Results 91 to 100 of about 184,798 (233)

Beyond the Training Data: Confidence‐Guided Mixing of Parameterizations in a Hybrid AI‐Climate Model

Journal of Advances in Modeling Earth Systems, Volume 18, Issue 5, May 2026.
Abstract Persistent systematic errors in Earth system models (ESMs) arise from difficulties in representing the full diversity of subgrid, multiscale atmospheric convection and turbulence. Machine learning (ML) parameterizations trained on short high‐resolution simulations show strong potential to reduce these errors.
Helge Heuer, Tom Beucler, Mierk Schwabe, Julien Savre, Manuel Schlund, Veronika Eyring   +5 more
wiley   +1 more source

Combining high performance simulation, data acquisition, and graphics display computers [PDF]

Issues involved in the continuing development of an advanced simulation complex are discussed. This approach provides the capability to perform the majority of tests on advanced systems, non-destructively.
Hickman, Robert J.
core   +1 more source

Synthesis of dynamic systems [PDF]

, 1971
FORTRAN matrix analysis /FORMA/ program finds solutions of small and medium size structural dynamics problems of up to 150 deg of ...
Admire, J. R., Wohlen, R.
core   +1 more source

DJ4Earth: Differentiable, and Performance‐Portable Earth System Modeling via Program Transformations

Journal of Advances in Modeling Earth Systems, Volume 18, Issue 5, May 2026.
Abstract Differentiable Earth system models (ESMs) enable powerful applications such as sensitivity analysis, gradient‐based calibration, state estimation, boundary flux inversions, uncertainty quantification, and online machine learning. Reverse‐mode automatic differentiation (AD) efficiently provides gradients for such tasks, yet models have rarely ...
William S. Moses, Gong Cheng, Valentin Churavy, Maximilian Gelbrecht, Milan Klöwer, Joseph Kump, Mathieu Morlighem, Sarah Williamson, Dhruv Apte, Paul Berg, Mosè Giordano, Christopher Hill, Nora Loose, Alexis Montoison, Sri Hari Krishna Narayanan, Avik Pal, Michel Schanen, Simone Silvestri, Greg Wagner, Patrick Heimbach   +19 more
wiley   +1 more source

Crowdsourcing the Frontier: Advancing Hybrid Physics‐ML Climate Simulation via a $50,000 Kaggle Competition

Journal of Advances in Modeling Earth Systems, Volume 18, Issue 5, May 2026.
Abstract Subgrid machine‐learning (machine learning [ML]) parameterizations have the potential to introduce a new generation of climate models that incorporate the effects of higher‐resolution physics without incurring the prohibitive computational cost associated with more explicit physics‐based simulations.
Jerry Lin, Zeyuan Hu, Tom Beucler, Katherine Frields, Hannah Christensen, Walter Hannah, Helge Heuer, Peter Ukkonen, Laura A. Mansfield, Tian Zheng, Liran Peng, Ritwik Gupta, Pierre Gentine, Yusef Al‐Naher, Mingjiang Duan, Kyo Hattori, Weiliang Ji, Chunhan Li, Kippei Matsuda, Naoki Murakami, Shlomo Ron, Marec Serlin, Hongjian Song, Yuma Tanabe, Daisuke Yamamoto, Jianyao Zhou, Mike Pritchard   +26 more
wiley   +1 more source

SHTools: Tools for Working with Spherical Harmonics

Geochemistry, Geophysics, Geosystems, 2018
Geophysical analyses are often performed in spherical geometry and require the use of spherical harmonic functions to express observables or physical quantities.
Mark A. Wieczorek, Matthias Meschede
doaj   +1 more source

Thrust Chamber Modeling Using Navier-Stokes Equations: Code Documentation and Listings [PDF]

A copy of the PHOENICS input files and FORTRAN code developed for the modeling of thrust chambers is given. These copies are contained in the Appendices. The listings are contained in Appendices A through E.
Daley, P. L., Owens, S. F.
core   +1 more source

FORTRAN 4 digital program changer [PDF]

, 1971
Computer program modifies other source language programs as aid to debugging, checkout and final documentation to eliminate manual performance of rearranging and incrementing statement numbers, identifying and sequencing cards and inserting and/or ...
Madden, M. F.
core   +1 more source

Reducing Model Biases With Machine Learning Corrections Derived From Ocean Data Assimilation Increments

Journal of Advances in Modeling Earth Systems, Volume 18, Issue 5, May 2026.
Abstract Large ocean data assimilation (DA) increments are concentrated in the mixed layer, indicating persistent biases in vertical mixing. These increments can therefore be used to derive bias corrections. Previous studies developed full‐depth climatological temperature and salinity corrections from these increments, known as the Ocean Tendency ...
Danni Du, Feiyu Lu, Alistair Adcroft
wiley   +1 more source

Legacy Code, Live Risk: Empirical Evidence of Malware Detection Gaps

Applied Sciences
Consistent detection of malicious loaders across varied programming languages and build tools remains a significant cybersecurity challenge. This study empirically measures how compiler and language choices affect the detectability of standard in-memory ...
Gang-Cheng Huang, Tai-Hung Lai
doaj   +1 more source