An overview of the atmospheric component of the Energy Exascale Earth System Model

PJ Rasch, S **e, PL Ma, W Lin, H Wang… - Journal of Advances …, 2019 - Wiley Online Library
Abstract The Energy Exascale Earth System Model Atmosphere Model version 1, the
atmospheric component of the Department of Energy's Energy Exascale Earth System …

Extratropical cooling, interhemispheric thermal gradients, and tropical climate change

JCH Chiang, AR Friedman - Annual Review of Earth and …, 2012 - annualreviews.org
Recent studies suggest the existence of a global atmospheric teleconnection of extratropical
cooling to the tropical rainfall climate, mediated through the development of a thermal …

The Norwegian Earth system model, NorESM2–evaluation of theCMIP6 DECK and historical simulations

Ø Seland, M Bentsen, L Seland Graff… - Geoscientific Model …, 2020 - gmd.copernicus.org
The second version of the fully coupled Norwegian Earth System Model (NorESM2) is
presented and evaluated. NorESM2 is based on the second version of the Community Earth …

Deep learning to represent subgrid processes in climate models

S Rasp, MS Pritchard, P Gentine - Proceedings of the national academy of …, 2018 - pnas.org
The representation of nonlinear subgrid processes, especially clouds, has been a major
source of uncertainty in climate models for decades. Cloud-resolving models better …

Enforcing analytic constraints in neural networks emulating physical systems

T Beucler, M Pritchard, S Rasp, J Ott, P Baldi… - Physical review …, 2021 - APS
Neural networks can emulate nonlinear physical systems with high accuracy, yet they may
produce physically inconsistent results when violating fundamental constraints. Here, we …

Evaluation of climate models

G Flato, J Marotzke, B Abiodun, P Braconnot… - Climate change 2013 …, 2014 - pure.mpg.de
Climate models have continued to be developed and improved since the AR4, and many
models have been extended into Earth System models by including the representation of …

Data-driven prediction of a multi-scale Lorenz 96 chaotic system using deep learning methods: Reservoir computing, ANN, and RNN-LSTM

A Chattopadhyay, P Hassanzadeh… - Nonlinear Processes …, 2020 - npg.copernicus.org
In this paper, the performance of three deep learning methods for predicting short-term
evolution and for reproducing the long-term statistics of a multi-scale spatio-temporal Lorenz …

Bounding the role of black carbon in the climate system: A scientific assessment

TC Bond, SJ Doherty, DW Fahey… - Journal of …, 2013 - Wiley Online Library
Black carbon aerosol plays a unique and important role in Earth's climate system. Black
carbon is a type of carbonaceous material with a unique combination of physical properties …

Quantification of Asian monsoon variability from 68 ka BP through pollen-based climate reconstruction

X Zhang, Z Zheng, K Huang, J Cheng, R Cheddadi… - Science Bulletin, 2023 - Elsevier
The glacial-interglacial variability of precipitation and its driving mechanism in monsoonal
regions has long been a subject of debate. However, there are few records of quantitative …

Complete ensemble empirical mode decomposition hybridized with random forest and kernel ridge regression model for monthly rainfall forecasts

M Ali, R Prasad, Y **ang, ZM Yaseen - Journal of Hydrology, 2020 - Elsevier
Persistent risks of extreme weather events including droughts and floods due to climate
change require precise and timely rainfall forecasting. Yet, the naturally occurring non …