How Terrain Geometry and Environmental Instability Shape Precipitation in Mountain‐Crossing Mesoscale Convective Systems
Abstract
Abstract This study uses idealized large‐eddy simulations to systematically examine how terrain geometry and environmental instability modulate precipitation produced by a mountain‐crossing mesoscale convective system (MCS). A suite of simulations isolates the effects of base‐state convective available potential energy (CAPE), mountain width, and crest height on rainfall distributions. The environmental instability that governs MCS intensity upstream of the mountain is the primary control on over‐mountain precipitation, with larger CAPE yielding greater rainfall. Mountain geometry provides an additional control on the spatial distribution of rainfall. Taller, narrower mountains (steeper slopes) yield larger localized windward rainfall enhancements, while taller, wider mountains induce broader areas of moderate enhancement. In the lee, taller and wider mountains induce larger precipitation reductions, as compared to shorter and narrower mountains. Terrain‐induced precipitation modifications are also sensitive to CAPE. In low‐CAPE environments, MCSs require orographic lift to sustain convection and support successful mountain crossings; without terrain, MCSs weaken rapidly. Therefore, mountains can extend the lifetime of MCSs in low‐CAPE environments. In high‐CAPE environments, MCSs remain robust and sustain substantial rainfall over flat surfaces without mountain forcing, so terrain contributes a proportionally smaller increase in windward rainfall even as rainfall totals increase, with the largest enhancements concentrated over steeper slopes. After crest passage, terrain‐induced reductions in near‐surface lifting are associated with larger leeside precipitation reductions, particularly for taller and wider mountains. Extreme rainfall production is also sensitive to CAPE and mountain geometry. Steep slopes increase extreme rainfall areal coverage, although their impact on extreme rainfall rates is more complex.
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Authors: Fan Wu, Kelly A. Lombardo
Institutions: Pennsylvania State University