WWRP Data Assimilation & Observing Systems





DAOS aims to provide guidance to the WWRP to optimize the use of the current WMO Global Observing System (GOS). DAOS will facilitate the development of data assimilation and observing system methodologies from the convective scale to planetary scales and for forecasts with time ranges of hours to weeks.

  • DAOS should promote research related to observing systems of the WWRP projects such as the development of observing systems (either to become more capable or at least less expensive), network design aspects (which variables, spatial and temporal sampling), and scientific methods to quantify the value of observations in numerical weather prediction and beyond.
  • DAOS should promote research related to data assimilation of the WWRP projects such as data assimilation techniques for earth system prediction systems including coupled data assimilation (including hydrological data assimilation), urban scale prediction (e.g., heat, air quality) and for severe weather events such as heavy precipitation.

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

Clara Draper, NOAA, USA


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