the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Assessing the skill of high-impact weather forecasts in southern South America: a study on Cut-off Lows
Abstract. Cut-off Lows (COL) are mid-tropospheric cyclonic systems that frequently form over southern South America, where they can cause high-impact precipitation events. However, their prediction remains a challenging task, even in state-of-the-art numerical weather prediction systems. In this study, we assess the skill of the Global Ensemble Forecasting System (GEFS) in predicting COL formation and evolution over the South American region where the highest frequency and intensity of such events is observed. The target season is austral autumn (March to May), in which the frequency of these events maximizes. Results show that GEFS is skillful in predicting the onset of COLs up to 3 days ahead, even though forecasts initialized up to 7 days ahead may provide hints of COL formation. We also find that as the lead time increases, GEFS is affected by a systematic bias in which the forecast tracks lay to the west of their observed positions. Analysis of two case studies provide useful information on the mechanisms explaining the documented errors. These are mainly related to the depth and the intensity of the cold core, which affect the thermodynamic instability patterns (thus shaping precipitation downstream) as well as the horizontal thermal advection which can act to reinforce or weaken the COLs. These results are expected to provide not only further insight into the physical processes at play in these forecasts, but also useful tools to be used in operational forecasting of these high-impact weather events over southern South America.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2024-1063', Anonymous Referee #1, 18 Jun 2024
Summary and recommendation
Cut-off lows (COLs) are important circulation systems that can often bring extreme precipitation. Using the Global Ensemble Forecasting System, the authors systematically assess the prediction skill of cut-off lows over Southern America during austral autumn. The showed that the COLs can be successfully predicted 3 days ahead. The model ensemble mean tends to underestimate the intensity and has track bias to the west. This provides a comprehensive assessment of the COL skills by current ensemble forecast systems. The results are clearly stated and I suggest minor revisions.
Minor comments:
- I think the current manuscript is missing a discussion of the physical processes responsible for the COLs in the Southern America. This is important because this may help readers to understand why the models tend to underestimate the COLs and have track bias. For example, does the bias result from the weak eddy-mean flow interaction in the evolution of COLs (e.g., Pinheiro et al., 2022; Nie et al, 2022, 2023)?
- Since the COLs often arise from the internal atmospheric variability similar to blocking high, I am curious about whether the ensemble spread of model is comparable to the variability of observed COLs.
- In the abstract (Lines 22-23), the author stated that the depth and intensity of cold core can affect the thermodynamic instability pattern, precipitation and horizontal temperature advection. I suggest the authors either add more related evidence to support these statements in the manuscript or adjust the statements in the abstract, since the current manuscript is missing a detailed corresponding discussion.
References:
Nie, Yu, Jie Wu, Jinqing Zuo, Hong-Li Ren, Adam Scaife, Nick Dunstone, and Steven Hardiman, 2023: Subseasonal Prediction of Early-summer Northeast Asian Cut-off Lows by BCC-CSM2-HR and GloSea5. Adv. Atmos. Sci. 40, 2127-2134. https://doi.org/10.1007/s00376-022-2197-9
Nie, Yu, Yang Zhang, Jinqing Zuo, Mengling Wang, Jie Wu and Ying Liu, 2022: Dynamical processes controlling the evolution of early-summer cut-off lows in Northeast Asia. Clim. Dyn., 60, 1103-1119.
Pinheiro, H., T. Ambrizzi, K. Hodges, M. Gan, K. Andrade, and J. Garcia, 2022: Are cut-off lows simulated better in CMIP6 compared to CMIP5? Climate Dyn., 59, 2117−2136, https://doi.org/10.1007/s00382-022-06200-9.
Citation: https://doi.org/10.5194/egusphere-2024-1063-RC1 - RC2: 'Comment on egusphere-2024-1063', Anonymous Referee #2, 15 Aug 2024
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