by Sukun Cheng, March 2026 To understand historical ocean changes, researchers produce reanalyses that reconstruct past states by combining numerical models with historical observations. Over the last century, observation quality…Read More >
data assimilation
Can you explain that again? Connecting explainable AI and data assimilation in Earth sciences
By Ieuan Higgs, February 2026 Perception of AI Artificial intelligence (AI) has become closely associated, in the public imagination, with large language models (LLMs). From a user perspective, AI chatbots such…Read More >
Gaussian anamorphosis for log-normal distributions
By Yumeng Chen, January 2026. Limitations of the normal distribution in data assimilation Operational data assimilation methods typically perform best when both background (forecast) and observation errors can be approximated…Read More >
Improving How We Represent the Land in Earth System Models
By Natalie Douglas, January 2026 A recent community paper, Parameter Estimation in Land Surface Models: Challenges and Opportunities with Data Assimilation and Machine Learning, addresses a deceptively simple question with…Read More >
11th International Symposium on Data Assimilation
By Alison Fowler At the end of September, I joined approximately 100 scientists from operational centres and academia, each contributing to progress in data assimilation. Together in Melbourne for the…Read More >
The value of observations for weather prediction in the age of machine learning
by Sarah L Dance A few months ago, on 25th February 2025, our colleagues at ECMWF (European Centre for Medium-range Weather Forecasts) took their deep-learning-based global weather forecasting system, known…Read More >
