首页|Data on Machine Learning Reported by Researchers at University of Maryland (Eval uation of Stratocumulus Evolution Under Contrasting Temperature Advections In Ce sm2 Through a Lagrangian Framework)
Data on Machine Learning Reported by Researchers at University of Maryland (Eval uation of Stratocumulus Evolution Under Contrasting Temperature Advections In Ce sm2 Through a Lagrangian Framework)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Machine Learning have been presented. According to news reporting originating from College Park, Mary land, by NewsRx correspondents, research stated, “This study leveraged a Lagrang ian framework to examine the evolution of stratocumulus clouds under cold and wa rm advections (CADV and WADV) in the Community Earth System Model 2 (CESM2) agai nst observations. We found that CESM2 simulates a too rapid decline in low-cloud fraction (LCF) and cloud liquid water path (CLWP) under CADV conditions, while it better aligns closely with observed LCF under WADV conditions but overestimat es the increase in CLWP.”
College ParkMarylandUnited StatesNorth and Central AmericaCyborgsEmerging TechnologiesMachine LearningUniv ersity of Maryland
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