Associate Professor, Ph. D. (Washington)
Office: Burnside Hall 839
Tel: (514) 398-3347
Fax: (514) 398-6115
daniel.kirshbaum [at] mcgill.ca (E-Mail)
Mesoscale dynamics and moist convection: cumulus convection is capable of producing severe local weather and plays a key role in the climate system. Because cumuli form at very small spatiotemporal scales and are inherently turbulent and chaotic, they are poorly resolved in weather and climate models and challenging to physically interpret. These challenges render cumulus convection and its collective effects highly uncertain in forecast models. Such uncertainty can be partially mitigated by ensemble methods (for convection-permitting regional weather models) or well-formulated physical parameterization schemes (for global weather and climate models).
The initiation of cumulus clouds in a conditionally unstable atmosphere is often decided by mesoscale processes that lift air to its level of free convection (LFC). The dynamics of such processes (e.g., mountain flows, fronts, drylines, and outflow boundaries) are thus another topic of intensive study. However, lifting to the LFC is only a necessary condition for convection initiation—other dynamical and microphysical processes (e.g., vertical wind shear, entrainment of dry environmental air, and the formation of ice) control whether such a cloud will ascend sufficiently deep to produce precipitation. My research uses a combination of observations and models of varying complexity to investigate the dynamics, cloud microphysics, and predictability of moist convection. It aims to quantify key related processes using simple mathematical models, which facilitate conceptual understanding and may be used to improve cumulus parameterization schemes in large-scale models.
- Initiation of deep convection
- Cumulus entrainment
- Dynamics of mesoscale circulations
- Orographic precipitation: morphology, sensitivities, and prediction.
- Parameterization of shallow and deep convection in large-scale models.
- Predictability of convective precipitation in convection-permitting weather forecast models.
Some recent publications
- Harrison, R. G., G. Pretor-Pinney, G. J. Marlton, G. D. Anderson, D. J. Kirshbaum, and R. J. Hogan, 2017: Asperitas---a newly identified cloud supplementary feature. Weather, 72, 5: 132-141.
- Wang*, C.-C. and D. J. Kirshbaum, 2017: Idealized simulations of sea breezes over mountainous islands. Q. J. R. Meteorol. Soc., 143: 1657-1669.
- Cookson-Hills*, P., D. J. Kirshbaum, M. Surcel, J. G. Doyle*, L. Fillion, D. Jacques, and S.-J. Baek, 2017: Verification of 24-hour quantitative precipitation forecasts over the Pacific Northwest from a high-resolution Ensemble Kalman Filter system. Wea. Forecasting, 32: 1185-1208.
- Fairman*, J. G. Jr, D. M. Schultz, D. J. Kirshbaum, S. L. Gray, and A. I. Barrett*, 2017: Climatology of size, shape and intensity of precipitation features over the United Kingdom and Republic of Ireland. J. Hydromet., 18: 1595-1615.
- Rousseau-Rizzi*, R., D. J. Kirshbaum, and M. K. Yau, 2017: Initiation of deep convection over an idealized mesoscale convergence line. J. Atmos. Sci., 74: 835--853.
- Kirshbaum, D. J., 2017: On upstream blocking over heated mountain ridges. Q. J. R. Meteorol. Soc., 143: 53--68.