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Thomas W. N. Haine, Renske Gelderloos, Miguel A. Jimenez-Urias, Ali H. Siddiqui, Gerard Lemson, Dimitri Medvedev, Alex Szalay, Ryan P. Abernathey, Mattia Almansi, and Christopher N. Hill

Abstract

Computational oceanography is the study of ocean phenomena by numerical simulation, especially dynamical and physical phenomena. Progress in information technology has driven exponential growth in the number of global ocean observations and the fidelity of numerical simulations of the ocean in the past few decades. The growth has been exponentially faster for ocean simulations, however. We argue that this faster growth is shifting the importance of field measurements and numerical simulations for oceanographic research. It is leading to the maturation of computational oceanography as a branch of marine science on par with observational oceanography. One implication is that ultraresolved ocean simulations are only loosely constrained by observations. Another implication is that barriers to analyzing the output of such simulations should be removed. Although some specific limits and challenges exist, many opportunities are identified for the future of computational oceanography. Most important is the prospect of hybrid computational and observational approaches to advance understanding of the ocean.

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Daniel B. Wright, Constantine Samaras, and Tania Lopez-Cantu

Abstract

Intensification of extreme rainfall due to climate change means that federally published rainfall metrics such as the “100-yr storm” are outdated throughout much of the United States. Given their central role in a wide range of infrastructure designs and risk management decisions, updating these metrics to reflect recent and future changes is essential to protect communities. There have been considerable advances in recent years in data collection, statistical methods, and climate modeling that can now be brought to bear on the problem. Scientists must take a lead in this updating process, which should be open, inclusive, and leverage recent scientific advances.

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Cenlin He, Olivia Clifton, Emmi Felker-Quinn, S. Ryan Fulgham, Julieta F. Juncosa Calahorrano, Danica Lombardozzi, Gemma Purser, Mj Riches, Rebecca Schwantes, Wenfu Tang, Benjamin Poulter, and Allison L. Steiner

Abstract

Interactions between air pollution and terrestrial ecosystems play an important role in the Earth system. However, process-based knowledge of air pollution–terrestrial ecosystem interactions is limited, hindering accurate quantification of how changes in tropospheric chemistry, biogeochemical cycling, and climate affect air quality and its impact on humans and ecosystems. Here we summarize current challenges and future directions for advancing the understanding of air pollution–ecosystem interactions by synthesizing discussions from a multidisciplinary group of scientists at a recent Integrated Land Ecosystem–Atmosphere Processes Study (iLEAPS) early-career workshop. Specifically, we discuss the important elements of air pollution–terrestrial ecosystem interactions, including vegetation and soil uptake and emissions of air pollutants and precursors, in-canopy chemistry, and the roles of human activities, fires, and meteorology. We highlight the need for a coordinated network of measurements of long-term chemical fluxes and related meteorological and ecological quantities with expanded geographic and ecosystem representation, data standardization and curation to reduce uncertainty and enhance observational syntheses, integrated multiscale observational and modeling capabilities, collaboration across scientific disciplines and geographic regions, and active involvement by stakeholders and policymakers. Such an enhanced network will continue to facilitate the process-level understanding and thus predictive ability of interactions between air pollution and terrestrial ecosystems and impacts on local-to-global climate and human health.

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Stéphane Vannitsem, John Bjørnar Bremnes, Jonathan Demaeyer, Gavin R. Evans, Jonathan Flowerdew, Stephan Hemri, Sebastian Lerch, Nigel Roberts, Susanne Theis, Aitor Atencia, Zied Ben Bouallègue, Jonas Bhend, Markus Dabernig, Lesley De Cruz, Leila Hieta, Olivier Mestre, Lionel Moret, Iris Odak Plenković, Maurice Schmeits, Maxime Taillardat, Joris Van den Bergh, Bert Van Schaeybroeck, Kirien Whan, and Jussi Ylhaisi

Abstract

Statistical postprocessing techniques are nowadays key components of the forecasting suites in many national meteorological services (NMS), with, for most of them, the objective of correcting the impact of different types of errors on the forecasts. The final aim is to provide optimal, automated, seamless forecasts for end users. Many techniques are now flourishing in the statistical, meteorological, climatological, hydrological, and engineering communities. The methods range in complexity from simple bias corrections to very sophisticated distribution-adjusting techniques that incorporate correlations among the prognostic variables. The paper is an attempt to summarize the main activities going on in this area from theoretical developments to operational applications, with a focus on the current challenges and potential avenues in the field. Among these challenges is the shift in NMS toward running ensemble numerical weather prediction (NWP) systems at the kilometer scale that produce very large datasets and require high-density high-quality observations, the necessity to preserve space–time correlation of high-dimensional corrected fields, the need to reduce the impact of model changes affecting the parameters of the corrections, the necessity for techniques to merge different types of forecasts and ensembles with different behaviors, and finally the ability to transfer research on statistical postprocessing to operations. Potential new avenues are also discussed.

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Andrew Hoell, Britt-Anne Parker, Michael Downey, Natalie Umphlett, Kelsey Jencso, F. Adnan Akyuz, Dannele Peck, Trevor Hadwen, Brian Fuchs, Doug Kluck, Laura Edwards, Judith Perlwitz, Jon Eischeid, Veva Deheza, Roger Pulwarty, and Kathryn Bevington

Abstract

The 2017 flash drought arrived without early warning and devastated the U.S. northern Great Plains region comprising Montana, North Dakota, and South Dakota and the adjacent Canadian Prairies. The drought led to agricultural production losses exceeding $2.6 billion in the United States, widespread wildfires, poor air quality, damaged ecosystems, and degraded mental health. These effects motivated a multiagency collaboration among academic, tribal, state, and federal partners to evaluate drought early warning systems, coordination efforts, communication, and management practices with the goal of improving resilience and response to future droughts. This essay provides an overview on the causes, predictability, and historical context of the drought, the impacts of the drought, opportunities for drought early warning, and an inventory of lessons learned. Key lessons learned include the following: 1) building partnerships during nondrought periods helps ensure that proper relationships are in place for a coordinated and effective drought response; 2) drought information providers must improve their understanding of the annual decision cycles of all relevant sectors, including, and beyond, direct impacts in agricultural sectors; and 3) ongoing monitoring of environmental conditions is vital to drought early warning, given that seasonal forecasts lack skill over the northern Great Plains.

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William B. Rossow and John J. Bates

Abstract

The current heterogeneity of the existing global collection of measuring assets, satellite and surface based, is a major obstacle to creating a truly integrated, globally uniform information system. Many surveys of Earth science needs over the last 40+ years mention research-to-operations (R2O) actions that are needed to develop such a system but focus mainly on making and collecting measurements with little discussion of the processing system and the integrated team of talented scientists needed to turn raw observations into usable information or the archival system needed to make reliable information readily and widely accessible. We discuss an example of addressing the problems in producing globally uniform information from such observations: the creation in 1982–83 of the data collection, processing, and archival system for the International Satellite Cloud Climatology Project (ISCCP). ISCCP was originally built in a research environment for climate studies, but has now transitioned to a fully operational environment to extend the length of the data record for climate research. Transforming multiple satellite observations into a uniform, global set of physical information about clouds that is readily accessible was and is challenging for several reasons. In this short commentary, we reflect on the experiences and lessons learned in building the ISCCP observation–processing–archival system to address these challenges and discuss the ISCCP R2O process to serve as a pathfinder for building a global observing and information system.

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Raul P. Lejano

Abstract

It is reasonable to assume that more effective communication of climate science might be the remedy for widespread climate skepticism. However, narrative analysis of climate-skeptical discourse suggests it can be otherwise. Taking the United States as a case in point, we argue how at least some forms of climate skepticism are founded upon an ideological narrative that (for its adherents) is prior to, or more fundamental than, the issue of climate. In other words, skepticism may not always (or even usually) be fundamentally about climate to begin with. This more basic, universal, ideological construct at the root of climate skepticism encompasses social status, race and ethnicity, class, culture, and other social conditions. If climate-skeptical discourse in the United States is commonly built upon a genetic metanarrative that is really about social fracture, it may be resilient to scientific argument. It is quite possible that responding to climate skepticism will require addressing the more basic ideological divide and challenging the underlying genetic narrative. In the rest of the essay, we sketch out possible avenues for positive steps forward.

Free access
Christopher F. Labosier and Isabel Fay

Abstract

Like many of the world’s most pressing challenges, climate change is a complex problem spanning the realms of science, economics, law and policy, ethics, communication, and more. With this multitude of implications, tomorrow’s leaders require the ability to think across academic disciplines to solve such problems. Here, we describe a newly developed course that responds to these demands by introducing undergraduate students to climate change as both a scientific theory and a policy concern. Through this integration of the fields of atmospheric science and communication, novel, pedagogically valuable questions and course themes emerged. Thus, students were engaged in readings and discussions of what science is and what it means for decision-making to be science based, in addition to acquiring a fundamental understanding of climate change science. Moreover, students developed media literacy skills by analyzing how science is presented in the public sphere and the challenges of communicating scientific uncertainty. In informative, narrative, and persuasive speech assignments, students practiced using rhetorical techniques to build audience interest in scientific questions of public relevance. These assignments required students to participate in public discourse on various aspects of climate change. With this note, we encourage other educators in a variety of disciplines to develop novel approaches to climate change education.

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Wendy S. Parker and Greg Lusk

Abstract

Increasingly there are calls for climate services to be “co-produced” with users, taking into account not only the basic information needs of users but also their value systems and decision contexts. What does this mean in practice? One way that user values can be incorporated into climate services is in the management of inductive risk. This involves understanding which errors in climate service products would have particularly negative consequences from the users’ perspective (e.g., underestimating rather than overestimating the change in an impact variable) and then prioritizing the avoidance of those errors. This essay shows how inductive risk could be managed in climate services in ways that serve user values and argues that there are both ethical and practical reasons in favor of doing so.

Open access
Erik W. Kolstad, Oda N. Sofienlund, Hanna Kvamsås, Mathew A. Stiller-Reeve, Simon Neby, Øyvind Paasche, Marie Pontoppidan, Stefan P. Sobolowski, Håvard Haarstad, Stina E. Oseland, Lene Omdahl, and Snorre Waage

Abstract

Climate change yields both challenges and opportunities. In both cases, costly adaptations and transformations are necessary and desirable, and these must be based on realistic and relevant climate information. However, it is often difficult for climate scientists to communicate this information to decision-makers and stakeholders, and it can be equally difficult for such actors to interpret and put the information to use. In this essay, we discuss experiences and present recommendations for scientists producing climate services. The basis is our work in several climate service projects. One of them aimed to provide local-scale climate data for municipalities in western Norway and to explore how the data were interpreted and implemented. The project was first based solely on climate science expertise, and the participants did not have sufficient competence on coproduction and knowledge about the regulatory and political landscape in which municipalities operate. Initially, we also subscribed to an outdated idea of climate services, where knowledge providers (climate scientists) “deliver” their information to knowledge users (e.g., municipal planners). Increasingly, as stressed in the literature on coproduction of knowledge, we learned that climate service should be an iterative process where actionable information is coproduced through two-way dialogue. On the basis of these and other lessons learned the hard way, we provide a set of concrete recommendations on how to embed the idea of coproduction from the preproposal stage to beyond the end of climate service projects.

Open access