Natalie Marie Mahowald

Aerosol radiative forcing represents the largest source of uncertainty for calculating present-day climate sensitivity. This uncertainty has been underestimated in climate models, as they have not adequately accounted for uncertainties in the emissions of aerosols prior to the satellite era. This is especially the case for natural aerosols, such as mineral dust and aerosols from biomass burning. In this paper, we take a step towards reducing this uncertainty by providing a roadmap for improved integration of proxy-based observational constraints on past aerosol variability with model simulations. We first review existing literature on the importance of natural aerosol radiative forcing during historical and paleo-time periods, with a focus on the Last Glacial Maximum and the preindustrial era (ca. 1850) to the present. We then compile existing paleo-data archives and describe their ability to constrain emissions of aerosols, highlighting existing gaps. Model-data combinations are available to estimate radiative effects for dust and volcanoes in several time periods, and for biomass burning for preindustrial to present day, but are not available for other aerosols. Modeled feedbacks of aerosols to climate (W/m²/°C) are 10–100⨉ lower than model-data derived estimates for dust, casting doubt on our ability to successfully model feedbacks in the current generation of Earth system models. Finally, we propose a framework for integrating paleo-archives with models through harmonized datasets, proxy–model translation metrics, and regularized inversion approaches, and identify priority measurements needed to reduce uncertainty in both aerosol loading and radiative-effect efficiency across climate states.

Aerosol radiative forcing represents the largest source of uncertainty for calculating present-day climate sensitivity. This uncertainty has been underestimated in climate models, as they have not adequately accounted for uncertainties in the emissions of aerosols prior to the satellite era. This is especially the case for natural aerosols, such as mineral dust and aerosols from biomass burning. In this paper, we take a step towards reducing this uncertainty by providing a roadmap for improved integration of proxy-based observational constraints on past aerosol variability with model simulations. We first review existing literature on the importance of natural aerosol radiative forcing during historical and paleo-time periods, with a focus on the Last Glacial Maximum and the preindustrial era (ca. 1850) to the present. We then compile existing paleo-data archives and describe their ability to constrain emissions of aerosols, highlighting existing gaps. Model-data combinations are available to estimate radiative effects for dust and volcanoes in several time periods, and for biomass burning for preindustrial to present day, but are not available for other aerosols. Modeled feedbacks of aerosols to climate (W/m²/°C) are 10–100⨉ lower than model-data derived estimates for dust, casting doubt on our ability to successfully model feedbacks in the current generation of Earth system models. Finally, we propose a framework for integrating paleo-archives with models through harmonized datasets, proxy–model translation metrics, and regularized inversion approaches, and identify priority measurements needed to reduce uncertainty in both aerosol loading and radiative-effect efficiency across climate states.

The mineral composition of dust aerosols affects radiation, clouds, atmospheric chemistry and biogeochemical cycles, but Earth system models (ESMs) have long relied on indirect inferences of soil mineralogy because of the sparse soil measurements in dust source regions. Here, we convert soil-surface mineral mass fractions from NASA's Earth Surface Mineral Dust Source Investigation (EMIT) mission into size-resolved emitted mineralogy for four ESMs using empirical clay/silt partitioning and brittle-fragmentation emission theory. Compared with a legacy method of inferring soil mineral composition from a global atlas of soil types, EMIT-derived simulations improve the agreement of airborne and deposited iron oxides, calcite-equivalent carbonates, and kaolinite with in situ observations, while the performance for the illite-smectite group remains comparable to previous estimates. Quartz and feldspar remain poorly constrained because the EMIT instrument does not provide direct retrievals of these minerals within its visible-to-shortwave-infrared spectral range. The multi-model ensemble reveals strong regional and size-dependent mineralogical contrasts of aerosols across major dust sources. This work provides a model-ready mineralogical source dataset that combines EMIT observations with empirical and process-based constraints on mineral size distributions for studies of dust impacts on radiation, chemistry, clouds and biogeochemistry.

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.

Atmospheric methane (CH ₄ ) plays a central role in Earth’s climate, yet the drivers of its decline during the high-dust conditions of glacial periods, such as the Last Glacial Maximum (LGM), remain uncertain. Previous explanations imply source-driven changes, assuming an atmospheric lifetime comparable to that of present day. Recent work shows that interactions between mineral dust and sea salt aerosols produce CH ₄ -removing chlorine radicals. In this work, we show that during the LGM, CH ₄ lifetime shortened to 7.8 years, 20% lower than that of present day. Chlorine contributed ~15% of global CH ₄ loss, fourfold that of present day. Our results reproduce ice core CH ₄ isotopic evidence, demonstrating that stronger-than-assumed atmospheric sinks can explain CH ₄ variability without invoking substantial source changes, highlighting the overlooked role of chlorine chemistry in the glacial CH ₄ budget.

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.

Mineral dust exerts a major but uncertain radiative influence on Earth's climate. Using near‐global mineralogical constraints from NASA's Earth Surface Mineral Dust Source Investigation (EMIT) mission in an Earth system model, we quantify the relative importance of iron‐oxide content and particle size for estimating the dust direct radiative effect (DRE). We show that the shortwave DRE is governed by a nonlinear interaction between the two factors, which jointly determine dust absorption. In contrast, the longwave DRE depends primarily on particle size and is largely insensitive to mineral composition under the assumptions of mixing state and aggregate structure. In the Earth system model, constraining the soil iron‐oxide distribution using EMIT shifts the dominant source of dust DRE uncertainty toward processes controlling atmospheric dust particle size distribution and loading. These findings highlight the importance of improved observational and process‐based constraints on dust size evolution and loading for better quantifying its climate impact.

Aerosol radiative forcing represents the largest source of uncertainty for calculating present-day climate sensitivity. This uncertainty has been underestimated in climate models, as they have not adequately accounted for uncertainties in the emissions of aerosols prior to the satellite era. This is especially the case for natural aerosols, such as mineral dust and aerosols from biomass burning. In this paper, we take a step towards reducing this uncertainty by providing a roadmap for improved integration of proxy-based observational constraints on past aerosol variability with model simulations. We first review existing literature on the importance of natural aerosol radiative forcing during historical and paleo-time periods, with a focus on the Last Glacial Maximum and the preindustrial era (ca. 1850) to the present. We then compile existing paleo-data archives and describe their ability to constrain emissions of aerosols, highlighting existing gaps. Model-data combinations are available to estimate radiative effects for dust and volcanoes in several time periods, and for biomass burning for preindustrial to present day, but are not available for other aerosols. Modeled feedbacks of aerosols to climate (W/m2/°C) are 10–100⨉ lower than model-data derived estimates for dust, casting doubt on our ability to successfully model feedbacks in the current generation of Earth system models. Finally, we propose a framework for integrating paleo-archives with models through harmonized datasets, proxy–model translation metrics, and regularized inversion approaches, and identify priority measurements needed to reduce uncertainty in both aerosol loading and radiative-effect efficiency across climate states.