Explore the vast range of titles available.

There is evidence that warming leads to greater evapotranspiration and surface drying, thus contributing to increasing intensity and duration of drought and implying that mitigation would reduce water stresses. However, understanding the overall impact of climate change mitigation on water resources requires accounting for the second part of the equation, i.e., the impact of mitigation-induced changes in water demands from human activities. By using integrated, high-resolution models of human and natural system processes to understand potential synergies and/or constraints within the climate–energy–water nexus, we show that in the United States, over the course of the 21st century and under one set of consistent socioeconomics, the reductions in water stress from slower rates of climate change resulting from emission mitigation are overwhelmed by the increased water stress from the emissions mitigation itself. The finding that the human dimension outpaces the benefits from mitigating climate change is contradictory to the general perception that climate change mitigation improves water conditions. This research shows the potential for unintended and negative consequences of climate change mitigation.

Conventional low‐resolution (LR) climate models, including the Energy Exascale Earth System Model (E3SMv1), have well‐known biases in simulating the frequency, intensity, and timing of precipitation. Approaches to next‐generation E3SM, whether the high‐resolution (HR) or multiscale modeling framework (MMF) configuration, improve the simulation of the intensity and frequency of precipitation, but regional and seasonal deficiencies still exist. Here we apply a methodology to assess the contribution of tropical cyclones (TCs), extratropical cyclones (ETCs), and mesoscale convective systems (MCSs) to simulated precipitation in E3SMv1‐HR and E3SMv1‐MMF relative to E3SMv1‐LR. Across the United States, E3SMv1‐MMF provides the best simulation in terms of precipitation accumulation, frequency and intensity from MCSs and TCs compared to E3SMv1‐LR and E3SMv1‐HR. All E3SMv1 configurations overestimate precipitation amounts from and the frequency of ETCs over CONUS, with conventional E3SMv1‐LR providing the best simulation compared to observations despite limitations in precipitation intensity within these events. Plain Language Summary Precipitation has direct and major impacts on society, both locally and globally, and thus understanding how precipitation may change in the future is important. Climate models, or mathematical representations of the Earth system, are the tools‐of‐choice, albeit imperfect for projecting future changes in precipitation. Precipitation occurs in many different environments and is produced by a variety of weather phenomena in the United States, including tropical cyclones (TCs), extratropical cyclones (ETCs), and mesoscale convective systems (MCSs). This work acts to quantify the characteristics of precipitation in configurations of the Energy Exascale Earth System Model by these storm‐types to better inform future development of the climate model and produce more accurate projections of future precipitation. Key Points Multiscale modeling framework E3SMv1 captures precipitation from mesoscale convective systems (MCSs) better than low‐ and high‐resolution High‐resolution and multiscale modeling framework E3SMv1 improve tropical cyclone (TC) precipitation All configurations capture realistic extratropical cyclone precipitation in contrast to TC and MCS, and conventional low‐resolution E3SMv1 does best

Heatwaves are strongly associated with temperature distributions, but the mechanisms by which distributions are influenced by climate change remains unclear. Comparing simulations from a high‐spatial resolution Community Earth System Model (CESM‐HR) with those from low‐resolution models, we identify substantial improvements by CESM‐HR in reproducing observed Northern Hemisphere summer temperature skewness, as well as the frequency, intensity, persistence, and total heatwave days. Temperature skewness is strongly linked to land‐atmosphere interactions and atmospheric circulation. Under global warming projections, some regions exhibit enhanced temperature skewness, along with more frequent and persistent heatwaves of greater intensity. We find that in energy‐limited regimes, such as India, negative skewness in latent heat flux facilitates large positive skewness in sensible heat flux, which modulates near‐surface air temperatures. Skewness differences of latent and sensible heat fluxes are amplified under global warming, increasing the temperature skewness. We find that this contrasting flux mechanism is active in several heatwave‐prone regions. Plain Language Summary Heatwaves have occurred frequently in the recent decades, exerting substantial impacts on human health. While it is well known that mean warming can induce more frequent heatwaves, how higher order characteristics of the temperature distribution like skewness influence extreme hot events has received less focus. Using a high‐resolution global climate model to simulate the response to future anthropogenic climate forcing, we find that regions with increasing positive temperature skewness tend to experience more frequent, persistent and intensified heatwaves. We also find that surface soil moisture and energy partitioning can significantly alter the shape of near surface air temperature distribution, and hence heatwaves. Key Points Striking improvements in simulating temperature skewness and heatwave days are achieved by a high‐resolution Earth system model Regions with enhanced temperature skewness in a warming climate tend to suffer more frequent, persistent and intense heatwaves Over energy‐limited regions, temperature distribution is affected by negatively skewed latent and positively skewed sensible heat fluxes

Predicted active‐layer (AL) thicknesses of permafrost‐affected soils influence earth system model predictions of C‐climate feedbacks; yet, only a few observation‐based studies have estimated AL thicknesses across large regions and at the spatial scale at which they vary. We used spatially referenced soil profile description data (n = 153) and environmental variables (topography, climate, and land cover) in a geographically weighted regression approach to predict the spatial variability of AL thickness across Alaska at a 60‐m spatial resolution. The predicted AL thickness across Alaska ranged from 0.14 to 0.93 m, with a spatial average of 0.46 m and a coefficient of variation of 30%. The average prediction error and ratio of performance to deviation were 0.11 m and 1.8, respectively. Our study showed mean annual surface air temperature, land cover type, and slope gradient were primary controllers of AL thickness spatial variability. We compared our estimates with Coupled Model Intercomparison Project Phase 5 (CMIP5) earth system model predictions; those predictions showed large interquartile ranges in predicted AL thicknesses (0.35–4.4 m) indicating substantial overestimate of current AL thickness in Alaska, which might result in higher positive permafrost C feedback under future warming scenarios. The CMIP5 predictions of AL thicknesses spatial heterogeneity were unrealistic when compared with observations, and prediction errors were several times larger in comparison to errors from our observation‐based approach. The coefficient of variability of AL thickness was substantially lower in CMIP5 predictions compared to our estimates when gridded at similar spatial resolutions. These results indicate the need for better process representations and representation of natural spatial heterogeneity due to local environment (topography, vegetation, and soil properties) in earth system models to generate a realistic variation of regional scale AL thickness, which could reduce the existing uncertainty in predicting permafrost C‐climate feedbacks.

Modern studies suggest that the upper ocean heat content (OHC) in the tropical Indian Ocean (TIO) is a better qualitative predictor of the Indian summer monsoon rainfall (ISMR). But it is still unknown how the OHC is mechanically linked to ISMR and whether it can be applied to long-term climate changes. By analyzing reanalysis datasets across the 20th century, we illustrate that in contrast to those anomalies associated with stronger ISM westerlies, higher ISMR is accompanied with summer surface high pressure and east wind anomalies from the South China Sea to the Bay of Bengal (BOB), and is loosely related to increased western TIO OHC during decayed phases of positive Indian Ocean dipole (IOD) and of El Niño. Except for 1944–1968 AD, this interannually lagged ISMR response to winter OHC is insignificant, probably suppressed by those simultaneous effects of positive IOD and El Niño on ISMR. In our paleoclimatic simulations, this modern observed lagged response is interrupted by seasonally reversed insolation anomalies at the 23,000-year precessional band. Our sensitivity experiments further prove that, the ISMR can be simultaneously reduced by positive IOD-like summer OHC anomalies both for modern and precessional situations. This damping effect is mainly contributed by the warmer western TIO that triggers anomalous surface high pressure, easterly winds, and drastically reduced rainfall from BOB to Arabian Peninsula, but with slightly increased rainfall in the northern ISM region. And the cooler southeastern TIO will only moderately increase rainfall in the southern ISM region.

The overestimation of surface ozone concentration in low‐resolution global atmospheric chemistry and climate models has been a long‐standing issue. We first update the ozone dry deposition scheme in both high‐ (0.25°) and low‐resolution (1°) Community Earth System Model (CESM) version 1.3 runs, by adding the effects of leaf area index and correcting the sunlit and shaded fractions of stomatal resistances. With this update, 5‐year‐long summer simulations (2015–2019) using the low‐resolution CESM still exhibit substantial ozone overestimation (by 6.0–16.2 ppbv) over the U.S., Europe, eastern China, and ozone pollution hotspots. The ozone dry deposition scheme is further improved by adjusting the leaf cuticle conductance, reducing the mean ozone bias by 19%, and increasing the model resolution further reduces the ozone overestimation by 43%. We elucidate the mechanism by which model grid spacing influences simulated ozone, revealing distinctive pathways in urban versus rural areas. In rural areas, grid spacing mainly affects daytime ozone levels, where additional NOx emissions from nearby urban areas result in an ozone boost and overestimation in low‐resolution simulations. In contrast, over urban areas, daytime ozone overestimation follows a similar mechanism due to the influence of volatile organic compounds from surrounding rural areas. However, nighttime ozone overestimation is closely linked to weakened NO titration owing to the redistribution of urban NOx to rural areas. Additionally, stratosphere‐troposphere exchange may also contribute to reducing ozone bias in high‐resolution simulations, warranting further investigation. This optimized high‐resolution CESM may enhance understanding of ozone formation mechanisms, sources, and changes in a warming climate. Plain Language Summary Traditionally, low‐resolution Earth system models have persistently overestimated surface ozone concentrations. Building on our previous optimization of the high‐resolution Community Earth System Model version 1.3 for the Sunway heterogeneous‐architecture high‐performance computing system, we have enhanced both the efficiency and accuracy of high‐resolution Earth system simulations with interactive atmospheric chemistry. This advancement enables a systematic evaluation of the benefits of high‐resolution (∼25 km atm) modeling compared to its low‐resolution (∼100 km atm) counterpart. Our findings show that while improving ozone sinks, such as ozone dry deposition velocity, can partially reduce bias in low‐resolution simulations, increasing model resolution significantly mitigates ozone overestimation. Furthermore, we identify a key mechanism driving simulated ozone differences across grid spacings: the misrepresentation of urban and rural emission redistribution in low‐resolution models alters the dominant ozone formation regimes controlled by volatile organic compounds and nitrogen oxides, leading to ozone biases. This newly optimized high‐resolution CESM is expected to improve our understanding of ozone formation mechanisms, emission sources, and future changes in a warming climate. Key Points A high‐resolution Earth system model with interactive atmospheric chemistry is optimized on the Sunway high‐performance computing system The updated ozone dry deposition velocity along with high‐resolution simulations greatly reduces ozone overestimates across many regions We identify the mechanism that modulates differences in simulated ozone across different grid spacings in Earth system models

The Intergovernmental Panel on Climate Change Fifth Assessment Report lists sea‐level rise as one of the major future climate challenges. Based on pre‐industrial and historical‐and‐future climate simulations with the Community Earth System Model, we analyze the projected sea‐level rise in the Northwest Atlantic Ocean with two sets of simulations at different horizontal resolutions. Compared with observations, the low resolution (LR) model simulated Gulf Stream does not separate from the shore but flows northward along the entire coast, causing large biases in regional dynamic sea level (DSL). The high resolution (HR) model improves the Gulf Stream representation and reduces biases in regional DSL. Under the RCP8.5 future climate scenario, LR projects a DSL trend of 1.5–2 mm/yr along the northeast continental shelf (north of 40° N), which is 2–3 times the trend projected by HR. Along the southeast shelf (south of 35° N), HR projects a DSL trend of 0.5–1 mm/yr while the DSL trend in LR is statistically insignificant. The different spatial patterns of DSL changes are attributable to the different Gulf Stream reductions in response to a weakening Atlantic Meridional Overturning Circulation. Due to its poor representation of the Gulf Stream, LR projects larger (smaller) current decreases along the north (south) east continental slope compared to HR. This leads to larger (smaller) trends of DSL rise along the north (south) east shelf in LR than in HR. The results of this study suggest that the better resolved ocean circulations in HR can have significant impacts on regional DSL simulations and projections. Plain Language Summary Projecting future sea‐level rise has great socioeconomic value. Based on long‐term global high‐resolution Community Earth System Model simulations, we analyze future sea‐level rise in the Northwest Atlantic Ocean. Two identical sets of simulations were conducted with different horizontal resolutions. Comparisons between the two sets of simulations show different sea‐level rise projections along the US east continental shelf between the low‐resolution (LR) and high‐resolution (HR) models. At the northeast shelf, HR projects a sea‐level rise of 0.8 mm/yr, less than half of the trend (1.7 mm/yr) projected by LR. At the southeast shelf, HR projects a sea‐level rise of 0.6 mm/yr, while the trend in LR is statistically insignificant at only 0.15 mm/yr. We attribute the different sea‐level rise projections to the different ocean circulations simulated in LR and HR. Under global warming, LR projects a decrease in Gulf Stream flow along the entire east continental slope, while the decrease in Gulf Stream strength is confined to the southeast continental slope in HR. This study provides an explanation for the discrepancy in regional sea‐level rise projections between low‐ and high‐resolution climate models and thus improves our understanding of projected future sea‐level rise. Key Points The high resolution (HR) Community Earth System Model reduces biases in dynamic sea level (DSL) and circulation on US east continental shelf Compared to the low resolution model, the HR projects enhanced (reduced) trends of DSL rise along the US south (north) east continental shelf Different DSL rise patterns are related to different Gulf Stream reductions under a weakening Atlantic Meridional Overturning Circulation

Earth system models (ESMs) serve as a unique research infrastructure for quality climate services, yet their application for environmental management at regional scale has not yet been fully explored. The unprecedented resolution and model fidelity of the Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations, especially of the High-Resolution Model Intercomparison Project (HighResMIP) focusing on regional phenomena, offer opportunities for such applications. This article presents the first venture into using the HighResMIP simulations to tackle a regional environmental issue, the Florida Red Tide. This is a harmful algae bloom caused by the dinoflagellate Karenia brevis, a toxic single-celled microscopic protist. We use CMIP6 historical simulations to establish a causal agreement between the position of Loop Current, a warm ocean current that moves into the Gulf of Mexico, and the occurrence of K. brevis blooms on the Western Florida shelf. Results show that the high-resolution ESMs are capable of simulating the phenomena of interest (i.e., Loop Current) at the regional spatial scale with generally adequate data-model agreement in the context of the relation between Loop Current and red tide. We use this case study to elaborate on the prospects and limitations of using publicly available CMIP data for regional environmental management. We highlight the current gaps and the developmental needs for the next generation ESMs, and discuss the role of stakeholder participation in future ESMs development to facilitate the translation of scientific understanding to better inform decision-making of regional environmental management.

The Arctic coastal margin receives a disproportionately large fraction of the global river discharge. The bio-geochemistry of the river water as it empties into the marine environment reflects inputs and processes that occur as the water travels from its headwaters. Climate-induced changes to Arctic vegetation and permafrost melt may impact river chemistry. Understanding the impact of river nutrients on coastal marine production, and how this may change in the future, are important for resource managers and community members who monitor and rely on coastal food resources. Using the Energy Exascale Earth System Model we explore the impact of timing and river nutrient concentrations on primary production in each coastal Arctic region and then assess how this influences secondary production and particle fluxes supporting the benthic food web. Our results indicate that while the concentration of Arctic river nitrogen can have a significant impact on annual average nitrogen and primary production in the coastal Arctic, with production increases of up to 20% in the river influenced interior Seas, the timing of the river nutrient inputs into the marine environment appears less important. Bloom timing and partitioning between small and large phytoplankton were minimally impacted by both river nutrient concentration and timing, suggesting that in general, coastal Arctic ecosystem dynamics will continue to be primarily driven by light availability, rather than nutrients. Under a doubling river nutrient scenario, the percentage increase in the POC flux to the benthos on river influenced Arctic coastal shelves was 2-4 times the percentage increase in primary production, suggesting changes to the river nutrient concentration has the potential to modify the Arctic food web structure and dynamics. Generally, the nutrient-induced changes to primary production were smaller than changes previously simulated in response to ice reduction and temperature increase. However, in the Laptev Sea, the production increase resulting from a doubling of river nutrients exceeded the production increase simulated with an atmospheric warming scenario. Dissolved organic carbon is presently poorly represented in the model so its impact on production is hard to simulate. Applying established relationships between modeled DOC, total DOC, and light absorption we illustrate that DOC could play a very important role in modulating production. Our findings highlight the importance of developing more realistic river nutrient and discharge forcing for Earth System Models such that their impact on the critical Arctic coastal domain can be more adequately resolved.

This article is a Commentary on Asner et al. (pp. 973–988), Bahar et al. (pp. 1002–1018), Chavana‐Bryant et al. (pp. 1049–1063), Goldsmith et al. (pp. 989–1001), Malhi et al. (pp. 1019–1032), Rowland et al. (pp. 1064–1077) and Wu et al. (pp. 1033–1048), all of which are published in this issue.