The Role of Atmosphere Feedbacks during ENSO in the CMIP3 Models. Part III: The Shortwave Flux Feedback

Abstract

International audiencePrevious studies using coupled general circulation models (GCMs) suggest that the atmosphere model plays a dominant role in the modeled El Niño–Southern Oscillation (ENSO), and that intermodel differences in the thermodynamical damping of sea surface temperatures (SSTs) are a dominant contributor to the ENSO amplitude diversity. This study presents a detailed analysis of the shortwave flux feedback (αSW) in 12 Coupled Model Intercomparison Project phase 3 (CMIP3) simulations, motivated by findings that αSW is the primary contributor to model thermodynamical damping errors.A “feedback decomposition method,” developed to elucidate the αSW biases, shows that all models underestimate the dynamical atmospheric response to SSTs in the eastern equatorial Pacific, leading to underestimated αSW values. Biases in the cloud response to dynamics and the shortwave interception by clouds also contribute to errors in αSW. Changes in the αSW feedback between the coupled and corresponding atmosphere-only simulations are related to changes in the mean dynamics.A large nonlinearity is found in the observed and modeled SW flux feedback, hidden when linearly calculating αSW. In the observations, two physical mechanisms are proposed to explain this nonlinearity: 1) a weaker subsidence response to cold SST anomalies than the ascent response to warm SST anomalies and 2) a nonlinear high-level cloud cover response to SST. The shortwave flux feedback nonlinearity tends to be underestimated by the models, linked to an underestimated nonlinearity in the dynamical response to SST. The process-based methodology presented in this study may help to correct model ENSO atmospheric biases, ultimately leading to an improved simulation of ENSO in GCMs

Strong and moderate nonlinear El Niño regimes

“…The good correspondence between the convective and wind stress response supports the conclusion that the nonlinearity in the Bjerknes feedback emerges from the triggering of deep convection. This is also consistent with the nonlinearity in the shortwave radiative feedback, that becomes negative as clouds transition from low to deep convective under strong surface warming (Lloyd et al 2012). …”

“…On the other hand, the radiative feedback associated with clouds becomes negative for strong EN and reduces the net warming (see Sect. 3.3;Lloyd et al 2012). In Drakkar, the decay of the strong EN in 1983 and 1998 (the two largest negative T in Fig.…”

“…In Drakkar, the decay of the strong EN in 1983 and 1998 (the two largest negative T in Fig. 5) is dominated by entrainment and surface heat fluxes (not shown), the latter of which would be associated with enhanced cloudiness response during the strong EN (Lloyd et al 2012), although with the use of a deeper layer (e.g. 150 m) for the heat budget, linear zonal advection is the dominant term (not shown).…”

Cloud climatologies from the infrared sounders AIRS and IASI: strengths and applications

“…Similar techniques were already utilized in other studies related to El Niño-Southern Oscillation (ENSO) and cloud feedback (e.g. Lloyd et al, 2012;Zhou et al, 2013;Liu et al, 2017). Figure 12 presents the change in amount of high opaque cloud (mostly of convective origin), in thick cirrus (often formed from convective outflow as anvils) and in thin cirrus (which might be formed as anvil or via in situ freezing) per kelvin of global surface warming, obtained as the linear slopes of these deseasonalized monthly anomaly relationships.…”

Contrasting the eastern Pacific El Niño and the central Pacific El Niño: process-based feedback attribution

“…air-sea heat fluxes, especially latent heat flux, have been found to have more important impacts on the SST anomalies over the central Pacific, compared to the SST anomalies over the eastern Pacific (e.g., Kao and Yu 2009;Kug et al 2010). Cloud shortwave and latent heat feedbacks usually represent a local damping of SST anomalies (Lloyd et al 2011(Lloyd et al , 2012. Water-vapor feedback acts to enhance SST anomalies (e.g., Chandra et al 1998Chandra et al , 2007Dessler and Wong 2009).…”