Department of Civil and Environmental Engineering, University of California, Davis. 1 Shields Ave, Davis, CA 95616, USA.
Int J Environ Res Public Health. 2019 Feb 26;16(5):687. doi: 10.3390/ijerph16050687.
In this article, a dynamical downscaling (DD) procedure is proposed to downscale tropical cyclones (TCs) from a general circulation model, with the goal of investigating inland intense precipitation from these storms in the future. This DD procedure is sequential as it is performed from the large scale to the small scale within a one-way nesting modeling framework with the Weather Research and Forecasting (WRF) model. Furthermore, it involves a two-step validation process to ensure that the model produces realistic TCs, both in terms of their general properties and in terms of their intense precipitation statistics. In addition, this procedure makes use of several algorithms such as for the detection and tracking of TCs, with the objective of automatizing the DD process as much as possible so that this approach could be used to downscale massively many climate projections with several sets of model options. The DD approach was applied to the Community Climate System Model (CCSM) version 4 using Representative Concentration Pathway (RCP) 4.5 during the period 2005⁻2100, and the resulting TCs and their intense precipitation were examined.
本文提出了一种动力降尺度(DD)程序,用于将热带气旋(TCs)从大气环流模型中降尺度化,目的是研究未来这些风暴在内陆地区产生的强降水。该 DD 程序是顺序执行的,因为它是在一个具有天气研究和预报(WRF)模型的单向嵌套建模框架内,从大尺度到小尺度进行的。此外,它涉及一个两步验证过程,以确保模型产生的 TC 具有现实性,无论是在其一般特性方面,还是在其强降水统计方面。此外,该程序还利用了一些算法,如 TC 的检测和跟踪,目的是尽可能使 DD 过程自动化,以便该方法可以用于降尺度化大量的气候预测,同时有几组模型选项。DD 方法应用于社区气候系统模型(CCSM)第 4 版,使用代表浓度途径(RCP)4.5,在 2005 年至 2100 年期间,研究了由此产生的 TC 及其强降水。