This research seeks to identify atmospheric structures and physical features for which uncertainties associated with initial and bottom boundary conditions are likely to limit the 0-24 h forecast predictability of convective weather phenomena over and east of the Rockies during the Mesoscale Predictability Experiment (MPEX) to be held in late spring and early summer 2013. MPEX will incorporate special datasets into high-resolution convection-allowing mesoscale models to test ways to reduce convective storm forecast uncertainty in the 0-24 h range. Specific atmospheric structures and physical features to be targeted include: 1) upper-tropospheric subsynoptic/mesoscale disturbances, 2) upper- and lower-level jets, 3) three-dimensional moisture plumes, 4) boundary layer moisture tongues, 5) lower and middle troposphere shear profiles, 6) atmospheric stability as manifest by the steepness of midlevel lapse rates, 7) low-level thermal and moisture boundaries, and low-level relative vorticity strips, and 8) soil moisture content and land use characteristics. The PI will be active in the forecasting component of MPEX will seek to identify potential atmospheric structures and physical features that can be targeted for extra dropsonde observations and Microwave Temperature Profiling data coverage needed for atmospheric predictability studies. A primary research focus will be the preparation of synoptic and mesoscale analyses of a variety of selected convective weather systems during MPEX to help assess the feedbacks between deep convective storms and their environment, given that the bulk upscale effects of organized deep convection are known to modify the downstream upper-level flow (e.g., jet/ridge structures). These physically based storm analyses will be used to help assess model predictability in collaboration with other MPEX principal investigators.
Intellectual merit: This project will enhance our understanding of the dynamical and thermodynamical processes that conspire to limit the atmospheric predictability a subset of convective weather phenomena that occur over complex terrain and are inherently difficult to predict. The results from this project should help to establish bounds on error growth rates for convective weather phenomena. The project will also provide an opportunity for collaborate research efforts between observationalists and modelers to assess to what extent subjectively derived feature-based uncertainty estimates can be employed in atmospheric predictability studies.
Broader impacts: The results from this study will have applications to the forecast community and the general public. Significant gaps in our core knowledge exist about how convective weather systems develop, organize, mature, and dissipate over complex terrain of the Rockies and the High Plains. Enhanced datasets obtained during the field phase of this study should allow researchers to gain a greater scientific understanding of convective storm phenomena. The results from this study will be disseminated widely to the research and operational communities. Graduate students will be trained in mesoscale analyses, convective storm dynamics, and atmospheric predictability studies.
