大气与海洋物理
Many forecast applications require high frequency temporal resolution, yet most state-of-the-art data-driven weather forecasting systems operate at 6-hourly resolution. Although direct hourly forecasting is possible, it suffers from error…
Best-track data have been typically used to explore long-term changes in typhoon intensity over the western North Pacific (WNP). However, the methods used to construct best-track intensities have changed over the past several decades.…
Identifying the causes of Earth's extremes is challenging because counterfactual experiments are not possible in the observed world, while numerical experiments are computationally expensive and subject to biases. Data-driven causal…
The advent of expendable wave buoys has greatly expanded the data available for evaluating and calibrating wave models. Ideally, the newer buoys now drifting around the world's oceans would be merged with conventional time series…
By analysis of the reflected solar contribution to mid-infrared radiance spectra collected by the IASI instrument, we investigate the influences of both the wind and significant wave height on the wave-slope probability distribution…
Coastal trapped wave modes are shown to be orthogonal in the sense that they make independent contributions to the energy of the wave field. The hydrostatic Boussinesq dynamics on an $f$-plane, linearized around a state of rest, are…
Earth system reanalysis datasets are foundational for weather and climate research and provide the gridded training data used by most machine learning weather prediction systems. Here we show results from a prototype system that suggest…
Super-resolution estimates a high-resolution image from a low-resolution image and has been used for downscaling and resolution enhancement of observations in meteorology. Super-resolution Gaussian process regression with a steering kernel…
Global Navigation Satellite Systems (GNSS), best known for positioning, also serve weather science, as atmospheric water vapour delays their signals. This delay, the Zenith Wet Delay (ZWD), is a direct, all-weather measure of column…
Data-driven models now rival numerical weather prediction in the medium range, but extending them to sub-seasonal lead times raises challenges absent at shorter horizons. Errors accumulate over long autoregressive rollouts, systematic…
This study proposes a real-time remote-sensing-guided decision-support framework for cloud-seeding operations using high frequency geostationary satellite and ground weather radar observations. The framework integrates cloud assessment,…
Modern machine-learning weather prediction (MLWP) has largely inherited the initial-value-problem (IVP) framing of numerical weather prediction (NWP). This inheritance leads to a dominant paradigm of learned autoregressive time-stepping and…
Ensemble Kalman filters (EnKFs) are widely used for data assimilation in geophysical systems. Among various implementations, the local ensemble transform Kalman filter (LETKF) has gained popularity because of its computational efficiency.…
We develop a Wigner-based phase-space framework for mean paraxial wave propagation in random media. Starting from the random parabolic wave equation, we derive the exact evolution of the realization-dependent Wigner distribution and…
We study the importance of surface characteristics when forecasting near-surface variables with a data-driven weather prediction model. To target the challenge of predicting small-scale weather conditions at high resolution, we introduce a…
Traditionally, midlatitude storm tracks are viewed as being driven by meridional temperature gradients maintained by differential solar heating. Yet in the Southern Hemisphere, storm activity remains strong even when the summertime…
The Earth's gravitational field exerts a significant influence on atmospheric dynamics, including the behavior of seasonal wind flux, defined by periodic variations in wind speed and direction. While temperature gradients and Earth's…
The limited predictive skill of forecasts makes it difficult for decision-makers to act decisively. Advance assessment of real-time forecast credibility can strengthen decision-makers' resolve and confidence to act. Such an assessment can…
With the data-driven artificial intelligence/machine learning (AI/ML) models having demonstrated their ability to extend the prediction horizon of large-scale weather at a fraction of computational cost of numerical weather prediction…
Kilometer-scale convection shapes precipitation extremes, tropical organization, and cloud feedbacks, but most global atmospheric models approximate these processes at 25-100 km resolution. Global storm-resolving physics models resolve…