Deep learning for creating surrogate models of precipitation in Earth system models

Theodore Weber; Austin Corotan; Brian Hutchinson; Ben Kravitz; Robert Link DOI: https://doi.org/10.5194/acp-20-2303-2020 Abstract: We investigate techniques for using deep neural networks to produce surrogate models for short-term climate forecasts. A convolutional neural network is trained on 97 years of monthly precipitation output from the 1pctCO2 run (the CO2 concentration increases by 1 %…

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Future western U.S. building electricity consumption in response to climate and population drivers: A comparative study of the impact of model structure

Casey D. Burleyson, Gokul Iyer, Mohamad Hejazi, Sonny Kim, Page Kyle, Jennie S. Rice, Amanda D. Smith, Z. Todd Taylor, Nathalie Voisin, Yulong Xie DOI: https://doi.org/10.1016/j.energy.2020.118312 Abstract: Projections of building electricity consumption are used in multiple fields and for a variety of purposes, from energy utility investment decisions to global…

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Impact of climate change on water availability and its propagation through the Western U.S. power grid

Nathalie Voisin, Ana Dyreson, Tao Fu, Matt O’Connell, Sean W.D. Turner, Tian Zhou, Jordan Macknick DOI: https://doi.org/10.1016/j.apenergy.2020.115467 Abstract: Climate change is expected to affect the availability of water for electricity generation, yet the propagation of climate impacts across a large and diverse power grid remains unexplored. In this study, we…

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Can exploratory modeling of water scarcity vulnerabilities and robustness be scenario neutral?

J. D. Quinn, A. Hadjimichael, P. M. Reed, S. Steinschneider DOI: https://doi.org/10.1029/2020EF001650 Abstract:Planning under deep uncertainty, when probabilistic characterizations of the future are unknown, is a major challenge in water resources management. Many planning frameworks advocate for “scenario‐neutral” analyses in which alternative policies are evaluated over plausible future scenarios with…

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U.S. State-level Projections of the Spatial Distribution of Population Consistent with Shared Socioeconomic Pathways

Hamidreza Zoraghein and Brian C. O’Neill DOI: https://doi.org/10.3390/su12083374 Abstract: Spatial population distribution is an important determinant of both drivers of regional environmental change and exposure and vulnerability to it. Spatial projections of population must account for changes in aggregate population, urbanization, and spatial patterns of development, while accounting for uncertainty…

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Metis – A Tool to Harmonize and Analyze Multi-Sectoral Data and Linkages at Variable Spatial Scales

Zarrar Khan, Thomas Wild, Chris Vernon, Andy Miller, Mohamad Hejazi, Leon Clarke, Fernando Miralles-Wilhelm, Raul Munoz Castillo, Fekadu Moreda, Julia Lacal Bereslawski, Micaela Suriano, Jose Casado DOI: http://doi.org/10.5334/jors.292 Abstract: Metis was developed to allow users to analyze regional and sub-regional multi-sector dynamics by providing a platform to harmonize and amalgamate…

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Initial Land Use/Cover Distribution Substantially Affects Global Carbon and Local Temperature Projections in the Integrated Earth System Model

A.V. Di Vittorio, X. Shi, B. Bond‐Lamberty, K. Calvin, A. Jones DOI: https://doi.org/10.1029/2019GB006383 Abstract: Initial land cover distribution varies among Earth system models, an uncertainty in initial conditions that can substantially affect carbon and climate projections. We use the integrated Earth System Model to show that a 3.9 M km2 difference in 2005…

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