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At least 253 records · Page 14

Observed declines in upper ocean phosphate-to-nitrate availability

Climate warming is increasing ocean stratification, which in turn should decrease the nutrient flux to the upper ocean. This may slow marine primary productivity, causing cascading effects throughout food webs. However, observing changes in upper ocean nutrients is challenging because surface concentrations are often below detection limits. We show that the nutricline depth, where nutrient concentrations reach well-detected levels, is tied to productivity and upper ocean nutrient availability. Next, we quantify nutricline depths from a global database of observed vertical nitrate and phosphate profiles to assess contemporary trends in global nutrient availability (1972–2022). We find strong evidence that the P-nutricline (phosphacline) is mostly deepening, especially throughout the southern hemisphere, but the N-nutricline (nitracline) remains mostly stable. Earth System Model (ESM) simulations support the hypothesis that reduced iron stress and increased nitrogen fixation buffer the nitracline, but not phosphacline, against increasing stratification. These contemporary trends are expected to continue in the coming decades, leading to increasing phosphorus but not nitrogen stress for marine phytoplankton, with important ramifications for ocean biogeochemistry and food web dynamics.

54 ENVIRONMENTAL SCIENCES↗

Assessing dynamic vegetation model parameter uncertainty across Alaskan arctic tundra plant communities

Abstract As the Arctic region moves into uncharted territory under a warming climate, it is important to refine the terrestrial biosphere models (TBMs) that help us understand and predict change. One fundamental uncertainty in TBMs relates to model parameters, configuration variables internal to the model whose value can be estimated from data. We incorporate a version of the Terrestrial Ecosystem Model (TEM) developed for arctic ecosystems into the Predictive Ecosystem Analyzer (PEcAn) framework. PEcAn treats model parameters as probability distributions, estimates parameters based on a synthesis of available field data, and then quantifies both model sensitivity and uncertainty to a given parameter or suite of parameters. We examined how variation in 21 parameters in the equation for gross primary production influenced model sensitivity and uncertainty in terms of two carbon fluxes (net primary productivity and heterotrophic respiration) and two carbon (C) pools (vegetation C and soil C). We set up different parameterizations of TEM across a range of tundra types (tussock tundra, heath tundra, wet sedge tundra, and shrub tundra) in northern Alaska, along a latitudinal transect extending from the coastal plain near Utqiaġvik to the southern foothills of the Brooks Range, to the Seward Peninsula. TEM was most sensitive to parameters related to the temperature regulation of photosynthesis. Model uncertainty was mostly due to parameters related to leaf area, temperature regulation of photosynthesis, and the stomatal responses to ambient light conditions. Our analysis also showed that sensitivity and uncertainty to a given parameter varied spatially. At some sites, model sensitivity and uncertainty tended to be connected to a wider range of parameters, underlining the importance of assessing tundra community processes across environmental gradients or geographic locations. Generally, across sites, the flux of net primary productivity (NPP) and pool of vegetation C had about equal uncertainty, while heterotrophic respiration had higher uncertainty than the pool of soil C. Our study illustrates the complexity inherent in evaluating parameter uncertainty across highly heterogeneous arctic tundra plant communities. It also provides a framework for iteratively testing how newly collected field data related to key parameters may result in more effective forecasting of Arctic change.

54 ENVIRONMENTAL SCIENCES↗

A Multivariate Space‐Time Dynamic Model for Characterizing the Atmospheric Impacts Following the Mt. Pinatubo Eruption

The June 1991 Mt. Pinatubo eruption resulted in a massive increase of sulfate aerosols in the atmosphere, absorbing radiation and leading to global changes in surface and stratospheric temperatures. A volcanic eruption of this magnitude serves as a natural analog for stratospheric aerosol injection, a proposed solar radiation modification method to combat a warming climate. The impacts of such an event are multifaceted and region-specific. Our goal is to characterize the multivariate and dynamic nature of the atmospheric impacts following the Mt. Pinatubo eruption. We developed a multivariate space-time dynamic linear model to understand the full extent of the spatially- and temporally-varying impacts. Specifically, spatial variation is modeled using a flexible set of basis functions for which the basis coefficients are allowed to vary in time through a vector autoregressive (VAR) structure. This novel model is cast in a Dynamic Linear Model (DLM) framework and estimated via a customized MCMC approach. We demonstrate how the model quantifies the relationships between key atmospheric parameters prior to and following the Mt. Pinatubo eruption with reanalysis data from MERRA-2 and highlight when such a model is advantageous over univariate models.

Dynamic Linear Model↗

A History of Molecular Level Analysis of Natural Organic Matter by FTICR Mass Spectrometry and The Paradigm Shift in Organic Geochemistry

Natural organic matter (NOM) is a complex mixture of biogenic molecules resulting from the deposition and transformation of plant and animal matter. It has long been recognized that NOM plays an important role in many geological, geochemical, and environmental processes. Of particular concern is the fate of NOM in response to a warming climate in environments that have historically sequestered carbon (e.g., peatlands and swamps) but may transition to net carbon emitters. In this review, we will highlight developments in the application of high-field Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) in identifying the individual components of complex NOM mixtures, focusing primarily on the fraction that is dissolved in natural waters (dissolved organic matter or DOM). We will first provide some historical perspective on developments in FTICR technology that made molecular-level characterizations of DOM possible. In conclusion, a variety of applications of the technique will then be described, followed by our view of the future of high-field FTICR MS in carbon cycling research, including a particularly exciting metabolomic approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

What explains the year-to-year variation in growing season timing of boreal black spruce forests?

Amplified climate warming in high latitudes is expected to affect growing season timing of the vast boreal biome. It is unclear whether the presence of permafrost (perennially frozen ground) might have an influence on changes in growing season timing. Here, this study examined how different environmental variables explained, either directly or indirectly, the variation in growing season timing of boreal forest stands with and without permafrost. We expected that environmental variables explaining the variation in growing season timing differed or had different explanatory power depending on permafrost presence or absence. The growing season was delineated from daily gross primary productivity (GPP) time series derived from 40 site-year data of net ecosystem carbon dioxide exchange measured with eddy covariance techniques over five black spruce (Picea mariana [Mill.])-dominated boreal forest stands in North America. In permafrost-free forest stands, a combination of start in canopy ‘green-up’ in spring and the timing of air and soil temperature increasing above freezing explained the start-of-season (SOS GPP ). Results from commonality analysis and structural equation modeling suggest that canopy ‘green-up’ and air temperature directly affected SOS GPP in permafrost-free forest stands. In addition, soil temperature acted as mediator for an indirect effect of air temperature on SOS GPP . In contrast, none of the environmental variables, or their combination, explained the variation in SOS GPP in forest stands with permafrost. The explanatory power of environmental variables was more consistent regarding the end-of-season (EOS GPP ). In both, forest stands with and without permafrost, EOS GPP was directly explained by mean soil water content in the fall and the first day of continuous snowpack formation. A better understanding how environmental variables control SOS GPP and EOS GPP in forest stands with and without permafrost will help to refine parameterizations of the boreal biome in Earth system models.

54 ENVIRONMENTAL SCIENCES↗

Hysteresis area at the canopy level during and after a drought event in the Central Amazon

Understanding forest water limitation during droughts within a warming climate is essential for accurate predictions of forest-climate interactions. In hyperdiverse ecosystems like the Amazon forest, the mechanisms shaping hysteresis patterns in transpiration relative to environmental factors are not well understood. From this perspective, we investigated these dynamics by conducting in situ leaf-level measurements throughout and after the 2015 El Niño-Southern Oscillation (ENSO) drought. Our findings indicate a substantial increase in the hysteresis area (H area ) among transpiration (E), vapor pressure deficit (VPD), and stomatal conductance (g s ) at canopy level during the ENSO peak, attributed to both temporal lag and differences in magnitude between g s and VPD peaks. Specifically, the canopy species Pouteria anomala exhibited an increased H area , due to earlier maximum g s rates leading to a greater temporal lag with VPD compared to the post-drought period. Additionally, leaf water potential (ψ L ) and canopy temperature (T canopy ) showed larger H area during the ENSO peak compared to post-drought conditions across all studied species, suggesting that stomatal closure, particularly during the afternoon, acts to minimize water loss and may explain the counterclockwise hysteresis observed between ψ L and T canopy . Here, the pronounced H area during the drought points to a potential imbalance between water supply and demand, underlining the role of stomatal behavior of isohydric species in response to drought.

54 ENVIRONMENTAL SCIENCES↗

Refining seasonal performance metrics for room air-conditioning in emerging markets: Integrating building simulations with real-world equipment performance data

Buildings significantly impact worldwide energy consumption, emphasizing the need to reduce the cooling energy demand, especially in warm climates. Minimum energy performance standards (MEPS) and seasonal performance metrics such as the Cooling Seasonal Performance Factor (CSPF) are crucial for improving room air conditioning (RAC) efficiency. However, challenges remain, particularly in emerging markets like Brazil, where seasonal performance metrics have recently been introduced. This study assesses the factors influencing country-level seasonal efficiency metrics and proposes a framework to refine these calculations by considering local climates and expected RAC usage in real-world households via building simulations. Key considerations include outdoor air temperature binning for different climates, RAC usage patterns (i.e., daytime and nighttime usages), envelope thermal performance of households, and urban heat island (UHI) effects. The results reveal that CSPF values can vary significantly based on climate conditions, with observed CSPF ranging from 4.10 to 11.59 Wh/Wh across 577 Brazilian climates. The inclusion of UHI effects led to a reduction in CSPF values by up to 29% during nighttime operations in hot urban areas. Additionally, building envelope efficiency showed contrasting impacts on RAC performance, with CSPFs reaching up to 15.35 Wh/Wh under specific optimized conditions. These findings highlight the need for transparent policymaking in RAC performance databases, facilitating the application of approaches like those proposed in this study and supporting diverse stakeholders in decision-making.

Bavaresco, Mateus↗

Composition and persistence of soil organic matter along eroding and depositional transects in buried vs. modern soil layers: A case of the Brady paleosol at Wauneta, Nebraska

Paleosols form when soils are buried through deposition by aeolian, colluvial, alluvial or other processes. Burial of former topsoil isolates soil organic matter (SOM) from surface conditions, allowing carbon to accumulate and potentially remain stable for millennia. In this study, SOM composition, distribution, and persistence were analyzed in the Brady Soil of Nebraska, USA to compare SOM spatial variability in modern and buried soils, as well as the impact of erosional exposure on SOM stability. The Brady Soil, formed as a surface soil during the Pleistocene-Holocene transition and now a paleosol buried up to 6 m deep (or more) by loess deposition during the Holocene, was sampled along burial (up to 5.8 m depth) and erosional (up to 1.8 m depth) transects to compare SOM dynamics in different geomorphic settings. Fourier Transform Infrared Spectroscopy (FTIR) and Fourier Transform ion cyclotron resonance mass spectrometry (FTICR-MS) were used to analyze SOM composition, while δ 13 C isotope analyses identified SOM sources and radiocarbon values were used to estimate turnover rates. Results confirmed a vegetation shift from C3 to C4 plants after Brady Soil formation, reflecting warming climatic conditions. Increasing SOM age and decreasing δ 13 C and δ 15 N values with depth indicated slowing of decomposition rate in buried soils. Higher pH in the Brady Soil suggested greater base cation content, supporting SOM stabilization through organo-mineral associations and aggregate formation. However, exposure of the Brady Soil due to surface erosion caused faster SOM turnover. This result suggested susceptibility of buried SOM to losses via decomposition upon erosional exposure, possibly accelerated by priming in response to modern SOM inputs. These findings highlight the potential loss of carbon stocks in buried soils under future climate change, as shifts in soil physicochemical properties may destabilize long-preserved SOM.

Environmental sciences↗

A multiphase flow model of water droplets dielectrophoretic-induced air dehumidification phenomena

Air humidity in indoor spaces plays a critical role in human comfort and health. Dehumidification systems are used for building humidity controls, but they can take significant energy consumption, especially in geographic locations with high outdoor humidity and warm climates. Consequently, there is a growing demand for innovative dehumidification processes that consume minimal energy. Dielectrophoretic air dehumidification represents one such promising approach. However, it has not garnered significant attention due to the absence of engineering models and simulation tools capable of evaluating its performance and limitations at large-scale airflows. A new numerical multiphase CFD model, which is also experimentally validated, is developed in a customized Reacting Foam solver based on OpenFOAM® version 9. The newly developed model seeks to decrease substantial energy consumption and lower costs by leveraging the dielectrophoretic phenomenon to regulate moisture levels in the air. The solver integrates a hybrid Eulerian-Lagrangian framework to track the droplet's trajectory and growth rate while solving the continuum equations for the moist air. An electrospray produces electrically charged droplets, which grow during their in-flight trajectories as water vapor condenses onto their surfaces. The role of electrostatic forces in promoting vapor condensation within a high-gradient electrical field is investigated, and the dielectrophoretic vapor nucleation process on charged water droplets is discussed. The CFD model was validated against results from the literature and from proof-of-concept experiments conducted by the authors, which showed a 2 % air dehumidification with a single electrospray and airflow rate of 5 cubic feet per minute. The simulation results indicated that augmenting the number of electrically charged spray droplets increased the dehumidification of the air to 25 %. The initial mean droplet diameter, the orientation of the injector and relative humidity significantly influence the assessment of dehumidification. As a result, scaling up this approach to larger airflow volumes is identified as a potential future research direction.

42 ENGINEERING↗

Insights into storm direction effect on flood response

In this study, we investigate the directional influence of storm movement on catchment flood peak response using the synthetic circular basin. Due to the complexity in defining storm movements that require meteorological modeling, we adopt a novel approach of combining the basin rotation method (BRM) with a circular basin construct. A systematic basin rotation approach provides a proxy for the storm direction relative to the river network topology to study its hydrologic response. Using Stage-IV rainfall with 4-km by 1-hour resolution for 16 years period from 2003 to 2018 in Iowa, U.S., we systematically analyze consequent flood peak response due to storm directions (basin rotations) using a distributed hydrologic model called the Hillslope-Link Model (HLM). HLM has demonstrated the ability to reproduce observed streamflow for real river basins studied in Iowa. The hydrologic simulation results show that the BRM can quantify the relationship between the rainstorm direction and catchment hydrologic response. Also, the maximum flood peak response is strongly dependent on the interaction of the peak of the rainstorm with the peak of the width function. The results indicate significant differences in runoff volume and runoff peak and their interannual variability due to rainstorm direction. The study has important implications for flood frequency predictions and developing flood resilience and watershed management strategies, particularly due to changing storm tracks under a warming climate.

42 ENGINEERING↗

A comprehensive analysis of the crop effect on the urban-rural differences in land surface phenology

The response of land surface phenology (LSP) to the urban heat island effect (UHI) is a useful biological indicator for understanding how vegetated ecosystems will be affected by future climate warming. However, vegetation cover in rural areas is often dominated by cultivated land, whose phenological timing is considerably influenced by agricultural managements (e.g., timing of sowing and harvesting), leading to biased conclusions derived from the urban-rural LSP differences. To demonstrate this problem, we investigated the crop influence on the phenological response to a warmer environment resulting from the UHI effect. We partitioned cities in the United States into cultivated and non-cultivated categories according to the proportion of crops in rural areas. We then built continuous buffer zones starting from the urban boundary to explore the urban-rural LSP differences considering the UHI effect on them. In this work, the results suggest crop inclusion is likely to lead to >14 days of urban-rural differences at both the start of the season (SOS) and the end of the season (EOS) between cultivated and non-cultivated cities. The temperature sensitivity (ST) of SOS is overestimated by approximately 2.7 days/°C, whereas the EOS is underestimated by 3.6 days/°C. Removing crop-dominated pixels (i.e., above 50 %) can minimize the influence of crop planting/harvesting on LSP and derive reliable results. We, therefore, suggest explicit consideration of crop impacts in future studies of phenological differences between urban and rural areas and the UHI effect on LSP in urban domains, as presented by this comprehensive study.

54 ENVIRONMENTAL SCIENCES↗

Environmental harshness mediates the relationship between aboveground and belowground communities in Antarctica

Linkages between aboveground and belowground communities are a key but globally under-researched component of responses to environmental change. Given the logistical complications to studying these relationships, much of our knowledge derives from laboratory experiments and localized field studies which have so far yielded inconsistent results. Because environmental factors may alter relationships between above- and belowground communities, there is a need for broad-scale field studies testing these interactions. The Antarctic Peninsula provides an ideal test setting, given the relatively simple communities both above- and belowground. The Peninsula is also experiencing rapid environmental changes, including alterations in species diversity and distribution both above- and belowground. Thus, an improved understanding of the broad-scale consequences of altered environments and vegetation communities for the soil microbiome is of high priority. To determine the nature and strength of the relationship between in situ plant and soil communities across a broad spatial scale and range of environmental conditions, we sampled soil communities at 9 locations (spanning 60–72°S along the Scotia Arc and Antarctic Peninsula) beneath the major aboveground habitats (moss, grass, lichen, algae and bare soil). We measured a comprehensive suite of soil physicochemical properties, microbial (bacterial and fungal) diversity and composition, and invertebrate abundance and community composition to determine the relationships between plant and soil communities. Furthermore, our results suggest that, with increased environmental severity, plant cover types become more important for influencing the physicochemical soil environment, and therefore the soil microbial communities. Although we found site-specific relationships, broad-scale patterns reveal significant differences among bare soils and vegetated soils, particularly soils beneath grass and moss. This suggests that expansion of vegetation communities under current climate warming projections will be accompanied by shifts in the soil microbiome, with important implications for the ecosystem functioning with which they are associated.

54 ENVIRONMENTAL SCIENCES↗

Impacts of Forest Fire Ash on Aquatic Mercury Cycling

Mercury (Hg) is a ubiquitous contaminant in the environment and its methylated form, methylmercury (MeHg), poses a worldwide health concern for humans and wildlife, primarily through fish consumption. Global production of forest fire ash, derived from wildfires and prescribed burns, is rapidly increasing due to a warming climate, but their interactions with aqueous and sedimentary Hg are poorly understood. In this study, we compared the differences of wildfire ash with activated carbon and biochar on the sorption of aqueous inorganic Hg and sedimentary Hg methylation. Sorption of aqueous inorganic Hg was greatest for wildfire ash materials (up to 0.21 μg g ₋1 or 2.2 μg g ₋1 C) among all of the solid sorbents evaluated. A similar Hg adsorption mechanism for activated carbon, biochar made of walnut, and wildfire ash was found that involves the formation of complexes between Hg and oxygen-containing functional groups, especially the ₋COO group. Notably, increasing dissolved organic matter from 2.4 to 70 mg C L ₋1 remarkably reduced Hg sorption (up to 40% reduction) and increased the time required to reach Hg–sorbent pseudo-equilibrium. Surprisingly, biochar and wildfire ash, but not activated carbon, stimulated MeHg production during anoxic sediment incubation, possibly due to the release of labile organic matter. Overall, our study indicates that while wildfire ash can sequester aqueous Hg, the leaching of its labile organic matter may promote production of toxic MeHg in anoxic sediments, which has an important implication for potential MeHg contamination in downstream aquatic ecosystems after wildfires.

54 ENVIRONMENTAL SCIENCES↗

Simulating and Evaluating Atmospheric River-Induced Precipitation Extremes Along the U.S. Pacific Coast: Case Studies From 1980–2017

Atmospheric rivers (ARs) are responsible for a majority of extreme precipitation and floodevents along the U.S. West Coast. To better understand the present-day characteristics of AR-relatedprecipitation extremes, a selection of nine most intense historical AR events during 1980–2017 is simulatedusing a dynamical downscaling modeling framework based on the Weather Research and ForecastingModel. We find that the chosen framework and Weather Research and Forecasting Model configurationreproduces both large-scale atmospheric features—including parent synoptic-scale cyclones—as well asthe filamentary corridors of integrated vapor transport associated with the ARs themselves. The accuracyof simulated extreme precipitation maxima, relative to in situ and interpolated gridded observations,improves notably with increasing model resolution, with improvements as large as 40–60% for fine scale(3 km) relative to coarse-scale (27 km) simulations. A separate set of simulations using smoothedtopography suggests that much of these gains stem from the improved representation of complex terrain.Additionally, using the 12 December 1995 storm in Northern California as an example, we demonstratethat only the highest-resolution simulations resolve important fine-scale features—such as localizedorographically forced vertical motion and powerful near hurricane-force boundary layer winds. Given thedemonstrated ability of a targeted dynamical downscaling framework to capture both local extremeprecipitation and key fine-scale characteristics of the most intense ARs in the historical record, we arguethat such a configuration may be highly conducive to understanding AR-related extremes and associatedchanges in a warming climate

54 ENVIRONMENTAL SCIENCES↗

Carbon Fluxes and Microbial Activities From Boreal Peatlands Experiencing Permafrost Thaw

Permafrost thaw is occurring in Alaska which may result in a positive feedback to climate warming, due to the release of greenhouse gases such as CO 2 and CH 4 from soils. Here we examined greenhouse gas production along a gradient of “time since thaw,” hypothesizing that fluxes and microbial activities would be highest soon after thaw, and then decline. We observed highest rates of microbial activities, particularly methanogenesis, soon after thaw, coinciding with less decomposed organic matter and higher concentrations of dissolved carbon and nitrogen in soil, possibly of permafrost origin. However, field fluxes were higher in the young thaw site, compared to the older sites, in winter and not summer, a phenomenon that is currently not well understood.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Remote Sensing Technique to Upscale Methane Emission Flux in a Subtropical Peatland

Abstract Quantification of methane (CH 4 ) gas emission from peat is critical to understand CH 4 budget from natural wetlands under a climate warming scenario. Previous studies have focused on prediction and mapping of CH 4 emission flux using process‐based models, while application of statistical‐empirical models for upscaling spatially sparse in situ measurements is scarce. In this study, we developed an empirical remote sensing upscaling approach to estimate CH 4 emission flux in the Everglades using limited in situ point‐based CH 4 emission flux measurements and Landsat data during 2013–2018. We spatially and temporally linked in situ data with Landsat surface reflectance based on temporally composite data sets and developed an object‐based machine learning framework to model and map CH 4 emission flux. An ensemble analysis of two machine learning models, k ‐Nearest Neighbor ( k ‐NN) and Support Vector Machine (SVM), shows that the upscaling approach is promising for predicting CH 4 emission flux with a R 2 of 0.65 and 0.87 based on a fivefold cross‐validation for a dry season and wet season estimation, respectively. We generated emission flux map products that successfully revealed the spatial and temporal heterogeneity of CH 4 emission within the dominant freshwater marsh ecosystem in the Everglades. We conclude that Landsat is promising for upscaling and monitoring CH 4 emission flux and reducing the uncertainty in emission estimates from wetlands.

Zhang, Caiyun↗

Long-Term Changes in Concentration and Yield of Riverine Dissolved Silicon From the Poles to the Tropics

Riverine exports of silicon (Si) influence global carbon cycling through the growth of marine diatoms, which account for ~25% of global primary production. Climate change will likely alter river Si exports in biome-specific ways due to interacting shifts in chemical weathering rates, hydrologic connectivity, and metabolic processes in aquatic and terrestrial systems. Nonetheless, factors driving long-term changes in Si exports remain unexplored at local, regional, and global scales. We evaluated how concentrations and yields of dissolved Si (DSi) changed over the last several decades of rapid climate warming using long-term data sets from 60 rivers and streams spanning the globe (e.g., Antarctic, tropical, temperate, boreal, alpine, Arctic systems). We show that widespread changes in river DSi concentration and yield have occurred, with the most substantial shifts occurring in alpine and polar regions. The magnitude and direction of trends varied within and among biomes, were most strongly associated with differences in land cover, and were often independent of changes in river discharge. These findings indicate that there are likely diverse mechanisms driving change in river Si biogeochemistry that span the land-water interface, which may include glacial melt, changes in terrestrial vegetation, and river productivity. Finally, trends were often stronger in months outside of the growing season, particularly in temperate and boreal systems, demonstrating a potentially important role of shifting seasonality for the flux of Si from rivers. Our results have implications for the timing and magnitude of silica processing in rivers and its delivery to global oceans.

54 ENVIRONMENTAL SCIENCES↗

Evaluating Large‐Storm Dominance in High‐Resolution GCMs and Observations Across the Western Contiguous United States

Abstract Extreme precipitation events are projected to increase in frequency across much of the land‐surface as the global climate warms, but such projections have typically relied on coarse‐resolution (100–250 km) general circulation models (GCMs). The ensemble of HighResMIP GCMs presents an opportunity to evaluate how a more finely resolved atmosphere and land‐surface might enhance the fidelity of the simulated contribution of large‐magnitude storms to total precipitation, particularly across topographically complex terrain. Here, the simulation of large‐storm dominance, that is, the number of wettest days to reach half of the total annual precipitation, is quantified across the western United States (WUS) using four GCMs within the HighResMIP ensemble and their coarse resolution counterparts. Historical GCM simulations (1950–2014) are evaluated against a baseline generated from station‐observed daily precipitation (4,803 GHCN‐D stations) and from three gridded, observationally based precipitation data sets that are coarsened to match the resolution of the GCMs. All coarse‐resolution simulations produce less large‐storm dominance than in observations across the WUS. For two of the four GCMs, bias in the median large‐storm dominance is reduced in the HighResMIP simulation, decreasing by as much as 62% in the intermountain west region. However, the other GCMs show little change or even an increase (+28%) in bias of median large‐storm dominance across multiple sub‐regions. The spread in differences with resolution amongst GCMs suggests that, in addition to resolution, model structure and parameterization of precipitation generating processes also contribute to bias in simulated large‐storm dominance.

Environmental Sciences & Ecology↗