Earthmover Expands Data Marketplace With New Oceanography Segment

According to a recent LinkedIn post from Earthmover, the company’s data marketplace has expanded to include a new oceanography segment alongside its existing atmosphere and land categories. The post highlights that this third pillar appears designed to extend the platform’s relevance across Earth system science use cases, particularly for data-intensive modeling and analytics.

The LinkedIn post suggests that multi-terabyte ocean model hindcasts, traditionally stored in large collections of NetCDF files, are being made accessible as single, cloud-native data cubes compatible with tools such as Xarray and Flux APIs. This approach could reduce friction for users building machine learning and advanced analytics pipelines, potentially increasing usage of Earthmover’s infrastructure and related services.

As shared in the post, two initial ocean datasets are now available on the marketplace and are described as free and open. One comes from the U.K. National Oceanography Centre, offering a near-present day 1/12° ocean sea-ice hindcast covering 1976 to the present, with a subset aligned to satellite-era observations, which may attract climate and ocean research workloads.

The second dataset, described as ARCO-OCEAN from OGS in Italy, bundles ocean, wave, and sea-ice physics with hydrological and atmospheric forcing in a single Zarr store optimized for machine learning. By curating multi-physics, ML-ready ocean data, Earthmover may be positioning itself as a key intermediary for AI-driven climate and environmental modeling, which could support long-term demand from academic, public, and commercial users.

For investors, the move to incorporate ocean data suggests a broader platform strategy that spans major components of the Earth system, potentially increasing the addressable market for Earthmover’s marketplace and tooling. While the post emphasizes open and free datasets, greater user engagement and reliance on the platform could translate into future monetization opportunities around premium data, compute, or enterprise services in the climate-tech and geospatial analytics sectors.