CISL Seminar Series: CISL's Data Assimilation Research Section: Accelerating NCAR Science with Ensemble Data Assimilation

11/06/2019 - 10:00am
Mesa Lab Main Seminar Room

Title: CISL's Data Assimilation Research Section: Accelerating NCAR Science with Ensemble Data Assimilation

Speaker: Jeff Anderson (Section Head, NCAR/Data Assimilation Research Section)


     Data assimilation (DA) is a vital part of modern numerical weather prediction; DA combines model weather forecasts with observations of the atmosphere to produce improved initial conditions for subsequent forecasts. DA can be applied in a similar fashion to any application with a prediction model and observations (ocean, land surface, space weather, spread of influenza, etc.). DA is essential for making predictions, but can also be used to improve models, design observing systems, and many other things. The Data Assimilation Research Section (DAReS) provides state-of-the-art DA tools to earth system scientists by developing, maintaining, and supporting use of the Data Assimilation Research Testbed (DART).

     DART supports a diverse set of dozens of large earth system models and runs on a variety of computational platforms. This necessitates a software design that allows inexpensive implementation for new models or observations while retaining flexibility to explore new science problems. These requirements led to the use of ensemble data assimilation algorithms which will be reviewed in the context of the DART system.

     Several ongoing collaborations between DAReS and scientists from across NCAR and the UCAR University community will be highlighted. This will provide an opportunity to introduce the DAReS team. Plans for several new collaborations including global coupled earth system prediction will also be presented.

     The DAReS team also actively develops new advanced ensemble assimilation algorithms. Recent advances on dealing with non-Gaussian and nonlinear DA problems will be discussed along with their potential to provide major improvements for important earth system applications.


Jeff Anderson’s research career has spanned two decades and has been focused by the common theme to improve predictions of the earth’s atmosphere. He has made research contributions in theoretical geophysical fluid dynamics, seasonal prediction , predictability , ensemble prediction and ensemble data assimilation. His accomplishments in software engineering, applied mathematics and statistics have been directly in support of his goal to improve prediction.

Refreshments will be served at 9:45 a.m.!

Date: November 6, 2019

Time: 10:00-11:00am

Location: Mesa Lab, Main Seminar Room (MSR)