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• W2895870048 endingPage "206" @default.
• W2895870048 startingPage "186" @default.
• W2895870048 abstract "High-impact weather events over sparse data regions with complex orography, such as the Mediterranean region, remain a challenge for numerical weather prediction. This study evaluates, for the first time, the ability of a multiscale ensemble-based data assimilation system to reproduce a heavy precipitation episode that occurred during the first Special Observation Period (SOP1) of the Hydrological cycle in the Mediterranean Experiment (HyMeX). During the Intense Observation Period (IOP13) from 14 to 15 October 2012, convective maritime activity associated with an advancing cold front affected coastal areas of southern France, Corsica and Italy. With the main objective of improving forecasts of this weather event, a data assimilation (DA) system using the Ensemble Kalman Filter (EnKF) algorithm is implemented. The potential impact of assimilating conventional in-situ observations (METAR, aircrafts, buoys and rawinsondes) and single-Doppler reflectivity data to improve numerical representation of growing convective maritime structures that will evolve towards coastal populated areas is evaluated. Results indicate that information provided by both observation sources contribute to initiation and subsequent evolution of convective structures not captured by the conventional runs. Notably, data assimilation experiments produce the best quantitative verification scores for the short range (6–8 h) forecasts of accumulated precipitation. Beyond 6–8 h, data assimilation experiments and those without data assimilation are indistinguishable. Sensitivity experiments, evaluating the impact of increasing the length of the radar data assimilation period, reveal the importance of assimilating high-frequency reflectivity data during a mid-term period (6 h approx.) to better depict deep convective structures initiated over the sea that evolve towards populated coastal areas." @default.
• W2895870048 created "2018-10-26" @default.
• W2895870048 creator A5015806770 @default.
• W2895870048 creator A5035315366 @default.
• W2895870048 creator A5040300653 @default.
• W2895870048 date "2019-02-01" @default.
• W2895870048 modified "2023-10-10" @default.
• W2895870048 title "Potential of an EnKF Storm-Scale Data Assimilation System Over Sparse Observation Regions with Complex Orography" @default.
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• W2895870048 doi "https://doi.org/10.1016/j.atmosres.2018.10.004" @default.
• W2895870048 hasPublicationYear "2019" @default.
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