Research, AI & Environment
Ground observations for research and AI. Providing scientists and developers with verifiable physical ground truth to validate models and evaluate environmental exposure.
Ground observations for research and AI.
Google DeepMind is a WeatherXM data customer. Our observations are also used by research organizations and university teams studying weather and environmental conditions.
Measurements give researchers a record of the physical world to set against model output and other datasets. Station context, available history and quality assessment are part of choosing appropriate data for a study — and we would rather have that conversation before the study than after it.
Environmental exposure in materials research.
Our materials R&D work connects local environmental conditions to questions about how materials and products perform over time. Observing exposure at the relevant location adds evidence a regional weather summary cannot.
We support academic and non-commercial research with access arranged case by case rather than through a published tariff — tell us the institution, the study and the locations and period you need.
Ground Truth for Modern Science
AI Weather Evaluation
Evaluating global AI models (GraphCast, ClimaX, Pangu-Weather) requires dense, independent surface truth to assess localized precipitation bias and surface thermal gradients.
Photodegradation & UV Index
Continuous solar irradiance and UV spectrum logging correlate directly with polymer breakdown, paint discoloration, and outdoor material weathering cycles.
Verifiable science datasets
Sub-minute historical telemetry archives stored on decentralized storage ensure published academic studies remain reproducible and citeable decades into the future.
Ready to explore research datasets?
Arrange academic data access or read our published meteorological quality evaluations.