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Abstract A fundamental issue when evaluating the simulation of precipitation is the difficulty of quantifying specific sources of errors and recognizing compensation of errors. We assess how well a large ensemble of high‐resolution simulations represents the precipitation associated with strong cyclones. We propose a framework to breakdown precipitation errors according to different dynamical (vertical velocity) and thermodynamical (vertically integrated water vapor) regimes and the frequency and intensity of precipitation. This approach approximates the error in the total precipitation of each regime as the sum of three terms describing errors in the large‐scale environmental conditions, the frequency of precipitation and its intensity. We show that simulations produce precipitation too often, that its intensity is too weak, that errors are larger for weak than for strong dynamical forcing and that biases in the vertically integrated water vapor can be large. Using the error breakdown presented above, we define four new error metrics differing on the degree to which they include the compensation of errors. We show that convection‐permitting simulations consistently improve the simulation of precipitation compared to coarser‐resolution simulations using parameterized convection, and that these improvements are revealed by our new approach but not by traditional metrics which can be affected by compensating errors. These results suggest that convection‐permitting models are more likely to produce better results for the right reasons. We conclude that the novel decomposition and error metrics presented in this study give a useful framework that provides physical insights about the sources of errors and a reliable quantification of errors. , Plain Language Summary The simulations of complex physical processes always entail various sources of errors. These errors can be of different sign and can consequently cancel each other out when using traditional performance metrics such as the bias error metric. We present a formal framework that allows us to approximate precipitation according to three terms that describe different aspects of the rainfall field including large‐scale environmental conditions and the frequency and intensity of rainfall. We apply the methodology to a large ensemble of high‐resolution simulations representing the precipitation associated with strong cyclones in eastern Australia. We show that simulations produce precipitation too often, with an intensity that is too weak leading to strong compensation. We further define new error metrics that explicitly quantify the degree of error compensation when simulating precipitation. We show that convection‐permitting simulations consistently improve the performance compared to coarser resolution simulations using parameterized convection and that these improvements are only revealed when using the new error metrics but are not apparent in traditional metrics (e.g., bias). , Key Points Multiple high‐resolution simulations produce precipitation too often with underestimated intensity leading to strong error compensation Errors in precipitation are quantified using novel metrics that prevent error compensation showing value compared with traditional metrics Convection permitting simulations outperform the representation of precipitation compared to simulations using parameterized convection
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Abstract The importance of resolving mesoscale air‐sea interactions to represent cyclones impacting the East Coast of Australia, the so‐called East Coast Lows (ECLs), is investigated using the Australian Regional Coupled Model based on NEMO‐OASIS‐WRF (NOW) at resolution. The fully coupled model is shown to be capable of reproducing correctly relevant features such as the seasonality, spatial distribution and intensity of ECLs while it partially resolves mesoscale processes, such as air‐sea feedbacks over ocean eddies and fronts. The mesoscale thermal feedback (TFB) and the current feedback (CFB) are shown to influence the intensity of northern ECLs (north of ), with the TFB modulating the pre‐storm sea surface temperature (SST) by shifting ECL locations eastwards and the CFB modulating the wind stress. By fully uncoupling the atmospheric model of NOW, the intensity of northern ECLs is increased due to the absence of the cold wake that provides a negative feedback to the cyclone. The number of ECLs might also be affected by the air‐sea feedbacks but large interannual variability hampers significant results with short‐term simulations. The TFB and CFB modify the climatology of SST (mean and variability) but no direct link is found between these changes and those noticed in ECL properties. These results show that the representation of ECLs, mainly north of , depend on how air‐sea feedbacks are simulated. This is particularly important for atmospheric downscaling of climate projections as small‐scale SST interactions and the effects of ocean currents are not accounted for. , Plain Language Summary Air‐sea interactions occur at a variety of spatial scales, including those of the size of ocean eddies. Such interactions are partially resolved in the Australian Regional Coupled Model used to simulate the cyclones impacting the East Coast of Australia, the so‐called East Coast Lows (ECLs). The effect of different feedbacks between the ocean and the atmosphere, including those due to mechanical and thermal exchanges over ocean eddies, are tested on the properties of ECLs. Significant effects are found on the intensity of ECLs north of , with also potential effects on the number of ECLs. The air‐sea feedbacks modify the climatology of sea surface temperature, with no direct link to ECL changes. Such experiments eventually demonstrate that small‐scale air‐sea feedbacks may matter for representing current Australian climate and its change in the future. , Key Points High‐resolution regional coupled modeling can simulate key features of East Australian cyclones Cyclone intensity is sensitive to mechanical and thermal air‐sea feedbacks at mesoscales Coupled and atmosphere‐only models mainly differ in simulating cyclone properties north of