Zobrazeno 1 - 10
of 208
pro vyhledávání: '"P J, Rasch"'
Autor:
P. J. Rasch, H. Hirasawa, M. Wu, S. J. Doherty, R. Wood, H. Wang, A. Jones, J. Haywood, H. Singh
Publikováno v:
Geoscientific Model Development, Vol 17, Pp 7963-7994 (2024)
A modeling protocol (defined by a series of climate model simulations with specified model output) is introduced. Studies using these simulations are designed to improve the understanding of climate impacts using a strategy for climate intervention (
Externí odkaz:
https://doaj.org/article/7715e87f25f549bc93cda3ba00f215be
Publikováno v:
Atmospheric Measurement Techniques, Vol 17, Pp 6213-6222 (2024)
The second generation of the Global navigation satellite system Receiver for Atmospheric Sounding (GRAS-2) is a radio occultation (RO) instrument which is capable of providing 2000 atmospheric profiles per day. The instrument is hosted on all satelli
Externí odkaz:
https://doaj.org/article/a96e4c6301a8492ea784d71e250fe786
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-15 (2024)
Abstract Analog in-memory computing is a promising future technology for efficiently accelerating deep learning networks. While using in-memory computing to accelerate the inference phase has been studied extensively, accelerating the training phase
Externí odkaz:
https://doaj.org/article/891ce736eb194cf1bb07219e2ec6dda5
Autor:
Y. Liu, Y. Qian, P. J. Rasch, K. Zhang, L.-R. Leung, Y. Wang, M. Wang, H. Wang, X. Huang, X.-Q. Yang
Publikováno v:
Atmospheric Chemistry and Physics, Vol 24, Pp 3115-3128 (2024)
Fires have great ecological, social, and economic impact. However, fire prediction and management remain challenges due to a limited understanding of their roles in the Earth system. Fires over southern Mexico and Central America (SMCA) are a good ex
Externí odkaz:
https://doaj.org/article/7144d011d60a4971b5e83a246e62e4d2
Autor:
Weiming Ma, Hailong Wang, Gang Chen, L. Ruby Leung, Jian Lu, Philip J. Rasch, Qiang Fu, Ben Kravitz, Yufei Zou, John J. Cassano, Wieslaw Maslowski
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-11 (2024)
Abstract Atmospheric rivers (ARs), intrusions of warm and moist air, can effectively drive weather extremes over the Arctic and trigger subsequent impact on sea ice and climate. What controls the observed multi-decadal Arctic AR trends remains unclea
Externí odkaz:
https://doaj.org/article/4203e923d6474463a93082fc52447356
Autor:
Dipti Hingmire, Haruki Hirasawa, Hansi Singh, Philip J. Rasch, Sookyung Kim, Subhashis Hazarika, Peetak Mitra, Kalai Ramea
Publikováno v:
Geophysical Research Letters, Vol 51, Iss 11, Pp n/a-n/a (2024)
Abstract We study the sensitivity of South Asian Summer Monsoon (SASM) precipitation to Southern Hemisphere (SH) subtropical Absorbed Solar Radiation (ASR) changes using Community Earth System Model 2 simulations. Reducing positive ASR biases over th
Externí odkaz:
https://doaj.org/article/5cdf4d39630b4fee83d7678310ace6a0
Autor:
Oluwayemi Garuba, Philip J. Rasch, L. Ruby Leung, Hailong Wang, Samson Hagos, Balwinder Singh
Publikováno v:
Journal of Advances in Modeling Earth Systems, Vol 16, Iss 5, Pp n/a-n/a (2024)
Abstract This work describes the implementation and evaluation of the Slab Ocean Model component of the Energy Exascale Earth System Model version 2 (E3SMv2‐SOM) and its application to understanding the climate sensitivity to ocean heat transports
Externí odkaz:
https://doaj.org/article/84bd30da70ee47308dc0f3b7fe234bb6
Publikováno v:
Atmospheric Chemistry and Physics, Vol 23, Pp 15305-15324 (2023)
The difficulties in using conventional mitigation techniques to maintain global-mean temperatures well below 2 ∘C compared with pre-industrial levels have been well documented, leading to so-called “climate intervention” or “geoengineering”
Externí odkaz:
https://doaj.org/article/7e2a4ad2b4d54b1ab347872baa641428
Autor:
Malte J. Rasch, Charles Mackin, Manuel Le Gallo, An Chen, Andrea Fasoli, Frédéric Odermatt, Ning Li, S. R. Nandakumar, Pritish Narayanan, Hsinyu Tsai, Geoffrey W. Burr, Abu Sebastian, Vijay Narayanan
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-18 (2023)
Abstract Analog in-memory computing—a promising approach for energy-efficient acceleration of deep learning workloads—computes matrix-vector multiplications but only approximately, due to nonidealities that often are non-deterministic or nonlinea
Externí odkaz:
https://doaj.org/article/35c750944f924737bca0b86c136a18ab
Autor:
Fabia Farlin Athena, Omobayode Fagbohungbe, Nanbo Gong, Malte J. Rasch, Jimmy Penaloza, SoonCheon Seo, Arthur Gasasira, Paul Solomon, Valeria Bragaglia, Steven Consiglio, Hisashi Higuchi, Chanro Park, Kevin Brew, Paul Jamison, Christopher Catano, Iqbal Saraf, Claire Silvestre, Xuefeng Liu, Babar Khan, Nikhil Jain, Steven McDermott, Rick Johnson, I. Estrada-Raygoza, Juntao Li, Tayfun Gokmen, Ning Li, Ruturaj Pujari, Fabio Carta, Hiroyuki Miyazoe, Martin M. Frank, Antonio La Porta, Devi Koty, Qingyun Yang, Robert D. Clark, Kandabara Tapily, Cory Wajda, Aelan Mosden, Jeff Shearer, Andrew Metz, Sean Teehan, Nicole Saulnier, Bert Offrein, Takaaki Tsunomura, Gert Leusink, Vijay Narayanan, Takashi Ando
Publikováno v:
Frontiers in Electronics, Vol 4 (2024)
Analog memory presents a promising solution in the face of the growing demand for energy-efficient artificial intelligence (AI) at the edge. In this study, we demonstrate efficient deep neural network transfer learning utilizing hardware and algorith
Externí odkaz:
https://doaj.org/article/251ccb96d4dd435e83908250513bf0fa