Impact of Coastal Marsh Eco-Geomorphologic Change on Saltwater Intrusion Under Future Sea Level Rise

Yu Zhang, Daniil Svyatsky, Joel C. Rowland, J. David Moulton, Zhendong Cao, Phillip J. Wolfram, Chonggang Xu, Donatella Pasqualini https://doi.org/10.1029/2021WR030333 Department of Energy, Office of Science, Earth & Environmental Systems Modeling Program Acknowledged Support: Yes, Regional and Global Modeling Analysis, and Earth System Model Development Programs Abstract Coastal saltwater intrusion (SWI)…

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The unequal distribution of water risks and adaptation benefits in coastal Bangladesh

Emily J. Barbour, Mohammed Sarfaraz Gani Adnan, Edoardo Borgomeo, Kasia Paprocki, M. Shah Alam Khan, Mashfiqus Salehin & Jim W. Hall  DOI: https://doi.org/10.1038/s41893-021-00846-9 Department of Energy, Office of Science, Earth & Environmental Systems Modeling Program Acknowledged Support: No, other Non-DOE EESM source of support Abstract Increasing flood risk, salinization and waterlogging…

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Assessing the large-scale drivers of precipitation in the Northeastern United States via linear orthogonal decomposition

Raymond Sukhdeo, Paul A. Ullrich & Richard Grotjahn DOI: https://doi.org/10.1007/s00382-022-06289-y Department of Energy, Office of Science, Earth & Environmental Systems Modeling, MultiSector Dynamics Program Acknowledged Support: Yes, Regional and Global Modeling Analysis, and Earth System Model Development Programs Abstract This study examines the linear orthogonal modes associated with monthly precipitation…

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Exploring ENSO-Induced Anomalies over North America in Historical and Future Climate Simulations That Use HadGEM2-ESM Output to Drive WRF

Tristan Shepherd, Jacob J. Coburn, Rebecca J. Barthelmie, and Sara C. Pryor DOI: https://doi.org/10.3390/cli10080117 Department of Energy, Office of Science, Earth & Environmental Systems Modeling Program Acknowledged Support: No, other Non-DOE EESM source of support Abstract Projected changes to the El Niño Southern Oscillation (ENSO) climate mode have been explored using…

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Do Machine Learning Approaches Offer Skill Improvement for Short-Term Forecasting of Wind Gust Occurrence and Magnitude?

Jacob Coburn and Sara C. Pryor DOI: https://doi.org/10.1175/WAF-D-21-0118.1 Department of Energy, Office of Science, Earth & Environmental Systems Modeling Program Acknowledged Support: No, other Non-DOE EESM source of support Abstract Wind gusts, and in particular intense gusts, are societally relevant but extremely challenging to forecast. This study systematically assesses the skill…

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