Výsledky vyhledávání - "Scott Sellars"

ARTMIP-early start comparison of atmospheric river detection tools: how many atmospheric rivers hit northern California’s Russian River watershed?

Autor: F. Martin Ralph, Bin Guan, Elizabeth A. Barnes, Tashiana Osborne, Scott Sellars, Alexander Gershunov, Kyle M. Nardi, Tamara Shulgina, Brian Kawzenuk, Maryam A. Lamjiri, Gary A. Wick, Anna Wilson, Jonathan J. Rutz

Publikováno v: Climate Dynamics. 52:4973-4994

Many atmospheric river detection tools (ARDTs) have now been developed. However, their relative performance is not well documented. This paper compares a diverse set of ARDTs by applying them to a single location where a unique 12-year-long time-seri

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f897d929becfa240aa372a474709488f
https://doi.org/10.1007/s00382-018-4427-5

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The Evolution of Bits and Bottlenecks in a Scientific Workflow Trying to Keep Up with Technology: Accelerating 4D Image Segmentation Applied to NASA Data

Autor: John Graham, Scott Sellars, Joulien Tatar, F. Martin Ralph, Kyle Marcus, Frank Wuerthwein, Ilkay Altintas, Larry Smarr, Dmitry Mishin, Phu Nguyen, Thomas A. DeFanti, E. J. Shearer, Camille Crittenden, Soroosh Sorooshian

Publikováno v: eScience

In 2016, a team of earth scientists directly engaged a team of computer scientists to identify cyberinfrastructure (CI) approaches that would speed up an earth science workflow. This paper describes the evolution of that workflow as the two teams bri

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::56cabcdb6d50c92718f6b283cc6a8308
https://doi.org/10.1109/escience.2019.00016

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Workflow-Driven Distributed Machine Learning in CHASE-CI: A Cognitive Hardware and Software Ecosystem Community Infrastructure

Autor: Ilkay Altintas, John Graham, Isaac Nealey, Daniel Crawl, Kyle Marcus, Joel Polizzi, Larry Smarr, Dima Mishin, Thomas A. DeFanti, Scott Sellars

Publikováno v: IPDPS Workshops

The advances in data, computing and networking over the last two decades led to a shift in many application domains that includes machine learning on big data as a part of the scientific process, requiring new capabilities for integrated and distribu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::85c446271c5c35a0d6df693b720cacd0
http://arxiv.org/abs/1903.06802

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Isotopic signature of extreme precipitation events in the western U.S. and associated phases of Arctic and tropical climate modes

Autor: Jeffrey M. Welker, Jin-Yi Yu, Staryl McCabe-Glynn, Yuhao Zou, Scott Sellars, Kathleen R. Johnson, Courtenay Strong

Publikováno v: Journal of Geophysical Research: Atmospheres. 121:8913-8924

PUBLICATIONS Journal of Geophysical Research: Atmospheres RESEARCH ARTICLE 10.1002/2016JD025524 Key Points: • 90% of the extreme precipitation events at California site occurred during the negative Arctic Oscillation • Extreme events show diverse

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c29538f69412040e4e23fb5b937a411e
https://doi.org/10.1002/2016jd025524

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Improving the multi-objective evolutionary optimization algorithm for hydropower reservoir operations in the California Oroville–Thermalito complex

Autor: Scott Sellars, Xiaogang Gao, Tiantian Yang, Soroosh Sorooshian

Publikováno v: Environmental Modelling & Software. 69:262-279

This study demonstrates the application of an improved Evolutionary optimization Algorithm (EA), titled Multi-Objective Complex Evolution Global Optimization Method with Principal Component Analysis and Crowding Distance Operator (MOSPD), for the hyd

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e1ef9b2eb85cf95a779f51792a887d0c
https://doi.org/10.1016/j.envsoft.2014.11.016

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An Object-Oriented Approach to Investigate Impacts of Climate Oscillations on Precipitation: A Western United States Case Study

Autor: Scott Sellars, Soroosh Sorooshian, Xiaogang Gao

Publikováno v: Journal of Hydrometeorology. 16:830-842

This manuscript introduces a novel computational science approach for studying the impact of climate variability on precipitation. The approach uses an object-oriented connectivity algorithm that segments gridded near-global satellite precipitation d

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d69eaf72b0d7ad5096611bcf3f0fd0c2
https://doi.org/10.1175/jhm-d-14-0101.1

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