01
Climate Modeling
Model output analysis. Inter-model comparison. Bias correction.
← Industries
CLIMATE & ENVIRONMENT
Petabytes, in plain English.
Climate models generate petabytes. Sensor networks stream continuously. Satellite imagery arrives daily. Calliope AI gives you analysis that scales — and governance that lets institutions collaborate without compromising data integrity.
Climate science is a data problem. And a collaboration problem.
Multi-institution collaborations. Terabytes of model output. Decades of observational data. Multiple funding agencies with different requirements.
The question-answering machine for your climate data.
Massive data. Complex collaboration. Reproducible results.
Scale to your data — From gigabytes to petabytes. Same environment, same tools, more compute.
Multi-institution collaboration — Share analyses without sharing credentials. Governed access across organizations.
Reproducibility built-in — Containerized environments. Version-controlled notebooks. No more 'worked on my cluster.'
AI-powered analysis — Turn your climate scientists into 10x data analysts. Natural language queries on model output.
Any data source — NetCDF, GRIB, satellite imagery, station data, reanalysis. Query anything, build any visualization.
Grant compliance — Demonstrate data governance for NSF, DOE, NOAA, and international funding agencies.
Earth science data, and the questions you can finally just ask it:
- Climate model output (CMIP, CESM, WRF)
- Satellite and remote sensing data
- Observational networks and station data
- Reanalysis products (ERA5, MERRA-2)
- Your institution’s data archives
- “Show me temperature anomalies for 2024 vs 1990-2020 baseline”
- “Which CMIP6 models best match observed precipitation in the Amazon?”
- “Generate a time series of Arctic sea ice extent by month”
Climate & Environmental Capabilities
02
Remote Sensing
Satellite imagery processing. Land use change detection. Vegetation indices.
03
Observational Networks
Station data QC. Network analysis. Gap filling.
04
Ecosystem Modeling
Carbon cycle analysis. Ecosystem services. Biodiversity metrics.
05
Air & Water Quality
Pollution monitoring. Source attribution. Trend analysis.
06
Climate Risk
Hazard assessment. Vulnerability mapping. Adaptation planning.
Deployment
How it deploys for climate & environment.
Deploy where your data lives and scale to the size of the problem — from gigabytes on a laptop to petabytes across a cluster, same environment and tools throughout. Multi-institution teams share analyses without sharing credentials. Choose the mode that matches the work.
Cloud-native
Scale to thousands of cores for massive model runs, single-tenant inside your own account. Containerized, version-controlled environments keep results reproducible across every run.
Explore →HPC integration
Connect to your institution's supercomputing resources and run alongside existing batch and scheduler infrastructure. The footprint is light enough to deploy at a remote field station or partner facility without heavy infrastructure.
Explore →Desktop
Local analysis with Ollama for offline fieldwork — run entirely on your own machine where connectivity is thin or absent. Bring your own keys and keep everything private.
Explore →Researchers in the field or at partner institutions reach the platform through browser-based desktops, and grant data-governance for NSF, DOE and NOAA is demonstrable from the audit trail. AWS is fully supported today; additional clouds are on the roadmap — built to port.
