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Large language models (LLMs) have revolutionized scientific research with their exceptional capabilities and transformed various fields. Among their practical applications, LLMs have been playing a crucial role in mitigating threats to…

Computation and Language · Computer Science 2025-08-26 Zhenyu Lei , Yushun Dong , Weiyu Li , Rong Ding , Qi Wang , Jundong Li

Most electricity systems worldwide are deploying advanced metering infrastructures to collect relevant operational data. In particular, smart meters allow tracking electricity load consumption at a very disaggregated level and at high…

Machine Learning · Statistics 2020-03-09 Andrés M. Alonso , F. Javier Nogales , Carlos Ruiz

Streamflow prediction is one of the key challenges in the field of hydrology due to the complex interplay between multiple non-linear physical mechanisms behind streamflow generation. While physics based models are rooted in rich…

Atmospheric and Oceanic Physics · Physics 2025-11-12 Ankush Khandelwal , Shaoming Xu , Xiang Li , Xiaowei Jia , Michael Stienbach , Christopher Duffy , John Nieber , Vipin Kumar

In recent years, the paradigms of data-driven science have become essential components of physical sciences, particularly in geophysical disciplines such as climatology. The field of hydrology is one of these disciplines where machine…

Atmospheric and Oceanic Physics · Physics 2020-06-24 Martin Gauch , Jimmy Lin

Precipitation and its response to forcings is an important aspect of planetary climate system. In this study, we examine the strength of precipitation in the experiments with different atmospheric masses and their response to surface…

Earth and Planetary Astrophysics · Physics 2022-10-05 Junyan Xiong , Jun Yang , Jiachen Liu

Traditionally, weather predictions are performed with the help of large complex models of physics, which utilize different atmospheric conditions over a long period of time. These conditions are often unstable because of perturbations of…

Machine Learning · Computer Science 2020-08-26 A H M Jakaria , Md Mosharaf Hossain , Mohammad Ashiqur Rahman

Climate projections continue to be marred by large uncertainties, which originate in processes that need to be parameterized, such as clouds, convection, and ecosystems. But rapid progress is now within reach. New computational tools and…

Machine Learning · Statistics 2018-02-14 Tapio Schneider , Shiwei Lan , Andrew Stuart , João Teixeira

Flooding remains a major global challenge, worsened by climate change and urbanization, demanding advanced solutions for effective disaster management. While traditional 2D flood mapping techniques provide limited insights, 3D flood…

Computer Vision and Pattern Recognition · Computer Science 2025-07-14 Wenfeng Jia , Bin Liang , Yuxi Liu , Muhammad Arif Khan , Lihong Zheng

Accurate and computationally-viable representations of clouds and turbulence are a long-standing challenge for climate model development. Traditional parameterizations that crudely but efficiently approximate these processes are a leading…

Atmospheric and Oceanic Physics · Physics 2024-01-05 Jerry Lin , Mohamed Aziz Bhouri , Tom Beucler , Sungduk Yu , Michael Pritchard

Rainfall-induced landslides pose a growing risk worldwide as climate change intensifies extreme rainfall events. To provide sufficient evacuation time, landslide early warning systems (LEWS) for real-time disaster monitoring must estimate…

Machine Learning · Computer Science 2026-05-19 Ren Ozeki , Hamada Rizk , Hirozumi Yamaguchi

The goal of precipitation nowcasting is to predict the future rainfall intensity in a local region over a relatively short period of time. Very few previous studies have examined this crucial and challenging weather forecasting problem from…

Computer Vision and Pattern Recognition · Computer Science 2015-09-22 Xingjian Shi , Zhourong Chen , Hao Wang , Dit-Yan Yeung , Wai-kin Wong , Wang-chun Woo

As global climate change intensifies, accurate weather forecasting is increasingly crucial for sectors such as agriculture, energy management, and environmental protection. Traditional methods, which rely on physical and statistical models,…

Machine Learning · Computer Science 2024-09-17 Bangyu Li , Yang Qian

Understanding how vegetation loss alters rainfall remains a major challenge in climate and hydrological science, as deforestation modifies precipitation through heterogeneous, seasonal and nonlinear land-atmosphere feedbacks. Existing…

Atmospheric and Oceanic Physics · Physics 2026-05-13 Lilly Horvath-Makkos , Fayyaz Minhas

Sea-levels are rising in many areas around the world, posing risks to coastal communities and infrastructures. Strategies for managing these flood risks present decision challenges that require a combination of geophysical, economic, and…

Climate change has increased the severity and frequency of weather disasters all around the world. Flood inundation mapping based on earth observation data can help in this context, by providing cheap and accurate maps depicting the area…

Machine Learning · Computer Science 2023-03-02 Kevin Iselborn , Marco Stricker , Takashi Miyamoto , Marlon Nuske , Andreas Dengel

The response of precipitation extremes to climate change is considered using results from theory, modeling, and observations, with a focus on the physical factors that control the response. Observations and simulations with climate models…

Atmospheric and Oceanic Physics · Physics 2015-05-05 Paul A. O'Gorman

Improving the representation of precipitation in Earth system models (ESMs) is critical for assessing the impacts of climate change and especially of extreme events like floods and droughts. In existing ESMs, precipitation is not resolved…

Machine Learning · Computer Science 2026-05-27 Michael Aich , Sebastian Bathiany , Philipp Hess , Yu Huang , Niklas Boers

Extreme streamflow is a key indicator of flood risk, and quantifying the changes in its distribution under non-stationary climate conditions is key to mitigating the impact of flooding events. We propose a non-stationary process mixture…

Methodology · Statistics 2024-05-08 Reetam Majumder , Brian Reich

Hydroelectric power generation is a critical component of the global energy matrix, particularly in countries like Brazil, where it represents the majority of the energy supply. However, its strong dependence on river discharges, which are…

Machine Learning · Computer Science 2024-12-19 Julio Alberto Silva Dias

Ecosystems monitoring is essential to properly understand their development and the effects of events, both climatological and anthropological in nature. The amount of data used in these assessments is increasing at very high rates. This is…

Networking and Internet Architecture · Computer Science 2011-07-01 Gilberto Z. Pastorello , G. Arturo Sanchez-Azofeifa , Mario A. Nascimento