no code implementations • 5 Mar 2024 • Philipp Hess, Michael Aich, Baoxiang Pan, Niklas Boers
Accurate and high-resolution Earth system model (ESM) simulations are essential to assess the ecological and socio-economic impacts of anthropogenic climate change, but are computationally too expensive.
no code implementations • 16 Dec 2023 • Pumeng Lyu, Tao Tang, Fenghua Ling, Jing-Jia Luo, Niklas Boers, Wanli Ouyang, Lei Bai
Recent studies have shown that deep learning (DL) models can skillfully predict the El Ni\~no-Southern Oscillation (ENSO) forecasts over 1. 5 years ahead.
no code implementations • 30 Nov 2023 • Nils Bochow, Anna Poltronieri, Martin Rypdal, Niklas Boers
Historical records of climate fields are often sparse due to missing measurements, especially before the introduction of large-scale satellite missions.
no code implementations • 13 Sep 2023 • Hao Zhang, Jin-Jian Xu, Hong-Wei Cui, Lin Li, Yaowen Yang, Chao-Sheng Tang, Niklas Boers
Critically, the scalability and generalizability of GFMs empower them to address a wide array of prediction, simulation, and decision tasks related to the intricate interactions among Earth system components.
no code implementations • 11 Sep 2023 • Shan Zhao, Sudipan Saha, Zhitong Xiong, Niklas Boers, Xiao Xiang Zhu
Motivated by this, we explore a geometric deep learning-based temporal Graph Convolutional Network (GCN) for precipitation nowcasting.
1 code implementation • NeurIPS 2023 • Alistair White, Niki Kilbertus, Maximilian Gelbrecht, Niklas Boers
Many successful methods to learn dynamical systems from data have recently been introduced.
no code implementations • 16 Dec 2022 • Philipp Hess, Stefan Lange, Christof Schötz, Niklas Boers
The accurate representation of precipitation in Earth system models (ESMs) is crucial for reliable projections of the ecological and socioeconomic impacts in response to anthropogenic global warming.
no code implementations • 29 Aug 2022 • Maximilian Gelbrecht, Alistair White, Sebastian Bathiany, Niklas Boers
Earth System Models (ESMs) are the primary tools for investigating future Earth system states at time scales from decades to centuries, especially in response to anthropogenic greenhouse gas release.
no code implementations • 25 Aug 2022 • Philipp Hess, Markus Drüke, Stefan Petri, Felix M. Strnad, Niklas Boers
Our method outperforms existing ones in correcting local distributions, and leads to strongly improved spatial patterns especially regarding the intermittency of daily precipitation.
no code implementations • Journal of Advances in Modeling Earth Systems 2022 • Philipp Hess, Niklas Boers
The accurate prediction of rainfall, and in particular of the heaviest rainfall events, remains challenging for numerical weather prediction (NWP) models.
no code implementations • 22 Jan 2021 • Christopher Irrgang, Niklas Boers, Maike Sonnewald, Elizabeth A. Barnes, Christopher Kadow, Joanna Staneva, Jan Saynisch-Wagner
We outline a perspective of an entirely new research branch in Earth and climate sciences, where deep neural networks and Earth system models are dismantled as individual methodological approaches and reassembled as learning, self-validating, and interpretable Earth system model-network hybrids.
1 code implementation • 4 Apr 2016 • Dominik Traxl, Niklas Boers, Jürgen Kurths
These include, most importantly, an explicit association of information with possibly heterogeneous types of objects and relations, and a conclusive representation of the properties of groups of nodes as well as the interactions between such groups on different scales.
Data Analysis, Statistics and Probability Social and Information Networks Atmospheric and Oceanic Physics Physics and Society