大气与海洋物理

We suggest the procedure of building the maps of noctilucent clouds (NLC) zonal and meridional velocity, mean altitude and particle size based on three-color photometry by identical all-sky RGB-cameras separated by 115 km in a…

The Gulf of Eilat (Gulf of Aqaba) is a semi-enclosed basin situated at the northern end of the Red Sea, renowned for its exceptional marine ecosystem. To evaluate the response of the Gulf to climate variations, we analyzed various factors…

Clouds containing ice particles play a crucial role in the climate system. Yet they remain a source of great uncertainty in climate models and future climate projections. In this work, we create a new observational constraint of…

Climate change has led to an increase in frequency of extreme weather events. Early warning systems can prevent disasters and loss of life. Managing such events remain a challenge for both public and private institutions. Precipitation…

Due to costs and practical constraints, field campaigns in the atmospheric boundary layer typically only measure a fraction of the atmospheric volume of interest. Machine learning techniques have previously successfully reconstructed…

Combining remote-sensing data with in-situ observations to achieve a comprehensive 3D reconstruction of the ocean state presents significant challenges for traditional interpolation techniques. To address this, we developed the CLuster…

In a joint effort, MeteoSwiss and Deutscher Wetterdienst (DWD) address the need for improving the initial state of the atmospheric boundary layer (ABL) by exploiting ground-based profiling observations that aim to fill the existing…

Coastal upwelling, driven by alongshore winds and characterized by cold sea surface temperatures and high upper-ocean nutrient content, is an important physical process sustaining some of the oceans' most productive ecosystems. To fully…

Designing early warning system for precipitation requires accurate short-term forecasting system. Climate change has led to an increase in frequency of extreme weather events, and hence such systems can prevent disasters and loss of life.…

Existing ML-based atmospheric models are not suitable for climate prediction, which requires long-term stability and physical consistency. We present ACE (AI2 Climate Emulator), a 200M-parameter, autoregressive machine learning emulator of…

The rapidly shrinking Arctic sea ice is changing weather patterns and disrupting the balance of nature. Dynamics of Arctic weather variability (WV) plays a crucial role in weather forecasting and is closely related to extreme weather…

Methane (CH4) is the second most critical greenhouse gas after carbon dioxide, contributing to 16-25% of the observed atmospheric warming. Wetlands are the primary natural source of methane emissions globally. However, wetland methane…

Mitigation of climate change will highly rely on a carbon emission trajectory that achieves carbon neutrality by the 2050s. The ocean plays a critical role in modulating climate change by sequestering CO2 from the atmosphere. Relying on the…

Global Storm-Resolving Models (GSRMs) have gained widespread interest because of the unprecedented detail with which they resolve the global climate. However, it remains difficult to quantify objective differences in how GSRMs resolve…

The aim of this note is to describe several meteorological properties shown in a conference talk (Marquet, January 2022) for the moist-air specific entropy, the associated potential temperature ($\theta_s$) defined in Marquet (2011) and the…

Accurate atmospheric 3D wind observations are a high priority in the science community. To address this requirement and to support researchers' needs to acquire and analyze wind data from multiple sources, the System for Analysis of Wind…

The use of neural operators in a digital twin model of an offshore floating structure can provide a paradigm shift in structural response prediction and health monitoring, providing valuable information for real-time control. In this work,…

Despite the importance of quantifying how the spatial patterns of extreme precipitation will change with warming, we lack tools to objectively analyze the storm-scale outputs of modern climate models. To address this gap, we develop an…

This paper introduces Precipitation Attention-based U-Net (PAUNet), a deep learning architecture for predicting precipitation from satellite radiance data, addressing the challenges of the Weather4cast 2023 competition. PAUNet is a variant…

Wind, as a clean and sustainable source of energy, has witnessed significant growth in recent years. However, with a growing number of wind farms authorised, constructed and commissioned, the wake effect (the reduced wind speed caused by…