Machine learning for weather and climate are worlds apart.

ABSTRACT: Modern weather and climate models share a common heritage and often even components; however, they are used in different ways to answer fundamentally different questions. As such, attempts to emulate them using machine learning should reflect this. While the use of machine learning to emulate weather forecast models is a relatively new endeavour, there is a rich history of climate model emulation. This is primarily because while weather modelling is an initial condition problem, which intimately depends on the current state of the atmosphere, climate modelling is predominantly a boundary condition problem. To emulate the response of the climate to different drivers therefore, representation of the full dynamical evolution of the atmosphere is neither necessary, or in many cases, desirable.

SUBMITTER: Watson-Parris D 

PROVIDER: S-EPMC7898127 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature