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  • 1
    Publication Date: 2019-07-18
    Description: It is by no means a simple task to retrieve storm electric fields from an aircraft instrumented with electric field mill sensors. The presence of the aircraft distorts the ambient field in a complicated way. Before retrievals of the storm field can be made, the field mill measurement system must be "calibrated". In other words, a relationship between impressed (i.e., ambient) electric field and mill output must be established. If this relationship can be determined, it is mathematically inverted so that ambient field can be inferred from the mill outputs. Previous studies have primarily focused on linear theories where the relationship between ambient field and mill output is described by a "calibration matrix" M. Each element of the matrix describes how a particular component of the ambient field is enhanced by the aircraft. For example the product M(sub ix), E(sub x), is the contribution of the E(sub x) field to the i(th) mill output. Similarly, net aircraft charge (described by a "charge field component" E(sub q)) contributes an amount M(sub iq)E(sub q) to the output of the i(th) sensor. The central difficulty in obtaining M stems from the fact that the impressed field (E(sub x), E(sub y), E(sub z), E(sub q) is not known but is instead estimated. Typically, the aircraft is flown through a series of roll and pitch maneuvers in fair weather, and the values of the fair weather field and aircraft charge are estimated at each point along the aircraft trajectory. These initial estimates are often highly inadequate, but several investigators have improved the estimates by implementing various (ad hoc) iterative methods. Unfortunately, none of the iterative methods guarantee absolute convergence to correct values (i.e., absolute convergence to correct values has not been rigorously proven). In this work, the mathematical problem is solved directly by analytic means. For m mills installed on an arbitrary aircraft, it is shown that it is possible to solve for a single 2m-vector that provides all other needed variables (i.e., the unknown fair weather field, the unknown aircraft charge, and the unknown matrix M). Numerical tests of the solution, effects of measurement errors, and studies of solution non-uniqueness are ongoing as of this writing.
    Keywords: Numerical Analysis
    Type: Fall American Geophysical Union Conference; Dec 08, 2003 - Dec 12, 2003; San Francisco, CA; United States
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  • 2
    Publication Date: 2019-07-13
    Description: No abstract available
    Keywords: Meteorology and Climatology; Earth Resources and Remote Sensing
    Type: MSFC-E-DAA-TN35577 , Columbia University School of Engineering and Applied Science (SEAS) SEAS Colloquium in Climate Science (SCiCS); Sep 15, 2016; New York City, NY; United States
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  • 3
    Publication Date: 2019-07-13
    Description: No abstract available
    Keywords: Numerical Analysis
    Type: M11-1070 , GOES-R Risk Reduction Annual Review; Sep 21, 2011 - Sep 23, 2011; Huntsville, AL; United States
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  • 4
    Publication Date: 2019-07-13
    Description: No abstract available
    Keywords: Meteorology and Climatology; Earth Resources and Remote Sensing
    Type: MSFC-E-DAA-TN47608-1 , Annual Community Modeling and Analysis System (CMAS) Conference; Oct 23, 2017 - Oct 25, 2017; Chapel Hill, NC; United States
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  • 5
    Publication Date: 2019-07-13
    Description: The intense heating of air by a lightning channel, and subsequent rapid cooling, leads to the production of lightning nitrogen oxides (NOx = NO + NO2) as discussed in Chameides [1979]. In turn, the lightning nitrogen oxides (or "LNOx" for brevity) indirectly influences the Earth's climate because the LNOx molecules are important in controlling the concentration of ozone (O3) and hydroxyl radicals (OH) in the atmosphere. Climate is most sensitive to O3 in the upper troposphere, and LNOx is the most important source of NOx in the upper troposphere at tropical and subtropical latitudes; hence, lightning is a useful parameter to monitor for climate assessments. The National Climate Assessment (NCA) program was created in response to the Congressionally-mandated Global Change Research Act (GCRA) of 1990. Thirteen US government organizations participate in the NCA program which examines the effects of global change on the natural environment, human health and welfare, energy production and use, land and water resources, human social systems, transportation, agriculture, and biological diversity. The NCA focuses on natural and human-induced trends in global change, and projects major trends 25 to 100 years out. In support of the NCA, the NASA Marshall Space Flight Center (MSFC) continues to assess lightning-climate inter-relationships. This activity applies a variety of NASA assets to monitor in detail the changes in both the characteristics of ground- and space- based lightning observations as they pertain to changes in climate. In particular, changes in lightning characteristics over the conterminous US (CONUS) continue to be examined by this author using data from the Tropical Rainfall Measuring Mission Lightning Imaging Sensor. In this study, preliminary estimates of LNOx trends derived from TRMM/LIS lightning optical energy observations in the 17 yr period 1998-2014 are provided. This represents an important first step in testing the ability to make remote retrievals of LNOx from a satellite-based lightning sensor. As is shown, the methodology can also be directly applied to more recently launched lightning mappers, such as the Geostationary Lightning Mapper, and the International Space Station LIS.
    Keywords: Meteorology and Climatology; Earth Resources and Remote Sensing
    Type: MSFC-E-DAA-TN47608-2 , Annual Community Modeling and Analysis System (CMAS) Conference; Oct 23, 2017 - Oct 25, 2017; Chapel Hill, NC; United States
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  • 6
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    In:  CASI
    Publication Date: 2019-07-13
    Description: No abstract available
    Keywords: Meteorology and Climatology; Earth Resources and Remote Sensing
    Type: MSFC-E-DAA-TN35911 , 2016 GLM Annual Science Team Meeting; Sep 27, 2016 - Sep 29, 2016; Huntsville, AL; United States
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  • 7
    Publication Date: 2019-07-13
    Description: No abstract available
    Keywords: Meteorology and Climatology; Earth Resources and Remote Sensing
    Type: MSFC-E-DAA-TN37859 , 2017 American Meteorological Society Conference; Jan 22, 2017 - Jan 26, 2017; Seattle, WA; United States
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