Elsevier

Atmospheric Research

Volume 216, 1 February 2019, Pages 186-206
Atmospheric Research

Potential of an EnKF Storm-Scale Data Assimilation System Over Sparse Observation Regions with Complex Orography

https://doi.org/10.1016/j.atmosres.2018.10.004Get rights and content
Under a Creative Commons license
open access

Highlights

  • Potential of assimilating different observations over regions with a lack of in-situ observations

  • Impact of assimilating in-situ and remote sensing over areas influenced by complex terrain.

  • Highlight the importance of assimilating high-resolution reflectivity observations from Doppler radars

  • Improve forecasts of deep convective systems initiated over the sea that evolve towards populated coastal areas.

  • Prove the ability of the EnKF to improve short-range (6-8 h) forecasts of the IOP13 heavy precipitation event.

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.

Keywords

Data assimilation
EnKF
Radar reflectivity
HyMeX
WRF-DART
Western mediterranean

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