Frontiers in Climate

Journal: Frontiers in Climate

Abbreviation

Front. Clim.

Publisher

Frontiers Media

ISSN

2624-9553

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Publications 1 - 10 of 13

Frontiers in attributing climate extremes and associated impacts
Perkins-Kirkpatrick, Sarah E.; Alexander, Lisa V.; King, Andrew D.; et al. (2024)
Frontiers in Climate
The field of extreme event attribution (EEA) has rapidly developed over the last two decades. Various methods have been developed and implemented, physical modelling capabilities have generally improved, the field of impact attribution has emerged, and assessments serve as a popular communication tool for conveying how climate change is influencing weather and climate events in the lived experience. However, a number of non-trivial challenges still remain that must be addressed by the community to secure further advancement of the field whilst ensuring scientific rigour and the appropriate use of attribution findings by stakeholders and associated applications. As part of a concept series commissioned by the World Climate Research Programme, this article discusses contemporary developments and challenges over six key domains relevant to EEA, and provides recommendations of where focus in the EEA field should be concentrated over the coming decade. These six domains are: (1) observations in the context of EEA; (2) extreme event definitions; (3) statistical methods; (4) physical modelling methods; (5) impact attribution; and (6) communication. Broadly, recommendations call for increased EEA assessments and capacity building, particularly for more vulnerable regions; contemporary guidelines for assessing the suitability of physical climate models; establishing best-practice methodologies for EEA on compound and record-shattering extremes; co-ordinated interdisciplinary engagement to develop scaffolding for impact attribution assessments and their suitability for use in broader applications; and increased and ongoing investment in EEA communication. To address these recommendations requires significant developments in multiple fields that either underpin (e.g., observations and monitoring; climate modelling) or are closely related to (e.g., compound and record-shattering events; climate impacts) EEA, as well as working consistently with experts outside of attribution and climate science more generally. However, if approached with investment, dedication, and coordination, tackling these challenges over the next decade will ensure robust EEA analysis, with tangible benefits to the broader global community.
A Physics-Aware Neural Network Approach for Flow Data Reconstruction from Satellite Observations
Schweri, Luca; Foucher, Sebastien; Tang, Jingwei; et al. (2021)
Frontiers in Climate
An accurate assessment of physical transport requires high-resolution and high-quality velocity information. In satellite-based wind retrievals, the accuracy is impaired due to noise while the maximal observable resolution is bounded by the sensors. The reconstruction of a continuous velocity field is important to assess transport characteristics and it is very challenging. A major difficulty is ambiguity, since the lack of visible clouds results in missing information and multiple velocity fields will explain the same sparse observations. It is, therefore, necessary to regularize the reconstruction, which would typically be done by hand-crafting priors on the smoothness of the signal or on the divergence of the resulting flow. However, the regularizers can smooth the solution excessively and will not guarantee that possible solutions are truly physically realizable. In this paper, we demonstrate that data recovery can be learned by a neural network from numerical simulations of physically realizable fluid flows, which can be seen as a data-driven regularization. We show that the learning-based reconstruction is especially powerful in handling large areas of missing or occluded data, outperforming traditional models for data recovery. We quantitatively evaluate our method on numerically-simulated flows, and additionally apply it to a Guadalupe Island case study—a real-world flow data set retrieved from satellite imagery of stratocumulus clouds.
Toward Consistent Observational Constraints in Climate Predictions and Projections
Hegerl, Gabriele C.; Ballinger, Andrew P.; Booth, Ben B.B.; et al. (2021)
Frontiers in Climate
Observations facilitate model evaluation and provide constraints that are relevant to future predictions and projections. Constraints for uninitialized projections are generally based on model performance in simulating climatology and climate change. For initialized predictions, skill scores over the hindcast period provide insight into the relative performance of models, and the value of initialization as compared to projections. Predictions and projections combined can, in principle, provide seamless decadal to multi-decadal climate information. For that, though, the role of observations in skill estimates and constraints needs to be understood in order to use both consistently across the prediction and projection time horizons. This paper discusses the challenges in doing so, illustrated by examples of state-of-the-art methods for predicting and projecting changes in European climate. It discusses constraints across prediction and projection methods, their interpretation, and the metrics that drive them such as process accuracy, accurate trends or high signal-to-noise ratio. We also discuss the potential to combine constraints to arrive at more reliable climate prediction systems from years to decades. To illustrate constraints on projections, we discuss their use in the UK's climate prediction system UKCP18, the case of model performance weights obtained from the Climate model Weighting by Independence and Performance (ClimWIP) method, and the estimated magnitude of the forced signal in observations from detection and attribution. For initialized predictions, skill scores are used to evaluate which models perform well, what might contribute to this performance, and how skill may vary over time. Skill estimates also vary with different phases of climate variability and climatic conditions, and are influenced by the presence of external forcing. This complicates the systematic use of observational constraints. Furthermore, we illustrate that sub-selecting simulations from large ensembles based on reproduction of the observed evolution of climate variations is a good testbed for combining projections and predictions. Finally, the methods described in this paper potentially add value to projections and predictions for users, but must be used with caution.
Phytoprevention of Heavy Metal Contamination From Terrestrial Enhanced Weathering: Can Plants Save the Day?
Suhrhoff, Tim Jesper (2022)
Frontiers in Climate
Enhanced weathering is a promising approach to remove carbon dioxide from the atmosphere. However, it may also pose environmental risks through the release of heavy metals, in particular nickel and chromium. In this perspective article I explore the potential role of plants in modulating these heavy metal fluxes. Agricultural basaltic soils may be valuable study sites in this context. However, the effect of biomass harvesting on the accumulation of heavy metals is currently not well studied. Mostly caused by different parent rock concentrations, there is a large variability of heavy metal concentrations in basaltic and ultramafic soils. Hence, to minimize environmental risks of enhanced weathering, basalts with low heavy metal concentrations should be favored. Existing phytoremediation strategies may be used to “phytoprevent” the accumulation of nickel and chromium released from enhanced weathering in soils. As a result, elevated nickel and chromium concentrations in rocks must not preclude enhanced weathering in all settings. In particular, hyperaccumulating plants could be used as part of a crop rotation to periodically remove heavy metals from soils. Enhanced weathering could also be employed on fields or forests of (non-hyper) accumulating plants that have a high primary production of biomass. Both approaches may have additional synergies with phytomining or bioenergy carbon capture and storage, increasing the total amount of carbon dioxide drawdown and at the same time preventing heavy metal accumulation in soils.
Technological Demonstration and Life Cycle Assessment of a Negative Emission Value Chain in the Swiss Concrete Sector
Tiefenthaler, Johannes; Braune, Lisa; Bauer, Christian; et al. (2021)
Frontiers in Climate
Switzerland, such as most of the other countries which are part of the Paris agreement, decided to reduce GHG emissions to zero by 2050. The ambition of net-zero GHG emission across all industrial sectors can only be achieved by rapid decarbonization and the deployment of negative emission technologies to compensate residual emissions from for example agriculture. In the scope of this work, the proof of technology of a negative emission value chain at industrial scale in the concrete sector is presented. The core of the system is a mineralization technology, which fixes biogenic CO2 permanently as calcium carbonate in concrete aggregate. In addition, the net-negativity in terms of GHG emissions and environmental burdens beyond these are quantified in a Life Cycle Assessment (LCA). It could be shown that an industrial-scale mineral carbonation process can be seamlessly integrated in today's concrete recycling processes and that it can process relevant amounts of concrete aggregate while storing on average 7.2 kg CO2 per ton of concrete aggregate. Moreover, material tests revealed that the carbonated concrete aggregate fulfills the same service as the regular one—thus no significant effects on the concrete properties could be observed. The LCA shows that every processing step requires materials and energy, and thus generates associated emissions. However, from a cradle to gate perspective, the carbon removal efficiency is 93.6%. Thus, 1,000 kg of CO2 stored generate 64 kg of CO2-eq. emissions. Furthermore, it could be shown that biogas upgrading can supply sufficient amounts of CO2 until 2030 in Switzerland. From 2030 on, more and more CO2 from other emission sources, such as waste incineration, need to be utilized to exploit the full potential of the value chain, which is going to be 560 kt of negative CO2 emissions in Switzerland in 2050, corresponding to 30% of the projected demand within the national borders.
Adapting Technology Learning Curves for Prospective Techno-Economic and Life Cycle Assessments of Emerging Carbon Capture and Utilization Pathways
Faber, Grant; Ruttinger, Andrew; Strunge, Till; et al. (2022)
Frontiers in Climate
Comparisons of emerging carbon capture and utilization (CCU) technologies with equivalent incumbent technologies are necessary to support technology developers and to help policy-makers design appropriate long-term incentives to mitigate climate change through the deployment of CCU. In particular, early-stage CCU technologies must prove their economic viability and environmental reduction potential compared to already-deployed technologies. These comparisons can be misleading, as emerging technologies typically experience a drastic increase in performance and decrease in cost and greenhouse gas emissions as they develop from research to mass-market deployment due to various forms of learning. These changes complicate the interpretation of early techno-economic assessments (TEAs) and life cycle assessments (LCAs) of emerging CCU technologies. The effects of learning over time or cumulative production themselves can be quantitatively described using technology learning curves (TLCs). While learning curve approaches have been developed for various technologies, a harmonized methodology for using TLCs in TEA and LCA for CCU in particular is required. To address this, we describe a methodology that incorporates TLCs into TEA and LCA to forecast the environmental and economic performance of emerging CCU technologies. This methodology is based on both an evaluation of the state of the art of learning curve assessment and a literature review of TLC approaches developed in various manufacturing and energy generation sectors. Additionally, we demonstrate how to implement this methodology using a case study on a CO2 mineralization pathway. Finally, commentary is provided on how researchers, technology developers, and LCA and TEA practitioners can advance the use of TLCs to allow for consistent, high-resolution modeling of technological learning for CCU going forward and enable holistic assessments and fairer comparisons with other climate technologies.
Orders of Social Science: Understanding Social-Scientific Controversies and Confluence on What “High-Quality” Knowledge and “Good” Adaptation Is
Skelton, Maurice (2021)
Frontiers in Climate
Various scholars have noted—and experienced—tribal tendencies between social-scientific “schools of thought” or “paradigms.” The intensity and fervor of such controversies has led some scientists to compare them with frictions between religious orders. In the research domain focused on the use of climate science for climate adaptation, such disputes revolve around the what “high-quality” climate knowledge and “good” adaptation is or should be. Emphasizing this diversity of orders of social science and the humanities, this article describes five distinct ways social scientists and humanities scholars have thought and written about climate adaptation: descriptivists aim to empirically portray climate adaptation as objectively as possible from an assumed subject-independent perspective; pragmatists' research wants to increase climate resilience through usable climate information; argumentivists strive for assessing the justification of climate scientific findings, as well as adaptation decision-making that is based on these findings; interpretivists seek to empirically redescribe how the use of climate science for adaptation is shaped by, and shapes, various other social processes and political actors; and critical scholars work toward revealing how pervasive powerful interests and marginalizing discourses shape adaptation projects negatively. By comparing these five orders' respective scientific, environmental and social aims and concerns, this article pinpoints to how epistemological, ontological and methodological priorities not only drive scientific controversies on issues such as what “high-quality knowledge” is, but also how interdependent orders' methodological choices are with their epistemological and ontological positions. However, this analysis also reveals that while some scholars implicitly stick to their order, others are comfortable to collaborate across such borders. Overall, the diverging aims, priorities, and methods are unlikely to be ever fully reconciled. A better understanding of why academics from different orders differ in the approaches they take and the issues they care about will likely lead to a larger appreciation of the differences of other orders' research and broaden our understanding of key dynamics in studying “good” climate adaptation and “high-quality” climate knowledge.
Climate extremes and risks: links between climate science and decision-making
Sillmann, Jana; Raupach, Timothy H.; Findell, Kirsten L.; et al. (2024)
Frontiers in Climate
The World Climate Research Programme (WCRP) envisions a future where actionable climate information is universally accessible, supporting decision makers in preparing for and responding to climate change. In this perspective, we advocate for enhancing links between climate science and decision-making through a better and more decision-relevant understanding of climate impacts. The proposed framework comprises three pillars: climate science, impact science, and decision-making, focusing on generating seamless climate information from sub-seasonal, seasonal, decadal to century timescales informed by observed climate events and their impacts. The link between climate science and decision-making has strengthened in recent years, partly owing to undeniable impacts arising from disastrous weather extremes. Enhancing decision-relevant understanding involves utilizing lessons from past extreme events and implementing impact-based early warning systems to improve resilience. Integrated risk assessment and management require a comprehensive approach that encompasses good knowledge about possible impacts, hazard identification, monitoring, and communication of risks while acknowledging uncertainties inherent in climate predictions and projections, but not letting the uncertainty lead to decision paralysis. The importance of data accessibility, especially in the Global South, underscores the need for better coordination and resource allocation. Strategic frameworks should aim to enhance impact-related and open-access climate services around the world. Continuous improvements in predictive modeling and observational data are critical, as is ensuring that climate science remains relevant to decision makers locally and globally. Ultimately, fostering stronger collaborations and dedicated investments to process and tailor climate data will enhance societal preparedness, enabling communities to navigate the complexities of a changing climate effectively.
Expert insights into future trajectories: assessing cost reductions and scalability of carbon dioxide removal technologies
Abegg, Manon; Clulow, Zeynep; Nava, Lucrezia; et al. (2024)
Frontiers in Climate
Introduction: To achieve net-zero targets, it is essential to evaluate and model the costs and scalability of emerging carbon dioxide removal technologies like direct air capture with CO2 storage (DACCS) and bioenergy with carbon capture and storage (BECCS). Yet such efforts are often impeded by varying assessments of the climate impact and potential contributions of these technologies. This study explores the future costs and scalability of DACCS and BECCS to advance net-zero goals. Methods: We analyze expert opinions on these technologies’ potential costs and deployment scales for 2030, 2040, and 2050. Data was collected from 34 experts, comprising 21 DACCS and 13 BECCS specialists. They provided 90% confidence interval estimates and ‘best estimates’ for future costs and deployment under two International Energy Agency (IEA) policy scenarios—Stated Policies (STEPS) and Net Zero Emissions by 2050 (NZE). Results: We find that BECCS costs start at a lower level but decrease more slowly, whereas DACCS costs decline more steeply from a higher initial cost. However, DACCS estimates varied significantly among experts, showing no convergence over time. Regarding potential scalability, both technologies are associated with substantially higher deployment under the NZE scenario. Yet the combined estimated capacity of DACCS and BECCS by 2050 is only about a quarter of the CO2 removals projected by the IEA for its NZE scenario (1.9 GtCO2). Discussion: This study provides valuable insights into the future of DACCS and BECCS technologies in Europe, especially since our experts expect that DACCS and BECCS costs will be even higher (and deployment scales lower) than those predicted by recent IEA tracking, opening future research directions.
The Critical Importance of Citizen Science Data
de Sherbinin, Alex; Bowser, Anne; Chuang, Tyng-Ruey; et al. (2021)
Frontiers in Climate
Citizen science is an important vehicle for democratizing science and promoting the goal of universal and equitable access to scientific data and information. Data generated by citizen science groups have become an increasingly important source for scientists, applied users and those pursuing the 2030 Agenda for Sustainable Development. Citizen science data are used extensively in studies of biodiversity and pollution; crowdsourced data are being used by UN operational agencies for humanitarian activities; and citizen scientists are providing data relevant to monitoring the sustainable development goals (SDGs). This article provides an International Science Council (ISC) perspective on citizen science data generating activities in support of the 2030 Agenda and on needed improvements to the citizen science community's data stewardship practices for the benefit of science and society by presenting results of research undertaken by an ISC-sponsored Task Group.

Publications 1 - 10 of 13

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