Tackling Technical Challenges in Land Data Assimilation
June 14-16, 2021 ⋅ 9:00-12:00 EDT
Organizers†: Natasha MacBean (1), Jana Kolassa (2), Andy Fox (3), Tristan Quaife (4), Hannah Liddy (5)
(1) Indiana University, (2) NASA GMAO, (3) Joint Center for Satellite Data Assimilation, (4) University of Reading, (5) Columbia University/NASA GISS
† Organized by the AIMES Land Data Assimilation Working Group
Workshop Overview: There is growing consensus that land surface models need to be confronted with a wide range of data to constrain uncertainty in parameters, initialize surface states, and address model structural uncertainty. However, there are limited opportunities at scientific meetings to specifically discuss the challenges faced by modeling teams when implementing data assimilation (DA) techniques. To strengthen communication between modeling groups, this workshop will bring together land DA scientists to highlight a range of DA methods used within the community, discuss challenges facing different modeling communities, and identify strategies for addressing those challenges. We welcome participation from a broad range of research interests including land surface states and fluxes (carbon, energy, and water cycles to crop, fire, and land management), timescales (daily, seasonal to subseasonal, centennial/millennial), and scientific and practical applications (improving understanding of carbon-climate feedbacks, weather prediction, agricultural forecasting, and climate change impacts). The outcome of this workshop is to increase collaboration and coordination within the land DA community to tackle technical challenges and promote the routine use of DA tools in the wider modeling community.
Key themes and associated example questions will include:
Day 1: Applicability of data assimilation approaches across different land modeling communities
- To what extent can “standard” approaches from atmospheric DA be applied to land models?
- To what extent can approaches used with land models in NWP be applied to Earth System Model timescales?
- Is land model initialization important in S2S predictions? Decadal prediction?
Day 2: Emerging techniques
- What are the advantages and disadvantages of different analysis methods?
- What approaches can we use to populate the full (off-diagonal elements) of the background and observation error covariance matrices?
- For ensemble-based approaches, how should we best initialize and perturb the ensemble?
Day 3: Challenges in dealing with observations
- What are the state-of-the-art methods for assessing the information content of different observation types?
- At what time scales do different observation types provide the most ‘useful’ information to models?
- Can manipulation experiments help us to constrain carbon-climate relationships?
In addition, the workshop will have cross-cutting themes addressing issues related to error characterization and the different spatial and temporal scales over which we assimilate data.
We welcome participants who not only represent a relevant area of expertise but may also be earlier in their careers, and/or from historically underrepresented groups. Invited speakers will give short talks (15 minutes) over 1.5 hours each day on a range of topics under each of the 3 themes. The remaining 1.5 hours will be devoted to discussion around these topics. If you wish to attend the workshop, please complete the registration form: