transition. These observations are consistent with the elevated-dipole hypothesis to explain low CG production in convective storms, especially if the observed high IC flash rates mostly neutralized any charged core before it descended toward the ground. Alternatively, if significant charging does not occur during wet growth of hail and graupel, both these storms might have produced enough wet-growth ice to prevent the generation of a lower positive charge center that could act to stimulate CG production. However, the radar data, in particular the linear depolarization ratio (LOR) data, suggest that dry growth was more prevalent than wet growth.Sponsored by the National Science Foundation under grant ATM-9321361

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

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    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

    Investigating The Seasonal and Diurnal Cycles of Ocean Vector Winds Near the Philippines Using RapidScat and CCMP

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    The seasonal and diurnal cycles of ocean vector winds in the domain of the South China Sea are characterized and compared using RapidScat and the Cross-Calibrated Multi-Platform (CCMP) data sets. Broad agreement in seasonal flow patterns exists between these data sets during the year 2015. Both observe the dramatic reversal from wintertime trade winds (November-April) to westerly flow associated with the summer monsoon (May-October). These seasonal changes have strong but not equivalent effects on mean wind divergence patterns in both data sets. Specifically near the Philippines, the data sets agree on several aspects of the seasonal mean and diurnal cycle of near-surface vector winds and divergence. In particular, RapidScat and CCMP agree that daytime onshore and nocturnal offshore flow patterns affect the diurnal cycle of winds up to ~200 km west of Luzon, Philippines. Observed disagreements over the diurnal cycle are explainable by measurement uncertainty, as well as shortcomings in both data sets

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

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    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

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    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)
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