Establishing a non-hydrostatic global atmospheric modeling system at 3-km horizontal resolution with aerosol feedbacks on the Sunway supercomputer of China

J Gu, J Feng, X Hao, T Fang, C Zhao, H An, J Chen… - Science Bulletin, 2022 - Elsevier
During the era of global warming and highly urbanized development, extreme and high
impact weather as well as air pollution incidents influence everyday life and might even …

High Throughput Training of Deep Surrogates from Large Ensemble Runs

LT Meyer, M Schouler, RA Caulk, A Ribés… - Proceedings of the …, 2023 - dl.acm.org
Recent years have seen a surge in deep learning approaches to accelerate numerical
solvers, which provide faithful but computationally intensive simulations of the physical …

Melissa: coordinating large-scale ensemble runs for deep learning and sensitivity analyses

M Schouler, RA Caulk, L Meyer, T Terraz… - Journal of Open …, 2023 - inria.hal.science
Large-scale ensemble runs typically consist of executing thousands of physical simulation
instances according to a range of different input parameters. These ensemble runs enable …

An elastic framework for ensemble-based large-scale data assimilation

S Friedemann, B Raffin - The international journal of high …, 2022 - journals.sagepub.com
Prediction of chaotic systems relies on a floating fusion of sensor data (observations) with a
numerical model to decide on a good system trajectory and to compensate non-linear …

[HTML][HTML] Overcoming computational challenges to realize meter-to submeter-scale resolution in cloud simulations using the super-droplet method

T Matsushima, S Nishizawa… - Geoscientific Model …, 2023 - gmd.copernicus.org
A particle-based cloud model was developed for meter-to submeter-scale-resolution
simulations of warm clouds. Simplified cloud microphysics schemes have already made …

Continuous data assimilation of large eddy simulation by lattice Boltzmann method and local ensemble transform Kalman filter (LBM-LETKF)

Y Hasegawa, N Onodera, Y Asahi, T Ina… - Fluid Dynamics …, 2023 - iopscience.iop.org
We investigate the applicability of the data assimilation (DA) to large eddy simulations based
on the lattice Boltzmann method (LBM). We carry out the observing system simulation …

Rapid simulations of atmospheric data assimilation of hourly-scale phenomena with modern neural networks

Y Li, X Ju, Y Xiao, Q Jia, Y Zhou, S Qian, R Lin… - Proceedings of the …, 2023 - dl.acm.org
Atmospheric data assimilation is essential for numerical weather prediction. Ensemble data
assimilation connects multiple instances of an atmospheric model through a Kalman filter …

Swmpas-a: scaling mpas-a to 39 million heterogeneous cores on the new generation sunway supercomputer

X Hao, T Fang, J Chen, J Gu, J Feng… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
With the computing power of High-Performance Computing (HPC) systems having stepped
into the exascale era, more complex problems can be solved with scientific applications on a …

A 1024-member NICAM-LETKF experiment for the July 2020 heavy rainfall event

K Terasaki, T Miyoshi - SOLA, 2022 - jstage.jst.go.jp
This study investigated the predictability and causes of the heavy rainfall event 16 that
brought severe disasters in Kyushu in July 2020 with a global numerical weather 17 …

Emulating Rainfall–Runoff-Inundation Model Using Deep Neural Network with Dimensionality Reduction

M Momoi, S Kotsuki, R Kikuchi… - … Intelligence for the …, 2023 - journals.ametsoc.org
Predicting the spatial distribution of maximum inundation depth (depth-MAP) is important for
the mitigation of hydrological disasters induced by extreme precipitation. However, physics …