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    Storm-Scale Ensemble Kalman Filter Assimilation of Total Lightning Flash-Extent Data

    Source: Monthly Weather Review:;2014:;volume( 142 ):;issue: 010::page 3683
    Author:
    Mansell, Edward R.
    DOI: 10.1175/MWR-D-14-00061.1
    Publisher: American Meteorological Society
    Abstract: set of observing system simulation experiments (OSSEs) demonstrates the potential benefit from ensemble Kalman filter (EnKF) assimilation of total lightning flash mapping data. Synthetic lightning data were generated to mimic the Geostationary Lightning Mapper (GLM) instrument that is planned for the Geostationary Operational Environmental Satellite-R series (GOES-R) platform. The truth simulation was conducted using multimoment bulk microphysics, explicit electrification mechanisms, and a branched lightning parameterization to produce 2-min-averaged synthetic pseudo-GLM observations at 8-km GLM resolution and at a hypothetical 1-km resolution.The OSSEs use either perfect (two-moment bulk) or imperfect (single-moment, graupel only) microphysics. One OSSE with perfect microphysics included the same electrification physics as the truth simulation to generate lightning flash rates and flash-extent densities (FED). The other OSSEs used linear relationships between flash rate and graupel echo volume as the observation operator. The assimilation of FED at 8-km horizontal resolution can effectively modulate the convection simulated at 1-km horizontal resolution by sharpening the location of reflectivity echoes and the spatial location probability of convective updrafts. Tests with zero flash rates show that the lightning assimilation can help to limit spurious deep convection, as well. Pseudo-GLM observations at 1 km further sharpen the analyses of location (updraft and reflectivity) of the relatively simple storm structure.
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      Storm-Scale Ensemble Kalman Filter Assimilation of Total Lightning Flash-Extent Data

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    contributor authorMansell, Edward R.
    date accessioned2017-06-09T17:32:02Z
    date available2017-06-09T17:32:02Z
    date copyright2014/10/01
    date issued2014
    identifier issn0027-0644
    identifier otherams-86851.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4230454
    description abstractset of observing system simulation experiments (OSSEs) demonstrates the potential benefit from ensemble Kalman filter (EnKF) assimilation of total lightning flash mapping data. Synthetic lightning data were generated to mimic the Geostationary Lightning Mapper (GLM) instrument that is planned for the Geostationary Operational Environmental Satellite-R series (GOES-R) platform. The truth simulation was conducted using multimoment bulk microphysics, explicit electrification mechanisms, and a branched lightning parameterization to produce 2-min-averaged synthetic pseudo-GLM observations at 8-km GLM resolution and at a hypothetical 1-km resolution.The OSSEs use either perfect (two-moment bulk) or imperfect (single-moment, graupel only) microphysics. One OSSE with perfect microphysics included the same electrification physics as the truth simulation to generate lightning flash rates and flash-extent densities (FED). The other OSSEs used linear relationships between flash rate and graupel echo volume as the observation operator. The assimilation of FED at 8-km horizontal resolution can effectively modulate the convection simulated at 1-km horizontal resolution by sharpening the location of reflectivity echoes and the spatial location probability of convective updrafts. Tests with zero flash rates show that the lightning assimilation can help to limit spurious deep convection, as well. Pseudo-GLM observations at 1 km further sharpen the analyses of location (updraft and reflectivity) of the relatively simple storm structure.
    publisherAmerican Meteorological Society
    titleStorm-Scale Ensemble Kalman Filter Assimilation of Total Lightning Flash-Extent Data
    typeJournal Paper
    journal volume142
    journal issue10
    journal titleMonthly Weather Review
    identifier doi10.1175/MWR-D-14-00061.1
    journal fristpage3683
    journal lastpage3695
    treeMonthly Weather Review:;2014:;volume( 142 ):;issue: 010
    contenttypeFulltext
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