Daymet: Open-Source Science Leverages Standardized Interoperable Data
Daymet (Thornton et al., 2020; Thornton et al., 2021) is a 40+-year meteorological dataset at a fine-scale spatial (1km) and temporal (daily) resolution for North America, Hawaii, and Puerto Rico. Model inputs are a DEM, derived horizon files, a land water mask, and daily observations from ground-based meteorological stations (Menne et al. , 2012) . Machine interoperability and programmatic access to Daymet provide data retrieval options for users. The two most heavily used access methods are through a customized tool and API (The Single Pixel Extraction Tool (SPET)) and the THREDDS Data Server (TDS) web service.
Researchers, agencies, and educators take advantage of open access to develop programmatic interfaces and web services to Daymet data, creating higher-lever domain specific frameworks in an open-source, open-science environment. Due to Daymet’s high ESDIS usage, the ORNL DAAC’s Earthdata Cloud migration started with Daymet as a primary focus. Working with ESDIS, the ORNL DAAC is improving cloud-optimized file formats, cloud-based web access, and developing learning resources to support the research community.