WWRP Data Assimilation & Observing Systems
Mission
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
News
Open Special Issues
- QJRMS special collection on Coupled Earth System data assimilation (open through the end of 2024)
- QJRMS special collection: Combined machine learning and data assimilation for the atmosphere and ocean sciences (open through July 2024)
Educational/Training Links
@University of Reading
- DARC/NCEO Training for PhD students/early career researchers Technical/mathematical training, 1 week course held annually - often to tie in with ECMWF training.
- MOOC - Dare to discover data assimilation Non-technical free course open any time (Facilitated run Nov 2022) @ECMWF
- MOOC - Machine Learning in Weather and Climate
- ECMWF training on DA and the use of satellite data (annual)
- General DA: https://events.ecmwf.int/event/272/timetable/
- Use of satellite data: https://events.ecmwf.int/event/273/timetable/
Upcoming Events
Past Events
Documents