A low-dimensional dynamical systems approach for ensemble design and interpretation in climate science

Abstract. The design and use of conceptual models have been a longstanding and successful practice of mathematicians and scientists to study and gain insights about complex phenomena in climate and beyond. Here, we demonstrate how low-dimensional dynamical systems can also be useful in the design and interpretation of climate model ensembles. We argue that, provided they possess a small number of key characteristics, such systems can serve as computationally inexpensive laboratories for investigating questions of ensemble methodology that would be difficult to explore systematically in comprehensive Earth System Models. To this end, we identify the characteristics required of informative low-dimensional systems, formalise a framework for their use, and illustrate the approach through a series of examples.