Brett F. Sanders

Scientific assessments play a critical role in synthesizing evidence to support evidence‐based decision‐making in many sectors and topics. For climate change, large‐scale assessments like the Intergovernmental Panel on Climate Change (IPCC) and the United States (U.S.) National Climate Assessment (NCA) reports help many different users—from national government to local governments, Indigenous Peoples and communities, the private sector, the social sector, and the scientific community itself—navigate the complex field of climate risks, impacts, and integrated solutions. While co‐creation with users is essential to developing actionable assessments, this paper lays the groundwork for future processes by identifying many advancing and emerging areas of relevant knowledge ready for assessment or additional near‐term research. Drawing on the expertise of many scholars who were formerly tasked with producing the Sixth NCA and authors of other national or sub‐national climate assessment reports, this paper highlights select U.S.‐relevant topics in which research advances since the 2023 Fifth NCA make new syntheses particularly valuable for future national, sub‐national, and sectoral climate assessments. It also identifies critical research topics in those select areas that would be useful for future climate assessment efforts. Overall, this research priorities roadmap aims to catalyze collaborations, research, and a network of climate assessments to synthesize the state of climate impacts, risks, and responses and to provide widely accessible and foundational information for sectoral, regional, and cross‐cutting climate action plans and decisions in the U.S.

Scientific assessments play a critical role in synthesizing evidence to support evidence-based decision-making in many sectors and topics. For climate change, large-scale assessments like the Intergovernmental Panel on Climate Change (IPCC) and the U.S. National Climate Assessment (NCA) reports help many different users—from national government to local governments, Indigenous Peoples and communities, the private sector, the social sector, and the scientific community itself—navigate the complex field of climate risks, impacts, and integrated solutions. While cocreation with users is essential to developing actionable assessments, this paper lays the groundwork for future processes by identifying many advancing and emerging areas of relevant knowledge ready for assessment or additional near-term research. Drawing on the expertise of many scholars who were formerly tasked with producing the Sixth NCA and authors of other national or subnational climate assessment reports, this paper highlights select U.S.-relevant topics in which research advances since the 2023 Fifth NCA make new syntheses particularly valuable for future national, subnational, and sectoral climate assessments. It also identifies critical research topics in those select areas that would be useful for future climate assessment efforts. Overall, this research priorities road map aims to catalyze collaborations, research, and a network of climate assessments to synthesize the state of climate impacts, risks, and responses and to provide widely accessible and foundational information for sectoral, regional, and cross-cutting climate action plans and decisions in the United States. PLAIN LANGUAGE SUMMARY: Scientific assessments are critical in informing households, communities, businesses, institutions, and governments as they respond to intensifying climate hazards. As climate change impacts accelerate, the pace of assessment and integration of science with decision-making and action must accelerate as well. A network of U.S. climate assessment efforts could rapidly synthesize actionable science and case studies to inform climate response strategies. To support future processes, this paper presents a selection of foundational topics needing assessment and near-term research across climate impacts, risks, and actions from the perspective of the United States and some of its key regions, environments, and economic sectors. For example, assessment is needed for the increasing threats posed by compound extremes and cascading climate risks, which can overwhelm systems developed for independent events. The effectiveness of climate responses likewise requires continuous evaluation and improvement, with consideration of the broader impacts (e.g., economic, environmental, health) associated with those strategies. System-level understanding of integrated climate response strategies can be advanced by combining observations and modeling with mitigation, adaptation, climate interventions, disaster management, and resilience decision scenarios. Overall, these research priorities aim to encourage new research and future national, regional, local, and sectoral climate assessments that support climate-informed decision-making in the United States.

With a Comment on our Commentary, “Flooding is not like filling a Bath” in Earth's Future , Hinkel and colleagues dispute our perspective that bathtub models should be abandoned in the context of large‐scale flood risk studies, and share an alternative perspective about the cause of climate hype from flood risk studies. Further analysis of the evidence including studies on the origination and propagation of hazard error through risk modeling frameworks, and literature on causal inference, leads us to reaffirm our original perspective. However, we acknowledge that bathtub models might be suitable in local studies of lakes or other water bodies lacking flood dynamics. Furthermore, we are pleased to be in agreement with Hinkel and colleagues that climate hype is of great concern to the scientific enterprise, and there are surely to be many contributing factors to climate hype which we hope will be more carefully considered by authors, reviewers, editors and journalists moving forward.

Porous shallow-water equations (PSWEs) predict the depth and velocity of urban flooding without resolving individual buildings in the grid, which can reduce computational costs by a factor ...

Flood inundation models are foundational to a variety of engineering design, risk mitigation, and real‐time decision making and response. The models have evolved, driven primarily by advances in data and computational resources. Despite these advances, modeling methods have increasingly diverged into separate development paths. Rather than experiencing parallel growth, where emerging approaches complement and enhance well‐established approaches, newer methods such as geomorphic and machine learning algorithms have, in some cases, supplanted or stalled the continued advancement of robust, time‐tested methodologies. This trend toward replacement rather than synergistic integration may limit opportunities to leverage the respective strengths of both established and innovative approaches. We define “siloing” as the isolation that occurs when development efforts evolve vertically and concentrate within narrow methodological boundaries, potentially overlooking opportunities for integration across different modeling paradigms. This phenomenon can arise when methods are selected based on convenience, lack of familiarity with parallel tracks, or popular trends. The negative consequences can lead to application of certain methods well beyond their intended scope and hinder progress by underutilization of complementary strengths across different approaches to overcome challenges. This paper first discusses four categories of state‐of‐the‐art flood inundation modeling methods—computational, data‐driven, observational and experimental, and conceptual—alongside their major strengths and limitations, followed by instances of methodological siloing challenges. We then propose a vision for future research emphasizing synergistic integration across all modeling trajectories rather than isolated development. We hope to spur dialog among modelers with the short‐term goal of convergent research and long‐term of integrated practice.

Human impacts from dams reduce river sediment fluxes and are primary causes of coastal erosion worldwide. Here we provide new satellite-derived shoreline observation techniques to examine beach area trends across the diverse coastal settings of California. Contrary to global trends, these data reveal that the most heavily urbanized and dammed region of southern California experienced net beach growth of over 2 million m ² during 1984-2024. While several beaches experienced severe erosion, overall widening is explained by sufficient sediment supply and concentrated widening from longshore transport captured at coastal structures and in littoral convergence zones. These results indicate that adequate sediment sources exist in this human-modified landscape to mitigate coastal erosion, but that this sediment is not effectively distributed to vulnerable beaches. This highlights the critical role that longshore sediment transport plays in long-term beach trends and illuminates management opportunities for coastal sustainability at the regional scale.

Damage and disruption from flooding have rapidly escalated over recent decades. Knowing who and what is at risk, how these risks are changing, and what is driving these changes is of immense importance to flood management and policy. Accurate predictions of flood risk are also critical to public safety. However, many high‐profile research studies reporting risks at national and global scales rely upon a significant oversimplification of how floods behave—as a level pool—an approach known as bathtub modeling that is avoided in flood management practice due to known biases (e.g., >200% error in flood area) compared to physics‐based modeling. With publicity by news media, findings that would likely not be trusted by flood management professionals are thus widely communicated to policy makers and the public, scientific credibility is put at risk, and maladaptation becomes more likely. Here, we call upon researchers to abandon the practice of bathtub modeling in flood risk studies, and for those involved in the peer‐review process to ensure the conclusions of impact analyses are consistent with the limitations of the assumed flood physics. We document biases and uncertainties from bathtub modeling in both coastal and inland geographies, and we present examples of physics‐based modeling approaches suited to large‐scale applications. Reducing biases and uncertainties in flood hazard estimates will sharpen scientific understanding of changing risks, better serve the needs of policy makers, enable news media to more objectively report present and future risks to the public, and better inform adaptation planning.

Urbanization and climate change are contributing to severe flooding globally, damaging infrastructure, disrupting economies, and undermining human well-being. Approaches to make cities more resilient to floods are emerging, notably with the design of flood-resilient structures, but relatively little is known about the role of urban form and its complexity in the concentration of flooding. We leverage statistical mechanics to reduce the complexity of urban flooding and develop a mean-flow theory that relates flood hazards to urban form characterized by the ground slope, urban porosity, and the Mermin order parameter which measures symmetry in building arrangements. The mean-flow theory presents a dimensionless flood depth that scales linearly with the urban porosity and the order parameter, with different scaling for disordered square- and hexagon-like forms. A universal scaling is obtained by introducing an effective mean chord length representative of the unobstructed downslope travel distance for flood water, yielding an analytical model for neighborhood-scale flood hazards globally. The proposed mean-flow theory is applied to probe city-to-city variations in flood hazards, and shows promising results linking recorded flood losses to urban form and observed rainfall extremes.