151 Radar Determined Dynamical and Microphysical Properties of Wet Season Convection in Darwin As a Function of Wet Season Regime

Tuesday, 29 August 2017
Zurich (Swissotel Chicago)
Robert Jackson, ANL, Lemont, IL; and S. Collis, A. Protat, V. Louf, L. Majewski, T. J. Lang, and C. K. Potvin

A known deficiency of general circulation models (GCMs) is their representation of convection (Arakawa 2004), typically parameterized using given assumptions about entrainment rates and mass fluxes that depend on the dynamical and microphysical characteristics of convection and lack any sort of representation of the organization of convection. Furthermore, mechanisms that couple large scale forcing and convective organization are poorly represented (Del Genio 2012). The Accelerated Climate Model for Energy (ACME) version 1 aims to run at resolutions of 25 km, too fine for typical convective parameterizations used in GCMs. This prompts the need for observational datasets to validate simulations and guide model development in ACME in several regions of the globe.

The focus of this study will be at the Tropical Western Pacific (TWP) site in Darwin, Australia and the surrounding maritime continent. In Darwin, well defined forcing regimes occur during the wet season of November to April with the onset and the break of the Northern Australian Monsoon (Drosdowsky 1996). In this study, the vertical velocities retrieved from over ten years of continuous plan position indicator scans from the C-band POLarimetric and Berrima radars stationed at the Atmospheric Radiation Measurement TWP site in Darwin are derived. To use this, Multidop, a Python wrapper around the Potvin et al. (2012) multiple Doppler retrieval technique (see related presentation “MultiDop: An open source, Python-powered, multi-Doppler radar analysis suite”) is used to retrieve the horizontal and vertical winds.

The retrieved vertical velocities in deep convective cores are within 5 m/s of retrievals of Collis et al. (2013) and Varble et al. (2014) for a monsoon and a break time period, showing that Multidop can reasonably retrieve vertical velocities in deep convective cores. The mean, median, and 90th percentiles of vertical velocity show a less than 5 m/s difference between monsoon and break regimes, indicating little difference between regimes. However, the 95th and 99th percentiles of vertical velocity are 5 to 10 m/s higher in break regimes than in monsoon regimes, with an enhancement of vertical velocities in monsoonal regimes when the convective mode of the MJO is inactive over Australia. This suggests that the magnitude of the extreme events encountered in each regime is sensitive to the large scale forcing.

References:

Arakawa, A. 2004: The Cumulus Parameterization Problem: Past, Present, and Future, J. Climate, 17(13), 2495-2595, doi: 10.1175/1520-0442(2004)017<2493%3ARATCPP>2.0.CO%3B2

Collis, S., A. Protat, P.T. May, and C. Williams, 2013: Statistics of Storm Updraft Velocities from TWP-ICE Including Verification with Profiling Measurements. J. Appl. Meteor. Climatol., 52, 1909–1922, doi: 10.1175/JAMC-D-12-0230.1.

Drosdowsky, W. 1996: Variability of the Australian Summer Monsoon at Darwin: 1957-1992, J. Climate, 85-96, doi:10.1175/1520-0442(1996)009<0085%3AVOTASM>2.0.CO%3B2

Del Genio, A.D. 2012: Representing the Sensitivity of Convective Cloud Systems to Tropospheric Humidity in General Circulation Models, Surv. Geophys., 33, 637–656 DOI: 10.1007/s10712-011-9148-9

Potvin, C., A. Shapiro, and M. Xue, 2012: Impact of a Vertical Vorticity Constraint in Variational Dual-Doppler Wind Analysis: Tests with Real and Simulated Supercell Data, J. Atmos. Oceanic Technol., 29, 32-49, doi:10.1175/JTECH-D-11-00019.1

Varble, A., E. J. Zipser, A. M. Fridlind, P. Zhu, A. S. Ackerman, J.-P. Chaboureau, S. Collis, J. Fan, A. Hill, and B. Shipway, 2014: Evaluation of cloud-resolving and limited area model intercomparison simulations using TWP-ICE observations: 1. Deep convective updraft properties, J. Geophys. Res. Atmos., 119, 13,891–13,918, doi:10.1002/2013JD021371.

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