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1. Scenarios for modeling solar radiation modification

   https://doi.org/10.1073/pnas.2202230119  

   MacMartin, D. G.; Visioni, D.; Kravitz, B.; Richter, J.H.; Felgenhauer, T.; Lee, W. R.; Morrow, D. R.; Parson, E. A.; Sugiyama, M. (August 2022, Proceedings of the National Academy of Sciences)

   Making informed future decisions about solar radiation modification (SRM; also known as solar geoengineering)—approaches such as stratospheric aerosol injection (SAI) that would cool the climate by reflecting sunlight—requires projections of the climate response and associated human and ecosystem impacts. These projections, in turn, will rely on simulations with global climate models. As with climate-change projections, these simulations need to adequately span a range of possible futures, describing different choices, such as start date and temperature target, as well as risks, such as termination or interruptions. SRM modeling simulations to date typically consider only a single scenario, often with some unrealistic or arbitrarily chosen elements (such as starting deployment in 2020), and have often been chosen based on scientific rather than policy-relevant considerations (e.g., choosing quite substantial cooling specifically to achieve a bigger response). This limits the ability to compare risks both between SRM and non-SRM scenarios and between different SRM scenarios. To address this gap, we begin by outlining some general considerations on scenario design for SRM. We then describe a specific set of scenarios to capture a range of possible policy choices and uncertainties and present corresponding SAI simulations intended for broad community use. 

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2. A Dynamics of Surface Temperature Forced by Solar Radiation

   https://doi.org/10.1029/2022GL101222  

   Jing, Weiqiang; Wang, Jingfeng (January 2023, Geophysical Research Letters)

   Abstract Due to lack of a unified description of the Earth surface temperature, a generic dynamic equation is postulated as an inference from the special case of snow. Solar radiation is explicitly included in the formulation for transparent media such as snow, ice and water while implicitly through (conductive) surface heat flux for non‐transparent media such as soil. The physical parameters of the equation are medium thermal inertia, thermal and radiative diffusivity. The equation for transparent media reduces to the familiar force‐restore model of soil surface temperature when the penetration depth of solar radiation tends to zero. Proof‐of‐concept validation for snow surface temperature as a paradigm of transparent media at three sites in the Arctic and Antarctica confirms the postulated equation as a generic description of the dynamics of surface temperature. 

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3. Prediction of Solar Radiation Based on Spatial and Temporal Embeddings for Solar Generation Forecast

   https://doi.org/10.24251/HICSS.2020.363  

   Alqudah, Mohammad; Dokic, Tatjana; Kezunovic, Mladen; Obradovic, Zoran. (January 2020, Proceedings of the Hawaii International Conference on System Sciences)

   Abstract A novel method for real-time solar generation forecast using weather data, while exploiting both spatial and temporal structural dependencies is proposed. The network observed over time is projected to a lower-dimensional representation where a variety of weather measurements are used to train a structured regression model while weather forecast is used at the inference stage. Experiments were conducted at 288 locations in the San Antonio, TX area on obtained from the National Solar Radiation Database. The model predicts solar irradiance with a good accuracy (R2 0.91 for the summer, 0.85 for the winter, and 0.89 for the global model). The best accuracy was obtained by the Random Forest Regressor. Multiple experiments were conducted to characterize influence of missing data and different time horizons providing evidence that the new algorithm is robust for data missing not only completely at random but also when the mechanism is spatial, and temporal. 

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4. Deep learning based solar radiation micro forecast by fusion of infrared cloud images and radiation data

   https://doi.org/10.1016/j.apenergy.2021.117014  

   Ajith, Meenu; Martínez-Ramón, Manel (July 2021, Applied Energy)

   null (Ed.)
5. Reconstruction of narrowband solar radiation for enhanced spectral selectivity in building-integrated solar energy simulations

   https://doi.org/10.1016/j.renene.2023.119554  

   Chen, Chenshun; Duan, Qiuhua; Feng, Yanxiao; Wang, Julian; Ghaeili_Ardabili, Neda; Wang, Nan; Hosseini, Seyed Morteza; Shen, Chao (December 2023, Renewable Energy)