• Alsdorf, D. E., E. Rodríguez, and D. P. Lettenmaier, 2007: Measuring surface water from space. Rev. Geophys., 45, RG2002, https://doi.org/10.1029/2006RG000197.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Biancamaria, S., D. P. Lettenmaier, and T. M. Pavelsky, 2016: The SWOT mission and its capabilities for land hydrology. Remote Sensing and Water Resources, A. Cazenave et al., Eds., Space Sciences Series of ISSI, Vol 55, Springer, 117–147.

    • Crossref
    • Export Citation
  • Hossain, F., and Coauthors, 2017: Engaging the user community for advancing societal applications of the Surface Water Ocean Topography Mission. Bull. Amer. Meteor. Soc., 98, ES285ES290, https://doi.org/10.1175/BAMS-D-17-0161.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Morrow, R., L.-L. Fu, F. D’Ovidio, and J. T. Farrar, 2019: Scientists invited to collaborate in satellite mission’s debut. Eos, Trans. Amer. Geophys. Union, 100, https://doi.org/10.1029/2019EO110423.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • NASEM, 2018: Thriving on Our Changing Planet: A Decadal Strategy for Earth Observation from Space. National Academies Press, 716 pp., https://doi.org/10.17226/24938.

    • Search Google Scholar
    • Export Citation
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The Early Adopter Program for the Surface Water Ocean Topography Satellite Mission: Lessons Learned in Building User Engagement during the Prelaunch Era

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  • 1 University of Washington, Seattle, Washington
  • 2 NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California
  • 3 Northeastern University, Boston, Massachusetts
  • 4 Centre for National D’Etudes Spatiales, Paris, France
  • 5 NASA Applied Sciences Program, Washington, D.C.
  • 6 Indian Institute of Technology, Bombay, India
  • 7 Asian Disaster Preparedness Center, Bangkok, Thailand
  • 8 FM Global, Norwood, Massachusetts
  • 9 Pakistan Council for Research in Water Resources, Islamabad, Pakistan
  • 10 NASA Short-Term Prediction Research and Transition Center, Huntsville, Alabama
  • 11 University of Bonn, Bonn, Germany
  • 12 Consortium of Universities for the Advancement of Hydrologic Science, Inc., Boston, Massachusetts
  • 13 Collectie Localisation Satellites, Paris, France
  • 14 Compagnie Nationale du Rhône, Paris, France
  • 15 BRL Ingénierie, Paris, France
  • 16 Mercator-Ocean, Paris, France
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Supplemental material: https://doi.org/10.1175/BAMS-D-19-0235.2

© 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Dr. Faisal Hossain, fhossain@uw.edu

Supplemental material: https://doi.org/10.1175/BAMS-D-19-0235.2

© 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Dr. Faisal Hossain, fhossain@uw.edu

2019 SWOT Early Adopters Training Workshop

What: A workshop was organized on the Surface Water and Ocean Topography (SWOT) mission that is planned for launch in 2021. Eleven early adopters representing a wide range of stakeholders of the SWOT mission presented projects for evaluation of SWOT’s application potential and helped identify pathways to achieving successful application of data from the SWOT mission.

When: 20–21 May 2019

Where: Paris, France

The Surface Water and Ocean Topography (SWOT) satellite is a research mission (Alsdorf et al. 2007; Biancamaria et al. 2016), planned for launch in 2022. It is being jointly developed by NASA and the Centre for National D’Etudes Spatiales (CNES), with contributions from the Canadian and U.K. space agencies. The SWOT mission will serve both the hydrology and oceanography communities by providing for the first time a global survey of Earth’s surface water, including spatially distributed and high-frequency measurement of elevation data for rivers, reservoirs, lakes, and wetlands, as well as unprecedented detail in the topography of the ocean surface (Morrow et al. 2019). The NASA Applied Sciences Program, the SWOT Applications Working Group (SAWG), the CNES SWOT Applications Program, the SWOT Project, and members of the SWOT Science Team (ST) have been coordinating these efforts. During spring 2019, a workshop was organized at CNES headquarters (HQ) in Paris (France) to assess the status of the Early Adopter Program (EAP) that was launched for SWOT Early Adopters (EAs) in 2018. Here, the key lessons learned from this program are shared.

The EAP supports recommendations of the National Research Council’s 2017 report “Thriving on Our Changing Planet: A Decadal Strategy for Earth Observation from Space” (NASEM 2018). In the vision of the EAP, each selected EA proposed an activity for the use of SWOT data. EAs were defined as those groups and individuals who will have a potential or clearly defined need for SWOT surface water or ocean topography data or information, and who are planning to apply their own resources to demonstrate the utility of SWOT data for their use, system, or model. The goal of this EAP is to accelerate the use of SWOT products after launch of the satellite by providing specific support to EAs who commit to engage in prelaunch research that would enable integration of SWOT data in their real-world applications. This research would provide a fundamental understanding of how SWOT data products may be scaled and integrated into their organizations’ policy, business, and management activities to improve decision-making efforts (Hossain et al. 2017).

In the initial cohort (beginning in 2018), 11 EAs were selected from various hydrology and oceanography domains. These were Asian Disaster Preparedness Center (ADPC)/SERVIR-Mekong; NASA Short-Term Prediction Research and Transition (SPoRT) Center; Pakistan Council of Research in Water Resources (PCRWR); Indian Institute of Technology (IIT Bombay); University of Bonn (UBonn); Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI); FM Global;1 Collecte Localisation Satellites (CLS); Compagnie Nationale du Rhône (CNR); BRL Ingénierie (BRLi); and Mercator Ocean.

WORKSHOP GOALS AND OBJECTIVES

The key goal for the workshop was to provide a voice for selected EAs to share their application projects involving SWOT data, their decision-making activity, and their progress, and to highlight their concerns and future needs. This workshop aimed to bring the EAs to a focal point for collaborative learning and sharing of lessons on what has worked for exploring the utility of SWOT data, and what more can be done in the years remaining before launch.

Over the span of 2 days, the workshop was designed to achieve the following objectives:

  • 1) to provide selected EAs an opportunity to share their SWOT-related application projects and their progress with the SWOT Mission and Science Team;
  • 2) to facilitate peer-to-peer collaborative learning for selected Early Adopters through lessons learned in other early adopter projects;
  • 3) to provide hands-on training on cloud computing to train Early Adopters to use an available cloud-computing platform to process, analyze and make decisions using massive amounts of satellite data in the cloud. [Note: This objective is designed to acclimatize EAs to NASA’s Physical Oceanography Distributed Active Archive Center (PO.DAAC), which will jointly host SWOT data products with the CNES data center, and their plans for hosting SWOT data on a cloud-computing platform.]; and
  • 4) to identify concerns and needs of EAs for successful completion of their projects.
To maximize the effectiveness of the workshop and the chances of fulfilling the workshop objectives, organizers worked proactively with many EAs to explain the purpose and specific expectations. EAs were mentored individually by SAWG leads and were encouraged to think carefully about the core issues in advance of the workshop. Each EA was requested to imagine desired future press releases or newspaper headlines that their EA project might enable. This could be an outcome of their use of SWOT data that they would like to aspire to as a success story of their project. These press releases are hypothetical and their realization is dependent on numerous conditions beyond the control of the EA or the SWOT mission. However, the workshop organizers felt that this was a good way to design a project trajectory for each EA, delineate a tangible goal as a shared-vision, and then work closely with EAs to realize that press release.

The supplementary file to this article provides a summary of the progress made by each EA, their needs, concerns, hurdles, and their desired future press release. Based on feedback from EAs and discussions, we present here the key findings from the EAP for SWOT mission.

COMMON UNDERLYING NEEDS OF EARLY ADOPTERS

Based on feedback shared by EAs, the following key underlying needs emerged as common to all EAs:

  • 1) EAs need simulated SWOT data for hydrology applications that mimic the real-world geophysical constraints of SWOT observation due to topography, climate, and vegetation.
  • 2) EAs need clear and timely metadata information on SWOT data products now to begin their projects if they are to use SWOT simulated (or actual) data properly and be acclimatized to actual SWOT data after launch.
  • 3) Many EAs require engagement support to visit a research center/collaborator relevant to their SWOT mission that can allow them to engage in weeklong immersive training to solve the specific application problems.
  • 4) Many EAs require online training programs and tutorials/webinars on how to handle SWOT data.
  • 5) EAs would benefit from SWOT-specific “hackathons for Early Adopters” to rapidly prototype solutions for their EA project, particularly for building components that require team-based thinking.

The key risks of the EAP can be summarized as follows:

  • 1) lack of access to simulator data for hydrologic application over river basins with steep topography, vegetation, and humid climates;
  • 2) lack of training in managing large volumes of data in cloud computing environment; and
  • 3) lack of prompt guidance/engagement from SAWG and ST for troubleshooting problems with EA projects as they emerge.

FUTURE IMAGINED PRESS RELEASES BY EAs

The future imagined press releases suggested by EAs with fictitious newspaper/magazine titles and years were as follows:

  • SWOT helps supporting early flood preparedness in Myanmar (ADPC),
  • SWOT data enables popular and blameless management of waterlogging in Sindh Province of Pakistan (PCRWR),
  • SWOT data helps in rationalizing irrigation supplies while preventing loss of land to waterlogging (PCRWR),
  • SWOT data improves reservoir outflow forecasting to reduce downstream flood risk in Kerala (IIT-Bombay),
  • The NOAA National Water Model forecast accuracy is improved (NASA SPoRT),
  • Demand for CUAHSI workshops on use of SWOT streamflow products is high (CUAHSI),
  • SWOT data improves navigability prediction and integrated resources water management on the Sangha River (CNR),
  • SWOT mission improves mapping of potential sites for hydropower projects in the Congo basin (CNR),
  • Assimilation of SWOT data improves forecasting skill of NOAA National Water Model (NASA-SPoRT),
  • SWOT follow-on mission in development after successful use of SWOT data in operational forecasting (NASA-SPoRT),
  • SWOT helps in predicting the 100-year event of Elbe water level extremes from Hamburg City to coast (UBonn), and
  • SWOT helps in understanding small scale dynamics in ocean circulation in Danish Straits (UBonn).
Assuming that all “press releases” were achievable through very close mentorship from the SAWG leads, the press releases were subjected to a vote by workshop participants for prioritization for future action by SAWG leads. Each workshop participant therefore chose their three favorite press release that they thought were most feasible and important to show the unique value of SWOT. The top three (with one tied) most popular future press releases were
  • 1) Assimilation of SWOT data improves forecasting skill of NOAA National Water Model (by NASA SPoRT)
  • 2) SWOT helps supporting early flood preparedness in Myanmar (by ADPC)
  • 3) (tie) SWOT data enables popular and blameless management of waterlogging in Sindh province of Pakistan (by PCRWR)
  • 3) (tie) SWOT follow-on mission in development after successful use of SWOT data in operational forecasting (by NASA SPoRT)

CONCLUSIONS FROM THE WORKSHOP

The following conclusions emerged from the workshop for the SWOT Project and science community:

  • 1) The SWOT Early Adopters have all made the demonstration of the usefulness of the future SWOT data in their tools and decision-making covering a wide range of applications from flood prediction, hydropower potential, and water resources management to operational oceanography.
  • 2) SWOT hydrology simulated datasets that represent accurate performance characteristics due to geophysical constraints (lay-over, vegetation, dark water) and to spatiotemporal sampling and that follows the SWOT data product definition need to be made available to EA for their projects.
  • 3) A faster SWOT simulator is an acceptable start and can help EAs acclimatize to SWOT data product structure. Such a simulator can be useful for large water bodies (lakes and reservoirs) in flat terrains.
  • 4) The EA community would benefit from additional online resources for tutorials on 1) cloud computing using platforms such as Google Earth Engine; 2) explanation of SWOT mission, how it works, and its data type; and 3) collection of existing tools and datasets that may be relevant to SWOT for the EA projects.
  • 5) SAWG leads should consider organizing hackathons for SWOT EA projects to solve specific hurdles and build tangible solutions. The EA projects are now gradually maturing and will likely need to start using high-resolution SWOT simulated data soon to complete the first run of proof of concepts for next year’s reporting. This means that hackathons tailored to enable rapid prototyping of real-world solutions for EAs using SWOT data are now timely.
  • 6) Programs that encourage deeper engagement for EAs at academic or research centers for immersive learning or training in the United States/France are required for EA organizations and future SWOT user communities.
  • 7) Close and more frequent mentoring support for EAs is needed as projects mature and they begin facing new challenges with data structure and processing. EAs will continue to require guidance, pointers on data access, and answers to queries on data structure/handling. Effective support of EAs will set a good precedent to maximize the user readiness of SWOT data after launch.

REFERENCES

  • Alsdorf, D. E., E. Rodríguez, and D. P. Lettenmaier, 2007: Measuring surface water from space. Rev. Geophys., 45, RG2002, https://doi.org/10.1029/2006RG000197.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Biancamaria, S., D. P. Lettenmaier, and T. M. Pavelsky, 2016: The SWOT mission and its capabilities for land hydrology. Remote Sensing and Water Resources, A. Cazenave et al., Eds., Space Sciences Series of ISSI, Vol 55, Springer, 117–147.

    • Crossref
    • Export Citation
  • Hossain, F., and Coauthors, 2017: Engaging the user community for advancing societal applications of the Surface Water Ocean Topography Mission. Bull. Amer. Meteor. Soc., 98, ES285ES290, https://doi.org/10.1175/BAMS-D-17-0161.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Morrow, R., L.-L. Fu, F. D’Ovidio, and J. T. Farrar, 2019: Scientists invited to collaborate in satellite mission’s debut. Eos, Trans. Amer. Geophys. Union, 100, https://doi.org/10.1029/2019EO110423.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • NASEM, 2018: Thriving on Our Changing Planet: A Decadal Strategy for Earth Observation from Space. National Academies Press, 716 pp., https://doi.org/10.17226/24938.

    • Search Google Scholar
    • Export Citation
1

Current FM global representative and project lead is Dr. Alain Dib (alain.dib@fmglobal.com).

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