Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, California.
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California.
Ann N Y Acad Sci. 2020 Jul;1472(1):139-154. doi: 10.1111/nyas.14368. Epub 2020 May 22.
Atmospheric rivers (ARs) are narrow regions of strong horizontal water vapor transport that play important roles in the global water cycle, weather, and hydrology. Motivated by challenges in simulating ARs with state-of-the-art global models, this paper diagnoses model errors with a focus on relative contributions of moisture convergence, evaporation, and precipitation to AR column-integrated water vapor (IWV) budget. Using 20-year simulations by 24 global weather/climate models, budget terms are calculated for four AR sectors: postfrontal, frontal, prefrontal, and pre-AR, with biases assessed against two reanalysis products. The results indicate that each sector is unique in terms of the dominant water vapor balance, and that the terms exhibiting the largest intermodel spread are the same terms dominating the water vapor balance in each sector. Overall, simulated bulk AR characteristics (e.g., geometry, frequency, and intensity) are more sensitive to biases in IVT convergence and IWV tendency than to biases in evaporation and precipitation, although evaporation/precipitation biases do affect key AR bulk characteristics in selected sectors. The large intermodel spread (particularly for precipitation) and, in certain cases, discrepancies between the reanalysis references themselves (particularly for precipitation types) highlight the need for observational efforts that target better constraining AR processes in weather/climate models and reanalyses.
大气河流(ARs)是水平水汽输送强烈的狭窄区域,在全球水循环、天气和水文学中起着重要作用。由于具有挑战性的是用最先进的全球模式模拟 ARs,本文通过关注水汽汇聚、蒸发和降水对 AR 柱积分水汽(IWV)预算的相对贡献,诊断模型误差。利用 24 个全球天气/气候模型的 20 年模拟,为四个 AR 扇区(后锋、锋前、锋中和前 AR)计算了预算项,并根据两个再分析产品评估了偏差。结果表明,每个扇区在水汽平衡方面都是独特的,表现出最大的模型间差异的项是主导每个扇区水汽平衡的相同项。总体而言,模拟的 AR 整体特征(如几何形状、频率和强度)对 IVT 汇聚和 IWV 趋势的偏差比对蒸发和降水的偏差更敏感,尽管蒸发/降水的偏差确实会影响某些扇区的关键 AR 整体特征。大的模型间差异(特别是降水),以及在某些情况下,再分析参考本身之间的差异(特别是降水类型)突出了需要进行观测工作,以更好地约束天气/气候模型和再分析中的 AR 过程。