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Because of the impact of extreme heat waves and heat domes on society and biodiversity, their study is a key challenge. We specifically study long-lasting extreme heat waves, which are among the most important for climate impacts. Physics…

Machine Learning · Computer Science 2022-01-14 Valérian Jacques-Dumas , Francesco Ragone , Pierre Borgnat , Patrice Abry , Freddy Bouchet

Data-driven approaches, most prominently deep learning, have become powerful tools for prediction in many domains. A natural question to ask is whether data-driven methods could also be used to predict global weather patterns days in…

Atmospheric and Oceanic Physics · Physics 2020-12-30 Stephan Rasp , Peter D. Dueben , Sebastian Scher , Jonathan A. Weyn , Soukayna Mouatadid , Nils Thuerey

Time series models often deal with extreme events and anomalies, both prevalent in real-world datasets. Such models often need to provide careful probabilistic forecasting, which is vital in risk management for extreme events such as…

Machine Learning · Statistics 2022-08-23 Ashkan Farhangi , Jiang Bian , Arthur Huang , Haoyi Xiong , Jun Wang , Zhishan Guo

To improve the trustworthiness of an AI model, finding consistent, understandable representations of its inference process is essential. This understanding is particularly important in high-stakes operations such as weather forecasting,…

Artificial Intelligence · Computer Science 2025-04-02 Soyeon Kim , Junho Choi , Subeen Lee , Jaesik Choi

Precipitation nowcasting, the high-resolution forecasting of precipitation up to two hours ahead, supports the real-world socio-economic needs of many sectors reliant on weather-dependent decision-making. State-of-the-art operational…

Accurate weather and climate modeling is critical for both scientific advancement and safeguarding communities against environmental risks. Traditional approaches rely heavily on Numerical Weather Prediction (NWP) models, which simulate…

Machine Learning · Computer Science 2024-09-13 Muhammad Akhtar Munir , Fahad Shahbaz Khan , Salman Khan

Drought is a complex stochastic natural hazard caused by prolonged shortage of rainfall. Several environmental factors are involved in determining drought classes at the specific monitoring station. Therefore, efficient sequence processing…

Earth System Models (ESMs) are essential tools for understanding the impact of human actions on Earth's climate. One key application of these models is studying extreme weather events, such as heat waves or dry spells, which have…

Atmospheric and Oceanic Physics · Physics 2023-04-25 Seth Bassetti , Brian Hutchinson , Claudia Tebaldi , Ben Kravitz

Accurate short range weather forecasting has significant implications for various sectors. Machine learning based approaches, e.g., deep learning, have gained popularity in this domain where the existing numerical weather prediction (NWP)…

Deploying large language model inference remains challenging due to their high computational overhead. Early exit optimizes model inference by adaptively reducing the number of inference layers. Current methods typically train internal…

Computation and Language · Computer Science 2026-03-05 Lianming Huang , Shangyu Wu , Yufei Cui , Ying Xiong , Haibo Hu , Xue Liu , Tei-Wei Kuo , Nan Guan , Chun Jason Xue

Heat waves are projected to increase in frequency and severity with global warming. Improved warning systems would help reduce the associated loss of lives, wildfires, power disruptions, and reduction in crop yields. In this work, we…

Atmospheric and Oceanic Physics · Physics 2023-01-13 Ignacio Lopez-Gomez , Amy McGovern , Shreya Agrawal , Jason Hickey

Earthquake early warning systems play crucial roles in reducing the risk of seismic disasters. Previously, the dominant modeling system was the single-station models. Such models digest signal data received at a given station and predict…

Machine Learning · Computer Science 2024-12-25 Yu-Ming Huang , Kuan-Yu Chen , Wen-Wei Lin , Da-Yi Chen

We present an ensemble prediction system using a Deep Learning Weather Prediction (DLWP) model that recursively predicts key atmospheric variables with six-hour time resolution. This model uses convolutional neural networks (CNNs) on a…

Atmospheric and Oceanic Physics · Physics 2021-12-10 Jonathan A. Weyn , Dale R. Durran , Rich Caruana , Nathaniel Cresswell-Clay

Due to the rapidly changing climate, the frequency and severity of extreme weather is expected to increase over the coming decades. As fully-resolved climate simulations remain computationally intractable, policy makers must rely on…

Atmospheric and Oceanic Physics · Physics 2024-02-29 Benedikt Barthel Sorensen , Alexis Charalampopoulos , Shixuan Zhang , Bryce Harrop , Ruby Leung , Themistoklis Sapsis

Complex Event Recognition (CER) systems have become popular in the past two decades due to their ability to "instantly" detect patterns on real-time streams of events. However, there is a lack of methods for forecasting when a pattern might…

Databases · Computer Science 2021-09-02 Elias Alevizos , Alexander Artikis , Georgios Paliouras

Species distribution models (SDMs) are key tools in ecology, conservation and management of natural resources. They are commonly trained by scientific survey data but, since surveys are expensive, there is a need for complementary sources…

Methodology · Statistics 2026-04-03 Karel Kaurila , Sanna Kuningas , Antti Lappalainen , Jarno Vanhatalo

Modeling biological networks serves as both a major goal and an effective tool of systems biology in studying mechanisms that orchestrate the activities of gene products in cells. Biological networks are context specific and dynamic in…

Molecular Networks · Quantitative Biology 2014-02-20 Ye Tian , Bai Zhang , Eric P. Hoffman , Robert Clarke , Zhen Zhang , Ie-Ming Shih , Jianhua Xuan , David M. Herrington , Yue Wang

This document is one of the deliverable reports created for the ESCAPE project. ESCAPE stands for Energy-efficient Scalable Algorithms for Weather Prediction at Exascale. The project develops world-class, extreme-scale computing…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-08-20 Gianmarco Mengaldo

An important issue in the use of expert systems is the so-called brittleness problem. Expert systems model only a limited part of the world. While the explicit management of uncertainty in expert systems itigates the brittleness problem, it…

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With broad applications in various public services like aviation management and urban disaster warning, numerical precipitation prediction plays a crucial role in weather forecast. However, constrained by the limitation of observation and…

Machine Learning · Computer Science 2019-10-18 Xiaoyang Xu , Yiqun Liu , Hanqing Chao , Youcheng Luo , Hai Chu , Lei Chen , Junping Zhang , Leiming Ma