Leading-edge DA technology
Data assimilation (DA) confronts predictive models with real-world observations to make both better and more powerful. It's where modeling meets the real world.
DAReS, the Data Assimilation Research Section at NSF NCAR, provides state-of-the-art ensemble data assimilation capabilities for NSF NCAR community modeling systems.
Our mission is to accelerate progress in actionable Earth systems science through DA capabilities—at NSF NCAR, UCAR, and in the broader science community.
Data assimilation for all
We make data assimilation accessible—so you don't need to spend decades mastering it.
Get going right away with our easy-to-use tools, documentation, tutorials, and consulting services. Helping you is our #1 priority.
The bottom line? We help people do science faster and better.
Get to know DART software
The Data Assimilation Research Testbed (DART) is a community facility for ensemble DA featuring exclusive, state-of-the-art capabilities offered nowhere else.
We develop algorithms like:
- the deterministic and stochastic ensemble Kalman filter
- the particle filter
- hybrid DA methods
- the quantile conserving ensemble filtering framework
We strive to produce the best DA algorithms available—algorithms at the leading edge of research.