Collection
Sciences de l'atmosphère, des océans et du climat.
Language-model agents are increasingly asked to carry out open-ended scientific research, yet their results are usually graded against a known answer, a rubric, or a language-model reviewer, none of which can tell whethe...
Rapid and accurate prediction of urban wind and temperature fields is important for urban microclimate design and climate adaptation. Large-eddy simulation (LES) effectively resolves these instantaneous fields, but its a...
Transient supplies of nutrients to the surface ocean, both natural and artificial, stimulate blooms of phytoplankton and the formation of organic matter, driving air-sea gradients and uptake of CO$_2$. However, quantifyi...
Assessing compound weather risks requires forecasts representing dependence between variables. CLARA (Calibrated Advection-Routing Attention) learns joint Gaussian predictive distributions of five surface variables from...
Accurate precipitation estimation at fine spatial scales is critical for hydrology, agriculture, and climate studies. Infrared brightness temperatures from geostationary satellites offer excellent temporal coverage over...
Deep learning has made rapid advances in weather forecasting: autoregressive models trained on atmospheric reanalyses now rival dynamical models across nowcasting, medium-range, and subseasonal-to-seasonal lead times, pr...
We introduce EC-EarthFlow, a generative flow matching model that emulates simulations from the physical climate model EC-Earth3. The model is trained on transient simulations from EC-Earth3 (1950-2166, SSP2-4.5) to predi...
The Global Ocean Observing System is key to understanding oceanic variability and climate change. The ocean is vast and often sparsely and irregularly sampled in time and space by various instruments and systems. Statist...
Atmospheric warming raises evaporative demand, but actual evapotranspiration (ETa) may track demand or decouple under water limitation. Here, we quantified demand-tracking ability from regression slopes relating deseason...
A combination of remote sensing techniques, open space data and field testing was developed to derive astronomical and meteorological parameters and assess Dark Sky brightness of the hitherto unstudied Schist Villages re...
Dissolved oxygen is important for the ocean's ecosystems and biogeochemical cycles. Yet, Earth System Models (ESMs) vary in their simulations of the present-day and future ocean oxygen inventory. To narrow down the uncer...
The production of adipic acid generates nitrous oxide as a by-product, which, if emitted, very effectively warms the climate and depletes the stratospheric ozone layer. There exists cost-effective technology to mitigate...
Data assimilation (DA) is the process of combining forecasts from a model with observations in order to optimally estimate the state of a system. This is critical for chaotic systems, such as the atmosphere, since if obs...
Deep learning has revolutionised weather forecasting in recent years, especially through atmospheric foundation models, which offer competitive skill for a fraction of the computational costs of classic physics-based mod...
Despite substantial progress in short-to-medium-range weather forecasting, predicting high-impact events such as flash droughts remains a key challenge for both early warning operations and physically-based subseasonal-t...
We develop structure-preserving methods for the compressible Euler equations with gravity in vector-invariant form and potential temperature as a prognostic variable within the flux-differencing discontinuous Galerkin sp...
Analytical greenhouse models traditionally rely on the gray approximation, simplifying radiative transfer but treating optical depth as an unconstrained parameter that yields unrealistic surface temperatures. We derive a...
We present ClimateBench v2, a standardized protocol for evaluating climate models on diagnostics expected to be informative for their skill in projecting mid-century regional temperature and precipitation changes. The pr...
The Gálvez Davison Index (GDI) is a thermodynamic diagnostic designed to summarize convective favorability in the tropical regions, yet its transferability across complex terrain and heterogeneous hydroclimates remains u...
Climate oscillations are intrinsically out-of-equilibrium phenomena, yet the connection between their predictability and nonequilibrium thermodynamic properties remains unexplored. We develop a coarse-grained stochastic...