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Data Assimilation (DA-TT)


The DA-TT brings together experts in the field from leading operational centres, research institutions, and groups from academia in a shared dialog about the current state-of-the-art, and common challenges faced by the ocean Data Assimilation (DA) community. The primary vehicles are regular workshops and collaborative activities. Since DA is an essential and common thread to many of the OceanPredict goals, an additional role of DA-TT is to catalyse interactions with other TTs.

The DA-TT promotes capacity building in several areas, including: the development of modelling, assimilation, and forecasting approaches and components; demonstrations of accuracy and utility; research value; and intellectual capacity building. The DA-TT also provides a conduit to the broader WMO data assimilation and prediction community. The ocean DA community is small compared to its atmospheric counterpart, and as such, capacity building to meet the current and future demands of the field is an important TT goal. Future DA-TT activities will therefore continue to expand capacity building activities, particularly in relation to intellectual capital, with a view to sustaining an active and vibrant ocean DA community.

The DA-TT is led by the co-chairs:


The DA-TT will foster coordination and monitor progress in activities related to:

  • Development of data assimilation algorithms.
  • Development of coupled data assimilation methods in collaboration with the CP-TT.
  • Assimilation of novel observations (under-utilised existing networks and upcoming missions) in collaboration with the OSEVal-TT and with the MEAP-TT.
  • Assimilation software infrastructure developments and application to new HPC architectures, as related to the adoption of tools developed in the wider data assimilation community which allow enhanced collaborations among operational agencies, research institutes and universities.
  • Performance assessment of data assimilation applications in the operational community, in collaboration with the IV-TT.
  • Application of data-driven algorithms (machine learning and deep learning) for improved pre-processing and exploitation of consolidated and new observing networks.


A major activity of the DA-TT is to organise regular meetings and workshops. In order to increase collaboration, these workshops are often held jointly with other TTs or groups.

The DA-TT coordinates inter-comparison activities aimed at improving our understanding of the operational data assimilation systems used by OceanPredict groups. These have previously included comparison of average increments to understand biases in the ocean models and forcing, and comparison of the impact of observations using idealised, widely spaced observations.

The DA-TT also coordinates contributions to other international activities. We have previously contributed to international conferences such as OceanObs’19 (Moore et al., 2019) and to the 2016 international workshop on coupled data assimilation (Penny et al., 2017).

Moore AM, Martin MJ, Akella S, Arango HG, Balmaseda M, Bertino L, Ciavatta S, Cornuelle B, Cummings J, Frolov S, Lermusiaux P, Oddo P, Oke PR, Storto A, Teruzzi A, Vidard A and Weaver AT (2019). Synthesis of Ocean Observations Using Data Assimilation for Operational, Real-Time and Reanalysis Systems: A More Complete Picture of the State of the Ocean. Front. Mar. Sci. 6:90. doi: 10.3389/fmars.2019.00090.

Penny, S.G., S. Akella, O. Alves, C. Bishop, M. Buehner, M. Chevallier, F. Counillon, C. Draper, S. Frolov, Y. Fujii, A. Karspeck, A. Kumar, P. Laloyaux, J.-F. Mahfouf, M. Martin, M. Peña, P. de Rosnay, A. Subramanian, R. Tardif, Y. Wang, X. Wu. 2017. Coupled Data Assimilation for Integrated Earth System Analysis and Prediction: Goals, Challenges and Recommendations. WWRP 2017-3

Members of the DA-TT


No First name Last name Institutions/projects Country Status
1 Santha Akella  NASA USA Member
2 Hernan Arango  Rutgers University USA Member
3 Ali Aydogdu  CMCC Italy Member
4 Laurent Bertino  NERSC Norway Member
5 Gary Brassington  BoM Australia Member
6 Marcin Chrust  ECMWF UK Member
7 Bruce Cornuelle  Scripps USA Member
8 Francois Counillon  NERSC Norway Member
9 James Cummings  NRL/NOAA USA Passive Member
10 Pierre De Mey-Fremaux  LEGOS France Member and co-chair of the COSS-TT
11 Sergey Frolov  NRL, Monterey USA Member
12 Patrick Heimbach  University of Texas at Austin USA Member
13 Young Ho Kim  KIOST South Korea Member
14 Alexander Kurapov  Oregon State University / NOAA USA Member
15 Daniel Lea  Met Office UK Member
16 Pierre Lermusiaux  MIT USA Member
17 Matt Martin  Met Office UK Co-chair
18 Andrew M
Moore  UCSC USA Co-chair
19 Hans N Ngodock  NRL USA Member
20 Paolo Oddo  CMRE Italy Member
TBC Peter OKE (TBC)  CSIRO Australia Member ?
21 Arya Paul  INCOIS India Member
22 Pavel Sakov  BoM Australia Member
23 Jozef Skakala  PML UK New member (14 Sep 20)
24 Gregory Smith  Environment Canada Canada Member and co-chair of the IV-TT
25 Joao Souza  Metocean New Zealand Member
26 Ann Kristin Sperrevick Norway Member
27 Andrea Storto  CMRE/NATO Italy Member
28 Clemente Tanajura  UFBA / REMO Brazil Member
29 Anna Teruzzi  OGS Italy Member
30 Charles-Emmanuel Testut  Mercator Ocean France Member
31 Norihisa Usui  JMA/MRI Japan Member
32 Arthur Vidard  Inria France Member
33 Anthony Weaver  CERFACS France Member
34 Xueming Zhu  NMEFC China Member

Patron champion:

Johnny Johannessen, NERSC


Status: September 2020

Meetings and workshops

A major activity of the DA-TT is to organise regular workshops. In order to increase collaboration, these workshops are often held jointly with other TTs or groups. Planned and previous workshops include:


The DA-TT is involved in the ESA A-TSCV project, to work of the assimilation of Total Surface Current Velocity Measurements.

Find out more from the A-TSCV project page.


Meeting reports:

TT Quad-chart

The task team quad-chart provides a quick glance at the TT’s activities, achievements and future plans.


Data Assimilation Task Team (DA-TT) – October 2019
Short description and objectives of the activities started or planned for this year:
Accomplishments of the TT this year:
Main activities:

1. Improving understanding of error covariances used in existing DA systems through coordinated “multiple widely-spaced observation” experiments.

2. Identifying and quantifying model and forcing bias through inter-comparison of average assimilation increments.

3. Promote the development of hybrid data assimilation methods in the ocean

4. Organise meetings aimed at fostering the development of the DA systems

Main achievements:

• The DA-TT co-chairs were active in the organization of the OceanPredict ’19 symposium in Halifax, NS.

• As part of OceanPredict ’19 a very successful DA training session was organized, with over 70 participants.

• The DA-TT co-chairs co-authored, with TT members, a mini-review paper published in Frontiers in Marine Science in support of OceanObs19.

• Several DA-TT members were active participants at OceanObs19, leading a discussion forum on ocean DA.

• Several new members have been invited to join the task team to expand representation from other international communities.

Future plans to continue/ improve current activities:
Issues/ problems:
Main future plans:

• Work plan item 1 has been on-hold because of preparation for the OceanPredict19 symposium and OceanObs19 white paper. This activity will resume pending TT engagement.

• Work plan item 2 has also been on hold, although several other groups have expressed interest in contributing.

• Organization of a TT workshop is under way for Jan 2020 at CERFACS, Toulouse.

• The DA-TT co-chairs are working with MEAP-TT to organize a dedicated DA session at their next workshop in 2020.

• Co-chair Moore will engage with wider DA community via his role as a member of the WMO WWRP DAOS WG.

Main issues:

• Need to move the work plan items forward with very little time/resource dedicated to the assessment work.

• Need to encourage more groups to contribute to the inter-comparisons.

• More engagement by the DA-TT patron

Resources needed to better support the TT effort:

• Dedicated funding for a scientist to analyse the results of the inter-comparison experiments would greatly improve their impact.