Understanding how low-level clouds and fog modify the diurnal cycle of orographic precipitation using in situ and satellite observations

Abstract

Satellite orographic precipitation estimates exhibit large errors with space-time structure tied to landform. Observations in the Southern Appalachian Mountains (SAM) suggest that low-level clouds and fog (LLCF) amplify mid-day rainfall via seeder-feeder interactions (SFI) at both high and low elevations. Here, a rainfall microphysics model constrained by fog observations was used first to reveal that fast SFI (2-5 min time-scales) modify the rain drop size distributions by increasing coalescence efficiency among small drops (<0.7 mm diameter), whereas competition between coalescence and filament-only breakup dominates for larger drops (3-5 mm diameter). The net result is a large increase in the number concentrations of intermediate size raindrops in the 0.7-3 mm range and up to a ten-fold increase in rainfall intensity. Next, a 10-year climatology of satellite observations was developed to map LLCF. Combined estimates from CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) and CloudSat products reveal persistent shallower cloud base heights at high elevations enveloping the terrain. The regional cloud top height climatology derived from the MODIS (Moderate Resolution Imaging Spectroradiometer) shows high-frequency daytime LLCF over mountain ridges in the warm season shifting to river valleys at nighttime. In fall and winter, LLCF patterns define a cloud-shadow region east of the continental divide, consistent with downwind rain-shadow effects. Optical and microphysical properties from collocated MODIS and ground ceilometers indicate small values of vertically integrated cloud water path (CWP < 100 g/m2), optical thickness (COT < 15), and particle effective radius (CER) <15 μm near cloud top whereas surface observed CER ~25 μm changes to ~150 μm and higher prior to the mid-day rainfall. The vertical stratification of LLCF microphysics and SFI at low levels pose a significant challenge to satellite-based remote sensing in complex topography.