Results 141 to 150 of about 204,542 (283)
Quarterly Journal of the Royal Meteorological Society, EarlyView.This article demonstrates that assimilating machine‐learning‐derived surface nitrate can improve five‐day phytoplankton forecast substantially within the Met Office operational system for the Northwest European Shelf. We explain the reasons behind this improvement and propose that an online system where machine learning and data assimilation are cycled
Deep S. Banerjee +2 more
wiley +1 more source
Quarterly Journal of the Royal Meteorological Society, EarlyView.We propose a new method for treating different timescales in coupled variational data assimilation for atmosphere–ocean models. The approach involves a series of short‐window coupled assimilations (red arrows in the schematic) followed by a long‐window correction to the ocean fields (blue arrow).
Amos S. Lawless +3 more
wiley +1 more source
How consistently do ensemble prediction systems represent the growth of atmospheric uncertainty?
Quarterly Journal of the Royal Meteorological Society, EarlyView.Spread‐based diagnostics calculated for 12 ensemble prediction systems are compared to understand the consistency with which they represent atmospheric uncertainty growth. Good correlation between all these systems is found in the extratropics for a lead time range from 48 hr to between 96 hr and 192 hr.
Douglas Wood +3 more
wiley +1 more source
Hybrid physics–data‐driven modeling for sea ice thermodynamics and transfer learning
Quarterly Journal of the Royal Meteorological Society, EarlyView.Icepack–NN, a machine‐learning‐based hybrid version of the sea‐ice column model Icepack, is developed to correct state‐dependent forecast errors arising from misspecified snow thermodynamics, using neural networks applied online within the physical model.
G. De Cillis +7 more
wiley +1 more source
Control System for the Navigation of the Agricultural Robots: A Review
Journal of Field Robotics, EarlyView.ABSTRACT Control systems for the navigation of autonomous agricultural robots—particularly those operating in uneven terrain and in the presence of static or dynamic obstacles—have advanced considerably in recent years. As conventional machinery evolves toward increasingly automated systems, the design of reliable navigation controllers has become ...
Edna Carolina Moriones Polanía +3 more
wiley +1 more source
Sliding Doors: Frame Uptake and Rejection by Learners in a Museum‐Based Climate Learning Experience
Science Education, EarlyView.ABSTRACT Science education efforts that support public understanding of modern climate change are critically needed. However, implementing climate‐related learning experiences can be challenging, as public audiences tend to experience a wide range of understandings of and emotions around the issue. In light of these challenges, many scholars have posed
Lynne Zummo +7 more
wiley +1 more source
Chaos in Spin-Wave Instabilities [PDF]
Progress of Theoretical Physics Supplement, 1989 Hitoshi Yamazaki, Michinobu Mino
openaire +1 more source
Unnatural Causes: Cryptocurrencies, Carbon Credits, and the rise of Neoliberalism from Below
Economic Anthropology, EarlyView.ABSTRACT Klima is a carbon‐backed cryptocurrency running as a decentralized autonomous organization (DAO). In 2021, it had accumulated 9 million metric tons of digital carbon credits and reached a market value of more than US$1 billion. In 2023, its treasury stored twice as many carbon credits, but its spot price was a tiny fraction compared to 2021 ...
Riccardo De Cristano, Alexander Paulsson
wiley +1 more source
Micro‐transitions and work identity: The case of academic entrepreneurs
Strategic Entrepreneurship Journal, EarlyView.Abstract Research Summary This paper examines how academic entrepreneurs—scientists who found research‐based startups while remaining in academia—construct and sustain their professional identities amid frequent transitions between academic and entrepreneurial roles.
Marouane Bousfiha, Henrik Berglund
wiley +1 more source
Artificial Intelligence for Engineering, EarlyView.An ultra‐lightweight semantic segmentation network RailNet with only 0.905 M parameters is proposed for rail surface defect detection. Combined with a CDBM image enhancement and GAN‐based data augmentation, RailNet achieves superior segmentation accuracy and real‐time speed on edge devices.
Ziqing Wu +4 more
wiley +1 more source