Implementing neural network mixed-effects models in Template Model Builder (TMB)
本文通过使用Template Model Builder(TMB)实现神经网络混合效应模型(NMMs)，利用自动微分和拉普拉斯近似解决了现有方法需手动推导目标函数及梯度的问题，提高了模型的复杂性和准确性。
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Bridging short- and medium-range weather forecasting with machine learning
研究通过开发Nested-EAGLE模型，结合短中期天气预报，利用机器学习提高美国本土地区天气预测准确性。
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Social Cost of Greenhouse Gases -- OPTiMEM and the Heat Conjecture(s)
This study addresses the disconnect between climate science and economics by proposing a physically grounded framework for estimating the social cost of greenhouse gases (SCGHG). To this end, the authors develop OPTiMEM, a coupled physical–macroeconomic model that, for the first time, integrates an ocean heat content (OHC) physics module with macroeconomic analysis. The model simulates fossil fuel emissions, atmospheric CO₂ concentrations, surface warming, and oceanic heat uptake through a carbon-consumption-driven climate component, constrained by state-of-the-art radiative forcing equations and an energy production model. OPTiMEM successfully reproduces historical records of emissions, temperature, and OHC, offering a verifiable and physically consistent SCGHG assessment framework. This approach overcomes key limitations of conventional purely economic models and provides a robust scientific foundation for climate policy design.
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Implementing neural network mixed-effects models in Template Model Builder (TMB)
本文通过使用Template Model Builder(TMB)实现神经网络混合效应模型(NMMs)，利用自动微分和拉普拉斯近似解决了现有方法需手动推导目标函数及梯度的问题，提高了模型的复杂性和准确性。
0 citationsRead paper
Bridging short- and medium-range weather forecasting with machine learning
研究通过开发Nested-EAGLE模型，结合短中期天气预报，利用机器学习提高美国本土地区天气预测准确性。
0 citationsRead paper
Social Cost of Greenhouse Gases -- OPTiMEM and the Heat Conjecture(s)
This study addresses the disconnect between climate science and economics by proposing a physically grounded framework for estimating the social cost of greenhouse gases (SCGHG). To this end, the authors develop OPTiMEM, a coupled physical–macroeconomic model that, for the first time, integrates an ocean heat content (OHC) physics module with macroeconomic analysis. The model simulates fossil fuel emissions, atmospheric CO₂ concentrations, surface warming, and oceanic heat uptake through a carbon-consumption-driven climate component, constrained by state-of-the-art radiative forcing equations and an energy production model. OPTiMEM successfully reproduces historical records of emissions, temperature, and OHC, offering a verifiable and physically consistent SCGHG assessment framework. This approach overcomes key limitations of conventional purely economic models and provides a robust scientific foundation for climate policy design.
0 citationsRead paper