大气与海洋物理
Oceanic processes at fine scales are crucial yet difficult to observe accurately due to limitations in satellite and in-situ measurements. The Surface Water and Ocean Topography (SWOT) mission provides high-resolution Sea Surface Height…
Despite advances in climate modeling, simulating the El Ni\~no-Southern Oscillation (ENSO) remains challenging due to its spatiotemporal diversity and complexity. To address this, we build upon existing model hierarchies to develop a new…
Similar to conventional video generation, current deep learning-based weather prediction frameworks often lack explicit physical constraints, leading to unphysical outputs that limit their reliability for operational forecasting. Among…
Infrasound sensing offers critical capabilities for detecting and geolocating bolide events globally. However, the observed back azimuths, directions from which infrasound signals arrive at stations, often differ from the theoretical…
Variations in stratospheric atmospheric circulation significantly influence tropospheric weather and climate, and understanding these variations can guide stratospheric aircraft development and operations. Despite a century of progress,…
The reentry of the OSIRIS-REx Sample Return Capsule (SRC) on September 24, 2023, presented a rare opportunity to study atmospheric entry dynamics through a dense network of ground-based infrasound sensors. As the first interplanetary…
The reconstruction of deep ocean currents is a major challenge in data assimilation due to the scarcity of interior data. In this work, we present a proof of concept for deep ocean flow reconstruction using a Physics-Informed Neural Network…
The development of robust Early Warning Signals (EWS) is necessary to quantify the risk of crossing tipping points in the present-day climate change. Classically, EWS are statistical measures based on time series of climate state variables,…
As the global climate changes, urban heat island (UHI) is a critical factor in ever expanding urban landscape, studying and mitigating the UHI is important for remediating climate change and providing for the human and ecosystem health…
We evaluate the performance of various configurations of the Canadian Regional Climate Model (CRCM6-GEM5) in simulating 10-meter wind speeds using data from 27 AmeriFlux stations across North America. The assessment employs a hierarchy of…
The livelihood and food security of more than a billion people depend on the Indian monsoon (IM). Yet, a universal definition of the large-scale season and progress of IM is missing. Even though IM is a planetary-scale convectively coupled…
The Indian monsoon, a multi-variable process causing heavy rains during June-September every year, is very heterogeneous in space and time. We study the relationship between rainfall and Outgoing Longwave Radiation (OLR, convective cloud…
Nowadays, the subsistent anisotropic non-Kolmogorov (ANK) turbulence models are all established on the supposition that the long axis of turbulence cell ought to be level with the ground. Nevertheless, Beason et al. and Wang et al. have…
Accurate precipitation estimates at individual locations are crucial for weather forecasting and spatial analysis. This study presents a paradigm shift by leveraging Deep Neural Networks (DNNs) to surpass traditional methods like Kriging…
Simulating the QBO remains a formidable challenge partly due to uncertainties in representing convectively generated gravity waves. We develop an end-to-end uncertainty quantification workflow that calibrates these gravity wave processes in…
The Canadian Fire Weather Index (FWI) is widely used to assess wildfire danger and relies on meteorological data at local noon. However, climate models often provide only daily aggregated data, which poses a challenge for accurate FWI…
To this day, accurately simulating local-scale precipitation and reliably reproducing its distribution remains a challenging task. The limited horizontal resolution of Global Climate Models is among the primary factors undermining their…
Numerical Weather Prediction (NWP) has advanced significantly in recent decades but still faces challenges in accuracy, computational efficiency, and scalability. Data-driven weather models have shown great promise, sometimes surpassing…
An attempt is made to estimate and forecast the trend of the global annual and monthly mean temperatures. The results of a conventional statistical analysis suggest that in the absence of unforeseeable events such as a sudden acceleration…
Cumulative emissions accounting for carbon-dioxide (CO2) is founded on recognition that global warming in Earth System Models (ESMs) is roughly proportional to cumulative CO2 emissions, regardless of emissions pathway. However, cumulative…