Abstract
Abstract. Optimizing radar observation strategies is one of the most
important considerations in pre-field campaign periods. This is especially
true for isolated convective clouds that typically evolve faster than the
observations captured by operational radar networks. This study investigates
uncertainties in radar observations of the evolution of the microphysical
and dynamical properties of isolated deep convective clouds developing in
clean and polluted environments. It aims to optimize the radar observation
strategy for deep convection through the use of high-spatiotemporal
cloud-resolving model simulations, which resolve the evolution of individual
convective cells every 1 min, coupled with a radar simulator and a cell
tracking algorithm. The radar simulation settings are based on the Tracking
Aerosol Convection Interactions ExpeRiment (TRACER) and Experiment of Sea
Breeze Convection, Aerosols, Precipitation and Environment (ESCAPE) field
campaigns held in the Houston, TX, area but are generalizable to other field
campaigns focusing on isolated deep convection. Our analysis produces the
following four outcomes. First, a 5–7 m s−1 median difference in
maximum updrafts of tracked cells is shown between the clean and polluted
simulations in the early stages of the cloud lifetimes. This demonstrates
the importance of obtaining accurate estimates of vertical velocity from
observations if aerosol impacts are to be properly resolved. Second,
tracking of individual cells and using vertical cross section scanning every minute capture the evolution of precipitation particle number concentration and size represented by polarimetric observables better than the operational radar observations that update the volume scan every 5 min. This approach also improves multi-Doppler radar updraft retrievals above 5 km above ground level for regions with updraft velocities greater than 10 m s−1. Third, we propose an optimized strategy composed of cell tracking by quick (1–2 min) vertical cross section scans from more than one
radar in addition to the operational volume scans. We also propose the use
of a single-RHI (range height indicator) updraft retrieval technique for cells
close to the radars, for which multi-Doppler radar retrievals are still
challenging. Finally, increasing the number of deep convective cells sampled
by such observations better represents the median maximum updraft evolution
with sample sizes of more than 10 deep cells, which decreases the error
associated with sampling the true population to less than 3 m s−1.
Funder
U.S. Department of Energy
National Science Foundation
Biological and Environmental Research
Office of Science
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