大气与海洋物理
This study presents an advanced framework for tropopause detection and analysis using ERA5 reanalysis data, with particular application to extreme meteorological events affecting Morocco and Southern Europe. The research implements and…
Representing and quantifying uncertainty in physical parameterisations is a central challenge in weather and climate modelling, and approaches are often developed separately for different timescales. Here, we introduce a unified framework…
We present a probabilistic data-driven weather model capable of providing an ensemble of high spatial resolution realizations of 87 variables at arbitrary forecast length and ensemble size. The model uses a stretched grid, dedicating 2.5 km…
Large ensembles of climate projections are essential for characterizing uncertainty in future climate and extreme weather events, yet computational constraints of numerical climate models limit ensemble sizes to a small number of…
In this work, we address the super-resolution problem of satellite-derived sea surface temperature (SST) using deep generative models. Although standard gap-filling techniques are effective in producing spatially complete datasets, they…
Predicting ocean wave behavior is challenging due to the difficulty in choosing suitable numerical models among many with varying capabilities. This review examines the development and performance of numerical wave models in coastal…
This study presents a comprehensive climatological benchmarking of tropical cyclones (TCs) generated by AI-based global weather prediction models. Using all TC events from the North Atlantic and Western Pacific basins between 2020 and 2025,…
Coupled atmosphere-ocean deep learning (DL) climate emulators are a new frontier but are known to exhibit weak ENSO variability, raising questions about their ability to simulate teleconnections. Here, we present the first Pacific pacemaker…
This paper discusses the initial development of Marine Cloud Brightening (MCB) as a theoretical idea, from its inception as a cloud microphysics process in circe 1990 to the full-blown concept by 2015. It primarily focuses on the work of…
The main determinants of Earth's absolute surface Temperature, T, are the solar constant, S, the Bond albedo, A, and the effective emissivity for thermal radiation, e. In this note we assume that the value of the effective emissivity, e =…
Column-integrated moist static energy (MSE) budgets underpin theories of tropical convection and circulation, yet in reanalyses and climate models the budget rarely closes; residuals routinely match the leading terms and mask physical…
An important process in tropical cyclone formation is the development of a deep, warm core, which corresponds to the growth of a barotropic cyclone. Persistent convective activity is known to be crucial for the growth of barotropic…
We investigate the large-scale structure and temporal evolution of cyclonic and anticyclonic systems in the North Atlantic using persistent homology applied to daily sea-level pressure anomalies from the ERA5 reanalysis (1950-2022). By…
Tropical regions may experience periodic extreme precipitation and suffer from associated periodic deluges in a warmer climate. Recent studies conducted small-domain (around 100 km x 100 km) atmospheric model simulations and found that…
Dust layers have already been reported to have negative impacts on the radiation budget of the atmosphere. But the questions are: How does the atmospheric surface temperature change during a dust outbreak, and what is its temporal…
Data-driven weather prediction models implicitly assume that the statistical relationship between predictors and targets is stationary. Under anthropogenic climate change, this assumption is violated, yet the structure of the resulting…
Side-scan sonar (SSS) imagery is widely used for seafloor mapping and underwater remote sensing, yet the measured intensity is strongly influenced by seabed reflectivity, terrain elevation, and acoustic path loss. This entanglement makes…
The Southwestern South Atlantic (SWSA) is a key region for climate research and renewable energy assessment, yet high-resolution meteorological data are scarce. We present a multiresolution dataset spanning February 2017--November 2018,…
Cloud-related parameterizations remain a leading source of uncertainty in climate projections. Although machine learning holds promise for Earth system models (ESMs), many data-driven parameterizations lack interpretability, physical…
Starting from a classical Budyko-Sellers-Ghil energy balance model for the average surface temperature of the Earth, a nonautonomous version is designed by allowing the solar irradiance and the cloud cover coefficients to vary with time in…