Accessibility navigation


Ensemble prediction for nowcasting with a convection-permitting model - II: forecast error statistics

Downloads

Downloads per month over past year

Bannister, R. N., Migliorini, S. and Dixon, M. A. G. (2011) Ensemble prediction for nowcasting with a convection-permitting model - II: forecast error statistics. Tellus Series A: Dynamic Meteorology and Oceanography, 63 (3). pp. 497-512. ISSN 0280-6495

[img] Text - Published Version
· Please see our End User Agreement before downloading.

1564Kb

To link to this article DOI: 10.1111/j.1600-0870.2010.00500.x

Abstract/Summary

A 24-member ensemble of 1-h high-resolution forecasts over the Southern United Kingdom is used to study short-range forecast error statistics. The initial conditions are found from perturbations from an ensemble transform Kalman filter. Forecasts from this system are assumed to lie within the bounds of forecast error of an operational forecast system. Although noisy, this system is capable of producing physically reasonable statistics which are analysed and compared to statistics implied from a variational assimilation system. The variances for temperature errors for instance show structures that reflect convective activity. Some variables, notably potential temperature and specific humidity perturbations, have autocorrelation functions that deviate from 3-D isotropy at the convective-scale (horizontal scales less than 10 km). Other variables, notably the velocity potential for horizontal divergence perturbations, maintain 3-D isotropy at all scales. Geostrophic and hydrostatic balances are studied by examining correlations between terms in the divergence and vertical momentum equations respectively. Both balances are found to decay as the horizontal scale decreases. It is estimated that geostrophic balance becomes less important at scales smaller than 75 km, and hydrostatic balance becomes less important at scales smaller than 35 km, although more work is required to validate these findings. The implications of these results for high-resolution data assimilation are discussed.

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)
ID Code:19772
Publisher:Wiley-Blackwell

Download Statistics for this item.

Centaur Editors: Update this record

Page navigation