J5.11
Impact of fine-scale landscape and soil-moisture variability in the initiation of deep convection

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Tuesday, 31 January 2006: 4:30 PM
Impact of fine-scale landscape and soil-moisture variability in the initiation of deep convection
A313 (Georgia World Congress Center)
Fei Chen, NCAR, Boulder, CO

Understanding the feedback between land-surface variability and precipitation has been a central GEWEX issue, because of its potential benefit in improving climate predictability. In summer, mesoscale boundaries play a critical role in the initiation of heavy precipitation. The zones of enhanced convergence along these boundaries have been recognized as areas of deep-convection initiation. The origin of these mesoscale boundaries includes synoptic-scale fronts, outflows from previous storms, orographic features, and differential surface heating. The differential heating can be enhanced by heterogeneities in land-surface conditions. The land surface may have differing impacts, depending on atmospheric conditions. Small-scale ground features, such as vegetation, hillslopes, and urban or industrial areas can also have subtle impacts that can determine the exact boundary and intensity of storms. We will present recent results to investigate 1) the impact of the land surface and terrain on the 1996 flash flood that struck Colorado's Buffalo Creek watershed, 2) a dryline deep convection initiated by the soil moisture variability both in the vicinity of dryline and at mesoscales, and 3) the role of soil moisture on a 10-day rainfall episode during the summer of 2002. Results from these and other recent research studies provide some hope that the careful treatment of land-surface physics and soil moisture in convection-resolving models can lead to increased rainfall predictability. In particular, this should be achievable by improving 1) the representation of land surface processes, 2) the initialization of soil properties, and 3) the specification of various vegetation characteristics by combining modeling, new remote sensing capabilities, and data-assimilation techniques.