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Wagman, Benjamin

Publications and source records attributed to Wagman, Benjamin.

15 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

E3SMFC

SAND2025-01123O E3SMFC is a software tool that integrates a feedback controller algorithm into the E3SM climate model to regulate sulfur dioxide injection, aiming to achieve specific climate outcomes. The program uses proportional-integral-derivative feedback control to adjusts sulfur dioxide levels in both spatial and temporal dimensions. It will only operate on computers that can run the DOE climate model E3SM. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Ojetola, Samuel↗
DOE OSTI2024

CLDERA-E3SM

SAND2025-03846O CLDERA-E3SM enhances the E3SMv2 model by adding new options such as complete stratospheric volcanic aerosol representation and idealized physics model configuration for the atmosphere component. CLDERA-E3SM also allows for aerosol source emission specification, which is a powerful method for tracking aerosol and its climate impacts in E3SMv2. This new code better represents stratospheric sulfate aerosol and includes modifications such as changes to the default aerosol size distributions and to stratospheric aerosol microphysical treatment, which allows stratospheric sulfate aerosol to grow larger than in the default E3SMv2. New aerosol source tagging can be customized to separate the global emission of select aerosol tracers—such as sulfate, black carbon, and organic carbon aerosol—into a new, user specified list of sources. It also includes idealized simulations of the atmosphere and volcanic aerosol tracers. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Hillman, Benjamin↗
DOE OSTI2024

Validating a microphysical prognostic stratospheric aerosol implementation in E3SMv2 using observations after the Mount Pinatubo eruption

Abstract. This paper describes the addition of a stratospheric prognostic aerosol (SPA) capability – developed with the goal of accurately simulating sulfate aerosol formation and evolution in the stratosphere – in the Department of Energy (DOE) Energy Exascale Earth System Model, version 2 (E3SMv2). The implementation includes changes to the four-mode Modal Aerosol Module microphysics in the stratosphere to allow for larger particle growth and more accurate stratospheric aerosol lifetime following the Pinatubo eruption. E3SMv2-SPA reasonably reproduces stratospheric aerosol lifetime, burden, aerosol optical depth, and top-of-atmosphere flux when compared to remote sensing observations. E3SMv2-SPA also has close agreement with the interactive chemistry–climate model CESM2-WACCM (Community Earth System Model version 2–Whole Atmosphere Community Climate Model) – which has a more complete chemical treatment – and the observationally constrained, prescribed volcanic aerosol treatment in E3SMv2. Global stratospheric aerosol size distributions identify the nucleation and growth of sulfate aerosol from volcanically injected SO2 from both major and minor volcanic eruptions from 1991 to 1993. The modeled aerosol effective radius is consistently lower than satellite and in situ measurements (max differences of ∼ 30 %). Comparisons with in situ size distribution samples indicate that this simulated underestimation in both E3SMv2-SPA and CESM2-WACCM is due to overly small accumulation and coarse-mode aerosols 6–18 months post-eruption, with E3SMv2-SPA simulating ∼ 50 % of the coarse-mode geometric mean diameters of observations 11 months post-eruption. Effective radii from the models and observations are used to calculate offline scattering and absorption efficiencies to explore the implications of smaller simulated aerosol size for the Pinatubo climate impacts. Scattering efficiencies at wavelengths of peak solar irradiance (∼ 0.5 µm) are 10 %–80 % higher for daily samples in models relative to observations through 1993, suggesting higher diffuse radiation at the surface and a larger cooling effect in the models due to the smaller simulated aerosol; absorption efficiencies at the peak wavelengths of outgoing terrestrial radiation (∼ 10 µm) are 15 %–40 % lower for daily samples in models relative to observations, suggesting an underestimation in stratospheric heating in the models due to the smaller simulated aerosol. These potential biases are based on aerosol size alone and do not take into account differences in the aerosol number. The overall agreement of E3SMv2-SPA with observations and its similar performance to the well-validated CESM2-WACCM makes E3SMv2-SPA a viable alternative to simulating climate impacts from stratospheric sulfate aerosols.

Brown, Hunter York (ORCID:0000000218147874)↗
DOE OSTI2023

Performance assessment for climate intervention (PACI): preliminary application to a stratospheric aerosol injection scenario

As the prospect of exceeding global temperature targets set forth in the Paris Agreement becomes more likely, methods of climate intervention are increasingly being explored. With this increased interest there is a need for an assessment process to understand the range of impacts across different scenarios against a set of performance goals in order to support policy decisions. The methodology and tools developed for Performance Assessment (PA) for nuclear waste repositories shares many similarities with the needs and requirements for a framework for climate intervention. Using PA, we outline and test an evaluation framework for climate intervention, called Performance Assessment for Climate Intervention (PACI) with a focus on Stratospheric Aerosol Injection (SAI). We define a set of key technical components for the example PACI framework which include identifying performance goals, the extent of the system, and identifying which features, events, and processes are relevant and impactful to calculating model output for the system given the performance goals. Having identified a set of performance goals, the performance of the system, including uncertainty, can then be evaluated against these goals. Using the Geoengineering Large Ensemble (GLENS) scenario, we develop a set of performance goals for monthly temperature, precipitation, drought index, soil water, solar flux, and surface runoff. The assessment assumes that targets may be framed in the context of risk-risk via a risk ratio, or the ratio of the risk of exceeding the performance goal for the SAI scenario against the risk of exceeding the performance goal for the emissions scenario. From regional responses, across multiple climate variables, it is then possible to assess which pathway carries lower risk relative to the goals. The assessment is not comprehensive but rather a demonstration of the evaluation of an SAI scenario. Future work is needed to develop a more complete assessment that would provide additional simulations to cover parametric and aleatory uncertainty and enable a deeper understanding of impacts, informed scenario selection, and allow further refinements to the approach.

climate intervention↗
DOE OSTI2021

Automated Custom Calibration for E3SM

Focal Area(s): Automated custom calibration for the Energy Exascale Earth System Model (E3SM) applies primarily to focal area 2: Predictive modeling through the use of AI techniques, and includes elements of focal area 3: Insight gleaned from complex data (both observed and simulated).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Climate Intervention Assessment and Attribution

Focal Area(s): To ensure the US is positioned to scientifically attribute noncooperative climate interventions, we propose developing a foundational analytical framework for increased confidence in the assessment and attribution of observed changes in the climate. This framework will enable probabilistic attribution of prospective climate interventions. The target is to glean insight from complex Earth system data (Focal Area 3) by using AI to develop a prediction system comprised of a hierarchy of models (Focal Area 2).

54 ENVIRONMENTAL SCIENCES↗