Climate-driven sectoral applications commonly require different types of climate data (e.g. observations, reanalysis, climate change projections) from different providers. Data access, harmonization and post-processing (e.g. bias correction) are time-consuming error-prone tasks requiring different specialized software tools at each stage of the data workflow, thus hindering reproducibility. Here we introduce climate4R, an R-based climate services oriented framework tailored to the needs of the vulnerability and impact assessment community that integrates in the same computing environment harmonized data access, post-processing, visualization and a provenance metadata model for traceability and reproducibility of results. climate4R allows accessing local and remote (OPeNDAP) data sources, such as the Santander User Data Gateway (UDG), a THREDDS-based service including a wide catalogue of popular datasets (e.g. ERA-Interim, CORDEX, etc.). This provides a unique comprehensive open framework for end-to-end sectoral reproducible applications. All the packages, data and documentation for reproducing the experiments in this paper are available from http://www.meteo.unican.es/climate4R.

气候驱动的部门应用通常需要来自不同提供者的不同类型的气候数据（例如，观测，再分析，气候变化预测）。数据访问，协调和后处理（例如，偏差校正）是耗时的易错任务，在数据工作流的每个阶段都需要不同的专用软件工具，从而阻碍了可重复性。在这里，我们介绍Climate4R，这是一个基于R的气候服务导向框架，专门针对脆弱性和影响评估社区的需求而设计，该框架集成在同一计算环境中，统一了数据访问，后处理，可视化和出处元数据模型，以实现可追溯性和可重复性。结果。气候4R允许访问本地和远程（OPeNDAP）数据源，例如桑坦德用户数据网关（UDG），这是一种基于THREDDS的服务，其中包括各种流行的数据集（例如ERA-Interim，CORDEX等）。这为端到端部门可重现的应用程序提供了一个独特的全面开放框架。可从http://www.meteo.unican.es/climate4R获得用于重现本文实验的所有软件包，数据和文档。