Google Earth Engine Climate Tool (GEEClimT): Enabling rapid, easy access to global climate reanalysis data

Abstract

Investigation of local to global scale environmental change is frequently underpinned by data from climate reanalysis products, yet access to these can be challenging for both new and established researchers. The practicalities of working with reanalysis data often includes handling large data files that can place limit users on the scale of analysis they can undertake; and working with specialist data formats (e.g. NetCDF, GRIB) that can pose significant barriers to entry for those who may be unfamiliar with them. Together, these factors are limiting the uptake and application of climate reanalysis data within both research and teaching of environmental science.Here we present the Google Earth Engine Climate Tool (GEEClimT), providing an intuitive “point and click” graphical user interface (GUI) for easy extraction of data from 17 climate reanalysis data products relating to atmospheric and oceanic variables (including, but not limited to: ERA5; ERA5-Land; NCEP/NCAR; MERRA; and HYCOM). The GUI is built within the Google Earth Engine geospatial cloud computing platform, meaning users only require an internet connection to rapidly obtain both point data and area averages for user defined regions of interest. To ensure a wide range of usability for researchers, students and instructors, both the GUI and its documentation have been co-created with those who may use reanalysis data for research, teaching, and project purposes. The tool has also been designed with flexibility in mind, allowing it to be easily updated as new datasets become available within the Google Earth Engine data catalogue.GEEClimT is shown to allow users with little or no previous experience of working with climate reanalysis data or coding to obtain temporally comprehensive data for their regions and time periods of interest. Case studies demonstrating the application of the tool to different environmental and ecological settings are presented, showcasing its potentially wide applicability to both research and teaching across environmental science.