The use of numerical weather prediction (NWP) models to provide input of spatial rainfall patterns for distributed hydrologic models has gained increasing popularity over the past decade. One of the key challenges in this approach is the discrepancy between the typical scale of NWP forecasts and the scale needed for accurate hydrologic predictions, especially in moderate to extreme topography. Issues of scale also arise when driving hydrologic models with observed precipitation as the observations may have space-time resolutions that are too coarse (satellite) or fine (gage) for the needs of the hydrologic model. A better understanding of the space-time scaling and dynamics of convective precipitation across spatial resolutions from 1 km to 50 km and temporal integrations from 5 minutes to 3 hours is needed to bridge these scale gaps.

Characterizing the space-time scaling and dynamics of convective precipitation, especially in mountainous terrain, and the development of downscaling methods to transfer precipitation fields from one scale to another is the overall motivation for this research. The focus of this paper is on linking multi-scale statistical properties of convective precipitation to meteorological forcings and orographic influences. Case studies of both orographic and non-orographic convective precipitation events will be presented to explore the interplay between meteorological forcings and orographic influences on the scale-invariant properties of convective precipitation.