Model Uncertainty

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, a virtual workshop was organized to 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. The outcome of the workshop was 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.

Introduction and Orientation to the Webinar Series

Speakers: Andy Fox (Joint Center for Satellite Data Assimilation), Hannah Liddy (AIMES), Jana Kolassa (NASA GSFC), Natasha MacBean (Indiana University), Tristan Quaife (Univesity of Reading)

Date aired: 14-16 June 2021

Applicability of data assimilation approaches across different land modeling groups

Speaker: Patricia De Rosnay (ECMWF)

Date aired: 14-16 June 2021

About: Patricia De Rosnay gives a presentation called: Technical challenges of coupled land-atmosphere data assimilation for operational Numerical Weather Prediction and reanalyses.

Applicability of data assimilation approaches across different land modeling groups

Speaker: Bertrand Bonan (CNRM)

Date aired: 14-16 June 2021

About: Bertran Bonan from CNRM gives a presentation on Monitoring land surface variables with LDAS-Monde: focus on assimilation approaches and applications to kilometric-scale spatial resolutions.

Applicability of data assimilation approaches across different land modeling groups

Speaker: Marko Scholze (Lund University)

Date aired: 14-16 June 2021

About: Marko Scholze from Lund University gives a presentation on: Experiences on terrestrial model parameter optimisation based from the Carbon Cycle Data Assimilation System using multiple observations.

Applicability of data assimilation approaches across different land modeling groups

Speaker: Sujay Kumar (NASA GSFC)

Date aired: 14-16 June 2021

About: Sujay Kumar from NASA GSFC gives a presentation: Land hydrology data assimilation – Are we on the right track?

Emerging techniques in land data assimilation

Speaker: Jianzhi Dong (MIT)

Date aired: 14-16 June 2021

About: Jianzhi Dong from MIT gives a presentation called: The added value of brightness temperature assimilation for global soil moisture estimation.

Emerging techniques in land data assimilation

Speaker: Ewan Pinnington (University of Reading)

Date aired: 14-16 June 2021

About: Ewan Pinnington from the University of Reading gives a presentation on Hybrid data assimilation methods for land surface modelling.

Emerging techniques in land data assimilation

Speaker: Istem Fer (Finnish Meteorological Institute)

Date aired: 14-16 June 2021

About: Istem Fer from the Finnish Meteorological Institute presented on Gaussian process emulators for efficient Bayesian calibration of process-based models.

Emerging techniques in land data assimilation

Speaker: Joanne Waller (UK Met Office)

Date aired: 14-16 June 2021

About: Joanne Waller from the UK Met Office gives her presentation on: Estimating the full observation error covariance matrix.

Emerging techniques in land data assimilation

Speaker: Moha El Gharamti (NCAR/UCAR)

Date aired: 14-16 June 2021

About: Moha El Gharamti from NCAR/UCAR presents on Enhanced streamflow forecasting using ensemble data assimilation.

Challenges in dealing with observations

Speaker: Nina Raoult (LSCE)

Date aired: 14-16 June 2021

About: Nina Raoult from LSCE gives a presentation on using the temporal dynamics of surface soil moisture to deal with biases when calibrating land surface models.

Challenges in dealing with observations

Speaker: Jina Jeong (Vrije Universiteit Amsterdam)

Date aired: 14-16 June 2021

About: Jina Jeong from Vrije Universiteit Amsterdam gave a presentation on: Using the International Tree-Ring Data Bank (ITRDB) records as century-long benchmarks for land-surface models.

Want to learn more?

If you are interested in model uncertainty, take a look at our webpage for the Land Data Assimilation Working Group. You’ll find information on our webinar series as well as recent developments in the field.