Assess the Impact of Climate Change on Agricultural Productivity Using GES DISC Data on Temperature, Precipitation, and Drought Indices

In the face of global climate change, agricultural productivity is increasingly under threat, with changes in temperature, precipitation, and drought conditions significantly impacting crop yields and food security. This study presents a comprehensive regional-level analysis, leveraging rich datasets from the Goddard Earth Science Data & Information Center (GES DISC) and the Galaxy Workflow Engine, an open-source science tool enabling Findable, Accessible, Interoperable, and Reusable (FAIR) science. The workflow, executed through Galaxy with high-performance computing resources from the National Science Foundation’s Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (NSF ACCESS), is applied to selected states in the United States of America and selected countries in Southeast Asia and Africa. The area of interest can be predefined or defined by an arbitrary polygon, enabled by processing capabilities for interoperability on both climate variables and agricultural productivity implemented in the Galaxy toolshed. The Open Geospatial Consortium (OGC) API - Processes service is used for customization services. Advanced analysis techniques, including time series analysis, machine learning, and statistical correlation, are incorporated to assess the impact of climate change on agricultural productivity. By leveraging GES DISC data, Galaxy Climate tools, and NSF ACCESS resources, valuable insights into the impact of climate change on agricultural productivity in various regions are gained. This informs the development of adaptation strategies, improvement of agricultural practices, and ensures long-term food security. The use of Galaxy workflows and GES DISC Giovanni for profiled time series data retrieval contributes to the development of an Open Science workflow, promoting open science principles and enhancing research reproducibility and accessibility. The designed workflow is reusable and can be applied to different regions, enhancing its utility for broader climate change impact assessments.