Machine learning methods in weather and climate applications: A survey
L Chen, B Han, X Wang, J Zhao, W Yang, Z Yang - Applied Sciences, 2023 - mdpi.com
With the rapid development of artificial intelligence, machine learning is gradually becoming
popular for predictions in all walks of life. In meteorology, it is gradually competing with …
popular for predictions in all walks of life. In meteorology, it is gradually competing with …
Foundation models for weather and climate data understanding: A comprehensive survey
As artificial intelligence (AI) continues to rapidly evolve, the realm of Earth and atmospheric
sciences is increasingly adopting data-driven models, powered by progressive …
sciences is increasingly adopting data-driven models, powered by progressive …
WeatherBench 2: A benchmark for the next generation of data‐driven global weather models
WeatherBench 2 is an update to the global, medium‐range (1–14 days) weather forecasting
benchmark proposed by (Rasp et al., 2020, https://doi. org/10.1029/2020ms002203) …
benchmark proposed by (Rasp et al., 2020, https://doi. org/10.1029/2020ms002203) …
A machine learning model that outperforms conventional global subseasonal forecast models
Skillful subseasonal forecasts are crucial for various sectors of society but pose a grand
scientific challenge. Recently, machine learning-based weather forecasting models …
scientific challenge. Recently, machine learning-based weather forecasting models …
Climateset: A large-scale climate model dataset for machine learning
Climate models have been key for assessing the impact of climate change and simulating
future climate scenarios. The machine learning (ML) community has taken an increased …
future climate scenarios. The machine learning (ML) community has taken an increased …
[HTML][HTML] Exploring Downscaling in High-Dimensional Lorenz Models Using the Transformer Decoder
BW Shen - Machine Learning and Knowledge Extraction, 2024 - mdpi.com
This paper investigates the feasibility of downscaling within high-dimensional Lorenz
models through the use of machine learning (ML) techniques. This study integrates …
models through the use of machine learning (ML) techniques. This study integrates …
Is Artificial Intelligence Providing the Second Revolution for Weather Forecasting?
The rapid advancement of artificial intelligence technologies, particularly in recent years,
has led to the emergence of several large parameter artificial intelligence weather forecast …
has led to the emergence of several large parameter artificial intelligence weather forecast …
Towards an end-to-end artificial intelligence driven global weather forecasting system
The weather forecasting system is important for science and society, and significant
achievements have been made in applying artificial intelligence (AI) to medium-range …
achievements have been made in applying artificial intelligence (AI) to medium-range …
Artificial intelligence for geoscience: Progress, challenges and perspectives
This paper explores the evolution of geoscientific inquiry, tracing the progression from
traditional physics-based models to modern data-driven approaches facilitated by significant …
traditional physics-based models to modern data-driven approaches facilitated by significant …
[HTML][HTML] Exploring the Origin of the Two-Week Predictability Limit: A Revisit of Lorenz's Predictability Studies in the 1960s
The 1960s was an exciting era for atmospheric predictability research: a finite predictability
of the atmosphere was uncovered using Lorenz's models and the well-acknowledged …
of the atmosphere was uncovered using Lorenz's models and the well-acknowledged …