Samuel P. Lillo

Samuel P. Lillo

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article


Samuel P. Lillo has a total of 6 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Open Access

    The Role of Continental Mesoscale Convective Systems in Forecast Busts within Global Weather Prediction Systems

    by David B. Parsons, Samuel P. Lillo, Christopher P. Rattray, Peter Bechtold, Mark J. Rodwell, Connor M. Bruce

    Despite significant, steady improvements in the skill of medium-range weather prediction systems over the past several decades, the accuracy of these forecasts are occasionally very poor. These forecast failures are referred to as “busts” or “dropouts”. The lack of a clear explanation for bust events limits the development and implementation of strategies designed to reduce their occurrence. This study seeks to explore a flow regime where forecast busts occur over Europe in association with mesoscale convective systems over North America east of the Rocky Mountains. Our investigation focuses on error growth in the European Centre for Medium-Range Weather Forecasting’s (ECMWF’s) global model during the summer 2015 PECAN (Plains Elevated Convection at Night) experiment. Observations suggest that a close, but varied interrelationship can occur between long-lived, propagating, mesoscale convection systems over the Great Plains and Rossby wave packets. Aloft, the initial error occurs in the ridge of the wave and then propagates downstream as an amplifying Rossby wave packet producing poor forecasts in middle latitudes and, in some cases, the Arctic. Our results suggest the importance of improving the representation of organized deep convection in numerical models, particularly for long-lived mesoscale convective systems that produce severe weather and propagate near the jet stream.


  • Investigating the dynamics of error growth in ECMWF medium‐range forecast busts

    by Samuel P. Lillo, David B. Parsons

    Despite steady and significant progress in the skill of global numerical weather prediction, ‘bust’ or ‘dropout’ events occur when forecast errors grow much larger than expected from the mean performance of the model. Researchers at the European Centre for Medium‐Range Weather Forecasts (ECMWF) identified 584 bust cases for 6 day predictions over Europe utilizing the ERA‐Interim system as a fixed forecast model. Rodwell et al. proposed that the model's handling of mesoscale convective systems over North America, particularly during the spring, is a likely culprit for these busts. In our study, the 584 cases were examined through an empirical orthogonal function (EOF) analysis of Northern Hemisphere 500 hPa heights during the 6 day forecast period. The cases were clustered according to their behaviour in the first EOF, revealing distinctly different pattern changes. Patterns are consistent with a low wave‐number Rossby train reflecting over Greenland and a higher wave‐number Rossby train trapped in the Atlantic waveguide. Analysis of the waveguide reveals increased definition of the southern reflecting boundary and an extension toward Europe during bust cases. The seasonal variation of these regimes is also examined, with the maximum in bust frequency taking place during September–October, when recurving tropical storms are common in the central Atlantic. Other seasonal peaks occur in the summer and winter, proposed to be associated with mesoscale convective systems over North America and east coast cyclogenesis. Overall, these results suggest that the busts are occurring in association with the triggering and amplification of Rossby‐wave activity across the Atlantic, leading to large‐scale pattern transitions.