论文标题
重新分析和高分辨率模型未能捕获开普分布的“高尾巴”
Reanalyses and a high-resolution model fail to capture the `high tail' of CAPE distributions
论文作者
论文摘要
对流可用的势能（CAPE）在气候建模中具有强烈的兴趣，因为它在恶劣天气和模型构建中的作用。 CAPE的极端水平（$> $ 2000 j/kg）与高影响力的天气事件有关，Cape广泛用于对流参数化，以帮助确定对流的强度和时机。但是，迄今为止，在气候环境中，在模型中，没有系统地评估了斗篷偏见，在足够大的评估中表征了斗篷分布的高尾巴。这项工作比较了来自四个来源的200,000多个夏季接近声音的CAPE分布：观察性辐射网络（IGRA），0.125度重新分析（ERA-In-Interim和ERA5），以及4公里的对流 - 渗透 - 渗透 - 由ERA-Interterim驱动的区域WRF模拟。 Reanalyses和模型都始终显示出CAPE的分布太多，高尾巴（$> $ 95％）系统地在基于表面的Cape中偏低高达10％，而最不稳定的层则具有20％。这种“缺失的尾巴”对应于最重要的相关条件。所有数据集中的CAPE偏差都受表面温度和湿度的偏差驱动：重新分析和模型未见的观察到的极热和水分的病例。这些结果表明，减少陆地表面和边界层模型中的不准确性对于准确再现斗篷至关重要。
Convective available potential energy (CAPE) is of strong interest in climate modeling because of its role in both severe weather and in model construction. Extreme levels of CAPE ($>$ 2000 J/kg) are associated with high-impact weather events, and CAPE is widely used in convective parametrizations to help determine the strength and timing of convection. However, to date no study has systematically evaluated CAPE biases in models in a climatological context, in an assessment large enough to characterize the high tail of the CAPE distribution. This work compares CAPE distributions in over 200,000 summertime proximity soundings from four sources: the observational radiosonde network (IGRA), 0.125 degree reanalysis (ERA-Interim and ERA5), and a 4 km convection-permitting regional WRF simulation driven by ERA-Interim. Both reanalyses and model consistently show too-narrow distributions of CAPE, with the high tail ($>$ 95th percentile) systematically biased low by up to 10% in surface-based CAPE and 20% at the most unstable layer. This "missing tail" corresponds to the most impacts-relevant conditions. CAPE bias in all datasets is driven by bias in surface temperature and humidity: reanalyses and model undersample observed cases of extreme heat and moisture. These results suggest that reducing inaccuracies in land surface and boundary layer models is critical for accurately reproducing CAPE.
