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Results for “Climate and Earth system modelling”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12

Arctic Warming in Response to Regional Aerosol Emissions Reductions

This study examines the Arctic surface air temperature response to regional aerosol emissions reductions using three fully coupled chemistry–climate models: National Center for Atmospheric Research-Community Earth System Model version 1, Geophysical Fluid Dynamics Laboratory-Coupled Climate Model version 3 (GFDL-CM3) and Goddard Institute for Space Studies-ModelE version 2. Each of these models was used to perform a series of aerosol perturbation experiments, in which emissions of different aerosol types (sulfate, black carbon (BC), and organic carbon) in different northern mid-latitude source regions, and of biomass burning aerosol over South America and Africa, were substantially reduced or eliminated. We find that the Arctic warms in nearly every experiment, the only exceptions being the U.S. and Europe BC experiments in GFDL-CM3 in which there is a weak and insignificant cooling. The Arctic warming is generally larger than the global mean warming (i.e. Arctic amplification occurs), particularly during non-summer months. The models agree that changes in the poleward atmospheric moisture transport are the most important factor explaining the spread in Arctic warming across experiments: the largest warming tends to coincide with the largest increases in moisture transport into the Arctic. In contrast, there is an inconsistent relationship (correlation) across experiments between the local radiative forcing over the Arctic and the simulated Arctic warming, with this relationship being positive in one model (GFDL-CM3) and negative in the other two. Our results thus highlight the prominent role of poleward energy transport in driving Arctic warming and amplification, and suggest that the relative importance of poleward energy transport and local forcing/feedbacks is likely to be model dependent.

Arctic↗

Microbial contribution to post-fire tundra ecosystem recovery over the 21st century

Abstract Tundra ecosystems have experienced an increased frequency of fire, and this trend is predicted to continue throughout the 21 st Century. Post-fire recovery is underpinned by complex interactions between microbial functional groups that drive nutrient cycling. Here we use a mechanistic model to demonstrate an acceleration of the nitrogen cycle post-fire driven by changes in niche space and microbial competitive dynamics. We show that over the first 5-years post-fire, fast-growing bacterial heterotrophs colonize regions of the soil previously occupied by slower-growing saprotrophic fungi. The bacterial heterotrophs mineralize organic matter, releasing nutrients into the soil. This pathway outweighs new sources of nitrogen and facilitates the recovery of plant productivity. We broadly show here that while consideration of distinct microbial metabolisms related to carbon and nutrient cycling remains rare in terrestrial ecosystem models, they are important when considering the rate of ecosystem recovery post-disturbance and the feedback to soil nutrient cycles on centennial timescales.

54 ENVIRONMENTAL SCIENCES↗

Eastern Equatorial Pacific Warming Delayed By Aerosols and Thermostat Response to Co2 Increase

Understanding the tropical Pacific response to global warming remains challenging. Here, we use a range of CMIP6 greenhouse warming experiments to assess the recent and future evolution of the equatorial Pacific east-west temperature gradient and corresponding Walker circulation. In abrupt CO2-increase scenarios many models generate an initial strengthening of this gradient resembling an ocean thermostat (OT), followed by a small weakening; other models generate an immediate weakening that becomes progressively stronger establishing a pronounced eastern equatorial Pacific (EP) warming pattern. The initial response in these experiments is a strong predictor for the future EP pattern simulated in both abrupt and realistic warming scenarios, but not in historical simulations showing no multi-model trend. The likely explanation is that the recent CO2-driven changes in the tropical Pacific are masked by aerosol effects and a potential OT-related delay, while the EP warming pattern will emerge as greenhouse gases overcome aerosol forcing.

Climate and Earth system modelling↗

Mapping the global distribution of C 4 vegetation using observations and optimality theory

Plants with the C 4 photosynthesis pathway typically respond to climate change differently from more common C 3 -type plants, due to their distinct anatomical and biochemical characteristics. These different responses are expected to drive changes in global C 4 and C 3 vegetation distributions. However, current C 4 vegetation distribution models may not predict this response as they do not capture multiple interacting factors and often lack observational constraints. Here, we used global observations of plant photosynthetic pathways, satellite remote sensing, and photosynthetic optimality theory to produce an observation-constrained global map of C 4 vegetation. We find that global C 4 vegetation coverage decreased from 17.7% to 17.1% of the land surface during 2001 to 2019. This was the net result of a reduction in C 4 natural grass cover due to elevated CO 2 favoring C 3 -type photosynthesis, and an increase in C 4 crop cover, mainly from corn (maize) expansion. Using an emergent constraint approach, we estimated that C 4 vegetation contributed 19.5% of global photosynthetic carbon assimilation, a value within the range of previous estimates (18–23%) but higher than the ensemble mean of dynamic global vegetation models (14 ± 13%; mean ± one standard deviation). Our study sheds insight on the critical and underappreciated role of C 4 plants in the contemporary global carbon cycle.

54 ENVIRONMENTAL SCIENCES↗

ESMs Latent Space Exploration for Uncertainty Quantification and Spatiotemporal Downscaling

This final report for DOE Award DE-SC0023044 presents advances in two key areas of climate modeling: (1) representative climate model selection and (2) Earth System Model (ESM) downscaling using hybrid AI methods. The first section introduces a reordered, three-stage workflow to select representative GCM runs that more effectively balance historical skill with ensemble spread, validated across Texas, Bihar, and New York. The second section introduces two novel super-resolution frameworks, ViSIR and ViFOR, that integrate Vision Transformers with sinusoidal and Fourier-based implicit neural representations. These models achieve state-of-the-art reconstruction accuracy for ESM variables including surface temperature and heat fluxes. The report includes detailed methodology, benchmarks, and results, demonstrating significant gains in uncertainty quantification, spatial fidelity, and scalability for climate-impact studies.

54 ENVIRONMENTAL SCIENCES↗

On the Relationship Between the Brewer-Dobson Circulation and the Southern Annular Mode During Austral Summer in Couple Chemistry-Climate Model Simulations

The Brewer-Dobson circulation (BDC) is the mean transport circulation in the stratosphere. It consists of an upwelling branch in the tropics, poleward flows from the tropics to the extratropics, and downward flows in the extratropics. The BDC plays a crucial role in the distribution of important stratospheric trace gases, such as ozone and water vapor. Therefore changes in the strength of the BDC under global warming could have significant impact on stratospheric ozone depletion and recovery. For example, all climate models that are used by the World Meteorological Organization to predict ozone evolution in the 21 st century project a strengthening of the BDC that leads to ozone superrecovery in the mid-latitudes. On the other hand, ozone changes could also affect the strength of the BDC. This work investigates an outstanding question: whether and how changes in the Brewer-Dobson circulation are connected to climate change in the troposphere, in particular, the annular modes. The annular modes are the leading variability in the extratropical troposphere, which describes a seesaw pattern of circulation fluctuations between the polar and middle latitudes. Using simulations from the Goddard Earth Observing System Coupled Chemistry Climate Model (GEOS CCM), we found the strengthening of the BDC in the summer Southern Hemisphere is strongly correlated with a shift of the Southern Hemisphere Annular Mode (SAM) toward its positive phase for the last 4 decades of the 20th century. This relationship is only present in model runs that simulate the stratospheric ozone depletion. Therefore it is concluded that the BDC-SAM relationship is driven by Antarctic ozone depletion. The ozone hole significantly cools the Antarctic stratosphere in late spring/early summer, which leads to a delayed breakdown of the polar vortex: strong circumpolar eastward flows that usually shift to westward winds in late spring. The prolonged persistence of stratospheric eastward flow enhances upward propagation of tropospheric waves into the stratosphere and strengthens the BDC. The increased wave flux in the stratosphere in turn drives a SAM trend toward its positive phase. Our results also show that the BDC-SAM relationship is robust on the interannual timescale

Li, Feng↗

An increase in marine heatwaves without significant changes in surface ocean temperature variability

Marine heatwaves (MHWs)—extremely warm, persistent sea surface temperature (SST) anomalies causing substantial ecological and economic consequences—have increased worldwide in recent decades. Concurrent increases in global temperatures suggest that climate change impacted MHW occurrences, beyond random changes arising from natural internal variability. Moreover, the long-term SST warming trend was not constant but instead had more rapid warming in recent decades. Here we show that this nonlinear trend can—on its own—appear to increase SST variance and hence MHW frequency. Using a Linear Inverse Model to separate climate change contributions to SST means and internal variability, both in observations and CMIP6 historical simulations, we find that most MHW increases resulted from regional mean climate trends that alone increased the probability of SSTs exceeding a MHW threshold. Our results suggest the need to carefully attribute global warming-induced changes in climate extremes, which may not always reflect underlying changes in variability.

54 ENVIRONMENTAL SCIENCES↗

The Implementation of Framework for Improvement by Vertical Enhancement Into Energy Exascale Earth System Model

Abstract The low cloud bias in global climate models (GCMs) remains an unsolved problem. Coarse vertical resolution in GCMs has been suggested to be a significant cause of low cloud bias because planetary boundary layer parameterizations cannot resolve sharp temperature and moisture gradients often found at the top of subtropical stratocumulus layers. This work aims to ameliorate the low cloud problem by implementing a new computational method, the Framework for Improvement by Vertical Enhancement (FIVE), into the Energy Exascale Earth System Model (E3SM). Three physics schemes representing microphysics, radiation, and turbulence as well as vertical advection are interfaced to vertically enhanced physics (VEP), which allows for these processes to be computed on a higher vertical resolution grid compared to the rest of the E3SM model. We demonstrate the better representation of subtropical boundary layer clouds with FIVE while limiting additional computational cost from the increased number of levels. When the vertical resolution approaches the large eddy simulation‐like vertical resolution in VEP, the climatological low cloud amount shows a significant increase of more than 30% in the southeastern Pacific Ocean. Using FIVE to improve the representation of low‐level clouds does not come with any negative side effects associated with the simulation of mid‐ and high‐level cloud and precipitation, that can occur when running the full model at higher vertical resolution.

54 ENVIRONMENTAL SCIENCES↗

Deciphering the capricious precipitation response: irrigation impact in the North China Plain

Intensive irrigation in the North China Plain (NCP) raises environmental concerns, yet its climate impacts remain inconsistent among current modeling studies. These inconsistencies may arise from deficiencies in existing models. To better capture irrigation impact, we employed a recently improved irrigation model tailored for the NCP, which significantly enhances simulations of crop growth and irrigation application. Results reveal that irrigation exerts competing effects on precipitation: enhancing it in May and June by increasing rainfall frequency and intensity, while suppressing it in July and August by reducing intensity. Spatial precipitation changes correlate with upper-tropospheric humidity, while inter-annual changes link to geopotential height and wind anomalies. This suggests that irrigation-induced surface cooling and moisturizing modulate atmospheric thermodynamic and dynamic structures, influencing convective precipitation unevenly across regions and time, leading to complex precipitation changes. These findings highlight the complexity of irrigation impacts and emphasize the need for improved land representation in climate models.

54 ENVIRONMENTAL SCIENCES↗

Prescreening-Based Subset Selection for Improving Predictions of Earth System Models With Application to Regional Prediction of Red Tide

We present the ensemble method of prescreening-based subset selection to improve ensemble predictions of Earth system models (ESMs). In the prescreening step, the independent ensemble members are categorized based on their ability to reproduce physically-interpretable features of interest that are regional and problem-specific. The ensemble size is then updated by selecting the subsets that improve the performance of the ensemble prediction using decision relevant metrics. We apply the method to improve the prediction of red tide along the West Florida Shelf in the Gulf of Mexico, which affects coastal water quality and has substantial environmental and socioeconomic impacts on the State of Florida. Red tide is a common name for harmful algal blooms that occur worldwide, which result from large concentrations of aquatic microorganisms, such as dinoflagellate Karenia brevis, a toxic single celled protist. We present ensemble method for improving red tide prediction using the high resolution ESMs of the Coupled Model Intercomparison Project Phase 6 (CMIP6) and reanalysis data. The study results highlight the importance of prescreening-based subset selection with decision relevant metrics in identifying non-representative models, understanding their impact on ensemble prediction, and improving the ensemble prediction. These findings are pertinent to other regional environmental management applications and climate services. Additionally, our analysis follows the FAIR Guiding Principles for scientific data management and stewardship such that data and analysis tools are findable, accessible, interoperable, and reusable. As such, the interactive Colab notebooks developed for data analysis are annotated in the paper. This allows for efficient and transparent testing of the results’ sensitivity to different modeling assumptions. Moreover, this research serves as a starting point to build upon for red tide management, using the publicly available CMIP, Coordinated Regional Downscaling Experiment (CORDEX), and reanalysis data.

54 ENVIRONMENTAL SCIENCES↗

Increasing Contribution of the Atmospheric Vertical Motion to Precipitation in a Warming Climate

Global warming already influences precipitation, with more intense precipitation in many locations. Although the ‘wet-get-wetter, dry-get-drier’ tendency in mean precipitation holds in many locations, the situations for precipitation extremes are more complex, due to changes in dynamic and thermodynamic influences on atmospheric moisture distributions. Here, we build a dynamically interactive atmospheric moisture model for the present (2006–2025) and the future climate (2081–2100), using outputs from coupled ocean-atmosphere general circulation models. We find that the dynamic process of vertical advection of moisture dominates the same-day precipitation, while the smaller impact of the thermodynamic process provides available moisture for several days. As climate warms, we find that the dynamical-induced precipitation more completely exhausts the vertically-integrated moisture and the distribution of the dynamic process’s impact on precipitation exhibits a greater spread in the warmer future. The dynamical process is primarily responsible for more extreme heavy precipitation as climate warms, at all latitudes.

Climate and Earth system modelling↗

Robust but weak winter atmospheric circulation response to future Arctic sea ice loss

The possibility that Arctic sea ice loss weakens mid-latitude westerlies, promoting more severe cold winters, has sparked more than a decade of scientific debate, with apparent support from observations but inconclusive modelling evidence. Here we show that sixteen models contributing to the Polar Amplification Model Intercomparison Project simulate a weakening of mid-latitude westerlies in response to projected Arctic sea ice loss. We develop an emergent constraint based on eddy feedback, which is 1.2 to 3 times too weak in the models, suggesting that the real-world weakening lies towards the higher end of the model simulations. Still, the modelled response to Arctic sea ice loss is weak: the North Atlantic Oscillation response is similar in magnitude and offsets the projected response to increased greenhouse gases, but would only account for around 10% of variations in individual years. We further find that relationships between Arctic sea ice and atmospheric circulation have weakened recently in observations and are no longer inconsistent with those in models.

54 ENVIRONMENTAL SCIENCES↗

Unified 0.25-degree gridded infrastructure-critical extreme weather for the United States from 1979 to 2100

Extreme weather events can severely disrupt critical infrastructure, triggering cascading effects on power, transportation, and essential services. However, standard weather and climate datasets often lack specialized variables necessary for hazard assessments. We present a unified dataset of infrastructure-critical weather and climate variables across the United States at 0.25° resolution, covering daily or sub-daily intervals from 1979 to 2100. The dataset includes temperature, dew point, wind gusts, precipitation partitioned by rain, snow, and freezing rain or ice pellets, lightning, and wildfire metrics. Historical conditions (1979-2023) are synthesized from observations and reanalysis products, while future projections are derived from 14 CMIP6 global climate models (historical, SSP245, and SSP585 experiments). Physically based and data-driven methods are used to estimate variables not directly provided by existing models. By integrating these variables into a single unified dataset, we enable consistent, high-resolution assessments of weather-related infrastructure risks across past and future periods, supporting wide-ranging applications in energy, transportation, water resources, emergency management, and beyond.

Climate and Earth system modelling↗

Anthropogenic influence on extreme precipitation over global land areas seen in multiple observational datasets

The intensification of extreme precipitation under anthropogenic forcing is robustly projected by global climate models, but highly challenging to detect in the observational record. Large internal variability distorts this anthropogenic signal. Models produce diverse magnitudes of precipitation response to anthropogenic forcing, largely due to differing schemes for parameterizing subgrid-scale processes. Meanwhile, multiple global observational datasets of daily precipitation exist, developed using varying techniques and inhomogeneously sampled data in space and time. Previous attempts to detect human influence on extreme precipitation have not incorporated model uncertainty, and have been limited to specific regions and observational datasets. Using machine learning methods that can account for these uncertainties and capable of identifying the time evolution of the spatial patterns, we find a physically interpretable anthropogenic signal that is detectable in all global observational datasets. Machine learning efficiently generates multiple lines of evidence supporting detection of an anthropogenic signal in global extreme precipitation.

54 ENVIRONMENTAL SCIENCES↗

Mid-Pliocene El Niño/Southern Oscillation Suppressed By Pacific Intertropical Convergence Zone Shift

The El Niño/Southern Oscillation (ENSO), the dominant driver of year-to-year climate variability in the equatorial Pacific Ocean, impacts climate pattern across the globe. However, the response of the ENSO system to past and potential future temperature increases is not fully understood. Here we investigate ENSO variability in the warmer climate of the mid-Pliocene (~3.0–3.3 Ma), when surface temperatures were ~2–3 °C above modern values, in a large ensemble of climate models—the Pliocene Model Intercomparison Project. We show that the ensemble consistently suggests a weakening of ENSO variability, with a mean reduction of 25% (±16%). We further show that shifts in the equatorial Pacific mean state cannot fully explain these changes. Instead, ENSO was suppressed by a series of off-equatorial processes triggered by a northward displacement of the Pacific intertropical convergence zone: weakened convective feedback and intensified Southern Hemisphere circulation, which inhibit various processes that initiate ENSO. The connection between the climatological intertropical convergence zone position and ENSO we find in the past is expected to operate in our warming world with important ramifications for ENSO variability.

Atmospheric dynamics↗

A Large Source of Cloud Condensation Nuclei from New Particle Formation in the Tropics

Cloud condensation nuclei (CCN) can affect cloud properties and therefore the Earth’s radiative balance. New particle formation (NPF) from condensable vapours in the free troposphere has been suggested to contribute to CCN, especially in remote, pristine atmospheric regions, but direct evidence is sparse, and the magnitude of this contribution is uncertain. Here we use in-situ aircraft measurements of vertical profiles of aerosol size distributions to present a global-scale survey of NPF occurrence. We observed intense NPF occurring at high altitude in tropical convective regions over both the Pacific and Atlantic Oceans. Together with the results of chemical-transport models, our findings indicate that NPF persists at all longitudes as a global-scale band in the tropical upper troposphere, covering about 40% of the Earth’s surface. Furthermore, we find that this NPF in the tropical upper troposphere is a globally important source of CCN in the lower troposphere, where they can affect cloud properties. Our findings suggest that the production of CCN, as these new particles descend towards the surface, is currently not adequately captured in global models, because they tend to underestimate both the magnitude of tropical upper tropospheric NPF and the subsequent growth to CCN sizes. This has potential implications for cloud albedo and the global radiative balance.

Atmospheric chemistry↗

Global tropical cyclone precipitation scaling with sea surface temperature

Understanding the relationship between tropical cyclone (TC) precipitation and sea surface temperature (SST) is essential for both TC hazard forecasting and projecting how these hazards will change in the future due to climate change. This work untangles how global TC precipitation is impacted by present-day SST variability (known as apparent scaling) and by long-term changes in SST caused by climate change (known as climate scaling). A variety of datasets are used including precipitation and SST observations, realistic climate model simulations, and idealized climate model simulations. The apparent scaling rates depend on precipitation metric; examples shown here have ranges of 6.1 to 9.5% per K versus 5.9 to 9.8% per K for two different metrics. The climate scaling is estimated at about 5% per K, which is slightly less than the atmospheric moisture scaling based on thermodynamic principles of about 7% per K (i.e., the Clausius–Clapeyron scaling). The apparent scaling is greater than the climate scaling, which implies that the relationship between TC precipitation and present-day SST variability should not be used to project the long-term response of TC precipitation to climate change.

54 ENVIRONMENTAL SCIENCES↗

Disproportionate control on aerosol burden by light rain

Atmospheric aerosols are of great climatic and environmental importance due to their effects on the Earth’s radiative energy balance and air quality. Aerosol concentrations are strongly influenced by rainfall via wet removal. Global climate models have been used to quantify their climate and health effects. However, they commonly suffer from a well-known problem of ‘too much light rain and too little heavy rain’. The impact of simulated rainfall intensities on aerosol burden at the global scale is still unclear. In this study, we show that rainfall intensity has profound impacts on aerosol burden, and light rain has a disproportionate control on it. By improving the representation of convection, the light-rain (1–20 mm d –1 ) frequency in two state-of-the-art global climate models is reduced. As a result, the aerosol burden is increased globally, especially over the tropics and subtropics, by as much as 0.3 in aerosol optical depth in tropical rain belts. It is attributed to the dominant contribution of light rain to the accumulated wet removal by its frequent occurrence despite its weak intensity. The implication of these findings is that understanding the nature of aerosol scavenging by rainfall is critical to aerosol–climate interaction and its impact on climate.

54 ENVIRONMENTAL SCIENCES↗