Therefore, creating a predictive model for global solar radiation is crucial for ensuring optimal energy dispatch and management practices [6].
This project proposes using machine learning to optimize uncertain parameters within these climate models to help produce worst-case SRM outcomes.
In this study, a comprehensive evaluation of nine ensemble learning algorithms (ELAs) was performed to estimate solar radiation in Santo Domingo with a 1 min
Modeling of solar radiation management: a comparison of simulations using reduced solar constant and stratospheric sulphate aerosols. Kalidindi, Sirisha; Bala,
This paper explores solar irradiance forecasting as a machine-learning problem. We utilize data from Izmir, Turkey, over a period spanning three years.
This briefing explores the potential consequences of using Solar Radiation. Management (SRM) – a form of geoengineering being considered by some governments to
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**Solar Radiation Modification (SRM) refers to deliberate, large-scale actions intended to decrease global average surface temperatures by increasing the reflection of sunlight away from the Earth.** Proposed SRM methods involve the use of aerosols (small particles) or other materials to increase the reflectivity of the atmosphere, clouds, or Earth’s surface. **Long-term protection of Earth’s climate and oceans requires substantial reductions in emissions and atmospheric concentrations of CO2 and other GHGs. SRM is not considered a substitute for climate mitigation efforts, which include decarbonization and GHG emission cuts.** SRM research is being conducted as a response to growing concerns that the pace of CO2 emissions reductions and CDR technology development is not sufficient to avoid severe impacts of climate change in the next decades. **Many of the processes most important for understanding SRM approaches—such as those that control the formation of clouds and aerosols—are among the most uncertain components of the climate system.** Climate models differ in simulating large-scale aerosol climate effects, including on surface temperatures, due to variations in how aerosol processes, atmospheric transport and mixing, and physics are represented.