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Sensitivity to Localization Radii for an Ensemble Filter Numerical Weather Prediction System with 30-Second Update

James TayloraRIKEN Center for Computational Science, Kobe, Japan
bRIKEN Cluster for Pioneering Research, Kobe, Japan

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Takumi HondaaRIKEN Center for Computational Science, Kobe, Japan
bRIKEN Cluster for Pioneering Research, Kobe, Japan
cFaculty of Science, Hokkaido University, Sapporo, Hokkaido, Japan

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Arata AmemiyaaRIKEN Center for Computational Science, Kobe, Japan
bRIKEN Cluster for Pioneering Research, Kobe, Japan

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Shigenori OtsukaaRIKEN Center for Computational Science, Kobe, Japan
bRIKEN Cluster for Pioneering Research, Kobe, Japan

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Yasumitsu MaejimaaRIKEN Center for Computational Science, Kobe, Japan
bRIKEN Cluster for Pioneering Research, Kobe, Japan

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Takemasa MiyoshiaRIKEN Center for Computational Science, Kobe, Japan
bRIKEN Cluster for Pioneering Research, Kobe, Japan
cFaculty of Science, Hokkaido University, Sapporo, Hokkaido, Japan

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Abstract

A sensitivity analysis for horizontal localization scale is performed for a numerical weather prediction (NWP) system that uses a 30-second update to refresh a 500-m mesh with observations from a new-generation multi-parameter phased array weather radar (MP-PAWR). Testing is performed using three case studies of convective weather events that occurred during August/September 2019, with the aim to determine the most suitable scale for short-range forecasting of precipitating convective systems and better understand model behavior to a rapid update cycle. Results showed that while the model could provide useful skill at lead times up to 30-minutes, forecasts would consistently over-estimate rainfall and were unable to outperform nowcasts performed with a simple advection model. Using a larger localization scale e.g., 4-km, generated stronger convective and dynamical instability in the analyzes that made conditions more favorable for spurious and intense convection to develop in forecasts. It was demonstrated that lowering the localization scale reduced the size of analysis increments during early cycling, limiting the buildup of these conditions. Improved representation of the localized convection in the initial conditions was suggested as an important step to mitigating this issue in the model.

Corresponding author: James Taylor, james.taylor@riken.jp

Abstract

A sensitivity analysis for horizontal localization scale is performed for a numerical weather prediction (NWP) system that uses a 30-second update to refresh a 500-m mesh with observations from a new-generation multi-parameter phased array weather radar (MP-PAWR). Testing is performed using three case studies of convective weather events that occurred during August/September 2019, with the aim to determine the most suitable scale for short-range forecasting of precipitating convective systems and better understand model behavior to a rapid update cycle. Results showed that while the model could provide useful skill at lead times up to 30-minutes, forecasts would consistently over-estimate rainfall and were unable to outperform nowcasts performed with a simple advection model. Using a larger localization scale e.g., 4-km, generated stronger convective and dynamical instability in the analyzes that made conditions more favorable for spurious and intense convection to develop in forecasts. It was demonstrated that lowering the localization scale reduced the size of analysis increments during early cycling, limiting the buildup of these conditions. Improved representation of the localized convection in the initial conditions was suggested as an important step to mitigating this issue in the model.

Corresponding author: James Taylor, james.taylor@riken.jp
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