Výsledky vyhledávání - "In situ data"

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An analysis on OpenMetBuoy-v2021 drifter in-situ data and Lagrangian trajectory simulations in the Agulhas Current System

Autor: Moerman, Bente, Breivik, Øyvind, Hole, Lars R., Hope, Gaute, Johannessen, Johnny A., Rabault, Jean

In order to perform a sensitivity analysis of Lagrangian trajectory models, Lagrangian trajectory simulations have been compared to six OpenMetBuoy-v2021 drifter trajectories in the Agulhas Current System (Jan-Mar 2023). Three different Lagrangian tr

Externí odkaz: http://arxiv.org/abs/2409.20096

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In-situ data extraction for pathway analysis in an idealized atmosphere configuration of E3SM

Autor: Steyer, Andrew, Bertagna, Luca, Harper, Graham, Watkins, Jerry, Tezaur, Irina, Bull, Diana

We propose an approach for characterizing source-impact pathways, the interactions of a set of variables in space-time due to an external forcing, in climate models using in-situ analyses that circumvent computationally expensive read/write operation

Externí odkaz: http://arxiv.org/abs/2408.04099

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Akademický článek

Remote Sensing and GIS in Natural Resource Management: Comparing Tools and Emphasizing the Importance of In-Situ Data.

Autor: Sharma, Sanjeev¹ (AUTHOR) pkhanal@clemson.edu, Beslity, Justin O.² (AUTHOR) justin.beslity@trincoll.edu, Rustad, Lindsey³ (AUTHOR) lindsey.rustad@usda.gov, Shelby, Lacy J.⁴ (AUTHOR) lshelby@gradcenter.cuny.edu, Manos, Peter T.⁴ (AUTHOR) peter.manos85@myhunter.cuny.edu, Khanal, Puskar¹ (AUTHOR), Reinmann, Andrew B.^4,5,6,7 (AUTHOR) areinmann@gc.cuny.edu, Khanal, Churamani⁸ (AUTHOR) ckhanal@clemson.edu

Publikováno v: Remote Sensing. Nov2024, Vol. 16 Issue 22, p4161. 18p.

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Frontiers in integrative structural biology: modeling disordered proteins and utilizing in situ data

Autor: Majila, Kartik, Arvindekar, Shreyas, Jindal, Muskaan, Viswanath, Shruthi

Integrative modeling enables structure determination for large macromolecular assemblies by combining data from multiple sources of experiment data with theoretical and computational predictions. Recent advancements in AI-based structure prediction a

Externí odkaz: http://arxiv.org/abs/2407.00566

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Implicit Assimilation of Sparse In Situ Data for Dense & Global Storm Surge Forecasting

Autor: Ebel, Patrick, Victor, Brandon, Naylor, Peter, Meoni, Gabriele, Serva, Federico, Schneider, Rochelle

Hurricanes and coastal floods are among the most disastrous natural hazards. Both are intimately related to storm surges, as their causes and effects, respectively. However, the short-term forecasting of storm surges has proven challenging, especiall

Externí odkaz: http://arxiv.org/abs/2404.05758

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