Weather and climate models in 16-bit arithmetics: Number formats, error
mitigation and scope
Abstract
The need for high precision calculations with 64-bit or 32-bit
floating-point arithmetic for weather and climate models is questioned.
Lower precision numbers can accelerate simulations and are increasingly
supported by modern computing hardware. This paper investigates the
potential of 16-bit arithmetic when applied within a shallow water model
that serves as a medium complexity weather or climate application. There
are several 16-bit number formats that can potentially be used (IEEE
half precision, BFloat16, posits, integer and fixed-point). It is
evident that a simple change to 16-bit arithmetic will not be possible
for complex weather and climate applications as it will degrade model
results by intolerable rounding errors that cause a stalling of model
dynamics or model instabilities. However, if the posit number format is
used as an alternative to the standard floating-point numbers the model
degradation can be reduced to a tolerable minimum. Furthermore, a number
of mitigation methods, such as rescaling, reordering and
mixed-precision, are available to make model simulations resilient
against a precision reduction. If mitigation methods are applied, 16-bit
floating-point arithmetic can be used successfully within the shallow
water model. The results show the potential of 16-bit formats for at
least parts of complex weather and climate models where rounding errors
would be entirely masked by initial condition, model or discretization
error.