WWRP Data Assimilation & Observing Systems

Working Group on Data Assimilation and Observing Systems (DAOS)


DAOS aims to advance the optimal use of observations and to drive the development of data assimilation for coupled Earth System models. Currently, DAOS has identified three main research focus areas where the WG can contribute with relevant progress to the overarching WWRP theme of advancing Seamless Prediction in Earth System modelling. These are

  • Coupled data assimilation
  • Machine learning for DA applications
  • Observation impact for existing and future observation systems

DAOS seeks collaboration with universities and research-performing institutions, environmental agencies as well as any kind of education institution interested in using observation data in weather and climate.

Group photo of DAOS and PDEF Joint Working Group Meeting at the University of Reading, UK, in November 2022

Working Group Members


Co-chair: Sarah L. Dance, University of Reading, UK

Co-chair: Ulrich Löhnert, University of Cologne, Germany

Rossella Arcucci, Imperial College of London, UK

Thomas Auligné, JCSDA, USA

Sean Healy, ECMWF, UK

Lili Lei, University of Nanjing, China

Andrew M. Moore, University of California, Santa Cruz, USA

Takemasa Miyoshi, Riken Center for Computational Science, Japan

Juan Ruiz, CIMA-UB, Argentina

Phillip Browne, ECMWF, Ireland




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