Developing the next-generation climate system models: challenges and achievements.
Although climate models have been improving in accuracy and efficiency over the past few decades, it now seems that these incremental improvements may be slowing. As tera/petascale computing becomes massively parallel, our legacy codes are less suitable, and even with the increased resolution that we are now beginning to use, these models cannot represent the multiscale nature of the climate system. This paper argues that it may be time to reconsider the use of adaptive mesh refinement for weather and climate forecasting in order to achieve good scaling and representation of the wide range of spatial scales in the atmosphere and ocean. Furthermore, the challenge of introducing living organisms and human responses into climate system models is only just beginning to be tackled. We do not yet have a clear framework in which to approach the problem, but it is likely to cover such a huge number of different scales and processes that radically different methods may have to be considered. The challenges of multiscale modelling and petascale computing provide an opportunity to consider a fresh approach to numerical modelling of the climate (or Earth) system, which takes advantage of the computational fluid dynamics developments in other fields and brings new perspectives on how to incorporate Earth system processes. This paper reviews some of the current issues in climate (and, by implication, Earth) system modelling, and asks the question whether a new generation of models is needed to tackle these problems.
Slingo
Julia
J
NCAS-Climate, Walker Institute for Climate Research, University of Reading, Reading RG6 6AH, UK. j.m.slingo@reading.ac.uk
Bates
Kevin
K
Nikiforakis
Nikos
N
Piggott
Matthew
M
Roberts
Malcolm
M
Shaffrey
Len
L
Stevens
Ian
I
Vidale
Pier Luigi
PL
Weller
Hilary
H
D002980:Climate; D055907:Climatic Processes; D003198:Computer Simulation; D004463:Ecology / Q000379:methods* / Q000639:trends*; D020407:Internet; D008962:Models, Theoretical; D012106:Research / Q000639:trends*; D012586:Science / Q000379:methods / Q000639:trends