Atmospheric River Tracking Method Intercomparison Project (ARTMIP): project goals and experimental design
Atmospheric River Tracking Method Intercomparison Project (ARTMIP): project goals and experimental design
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DOI：
10.5194/gmd-11-2455-2018
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发表时间：
2018-06
影响因子：
5.1
通讯作者：
C. Shields;J. Rutz;L. Leung;F. Ralph;M. Wehner;B. Kawzenuk;J. Lora;E. McClenny;Tashiana Osborne;A. Payne;P. Ullrich;A. Gershunov;N. Goldenson;B. Guan;Y. Qian;A. Ramos;C. Sarangi;S. Sellars;I. Gorodetskaya;K. Kashinath;V. Kurlin;K. Mahoney;G. Muszynski;R. Pierce;A. Subramanian;R. Tomé;D. Waliser;D. Walton;G. Wick;Anna M. Wilson;D. Lavers;Prabhat;A. Collow;Harinarayan Krishnan;G. Magnusdottir;P. Nguyen
中科院分区：
文献类型：
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作者：
C. Shields;J. Rutz;L. Leung;F. Ralph;M. Wehner;B. Kawzenuk;J. Lora;E. McClenny;Tashiana Osborne;A. Payne;P. Ullrich;A. Gershunov;N. Goldenson;B. Guan;Y. Qian;A. Ramos;C. Sarangi;S. Sellars;I. Gorodetskaya;K. Kashinath;V. Kurlin;K. Mahoney;G. Muszynski;R. Pierce;A. Subramanian;R. Tomé;D. Waliser;D. Walton;G. Wick;Anna M. Wilson;D. Lavers;Prabhat;A. Collow;Harinarayan Krishnan;G. Magnusdottir;P. Nguyen
抽象。大气河流跟踪方法相互比较项目（ARTMIP）是一项国际合作项目，旨在了解和量化仅基于检测算法的大气河流（AR）科学中的不确定性。目前，文献中已有许多AR识别和跟踪算法，技术和结论也各不相同。ARTMIP致力于为社区提供有关不同方法的信息，并为给定的科学问题或感兴趣的区域提供最合适的算法指导。所有ARTMIP参与者将在指定的公共数据集上实施他们的检测算法，并持续一段时间。该项目分为两个阶段：第一阶段将利用1980年1月至2017年6月的现代研究和应用回顾分析第2版（MERRA-2）再分析，并将用作所有后续比较的基线。需要参加Tier 1。第二级是可选的，包括围绕具体科学问题设计的敏感性研究，如再分析不确定性和气候变化。将尽可能使用高分辨率再分析和/或模型输出。建议的指标包括AR频率、持续时间、强度和归因于AR的降水。在这里，我们提出了ARTMIP的实验设计，时间轴，项目要求，并在目前的文献中的各种方法的简要说明。我们还介绍了为期1个月的“概念验证”试验结果，旨在说明ARTMIP项目的实用性和可行性。
Abstract. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is an international collaborative effort to understand and quantify the uncertainties in atmospheric river (AR) science based on detection algorithm alone. Currently, there are many AR identification and tracking algorithms in the literature with a wide range of techniques and conclusions. ARTMIP strives to provide the community with information on different methodologies and provide guidance on the most appropriate algorithm for a given science question or region of interest. All ARTMIP participants will implement their detection algorithms on a specified common dataset for a defined period of time. The project is divided into two phases: Tier 1 will utilize the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) reanalysis from January 1980 to June 2017 and will be used as a baseline for all subsequent comparisons. Participation in Tier 1 is required. Tier 2 will be optional and include sensitivity studies designed around specific science questions, such as reanalysis uncertainty and climate change. High-resolution reanalysis and/or model output will be used wherever possible. Proposed metrics include AR frequency, duration, intensity, and precipitation attributable to ARs. Here, we present the ARTMIP experimental design, timeline, project requirements, and a brief description of the variety of methodologies in the current literature. We also present results from our 1-month “proof-of-concept” trial run designed to illustrate the utility and feasibility of the ARTMIP project.