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Share insights beautifully using Data Visualization techniques

Second floor sphere - Earth visualization

Find the meaning in big data, create interactive data visualizations that tell your story beautifully, and communicate your findings to the world.

Visualize the Possibilities

Build a more accurate, multi-layered knowledge base via Data Assimilation

REAL during T-REX

Discover state-of-the-art ensemble data assimilation capabilities for the NSF NCAR community, including services, tutorials, and software.

 

Assimilate Now

Global Variability in Atmospheric New Particle...

Mechanisms of NPF and constraints from observations over rainforests.

By Bin Zhao, Neil M. Donahue, Kai Zhang, et al.

Leveraging a Novel Hybrid Ensemble and Optimal Interpolation Approach for Enhanced...

Leveraging a novel hybrid ensemble and optimal interpolation approach for enhanced streamflow and flood prediction

By Mohamad El Gharamti, Arezoo Rafieeinasab, and James L. McCreight

Exploring NWS Forecasters’ Assessment of AI Guidance...

Exploring NWS Forecasters’ Assessment of AI Guidance Trustworthiness

By Mariana G. Cains, Christopher D. Wirz, Julie L. Demuth, et al.

On a Structural Similarity Index Approach for Floating...

On a Structural Similarity Index Approach for Floating-Point Data

By Allison H. Baker, Alexander Pinard, and Dorit M. Hammerling

A Machine Learning-Based Approach to Quantify ENSO...

A Machine Learning-Based Approach to Quantify ENSO Sources of Predictability

By Ioana Colfescu, Hannah Christensen, and David John Gagne

Integrating Farmers’ Perspectives into Earth System Model Development: Interviews with...

Integrating Farmers’ Perspectives into Earth System Model Development: Interviews with End Users in the Willamette Valley, Oregon, to Guide Actionable Science

By Kelsey Emard, Olivia Cameron, William R. Wieder, et al.

Exploring Non-Gaussian Sea Ice Characteristics Via...

Exploring non-Gaussian sea ice characteristics via observing system simulation experiments

By Christopher Riedel and Jeffrey Anderson

Increasing the Reproducibility and Replicability of...

Increasing the Reproducibility and Replicability of Supervised AI/ML in the Earth Systems Science by Leveraging Social Science Methods

By Christopher D. Wirz, Carly Sutter, Julie L. Demuth, et al.

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This material is based upon work supported by the NSF National Center for Atmospheric Research, a major facility sponsored by the U.S. National Science Foundation and managed by the University Corporation for Atmospheric Research. Any opinions, findings and conclusions or recommendations expressed in this material do not necessarily reflect the views of the U.S. National Science Foundation.