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3D-Var assimilation of insect-derived Doppler radar radial winds in convective cases using a high resolution model

Rennie, S. J., Dance, S. L., Illingworth, A. J., Ballard, S. P. and Simonin, D. (2011) 3D-Var assimilation of insect-derived Doppler radar radial winds in convective cases using a high resolution model. Monthly Weather Review, 139 (4). pp. 1148-1163. ISSN 1520-0493

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To link to this article DOI: 10.1175/2010MWR3482.1

Abstract/Summary

The assimilation of Doppler radar radial winds for high resolution NWP may improve short term forecasts of convective weather. Using insects as the radar target, it is possible to provide wind observations during convective development. This study aims to explore the potential of these new observations, with three case studies. Radial winds from insects detected by 4 operational weather radars were assimilated using 3D-Var into a 1.5 km resolution version of the Met Office Unified Model, using a southern UK domain and no convective parameterization. The effect on the analysis wind was small, with changes in direction and speed up to 45° and 2 m s−1 respectively. The forecast precipitation was perturbed in space and time but not substantially modified. Radial wind observations from insects show the potential to provide small corrections to the location and timing of showers but not to completely relocate convergence lines. Overall, quantitative analysis indicated the observation impact in the three case studies was small and neutral. However, the small sample size and possible ground clutter contamination issues preclude unequivocal impact estimation. The study shows the potential positive impact of insect winds; future operational systems using dual polarization radars which are better able to discriminate between insects and clutter returns should provided a much greater impact on forecasts.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical and Physical Sciences > Department of Meteorology
Faculty of Science > School of Mathematical and Physical Sciences > National Centre for Earth Observation (NCEO)
Faculty of Science > School of Mathematical and Physical Sciences > Department of Mathematics and Statistics
ID Code:17548
Publisher:American Meteorological Society

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