This study evaluated the ability of Weather Research and Forecasting (WRF) multi-physics ensembles to simulate storm systems known as East Coast Lows (ECLs). ECLs are intense low-pressure systems that develop off the eastern coast of Australia. These systems can cause significant damage to the region. On the other hand, the systems are also beneficial as they generate the majority of high inflow to coastal reservoirs. It is the common interest of both hazard control and water management to correctly capture the ECL features in modeling, in particular, to reproduce the observed spatial rainfall patterns. We simulated eight ECL events using WRF with 36 model configurations, each comprising physics scheme combinations of two planetary boundary layer (pbl), two cumulus (cu), three microphysics
(mp), and three radiation (ra) schemes. The performance of each physics scheme combination and the ensembles of multiple physics scheme combinations were evaluated separately. Results show that using the ensemble average gives higher skill than the median performer within the ensemble. More importantly, choosing a composite average of the better performing pbl and cu schemes can substantially improve the representation of high rainfall both spatially and quantitatively.
Figure 3: Plots summarizing statistics from 36 members and ensemble averages for the JUN (top) and SURFERS (bottom) events. The boxes and whiskers show the results from 36 members. The boxes show the inter-quartile, the middle horizontal lines show the median and the whiskers show the best and the worst values. The bias, MAE and RMSE values were divided by 30, 40 and 80 respectively to allow them to be plotted in the same graph. The results from three ensembles are shown in different markers. “All” represents an ensemble average of all the 36 members, “YSU” represents the ensemble average for all members using YSU scheme, “KF” represents the ensemble average for all members using KF scheme and “YSU_KF” represents the ensemble average for all members using YSU and KF schemes.
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Last updated 31st January 2013