ESMValTool v2.0 – Technical overview
ESMValTool v2.0 – Technical overview
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EMValTool v2.0 – 技术概述
DOI：
10.5194/gmd-2019-226
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Klaus Zimmermann
中科院分区：
文献类型：
--
作者：
M. Righi;B. Andela;V. Eyring;A. Lauer;V. Predoi;Manuel Schlund;Javier Vegas;L. Bock;Björn Brötz;L. de Mora;F. Diblen;Laura Dreyer;N. Drost;P. Earnshaw;B. Hassler;Nikolay Koldunov;Bill Little;S. Loosveldt Tomas;Klaus Zimmermann
摘要。本文介绍了地球系统模型评估工具（ESMValTool）的第二个主要版本，ESMValTool是一个社区诊断和性能度量工具，用于评估参与耦合模型比对项目（CMIP）的地球系统模型（esm）。与2016年发布的1.0版本相比，ESMValTool 2.0版本（v2.0）具有全新的设计，改进了界面并修改了预处理器。它还具有显著增强的诊断部分，在三个同伴论文中描述。新版本的ESMValTool是专门针对CMIP第6阶段（CMIP6）数据量的增加以及分析和评估多个高分辨率或复杂esm输出所带来的相关挑战而开发的。新版本利用了最先进的计算库和方法来部署高效和用户友好的数据处理。对输入数据的常见操作（如重网格或多模型统计计算）集中在高度优化的预处理程序中，允许在应用诊断脚本之前应用一系列预处理功能，对模型输出进行深入的科学分析。对一组标准诊断进行的性能测试表明，新版本比其前身快了大约三倍。当使用新引入的基于任务的并行化选项时，性能可以进一步提高，最高可提高30倍以上，这使得能够有效地利用更大的计算基础设施。ESMValTool v2.0还包括修订和简化的安装过程，基于现代语言格式的用户可配置选项设置，以及遵循软件开发最佳实践的高代码质量标准。
Abstract. This paper describes the second major release of the Earth System Model Evaluation Tool (ESMValTool), a community diagnostic and performance metrics tool for the evaluation of Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP). Compared to version 1.0, released in 2016, ESMValTool version 2.0 (v2.0) features a brand new design, with an improved interface and a revised preprocessor. It also features a significantly enhanced diagnostic part that is described in three companion papers. The new version of the ESMValTool has been specifically developed to target the increased data volume of CMIP Phase 6 (CMIP6) and the related challenges posed by the analysis and the evaluation of output from multiple high-resolution or complex ESMs. The new version takes advantage of state-of-the-art computational libraries and methods to deploy an efficient and user-friendly data processing. Common operations on the input data (such as regridding or computation of multi-model statistics) are centralized in a highly optimized preprocessor, which allows applying a series of preprocessing functions before diagnostics scripts are applied for in-depth scientific analysis of the model output. Performance tests conducted on a set of standard diagnostics show that the new version is faster than its predecessor by about a factor of three. The performance can be further improved, up to a factor of more than 30, when the newly-introduced task-based parallelization options are used, which enable the efficient exploitation of much larger computing infrastructures. ESMValTool v2.0 also includes a revised and simplified installation procedure, setting of user configurable options based on modern language formats, and high code quality standards following the best practices for software development.
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影响因子：
11.4
作者：
M. Stengel;Stefan Stapelberg;O. Sus;C. Schlundt;C. Poulsen;G. Thomas;M. Christensen;C. C. Henken-C.;R. Preusker;J. Fischer;A. Devasthale;U. Willén;K. Karlsson;G. Mcgarragh;S. Proud;A. Povey;R. Grainger;J. F. Meirink;A. Feofilov;R. Bennartz;J. Bojanowski;R. Hollmann
通讯作者：
M. Stengel;Stefan Stapelberg;O. Sus;C. Schlundt;C. Poulsen;G. Thomas;M. Christensen;C. C. Henken-C.;R. Preusker;J. Fischer;A. Devasthale;U. Willén;K. Karlsson;G. Mcgarragh;S. Proud;A. Povey;R. Grainger;J. F. Meirink;A. Feofilov;R. Bennartz;J. Bojanowski;R. Hollmann
如何将稀疏海洋原位测量与连续模型进行比较：示例
影响因子：
5.1
作者：
De Mora L
通讯作者：
De Mora L
哥白尼气候变化服务 (C3S) 全球大气二氧化碳和甲烷卫星观测
DOI：
10.1007/s42423-018-0004-6
发表时间：
2018
期刊：
Advances in Astronautics Science and Technology
影响因子：
--
作者：
Buchwitz M
通讯作者：
Buchwitz M
影响因子：
5.1
作者：
D. Watson‐Parris;N. Schutgens;Nicholas Cook;Z. Kipling;P. Kershaw;E. Gryspeerdt;B. Lawrence;P. Stier
通讯作者：
D. Watson‐Parris;N. Schutgens;Nicholas Cook;Z. Kipling;P. Kershaw;E. Gryspeerdt;B. Lawrence;P. Stier