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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Long‐Term Impacts of Global Solid Biofuel Emissions on Ambient Air Quality and Human Health for 2000–2019

Globally, solid biofuels (SB) have been widely used for household cooking and energy production for decades due to electricity shortages and socio-economic barriers to adopting renewable energy alternatives. This has detrimental effects on air quality, human health, and climate through trace gas and aerosol emissions. Despite numerous studies, the long-term consequences of SB emissions remain poorly understood. Here, we use the Community Earth System Model and the Community Emissions Data System emission inventory to investigate the SB emission impacts on air quality and human health for 2000–2019. Global SB emission increased the ambient PM 2.5 (particulate matter with aerodynamic diameters ≤2.5 μm) and ozone (O 3 ) concentrations up to 23.61 μg/m 3 and 13.69 ppbv, with significant effects found in India, China, and the Rest of Asia (ROA). Our study estimates total annual premature deaths (APDs) associated with global SB-attributable PM 2.5 and O 3 exposure as 1.11 million [95% confidence interval (95% CI): 1.00–1.22 million] in 2000 up to 1.43 million (95% CI: 1.30–1.56 million) in 2019. China's SB emissions and associated APDs have reduced substantially, whereas India and ROA had a major leap in both estimates in 2019 compared to 2000. China's progress in cutting residential SB emissions accounts for its improvements. Our study urges the reduction of SB usage and emissions to potentially improve overall air quality and human health conditions, especially in highly populated, low- and middle-income countries, where the poor air quality and associated health burden attributable to SB emissions are estimated to be higher.

O 3↗
DOE OSTI2026

Model Sensitivities of Biomass-Burning Aerosol Chemical Aging, Sulfate Formation, and Cloud Droplet Activation in the Southeastern Atlantic Using CESM and E3SM

Biomass-burning smoke drives large uncertainty in climate projections of the Earth's radiative balance. This is due to the chemical and physical evolution of smoke and its impact on clouds and radiation. Here we focus on the southeastern Atlantic region and its inflow of African biomass-burning smoke during August 2017. We evaluate smoke properties and processes in two coupled earth-system models, the Energy Exascale Earth System Model (E3SM) and Community Earth System Model (CESM). These are compared against in situ aircraft observations from two field campaigns, ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) and CLoud–Aerosol–Radiation Interaction and Forcing: Year 2017 (CLARIFY-2017). Observations reveal an increase and subsequent decrease in smoke mean diameter, and a steady decrease in the mass ratio of organic aerosol (OA) to black carbon aerosol (BC) (OA:BC) over 4–12 days of aging, neither captured by the base models. Implementation of a photolytic loss scheme for secondary organic aerosol (SOA)—as a proxy for other heterogeneous volatilization chemistry—and a ∼1-day conversion for primary OA to SOA significantly improves the representation of this loss. In the boundary layer, both models show dimethyl sulfide driving a large increase in the sulfate aerosol mass fraction from the free troposphere, which is consistent with observations. Finally, models tend to underpredict cloud droplet number concentration partially due to weak modeled turbulent updraft strength, and model performance improves when the parameterized turbulent updraft strength is increased substantially. These results are expected to provide insights into future model development to reduce climate model uncertainties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Challenges and alternatives to empirical orthogonal functions for earth system data

Empirical orthogonal functions (EOFs) applied to gridded Earth system data enables users to diagnose modes of variability with relative ease. Yet, many challenges to interpretation exist such that they must be used with awareness and intention when applied to gridded climate data, especially with large ensembles. Utilizing data from two different Earth system modelling large ensemble frameworks, the Energy Exoscale Earth System Model and the Community Earth System Model, as well as reanalysis data, common EOF pitfalls are summarized and discussed. Challenges include erroneous mode swapping, sign flipping, and the temporal variability of the centers of action. For modes of variability with similar contribution to variance, mode swapping is not uncommon. Sign flipping can occur with almost any mode where the pattern is correct, but the sign is arbitrary. Although the variability of the center of action is not necessarily problematic, it potentially complicates interpretation over multi-century timescales. A wide variety of alternative methods to EOFs exist, but fitness-for-purpose must be evaluated. Additionally, illustrations of alternative methods and examples of proper use are provided. Alternative methods fit into three categories: EOF variants, linear methods, and multilinear methods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The Essential Role of Westerly Wind Bursts in ENSO Dynamics and Extreme Events Quantified in Model “Wind Stress Shaving” Experiments

Abstract Westerly wind bursts (WWBs)—brief but strong westerly wind anomalies in the equatorial Pacific—are believed to play an important role in El Niño–Southern Oscillation (ENSO) dynamics, but quantifying their effects is challenging. Here, we investigate the cumulative effects of WWBs on ENSO characteristics, including the occurrence of extreme El Niño events, via modified coupled model experiments within Community Earth System Model (CESM1) in which we progressively reduce the impacts of wind stress anomalies associated with model-generated WWBs. In these “wind stress shaving” experiments we limit momentum transfer from the atmosphere to the ocean above a preset threshold, thus “shaving off” wind bursts. To reduce the tropical Pacific mean state drift, both westerly and easterly wind bursts are removed, although the changes are dominated by WWB reduction. As we impose progressively stronger thresholds, both ENSO amplitude and the frequency of extreme El Niño decrease, and ENSO becomes less asymmetric. The warming center of El Niño shifts westward, indicating less frequent and weaker eastern Pacific (EP) El Niño events. Removing most wind burst–related wind stress anomalies reduces ENSO mean amplitude by 22%. The essential role of WWBs in the development of extreme El Niño events is highlighted by the suppressed eastward migration of the western Pacific warm pool and hence a weaker Bjerknes feedback under wind shaving. Overall, our results reaffirm the importance of WWBs in shaping the characteristics of ENSO and its extreme events and imply that WWB changes with global warming could influence future ENSO.

Meteorology & Atmospheric Sciences↗
DOE OSTI2023

Community Solar Program Design and Subscription Models

This slide deck provides an overview of community solar program design and subscription models. It introduces and explains the different elements of community solar program and subscription design, and proves proven practices and considerations when designing a community solar program. This slide deck was originally developed as part of a working group under the National Community Solar Partnership's Municipal Utility Collaborative.

community solar↗
DOE OSTI2020

Reaching 1.5 and 2.0 °C global surface temperature targets using stratospheric aerosol geoengineering

A new set of stratospheric aerosol geoengineering (SAG) model experiments has been performed with Community Earth System Model version 2 (CESM2) with the Whole Atmosphere Community Climate Model (WACCM6) that are based on the Coupled Model Intercomparison Project phase 6 (CMIP6) overshoot scenario (SSP5-34-OS) as a baseline scenario to limit global warming to 1.5 or 2.0 °C above 1850–1900 conditions. The overshoot scenario allows us to applying a peak-shaving scenario that reduces the needed duration and amount of SAG application compared to a high forcing scenario. In addition, a feedback algorithm identifies the needed amount of sulfur dioxide injections in the stratosphere at four pre-defined latitudes, 30 °N, 15 °N, 15 °S, and 30 °S, to reach three surface temperature targets: global mean temperature, and interhemispheric and pole-to-Equator temperature gradients. These targets further help to reduce side effects, including overcooling in the tropics, warming of high latitudes, and large shifts in precipitation patterns. These experiments are therefore relevant for investigating the impacts on society and ecosystems. Comparisons to SAG simulations based on a high emission pathway baseline scenario (SSP5-85) are also performed to investigate the dependency of impacts using different injection amounts to offset surface warming by SAG. We find that changes from present-day conditions around 2020 in some variables depend strongly on the defined temperature target (1.5 °C vs. 2.0 °C). These include surface air temperature and related impacts, the Atlantic Meridional Overturning Circulation, which impacts ocean net primary productivity, and changes in ice sheet surface mass balance, which impacts sea level rise. Others, including global precipitation changes and the recovery of the Antarctic ozone hole, depend strongly on the amount of SAG application. Furthermore, land net primary productivity as well as ocean acidification depend mostly on the global atmospheric CO 2 concentration and therefore the baseline scenario. Multi-model comparisons of experiments that include strong mitigation and carbon dioxide removal with some SAG application are proposed to assess the robustness of impacts on societies and ecosystems.

42 ENGINEERING↗
DOE OSTI2025

Collaborative Proposal: Improving understanding of the internal structure and dynamics of deep convection using ARM observations and large eddy simulations

Recent observational and large eddy simulation (LES) modeling studies have nearly unanimously supported the view of deep cumulus convection being composed of a series of quasi-spherical bubbles of buoyant air, known as moist thermals. Despite the prevalence of moist thermals in deep convection, a comprehensive theory for the dynamics of these structures is lacking. Most current conceptual models for cumulus convection are based on canonical scaling theories for dry thermals or plumes; however, there is considerable evidence that the behavior of moist thermals differs markedly from these theories. Furthermore, the theoretical basis for most cumulus parameterizations originates from the plume conceptual model, and therefore these parameterizations are inconsistent with the real structure of moist convection. Motivated by the aforementioned knowledge gaps, this “end-to-end” research effort use theory, observations, numerical simulations, and direct improvements to the Zhang-McFarlane (ZM) convection scheme in the global climate Community Atmosphere Model (CAM) to address the following research questions: What key environmental parameters determine whether or not shallow convection will transition into deep convection, in the context of thermal-like updrafts? What factors regulate the size of thermals within cumulus updrafts? How does vertical wind shear influence thermal behavior, and as a consequence, vertical velocity and mass flux profiles and the shallow-to-deep convective transition? What are the critical processes that determine updraft vertical velocities and their connection to the vertical mass flux profile for thermal-like updrafts? Idealized LES modeling will be used in conjunction with theoretical models for the core properties of thermal-like updrafts to better understand key processes that regulate thermal ascent rates and entrainment properties. Thermal-tracking procedures will be used to characterize the behavior of thermals within the LES, and recently developed direct measures of entrainment and detrainment will be used to quantify entrainment/detrainment rates. Building from these results, we will analyze the structure of moist thermals from hemispheric range-height indicator scans taken during the Atmospheric Radiation Measurement Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign, and from “real case” LES of CACTI events. This combined modeling and observational analysis will provide essential validation for the existing body of research on moist thermal dynamics, which is based primarily on modeling studies. With the insight gained from the aforementioned activities, we will modify the Zhang-McFarlane convection scheme to improve its representation of updraft vertical velocity and entrainment rate profiles. These process-level changes will be tested in the Community Atmosphere Model to assess the impact on global climate simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Climate impacts in scenarios: time to close the loop?

Reaching a full understanding of the consequences of climate change for society and ecosystems, and the ensuing needs for adaptation, requires a consideration of the interactions between human and Earth systems. Currently, however, climate research largely separates the influence of society on climate from the influence of climate on society; that is, it doesn’t “close the loop.” A primary example of this approach is the generation and use of earth system model (ESM) simulations in the climate change research community. Large-scale socio-economic models, known as integrated assessment models (IAMs), are used to project emissions and land use change which serve as input to ESMs. ESM projections then serve as input to models of impacts on society and ecosystems. But, according to this modeling chain, those impacts do not affect the emissions and land use that drove the ESMs in the first place. Previous work has not drawn firm conclusions on whether this feedback would be large enough to warrant explicitly accounting for it. Two prominent possibilities, however, are that emissions and land use scenarios representing the high and low ends of the plausible range of future climate change are both too extreme. The high-end scenario may miss damaging impacts that would reduce economic activity, and therefore emissions, while the low-end scenario may ignore climate feedbacks that would make large-scale land-based carbon removal ineffective and therefore would hamper mitigation at the level assumed by the scenario. In this piece, we identify the opportunities and challenges that implementing such feedback loops would face. We argue that recent developments in climate impact research, human system modeling and ESM emulation make the time ripe to use IAMs in a structured model intercomparison exercise. Model intercomparison projects have benefitted the climate modeling community for decade snow, and more recently have also benefitted the impact modeling community. An IAM intercomparison focused on integrating impacts could make large strides in testing the implications of these feedbacks and assessing whether closing the loop would fundamentally change our outlook on future climate changes and their consequences.

Tebaldi, Claudia↗
DOE OSTI2023

Modeling of a Networked Community Microgrid with High Solar Penetration Considering Control Dynamics of Inverter-Based Resources

Microgrids help facilitate the integration of renewable energy in distribution-level grids and increase the resilience of the electric grid to extreme weather, especially in rural areas. Compared to traditional microgrids, a networked microgrid leverages multiple grid-forming sources to form a potential meshed grid and is more flexible in operation. This paper demonstrates the simulation modeling of an actual networked microgrid located in Adjuntas, Puerto Rico. The model contains representations of power inverters that connect the battery energy storage systems and photovoltaic generation systems to the networked microgrid and is capable of simulating fast grid transients as well as long-term operation of the networked microgrid. The modeling technique for power inverters allows the time-efficient simulation of the microgrid with a minimal penalty on model accuracy.

Li, Dingrui↗
DOE OSTI2021

Impact of vegetation physiology and phenology on watershed hydrology in a semiarid watershed in the Pacific Northwest in a changing climate

Concurrent with changes in climate conditions, increases in atmospheric composition and transport can affect land surface processes by regulating physiological and phenological responses of plants, and consequently perturb water, carbon, and nitrogen (N) dynamics at multiple scales. Howerver, the relationships bwtween plants physiological and phenological and land surface processes in a changing climate are less well known due to the limitation of representing palnts properties in traditional hydrological models. In this study, we use the Community Land Model version 5 (CLM5) to investigate how projected changes in large scale atmospheric conditions can affect hydrologic and biogeochemical dynamics in the Upper Columbia-Priest Rapids (UCPR) watershed, a typical semi-arid watershed located in the north-western United States dominated by croplands. Six numerical experiments considering climate change, CO2 concentration, and N deposition consistent with the Representative Concentration Pathways (RCPs) 4.5 and 8.5 are performed at 1-km resolution over the period of 2015-2099. Our results show that, compared with historical results (1985-2014), the elevated CO2 directly increases plants N uptake rates that provide additional leaf N to enhance photosynthesis by the end of 21st century (2070-2099). The higher GPP leads to changes in stomatal resistance and increased leaf area index (LAI) that affect evaporatranspiration (ET) and its components. As a result of stomatal responses to a higher CO2 concentration, ET over corn fields declines by 24.6 mm yr-1 under RCP4.5, and by 64.0 mm yr-1 under RCP8.5, respectively by the end of the century from its historical mean of 428 mm yr-1. Meanwhile, ET over soybean fields increases by 27.7 mm yr-1 under RCP4.5 and 9.98 mm yr-1 under RCP8.5 from its historical mean of 507 mm yr-1 as a result of CO2 fertilization as soybeans are able to uptake more N to increase LAI significantly. Furtherfore, the changes in physiological and phenological in corn and soybean can strongly modulate water budget terms over the watershed in response to expected changes in greenhouse gas concentrations and atmospheric composition. Additionally, increases in CO2 concentration and N deposition are beneficial for improving water use efficiency of corn and soybean, therefore lead to less water consumption per unit gram of carbon produced from these crops. Our study elucidates the need to jointly consider effects of surface climate and atmospheric composition and transport in understanding and predicting watershed hydrologic and biogeochemical responses, especially for an agricultural watershed.

Zhu, Bowen↗
DOE OSTI2025

Influence of Lake Ice Biases in Reanalysis Data on Downscaled Climate Simulations over the Great Lakes Region

This data package contains observation-based and model-simulated datasets (all provided in NetCDF format) for evaluating how wintertime lake-ice representation affects regional weather and climate over the Laurentian Great Lakes (freshwater lake ecosystem) during the high–ice-cover winter of 2009. The observational component includes: (1) Stage IV gridded precipitation at 4 km, hourly resolution for January–February 2009 over the Great Lakes region (radar–gauge multisensor precipitation analyses); (2) Great Lakes Surface Environmental Analysis (GLSEA) satellite-derived lake-ice coverage at 1.3 km, daily resolution for the 2009 winter months, providing ice coverage over Lakes Superior, Michigan, Huron, Erie, and Ontario; and (3) in situ measurements at the Standard Rock site on Lake Superior from the Great Lakes Evaporation Network (GLEN) at hourly resolution, including near-surface atmospheric variables and sensible and latent heat fluxes (air–lake exchange) at a fixed point location. The modeling component provides corresponding fields from two simulations, both archived at 4 km, hourly resolution: a standalone Weather Research Forecasting model (WRF) run driven by the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA5), and a two-way coupled model using WRF and the Finite Volume Community Ocean Model (WRF-FVCOM, a 3-D hydrodynamic lake model). These outputs include variables relevant to air–lake interaction and lake-effect processes (e.g., near-surface temperature, humidity, wind, precipitation, and surface turbulent fluxes), enabling direct comparison with the observational datasets. Users can analyze and visualize these NetCDF files with common tools such as Python (e.g., xarray, netCDF4, numpy, pandas), NCO/CDO, Panoply, or ncview; NetCDF variables can also be converted to other formats (e.g., CSV, GeoTIFF) using these utilities.

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATU↗
DOE OSTI2021

How can biosphere models simulate enough vegetation biomass in the mountains of the western United States? Implications of meteorological forcing

Most carbon stocks and fluxes in the western United States are found in mountainous terrain, where observations and modeling are difficult. Terrestrial biosphere models generally underestimate above-ground biomass (AGB) over this region. In this report, we identify methods to reduce this underestimation by focusing upon 1) biases in meteorological datasets, 2) model representation of water stress, and 3) spatial resolution. We adopted the widely-used Community Land Model version 4.5 (CLM 4.5) with six different meteorological datasets and found a 6-fold variation in simulated AGB across Utah/Colorado. Simulations underestimated AGB because of warm and dry biases within the meteorological datasets that reduced water availability and restricted plant growth. To eliminate the AGB underestimation we adopted a meteorological dataset designed for complex terrain (gridMET), combined with a representation of plant hydraulic stress (CLM 5.0). Conversely, changes in spatial resolution (meteorological variables and land surface description) had negligible impact on simulated AGB.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The sum is greater than the parts: exploiting microbial communities to achieve complex functions

We report multi-species microbial communities are ubiquitous in nature. The widespread prevalence of these communities is due to highly elaborated interactions among their members thereby accomplishing metabolic functions that are unattainable by individual members alone. Harnessing these communal capabilities is an emerging field in biotechnology. The rational intervention of microbial communities for the purpose of improved function has been facilitated in part by developments in multi-omics approaches, synthetic biology, and computational methods. Recent studies have demonstrated the benefits of rational interventions to human and animal health as well as agricultural productivity. Emergent technologies, such as in situ modification of complex microbial community and community metabolic modeling, represent an avenue to engineer sustainable microbial communities. In this opinion, we review relevant computational and experimental approaches to study and engineer microbial communities and discuss their potential for biotechnological applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Evaluation of OpenAI Codex for HPC Parallel Programming Models Kernel Generation

We evaluate AI-assisted generative capabilities on fundamental numerical kernels in high-performance computing (HPC), including AXPY, GEMV, GEMM, SpMV, Jacobi Stencil, and CG. We test the generated kernel codes for a variety of language-supported programming models, including (1) C++ (e.g., OpenMP [including offload], OpenACC, Kokkos, SyCL, CUDA, and HIP), (2) Fortran (e.g., OpenMP [including offload] and OpenACC), (3) Python (e.g., numpy, Numba, cuPy, and pyCUDA), and (4) Julia (e.g., Threads, CUDA.jl, AMDGPU.jl, and KernelAbstractions.jl). We use the GitHub Copilot capabilities powered by the GPT-based OpenAI Codex available in Visual Studio Code as of April 2023 to generate a vast amount of implementations given simple + + prompt variants. To quantify and compare the results, we propose a proficiency metric around the initial 10 suggestions given for each prompt. Results suggest that the OpenAI Codex outputs for C++ correlate with the adoption and maturity of programming models. For example, OpenMP and CUDA score really high, whereas HIP is still lacking. We found that prompts from either a targeted language such as Fortran or the more general purpose Python can benefit from adding code keywords, while Julia prompts perform acceptably well for its mature programming models (e.g., Threads and CUDA.jl). We expect for these benchmarks to provide a point of reference for each programming model's community. Overall, understanding the convergence of large language models, AI, and HPC is crucial due to its rapidly evolving nature and how it is redefining human-computer interactions.

Godoy, William↗
DOE OSTI2020

Evaluation of Mesoscale Convective Systems in Climate Simulations: Methodological Development and Results from MPAS-CAM over the U.S.

In this study, a process-oriented approach is developed to evaluate warm-season mesoscale convective system (MCS) precipitation and their favorable large-scale meteorological patterns (FLSMPs) over the U.S. This approach features a novel observation-driven MCS-tracking algorithm using infrared brightness temperature and precipitation feature at 12, 25 and 50 km resolution and metrics to evaluate the model large-scale environment favorable for MCS initiation. The tracking algorithm successfully reproduces the observed MCS statistics from a reference 4-km radar MCS database. To demonstrate the utility of the new methodologies in evaluating MCS in climate simulations with mesoscale resolution, the process-oriented approach is applied to two climate simulations produced by the Variable-Resolution Model for Prediction Across Scales coupled to the Community Atmosphere Model physics, with refined horizontal grid spacing at 50 km and 25 km over North America. With the tracking algorithm applied to simulations and observations at equivalent resolutions, the simulated number of MCS and associated precipitation amount, frequency and intensity are found to be consistently underestimated in the Central U.S., particularly from May to August. The simulated MCS precipitation shows little diurnal variation and lasts too long, while MCS precipitation area is too large and intensity is too weak. The model is able to simulate four types of observed FLSMP associated with frontal systems and low-level jets (LLJ) in spring, but the frequencies are underestimated because of low-level dry bias and weaker LLJ. Precipitation simulated under different FLSMPs peak during daytime, in contrast to the observed nocturnal peak. Implications of these findings for future model development and diagnostics are discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A Multi-variable, Multi-value Hydrodynamic Modeling Approach to Support Marine Energy and Coastal Resilience Applications

Funded by the Marine Energy Seedling Laboratory Program, the study reported on here aimed to develop a multi-variable, multi-value hydrodynamic modeling approach based on the Finite-Volume Community Ocean Model (FVCOM) to support a wide range of marine renewable energy and coastal resilience applications. We migrated the marine hydrokinetic energy module to simulate tidal energy extraction by tidal turbines under wave-current interactions. We explored the particle tracking module in FVCOM and applied it to Sequim Bay, Washington, to illustrate the surface current field and mimic the pollutant transport near the surface. A tracer-water age module was added to FVCOM to examine water exchange through the entrance. Lastly, a user-specified vertical coordinate option was added to FVCOM to improve simulation of the effect of floating turbines on surface currents and scalar transport. The above-described model development has been tested using a simplified model domain and demonstrated in real-world coastal systems. The outcome of this project will provide a useful modeling code and approach for marine renewable energy and coastal resilience research and applications.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

FACETS Dynamical Downscaling Simulations over North America by the CAM-MPAS Variable-Resolution Model

Comprehensive assessment of climate datasets created by statistical or dynamical models is important for effectively communicating model projection and associated uncertainty to stakeholders and decision-makers. The Department of Energy FACETS project aims to foster such communication through development of metrics and their demonstration on a hierarchy of downscaled climate datasets to quantify aspects of climate change projections that are credible, particularly for supporting decisions related to the energy-water-land nexus. As a part of this effort, we have produced a regional climate dataset using the Model for Prediction Across Scales coupled to the Community Atmosphere Model (CAM-MPAS). This global modeling framework is configured with variable-resolution meshes featuring higher resolutions over North America, as well as quasi-uniform resolution meshes across the globe. The variable-resolution configurations allow fine-scale features to be better resolved inside the refinement and interact with global-scale circulations. The dataset includes multiple uniform- (240km and 120km) and variable-resolution (200-50km, 100-25km, and 46-12km) simulations that are designed to be compatible with other regional climate simulations that contribute to the hierarchy of downscaled climate datasets of the project. Furthermore, the dataset consists of simulations for both the present-day (1989-2010) and future (2079-2100) climate and post-processing of the model output has been coordinated across the project for consistency to facilitate common analysis across the hierarchy of datasets. Altogether, this CAM-MPAS model dataset provides a unique opportunity to assess the influence of resolutions and modeling framework on model credibility and climate change projection.

Sakaguchi, Koichi↗
DOE OSTI2021

Radiative Forcing of Nitrate Aerosols From 1975 to 2010 as Simulated by MOSAIC Module in CESM2-MAM4

In this work, we incorporate the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) module in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model Version 6 with interactive chemistry (CAM6-chem), and couple it with the four mode version of the Modal Aerosol Module (MAM4). The MOSAIC module is used to simulate the thermodynamics of the gas-aerosol mass exchange, with a special focus on simulating nitrate aerosol. By comparing against ground and satellite observations, we found that the MOSAIC/MAM4 scheme performs reasonably well in simulating spatiotemporal distributions of aerosols, including nitrate aerosol. We conducted a series of model experiments with and without nitrate aerosols, and examined the radiative effect (RE) associated with nitrate aerosols in 1975, 2000, and 2010, and accessed the radiative forcing (RF) of nitrate aerosols between the present day and pre-industrial periods. Comparing with the nitrate aerosol RE, we predicted relatively small RF of anthropogenic nitrate aerosol from aerosol-radiation interactions (RF ari : -0.014 W m -2 ) and large RF from aerosol-cloud interactions (RF aci : -0.219 W m -2 ). Regional signatures of nitrate RE/RF are noticeable and important: for instance, very small changes in RE ari in Europe and USA, but 2.8–3 times increases in RE ari in India and China from 1975 to 2010, while RE aci /RF aci in China is a warming effect due to the competing effect between sulfate and nitrate aerosols as cloud condensation nuclei.

54 ENVIRONMENTAL SCIENCES↗