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

Abstract

Nudging is a simulation technique widely used in sensitivity studies and in the evaluation of atmosphere models. Care is needed in the experimental setup in order to achieve the desired constraint on the simulated atmospheric processes without introducing undue intervention. In this study, sensitivity experiments are conducted with the Energy Exascale Earth System Model (E3SM) Atmosphere Model Version 1 (EAMv1) to identify setups that can give results representative of the model's long-term climate and meanwhile reasonably capture characteristics of the observed meteorological conditions to facilitate the comparison of model results with measurements. We show that when the prescribed meteorological conditions are temporally interpolated to the model time to constrain EAM's horizontal winds at each time step, a nudged simulation can reproduce the characteristic evolution of the observed weather events (especially in middle and high latitudes) as well as the model's long-term climatology, although nudging also leads to nonnegligible regional changes in wind-driven aerosol emissions, low-level clouds in the stratocumulus regime, and cloud and precipitation near the maritime continent. Compared to its predecessor model used in an earlier study, EAMv1 is less sensitive to temperature nudging, although significant impacts on the cloud radiative effects still exist. EAMv1 remains very sensitive to humidity nudging. Constraining humidity substantially improves the correlation between the simulated and observed tropical precipitation but also leads to large changes in the long-term statistics of the simulated precipitation, clouds, and aerosol lifecycle. Plain Language SummaryFor the development and application of numerical weather and climate models, it is often useful to constrain a numerical experiment so that the evolution of the meteorological conditions follows a specific pathway. One of the techniques to apply such constraints is nudging, which introduces additional terms to the model equations. This study performs and analyzes sensitivity experiments with an attempt to identify implementations of nudging that can provide sufficient constraints without severely interfering with the simulations.

Aerosols in the E3SM Version 1: New Developments and Their Impacts on Radiative Forcing

“…The same nudging methodology has been used in previous AeroCom model intercomparison studies for aerosol indirect effects among different climate models or within the same model with modified aerosol‐cloud physics (e.g., Ghan et al, ; Gryspeerdt et al 2017). Sun et al () found that the interannual variability of mean PD cloud forcing in EAMv1 is small for the nudged‐wind simulations.…”

A Lagrangian Perspective on Tropical Anvil Cloud Lifecycle in Present and Future Climate

“…Because many fields were archived hourly for subsequent analysis, longer simulations were not possible due to storage space limitations. The NUDGE simulation uses a linear interpolation nudging technique developed by Sun et al (2019). The model horizontal wind fields were nudged at every model time step to an interpolated value based on six hourly ERA-Interim reanalysis data (Dee GASPARINI ET AL.…”

Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction Project, Phase I (LS4P-I): Organization and Experimental design

“…To conduct LS4P type research, the modeling groups have to develop an approach in nudging the reanalysis data for a real time initialization. Nudging is one of the simplest data assimilation methods (Hoke and Anthes, 1976) and has been widely used in climate model evaluation and sensitivity studies (e.g., Xie et al, 2008;Sun et al, 2019;Tang et al, 2019) to constrain the simulations towards a predefined reference (the reanalysis data in this case) and hence to facilitate time-575 specific comparisons between model and observations. For the LS4P simulations, E3SM and CESM2…”