History of the American Geophysical Union Atmospheric and Space Electricity Section

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

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

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

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

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

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)

Diagnosing the Meteorological Conditions Associated with Sprites and Lightning with Large Change Moment Charges (CMC) over Oklahoma

Sprites are a category of Transient Luminous Events (TLE's) that occur in the upper atmosphere above the tops of Mesoscale Convective Systems (MCSs). They are commonly associated with lightning strokes that produce large charge moment changes (CMCs). Synergistic use of satellite and radar-retrieved observations together with sounding data, forecasts, and lightning-detection-networks allowed the diagnosis and analysis of the meteorological conditions associated with sprites as well as large-CMC lightning over Oklahom

Diagnosing Meteorological Conditions Associated with Sprites and Lightning with Large Charge Moment Changes (CMC) over Oklahoma

Sprites are a category of Transient Luminous Events (TLEs) that occur in the upper atmosphere above the tops of Mesoscale Convective Systems (MCSs). They are commonly associated with lightning strokes that produce large charge moment changes (CMCs). Synergistic use of satellite and radar-retrieved observations together with sounding data, forecasts, and lightning-detection networks allowed the diagnosis and analysis of the meteorological conditions associated with sprites as well as large-CMC lightning over Oklahoma. One goal of the NASA-funded effort reported herein is the investigation of the potential for sprite interference with aerospace activities in the 20- 100km altitude range, including research balloons, space missions and other aviation transports

Advanced Microwave Precipitation Radiometer (AMPR) Calibration and Geophysical Retrievals

No abstract availabl

Investigating the Relationship Between Turbulence and Lightning

No abstract availabl

Observations of Stratiform Lightning Flashes and Their Microphysical and Kinematic Environments

During the Midlatitude Continental Convective Clouds Experiment (MC3E), combined observations of clouds and precipitation were made from airborne and ground-based in situ and remote sensing platforms. These observations were coordinated for multiple mesoscale convective systems (MCSs) that passed over the MC3E domain in northern Oklahoma. Notably, during a storm on 20 May 2011 in situ and remote sensing airborne observations were made near the times and locations of stratiform positive cloud-to-ground (+CG) lightning flashes. These +CGs resulted from extremely large stratiform lightning flashes that were hundreds of km in length and lasted several seconds. This dataset provides an unprecedented look at kinematic and microphysical environments in the vicinity of large, powerful, and long-lived stratiform lightning flashes. We will use this dataset to understand the influence of low liquid water contents (LWCs) in the electrical charging of MCS stratiform regions