Call for Abstracts: New Directions in Land Data Assimilation Virtual Workshop

Call for Abstracts: New Directions in Land Data Assimilation Virtual Workshop

Submit Abstracts for: 

New Directions in Land Data Assimilation

2nd Annual Land Data Assimilation Community Virtual Workshop

13-15 June 2022 | 10:00-13:00 EDT // 16:00-19:00 CEST

The AIMES Land Data Assimilation Working Group will hold its 2nd annual workshop ‘New Directions in Land Data Assimilation’ on 13-15 June 2022 from 10:00 – 13:00 EDTThe goals of the workshop build on the principles of the working group to: (1) foster knowledge exchange across all groups working in land DA and (2) build a community of practice and collaboration in land DA, particularly for addressing the technical challenges we face in implementing DA systems. The themes of the workshop were identified by the land DA community during the 2021 meeting on Tackling Technical Challenges in Land DA and through feedback from a post-workshop survey.

We now invite abstract submissions for oral or poster presentations that address one of the following main themes: 

(1) Machine Learning in Land DA
(2) Observation and Model Uncertainty
(3) Ensemble DA methods
(4) Crossover in Land DA challenges between Numerical Weather Prediction and Land Surface Modeling communities
 

We are seeking abstracts that put greater weight on addressing the technical challenges associated with developing land DA systems than answering the scientific questions that lie behind those technical developments, which is typically the focus of other professional meetings and conferences. Oral presentations will prioritize the themes identified above. However, we will also consider abstracts that address important topics beyond the designated themes.

We are looking forward to continuing to build the land DA community and to seeing your abstracts! The deadline to submit your abstract is Friday, March 4, 2022. Email aimes@futureearth.org with any questions.

Land Modeling and Data Assimilation System Specialist with SSAI at NASA Goddard Space Flight Center in Greenbelt, MD

Land Modeling and Data Assimilation System Specialist with SSAI at NASA Goddard Space Flight Center in Greenbelt, MD

Land Modeling and Data Assimilation System Specialist with SSAI at NASA Goddard Space Flight Center in Greenbelt, MD

Science Systems and Applications, Inc. is seeking a GEOS Land Modeling and Data Assimilation System specialist to support the Global Modeling and Assimilation Office at the NASA Goddard Space Flight Center. This position will begin in a telecommuting status with the eventual likelihood of a hybrid model with work on site at NASA’s GSFC.

The position is designed for a mid-career scientist/programmer or numerical modeler with commensurate experience using and/or running coupled atmosphere and land models. The selected staff member will contribute to the maintenance and development of the land modeling and data assimilation components of the Global Earth Observing System (GEOS) at the NASA Global Modeling and Assimilation Office (GMAO). This involves the following expected duties:

*   Develop, implement, and document, under advisement of civil service staff, improvements in the GEOS land modeling and data assimilation system.
*   Perform simulations with the stand-alone land model and with various configurations of the full GEOS Earth system model; process results as required.
*   Integrate science software and model parameters into the operational version of GEOS and perform associated tests.
*   Assist in solving daily technical problems (in addition to strictly scientific problems).
*   Ensure proper coordination with other model development groups in the GMAO.
*   Maintain appropriate standards and interfaces to facilitate coupling of land model and assimilation components into the broader NASA GEOS system.

Required Qualifications:

*   A minimum of an MS degree in numerical land, atmospheric, or ocean modeling or a related field.
*   6-10 years of experience in designing, running, and analyzing output from standalone or coupled land, atmosphere, or ocean numerical models or data assimilation systems
*   Extensive experience in FORTRAN or C/C++ programming is required
*   The applicant must be detail-oriented.

Desired Qualifications:

*   Experience in land surface hydrology and data assimilation preferred
*   Experience in Python programming is highly desired, as are familiarity with relevant data formats (including NetCDF and HDF), object-oriented software paradigms (e.g., ESMF), and software version control (e.g., git and github.com)
*   Expert knowledge of parallel computing processes and languages is also desired, as is a strong familiarity with graphics software.

NOTICE TO APPLICANTS:  As a federal contractor, all employees of SSAI are required to be vaccinated (by no later than December 8, 2021) unless eligible for a religious or health exemption.  Applicants selected for employment by SSAI must provide SSAI with the following documentation upon commencement of employment:

(a) a copy of the record of immunization from a health care provider or pharmacy, such as a copy of the COVID-19 Vaccination Record Card (CDC Form MLS-319813_r, published on September 3, 2020),

(b) a copy of medical records documenting the vaccination,

(c) a copy of immunization records from a public health or State immunization information system, or

(d) a statement that you are scheduled to receive a vaccination (identifying the date by which you expect to meet vaccination requirements).

The record must verify vaccination with information on the vaccine name, date(s) of administration, and the name of health care professional or clinic site administering vaccine.
Applicants seeking employment subject to a religious or health exemption should contact SSAI Human Resource Department.

SSAI is an Equal Employment Opportunity and Affirmative Action Employer.
EEO/AA-Minorities/Females/Veterans/Individuals with Disabilities

Apply here:
https://ssaihq.com/employment/Careers.aspx?req=21-3298&type=JOBDESCR

Tackling Technical Challenges in Land Data Assimilation – Workshop Presentations

Tackling Technical Challenges in Land Data Assimilation – Workshop Presentations

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

Download Workshop Flyer

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
>pdf

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
>pdf

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
>pdf

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?
>pdf

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
>pdf

9:20 AM EDT Speaker 2: Ewan Pinnington (University of Reading) – Hybrid Data Assimilation Methods for Land Surface Modelling
>pdf

9:35 AM EDT Speaker 3: Istem Fer (Finnish Meteorological Institute) – Gaussian process emulators for efficient Bayesian calibration of process-based models
>pdf

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
>pdf

10:10 AM EDT Speaker 5: Moha El Gharamti (NCAR/UCAR) – Enhanced Streamflow Forecasting using Ensemble Data Assimilation
>pdf

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
>pdf

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
>pdf

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
>pdf


10:25 AM EDT Speaker 6: Manuela Girotto (UC Berkeley) – Technical challenges of assimilating observations with large spatiotemporal resolutions
>pdf

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

 

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.

Download Workshop Agenda and Abstract Booklet

Tackling Technical Challenges in Land Data Assimilation – Workshop Presentations

Register for the Tackling Technical Challenges in Land Data Assimilation Workshop

Register for: 
Tackling Technical Challenges in Land Data Assimilation
virtual workshop

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

Download Workshop Flyer

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: