Developments in Land Data Assimilation
Organizers†: Natasha MacBean (1), Jana Kolassa (2), Andy Fox (2), Tristan Quaife (3), Hannah Liddy (4)
(1) Western University, Canada, (2) NASA GSFC, USA, (3) University of Reading, UK, (4) Columbia University/NASA GISS, USA
† Organized by the AIMES Land Data Assimilation Working Group
Workshop Overview
The 4th annual Land Data Assimilation (DA) Community Virtual Workshop on “Developments in Land Data Assimilation” will take place on Monday, June 24th – Tuesday, June 25th.
Technical challenges are the focus of this annual meeting as the scientific questions that lie behind those technical developments are typically the focus of other professional meetings and conferences. 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. We seek to strengthen connections between land DA communities, increase knowledge exchange to tackle land DA challenges, and build a collaborative land DA community inclusive of all backgrounds and career stages. To learn more about the outcomes of previous workshops, please check out the following:
- MacBean, N., Liddy, H., Quaife, T., Kolassa, J., and Fox, A. (2022). Building a Land Data Assimilation Community to Tackle Technical Challenges in Quantifying and Reducing Uncertainty in Land Model Predictions. Bulletin of the American Meteorological Society 103, E733–E740. 10.1175/BAMS-D-21-0228.1.
- Kumar, S., Kolassa, J., Reichle, R., Crow, W., de Lannoy, G., de Rosnay, P., MacBean, N., Girotto, M., Fox, A., Quaife, T., et al. (2022). An Agenda for Land Data Assimilation Priorities: Realizing the Promise of Terrestrial Water, Energy, and Vegetation Observations From Space. J Adv Model Earth Syst 14. 10.1029/2022MS003259.
Learn more about the Land DA Community here: https://land-da-community.github.io.
Open Registration
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- Land data assimilation in CMIP 7
- Machine learning in land DA research and applications
- Including novel observations and processes in land DA systems
- Bridging the gap between methodological development and applications of DA in NWP and ESMs
- Community updates
- Other (we welcome your contributions beyond the above categories)
Friday, June 21st is the registration deadline. If you have any issues using the above Google Form, reach out to to aimes (at) futureearth.org to register.
Important Dates
April 26: Open call for abstracts
May 24: Abstract submission deadline
June 1: Abstract acceptance notification
June 3: Registration (free) opens and release of preliminary program
June 24–25: Workshop dates
