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Data · dataset · 2026

Constraining ensemble forecasts of discrete convective initiation with surface observations

Listed in National Center for Atmospheric Research

Predicting when and where individual convective storms will develop remains an elusive challenge.

Description

Previous studies have suggested that surface observations can capture convective-scale features relevant to the convective initiation (CI) process, and new surface observing platforms such as crowdsourcing could significantly increase surface observation density in the near future. Here, a series of observing system simulation experiments (OSSEs) are performed to determine the required density of surface observations necessary to constrain storm-scale forecasts of CI.

Ensemble simulations of an environment where CI occurs are cycled hourly using the CM1 model while assimilating synthetic surface observations at varying densities. Skillful and reliable storm-scale forecasts of CI are produced when surface observations of at least 4-km-and particularly with 1-km-density are assimilated, but only for forecasts initiated within 1 h of CI. Time scales of forecast improvement in surface variables suggest that hourly cycling is at the upper limit for CI forecast improvement.

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In addition, the structure of the assimilation increments, ensemble calibration in these experiments, and challenges of convective-scale assimilation are discussed.

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National Center for Atmospheric Research0d50d825-e279-4b62-889e-17e5f5d3e2f713 d agoJSON v1
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concepts[field].local:field:ocean-atmosphericmapping · data ucar educonnector:data_ucar_edu@1.0.0
concepts[method].local:method:simulationenrichment · data ucar edukeyword-concept-rules@1.0.0title+description (75%)
created_datesource · data ucar educonnector:data_ucar_edu@1.0.0
descriptionsource · data ucar educonnector:data_ucar_edu@1.0.0/notes
publication_datesource · data ucar educonnector:data_ucar_edu@1.0.0
titlesource · data ucar educonnector:data_ucar_edu@1.0.0/title
updated_datesource · data ucar educonnector:data_ucar_edu@1.0.0