Can nudging be used to quantify model sensitivities in precipitation and cloud forcing?

Abstract

Efficient simulation strategies are crucial for the development and evaluation of high‐resolution climate models. This paper evaluates simulations with constrained meteorology for the quantification of parametric sensitivities in the Community Atmosphere Model version 5 (CAM5). Two parameters are perturbed as illustrating examples: the convection relaxation time scale (TAU), and the threshold relative humidity for the formation of low‐level stratiform clouds (rhminl). Results suggest that the fidelity of the constrained simulations depends on the detailed implementation of nudging and the mechanism through which the perturbed parameter affects precipitation and cloud. The relative computational costs of nudged and free‐running simulations are determined by the magnitude of internal variability in the physical quantities of interest, as well as the magnitude of the parameter perturbation. In the case of a strong perturbation in convection, temperature, and/or wind nudging with a 6 h relaxation time scale leads to nonnegligible side effects due to the distorted interactions between resolved dynamics and parameterized convection, while 1 year free‐running simulations can satisfactorily capture the annual mean precipitation and cloud forcing sensitivities. In the case of a relatively weak perturbation in the large‐scale condensation scheme, results from 1 year free‐running simulations are strongly affected by natural noise, while nudging winds effectively reduces the noise, and reasonably reproduces the sensitivities. These results indicate that caution is needed when using nudged simulations to assess precipitation and cloud forcing sensitivities to parameter changes in general circulation models. We also demonstrate that ensembles of short simulations are useful for understanding the evolution of model sensitivities.

Uncertainty quantification based cloud parameterization sensitivity analysis in the NCAR community atmosphere model

“…7). In line with the findings of Lin et al 57 , the decrease in PRECC to an increase in rhminl is also seen by indirectly affecting the stability of the low-level atmosphere and hence the convection (Fig. 7).…”

Impact of Nudging Strategy on the Climate Representativeness and Hindcast Skill of Constrained EAMv1 Simulations

“…For cases where detailed comparison with observation in specific meteorological events is not needed, we recommend to use CLIM for nudging. However, nudging toward CLIM can still affect the physical quantities that are sensitive to the nudged fields (e.g., dust emission in this study and circulation feedback to heating in Lin et al ()).…”

“…In contrast, nudging can reduce the divergence of sensitivity experiments caused by natural variability and hence allow for the detection of signal from a substantially smaller amount of data. Examples of studies in this category include Lohmann and Ferrachat (), Kooperman et al (), and Lin et al ().…”

Identifying Key Driving Processes of Major Recent Heat Waves

“…The large‐scale atmospheric circulation is prescribed using atmospheric nudging. Previous studies on nudging found a reliable adjustment of the atmospheric circulation with the underlying climatology of the other variables in the model not being fundamentally affected (Lin et al, ; Wehrli et al, ; Zhang et al, ). Thus, climatological biases remain after introducing nudging, which was also found for CESM (Wehrli et al, ).…”