20 May 2022
20 May 2022
Status: this preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).

Optimizing Radar Scan Strategies for Observing Deep Convection Using Observing System Simulation Experiments

Mariko Oue1, Stephen M. Saleeby2, Peter J. Marinescu2,4, Pavlos Kollias1,3, and Susan C. van den Heever2 Mariko Oue et al.
  • 1School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY, USA
  • 2Department of Atmospheric Science, Colorado State University, Fort Collins, CO, USA
  • 3Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, NY, USA
  • 4Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, USA

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 and aims to optimize the radar observation strategy for deep convection through the use of cloud-resolving model simulations coupled with a radar simulator and a cell tracking algorithm. Our analysis results include the following four outcomes. First, a 5–7 m s-1 median difference in maximum updrafts of tracked cells was 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 captures 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 the multi-Doppler radar updraft retrievals above 5 km AGL for regions with updraft velocities greater than 10 m s-1. Third, we propose an optimized strategy which is 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 range-height indicator updraft retrieval technique for cells close to the radars, where the 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.

Mariko Oue et al.

Status: open (until 09 Jul 2022)

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Mariko Oue et al.

Mariko Oue et al.


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Short summary
This study provides an optimization of radar observation strategies to better capture convective cell evolutions in clean and polluted environments and a technique for the optimization. The suggested optimized radar observation strategy is to distinguish aerosol impacts on cloud dynamics and microphysics and particularly well resolve updrafts at middle and upper altitudes. This study sheds light on the challenge of designing remote sensing observations strategies in pre-field campaign periods.