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Advances in Meteorology
Volume 2014 (2014), Article ID 904571, 17 pages
http://dx.doi.org/10.1155/2014/904571
Research Article

Impacts of Aerosol Particle Size Distribution and Land Cover Land Use on Precipitation in a Coastal Urban Environment Using a Cloud-Resolving Mesoscale Model

Department of Mechanical Engineering, The City College of New York, New York, NY 10031, USA

Received 22 July 2013; Revised 22 September 2013; Accepted 1 December 2013; Published 14 January 2014

Academic Editor: George A. Isaac

Copyright © 2014 Nathan Hosannah and Jorge E. Gonzalez. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Urban environments influence precipitation formation via response to dynamic effects, while aerosols are intrinsically necessary for rainfall formation; however, the partial contributions of each on urban coastal precipitation are not yet known. Here, the authors use aerosol particle size distributions derived from the NASA aerosol robotic network (AERONET) to estimate submicron cloud condensation nuclei (CCN) and supermicron CCN (GCCN) for ingestion in the regional atmospheric modeling system (RAMS). High resolution land data from the National Land Cover Database (NLCD) were assimilated into RAMS to provide modern land cover and land use (LCLU). The first two of eight total simulations were month long runs for July 2007, one with constant PSD values and the second with AERONET PSDs updated at times consistent with observations. The third and fourth runs mirrored the first two simulations for “No City” LCLU. Four more runs addressed a one-day precipitation event under City and No City LCLU, and two different PSD conditions. Results suggest that LCLU provides the dominant forcing for urban precipitation, affecting precipitation rates, rainfall amounts, and spatial precipitation patterns. PSD then acts to modify cloud physics. Also, precipitation forecasting was significantly improved under observed PSD and current LCLU conditions.
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