June 14-16, 2021 ⋅ 9:00-12:00 EDT // 15:00 – 18:00 CEST

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

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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.

Workshop Agenda: This workshop is focused on the technical challenges of data assimilation, and we have a great lineup of technically-focused, thought-provoking talks that allow ample time for discussion. The second half of each day will be dedicated to making connections between land DA communities, increasing knowledge exchange to tackle land DA challenges, and building a collaborative land DA community inclusive of all backgrounds and career stages.