Earth's Radiation Budget

Model Development and Analysis

These projects focus on improving existing models, identifying model uncertainties and gaps, and developing new modeling capabilities to better simulate and project SRM outcomes. As there is a range of scales associated with SRM processes, NOAA's ERB Program supports projects using a variety of models from global models to regional and cloud-resolving models to large eddy simulation (LES), along with multi-model and multi-ensemble frameworks, emulators built on artificial intelligence/machine learning (AI/ML) methods, and model intercomparisons.

Evaluating the baseline albedo conditions using satellite-based remote sensing and reanalysis.
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Using a variety of techniques to study the fundamentals of aerosol-cloud interactions.
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Project goals are: to (a) explore strategies for a number of different cloud targets over the course of a diurnal cycle, and for different perturbation durations; (b) expand our understanding of the frequency of occurrence, areal coverage, seasonality, and geographical location of susceptible clouds at the global scale.
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Assessed the current stage of MCB research and provided guidance for future research.
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Investigating the possible stratospheric impacts of increased soot emissions from a projected increase in the frequency of rocket launches that use kerosene burning engines; as well as modeling the radiative forcing, temperature, and circulation changes in the stratosphere due to increased aerosol loading from more frequent satellite reentry. Goals are to address significant gaps in our understanding of how projected increases in the space industry may impact middle atmosphere climate.
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Investigating multiple climate model simulations including large ensembles using different SAI strategies and scenarios as well as specially designed sensitivity experiments, with a focus on understanding uncertainties in the resulting changes in large-scale stratospheric and tropospheric circulation, stratospheric ozone, and surface climate. As the suite of available runs increase, in particular runs done under the auspices of GeoMIP and CCMI, these will also be analyzed for circulation changes and impacts on the ozone layer.
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Using and evaluating the Community Earth System Model Version 2 performance on the stratospheric background sulfate aerosol, large volcanic eruptions, including the January 2022 Hunga Tonga-Hunga Ha'apai volcano eruption, as well as simulating aerosol compositions in the Asian Tropopause Aerosol Layer and validating the simulations against many observations taken during the ACCLIP campaign. Co-leading the APARC Hunga Tonga assessment, including coordinating an international model intercomparison regarding the dynamical, radiative and chemical responses to the Hunga Tonga eruption.
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Further developed a data insertion technique to improve predictions of long range transport of a high altitude plume. The eruption of Hunga Tonga - Hunga Ha’apai was used as a case study and lidar measurements made at Reunion Island were used for verification. Continued work includes improving a method of estimating emissions from a volcanic eruption and devising a workflow which can provide timely emissions estimates to the modeling community.
Extended and improved on short-range (3-24 hour) forecasts of ash and sulfur dioxide for aviation to long-range forecasting up to 16 days and to investigate impacts of alternative mixing schemes, source term characterization, and resolution of mean wind fields and other meteorological data on the accuracy of predicted transport and dispersion of injected materials.
Developing and demonstrating an advanced cloud-resolving model (HRRR-Chem, ~3-10 km grid resolution) with enhanced capabilities, including fire emissions and plume rise, gas/aerosol chemistry, photolysis, turbulent mixing, dry/wet removal processes, and aerosol-radiation and aerosol-cloud interactions. Detailed, fine-scale modeling studies of wildfire smoke episodes will help quantify the radiative and cloud effects of extreme aerosol emissions from wildfires by leveraging observations from intensive field studies including FIREX-AQ.
Six competitive grant awards to improve the model representation of aerosols and their potential role in solar radiation modification. Grants were awarded to project teams at Colorado State University, Columbia University, Cornell University, Indiana University, National Center for Atmospheric Research (NCAR), and the University of Washington. Read more about the grant projects
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Evaluated the impacts of aerosols as implemented in shallow, congestus, and deep convective parameterizations as well as microphysics parameterizations and then compared results to observations during intensive field campaigns.
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Developed specialized modeling tools that tease apart the changes in the individual factors controlling the chemical sink of methane, including sunlight, temperature, and water vapor, with an emphasis on the responses to persistent changes in reflectivity.
Developed a methodology to quantify and map the past and future annual changes in the Earth's radiation budget using NOAA's global climate models, and explain the contributions to the changing solar, longwave, and net radiation budget of the Earth system from anthropogenic and natural drivers, and consequent feedbacks.
This project started with the inclusion of a sophisticated aerosol representation into a leading Earth System model, CESM, in order to enhance our understanding of atmospheric aerosol processes and resulting feedbacks to the climate system. Subsequently, CESM (versions 1 and 2) used to (a) explore the effects of climate change with and without SAI on regional climate and air quality; and, (b) perform MCB simulations in CESM2 in both the default setting and with the newly built machine-learning emulator for warm cloud processes.
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Used GFDL's AM4, nudged with reanalysis data, and NASA CERES-measured top-of-the-atmosphere radiative fluxes to study the influence of the pandemic-related aerosol emission reductions.
Used GFDL climate prediction system SPEAR, which is based on AM4/CM4, to assess how fast a robust signal on top-of-atmosphere radiative fluxes, surface temperature, and precipitation from ERB perturbations can be detected on the regional scale.
Implemented a prognostic scheme of stratospheric aerosols in GFDL's ESM4 for tracking their concentrations, microphysical processes, radiative properties and long-range transport after injection.
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Conducted a series of high-resolution model runs to test against observations to quantify how well the model reproduces unperturbed cloud fields and to test cloud responses to the addition of small sea salt aerosol representative of what would be used for intentional MCB. See the FY22-25 grant project that builds on this work.
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Improved the representation of aerosol-cloud interactions in models and use the improved models to advance our understanding of cloud brightening and its climate impacts.
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