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Related Experiment Video

Updated: Dec 30, 2025

Exploring the Effects of Atmospheric Forcings on Evaporation: Experimental Integration of the Atmospheric Boundary Layer and Shallow Subsurface

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Published on: June 8, 2015

The physics of numerical analysis: a climate modelling case study.

¹Department of Physics, University of Oxford, Oxford, UK.

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences

|January 21, 2020

Summary

This summary is machine-generated.

Climate science, numerical analysis, and computer science require closer collaboration. This synergy is crucial for advancing high-performance computational science and climate modeling.

Keywords:

artificial intelligence climate modelling exascale computing low-precision modelling stochastic parametrization

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Area of Science:

Computational science
Climate science
Numerical analysis

Background:

High-performance computing is essential for modern scientific research.
Climate science increasingly relies on complex numerical simulations.
Interdisciplinary collaboration is vital for tackling grand challenges.

Purpose of the Study:

To advocate for enhanced synergy between climate science, numerical analysis, and computer science.
To highlight the importance of numerical algorithms in high-performance computational science.

Main Methods:

The article presents a perspective on the need for integration.
It draws upon the context of a discussion meeting on numerical algorithms.

Main Results:

A strong case is made for increased interdisciplinary collaboration.
The findings emphasize the critical role of advanced numerical methods.

Conclusions:

Closer integration of climate science, numerical analysis, and computer science will accelerate progress.
Developing efficient numerical algorithms is key to unlocking the potential of high-performance computing for climate research.