
Tackling Technical Challenges in Land Data Assimilation
virtual workshop
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
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.
Monday, June 14: Applicability of data assimilation approaches across different land modeling communities
9:00 AM EDT | Welcome from the Co-Chairs: Introduction to the workshop context and goals |
9:10 AM EDT | Speaker 1: Patricia De Rosnay (ECMWF) – Technical challenges of coupled land-atmosphere data assimilation for operational Numerical Weather Prediction and reanalyses |
9:25 AM EDT | Speaker 2: Eunjee Lee (NASA GSFC) – Effect of land initialization on the skill of forecasting carbon fluxes on sub-seasonal to seasonal (S2S) time scales |
9:40 AM EDT | Speaker 3: Bertrand Bonan (CNRM) – Monitoring land surface variables with LDAS-Monde: focus on assimilation approaches and applications to kilometric-scale spatial resolutions |
9:55 AM EDT | Break (5 minutes) |
10:00 AM EDT | Speaker 4: Marko Scholze (Lund University) – Experiences on terrestrial model parameter optimisation based from the Carbon Cycle Data Assimilation System using multiple observations |
10:15 AM EDT | Speaker 5: Breo Gomez (UK Met Office) – Differences between atmospheric and land data assimilation and challenges for strong coupling |
10:30 AM EDT | Speaker 6: Sujay Kumar (NASA GSFC) – Land hydrology data assimilation – Are we on the right track? |
10:45 AM EDT | Introduction to Break Out Groups |
10:50 AM EDT | Break (10 minutes) |
11:00 AM EDT | Break Out Groups |
11:45 AM EDT | Plenary Discussion/Report Backs |
11:55 AM EDT | Co-chair wrap up |
Tuesday, June 15: Emerging techniques
9:00 AM EDT | Welcome from the Co-Chairs: Introduction to Day 2 |
9:05 AM EDT | Speaker 1: Jianzhi Dong (MIT) – The added value of brightness temperature assimilation for global soil moisture estimation |
9:20 AM EDT | Speaker 2: Ewan Pinnington (University of Reading) – Hybrid Data Assimilation Methods for Land Surface Modelling |
9:35 AM EDT | Speaker 3: Istem Fer (Finnish Meteorological Institute) – Gaussian process emulators for efficient Bayesian calibration of process-based models |
9:50 AM EDT | Break (5 minutes) |
9:55 AM EDT |
Speaker 4: Joanne Waller (UK Met Office) – Estimating the full observation error covariance matrix |
10:10 AM EDT | Speaker 5: Moha El Gharamti (NCAR/UCAR) – Enhanced Streamflow Forecasting using Ensemble Data Assimilation |
10:25 AM EDT | Speaker 6: Anthony Bloom (NASA JPL/Caltech) – Using an ever-growing Earth Observation record to infer and predict terrestrial C and H2O dynamics |
10:40 AM EDT | Introduction to Break Out Groups |
10:45 AM EDT | Break (10 minutes) |
10:55 AM EDT | Break Out Groups |
11:40 AM EDT | Plenary Discussion/Report Backs |
11:55 AM EDT | Co-chair wrap up |
Wednesday, June 16: Challenges in dealing with observations
9:00 AM EDT | Welcome from the Co-Chairs: Introduction to Day 3 |
9:05 AM EDT | Speaker 1: Nina Raoult (LSCE) – Using the temporal dynamics of surface soil moisture to deal with biases when calibrating land surface models |
9:20 AM EDT | Speaker 2: Susan Steele-Dunne (Delft University of Technology) – Towards constraining water and carbon cycle processes with radar data through assimilation |
9:35 AM EDT | Speaker 3: Jina Jeong (Vrije Universiteit Amsterdam) – Using the International Tree-Ring Data Bank (ITRDB) records as century-long benchmarks for land-surface models |
9:50 AM EDT | Break (5 minutes) |
9:55 AM EDT | Speaker 4: Ann Raiho (NASA GSFC/University of Maryland) – Advances and challenges for using paleoecological data for state data assimilation within a forest gap model |
10:10 AM EDT | Speaker 5: Clara Draper (NOAA) – Time scales in land data assimilation |
10:25 AM EDT | Speaker 6: Manuela Girotto (UC Berkeley) – Technical challenges of assimilating observations with large spatiotemporal resolutions |
10:40 AM EDT | Introduction to Break Out Groups |
10:45 AM EDT | Break (10 minutes) |
10:55 AM EDT | Break Out Groups |
11:40 AM EDT | Plenary Discussion/Report Backs |
11:55 AM EDT |
Co-chair wrap up: Next step
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In addition to each day’s central theme, the workshop will include cross-cutting themes addressing issues related to error characterization and the different spatial and temporal scales over which we assimilate data.