Assessing the Dynamic Versus Thermodynamic Origin of Climate Model Biases

Abstract

Global climate models present systematic biases, among others, a tendency to overestimate hot and dry summers in midlatitude regions. Here we investigate the origin of such biases in the Community Earth System Model. To disentangle the contribution of dynamics and thermodynamics, we perform simulations that include nudging of horizontal wind and compare them to simulations with a free atmosphere. Prescribing the observed large‐scale circulation improves the modeled weather patterns as well as many related fields. However, the larger part of the temperature and precipitation biases of the free atmosphere configuration remains after nudging, in particular, for extremes. Our results suggest that thermodynamical processes, including land‐atmosphere coupling and atmospheric parameterizations, drive the errors present in Community Earth System Model. Our result may apply to other climate models and highlight the importance of distinguishing thermodynamic and dynamic sources of biases in present‐day global climate models.

Explaining Extreme Events of 2017 from a Climate Perspective

“…ES2). Such a separation could also facilitate tracking down and communicating the source of attribution uncertainties from both dynamic and thermodynamic perspectives (Vautard et al 2016;Wehrli et al 2018). least three consecutive days with T max exceeding the 90th percentile (centered on a 30-day window) for the reference period of 1971-2000 (Fischer and Schär 2010).…”

Anthropogenic Warming has Substantially Increased the Likelihood of July 2017–Like Heat Waves over Central Eastern China

“…ES2). Such a separation could also facilitate tracking down and communicating the source of attribution uncertainties from both dynamic and thermodynamic perspectives (Vautard et al 2016;Wehrli et al 2018).…”

Storylines of the 2018 Northern Hemisphere heat wave at pre-industrial and higher global warming levels

“…To impose the large-scale circulation of the event year (2018) in the model, we use atmospheric nudging of the horizontal winds. The approach is described and validated in Wehrli et al (2018) and Wehrli et al (2019). The horizontal winds are relaxed toward observations using a height-dependent nudging function (for the profile see Wehrli et al, 2018).…”

“…The approach is described and validated in Wehrli et al (2018) and Wehrli et al (2019). The horizontal winds are relaxed toward observations using a height-dependent nudging function (for the profile see Wehrli et al, 2018). At the surface the nudging strength is set to zero, meaning that the land surface can interact with the atmosphere through surface turbulent fluxes, resulting in balanced surface climate and winds.…”

“…At the surface the nudging strength is set to zero, meaning that the land surface can interact with the atmosphere through surface turbulent fluxes, resulting in balanced surface climate and winds. The large-scale circulation (mostly above 700 hPa) is forced to follow the observations and thus ensures that the observed large-scale weather patterns are reproduced (see Kooperman et al, 2012;Wehrli et al, 2018;Zhang et al, 2014). As a proxy for the observed winds, we use zonal and meridional 6-hourly wind fields from the ERA-Interim reanalysis (Dee et al, 2011).…”