National Academies of Sciences, Engineering, and Medicine 2020. Earth System Predictability Research and Development: Proceedings of a Workshop in Brief. Washington, DC: The National Academies Press, Jul 2020. https://doi.org/10.17226/25861
Panelist Ruby Leung, Department of Energy Pacific Northwest National Laboratory, emphasized that model biases are limiting understanding of Earth system predictability and the ability to make predictions. [Jean-Francois] Lamarque agreed, pointing out that several of these biases have been present in climate models for decades, but the reasons for them are not well understood. Improving understanding of how to resolve these biases has not been a focus of climate model intercomparison efforts.
Increasing model resolution could be a game changer in how persistent model biases and improving predictability are addressed, said Leung, because it would allow simulation of subgrid-scale processes that are currently parameterized. Furthermore, fully representing subgrid moist convection processes could help address the lack of variability or chaotic behavior in the models that results in misrepresentation of the signal-to-noise ratio used to estimate predictability. Similarly, fully simulating mesoscale eddies could improve modeling of air-sea interactions that contribute to subseasonal-to-interannual predictability.
Multi-disciplinary teams of observationalists, modelers, software engineers, computational scientists, and data analysts are needed to make progress in Earth system modeling, said Lamarque.
NEW RESEARCH FRAMEWORK FOR PRACTICABLE EARTH SYSTEM PREDICTABILITY
Development of a national approach and strategy to knit together predictability-focused theoretical work with observational, modeling, and technology research is an imperative for advancing practicable prediction, said session chair Jenni Evans, The Pennsylvania State University. This session explored opportunities to break down compartmentalization of communities. By making convergent research the new normal, and developing and sustaining a creative workforce, a new foundation on the science and applications of Earth system predictability research can be created.
Duane Waliser, NASA Jet Propulsion Laboratory, started off the session by suggesting the application of a more formal systems engineering approach (see Box 2), to break down the complexity of Earth system predictability into a coordinated and collaborative outcome-driven program. The need for a systems engineering approach stems from the sheer complexity of the questions and objectives being considered: Earth system science is complex, the technology and tools (including models and observations) are rapidly evolving, and the programmatic aspects of the enterprise (including civil, commercial and social) are challenging to optimally coordinate. Waliser argued that a system of systems (SoS) approach could be a way to judiciously integrate and evolve the underlying components to maximize value and societal impacts.
Waliser explained that the Earth system prediction enterprise could be roughly equated to a “collaborative” SoS (Box 2), one that has developed over the last 50 years on a somewhat ad-hoc basis. While this type of SoS tends to rely on a voluntary approach to coordination, it has yielded significant environmental forecast capabilities and decision support guidance. However, given the critical importance of Earth system prediction to the security and resilience of society, there may be reasons to consider moving to an SoS approach that would entail a more formal design and management process, in order to achieve future advances. Waliser posed the questions: “Are there means to help optimize the (science, technology, and enterprise) components? Would a top-down SoS design and development approach help advance Earth system predictability? Are there aspects of a systems engineering approach that would help to achieve an overall vision for Earth system prediction and the decision-support guidance it enables? Is there a need for a coordinating office or body that could direct effort and resources, one that takes into account the strengths and complementary elements of the various agencies and commercial enterprises that have a role and stake in contributing to this critical national capability?” To answer these questions, Waliser suggested assembling a team of systems engineering and Earth system prediction experts to assess the value of more formally engaging an SoS perspective to help guide the nation’s Earth systems predictability roadmap and prioritizations.
Panelist Paula Bontempi, NASA, highlighted the need for having a structure in place that integrates communities and avoids compartmentalization. Bontempi urged agencies to create opportunities that encourage disciplines, as well as scientists and managers, to work together towards common objectives. She said that one solution is to craft solicitations and competitions for federal research and development funding in ways that inspire the next generation to be creative in proposing ideas that break down compartmentalization.
Panelist Waleed Abdalati, NOAA/CIRES and University of Colorado at Boulder, reinforced the need to employ systems-level thinking. Abdalati spoke of the importance of a shared focus, shared vision, and shared strategy to empower agencies to prioritize a collective effort and move away from the sum of the parts approach for Earth systems predictability research. Abdalati said that agencies need to be liberated to do more than just play in the sandbox together; they need to build the sandbox together.
Panelist Chris Bretherton, University of Washington, reiterated the need for a coordinated interagency research agenda and identified other challenges to avoiding compartmentalization. To foster an environment of interdisciplinary research, it is important to have open, accessible, well-documented and publicized community models and data sets. An investment in software engineering is needed to make existing data and models as useful for interdisciplinary research as possible by lowering barriers to access. Furthermore, Bretherton advised clearly defining shared goals that naturally bring communities together.
Several panelists emphasized that achieving a new research framework to progress understanding of Earth system predictability requires an inspired next generation of scientists and engineers. Bretherton explained that students need to be educated on Earth system predictability as interdisciplinary research. According to Abdalati, to attract a talented workforce, a perception needs to prevail that this research is of utmost importance and is recognized and supported from leaders of all sectors of society.
Box 2: What is Systems Engineering?
Systems engineering concentrates on understanding, designing, and managing complex systems, namely, systems of interworking components that synergistically work together to perform a useful function (e.g. spacecraft, robotics, software, manufacturing processes, communication systems, healthcare, defense, etc.).
Systems engineering includes requirements development, logistics, team coordination, testing and evaluation, costs, reliability, work processes, optimization, risk management, and often the overlaps between technical and human systems.
Systems of systems (SoS) can be defined by the degree to which it relies upon formal design and management processes:
• Virtual SoS lack a central management authority and centrally recognized purpose but results in an emergent, useful behavior.
• Collaborative SoS involve voluntary actions by component systems to meet recognized central purposes.
• Acknowledged SoS have recognized central purposes, as well as a designated manager and resources, while component systems retain independence.
• Directed SoS entail an integrated SoS that is built and managed to meet specific purposes.
Source: MITRE. 2014. Systems Engineering Guide: Collected Wisdom from MITRE’s Systems Engineering Experts. Bedford, MA: The MITRE Corporation.
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