Mean State Biases and Interannual Variability Affect Perceived Sensitivities of the Madden‐Julian Oscillation to Air‐Sea Coupling

Abstract

Atmosphere‐ocean feedbacks often improve the Madden‐Julian oscillation (MJO) in climate models, but these improvements are balanced by mean state biases that can degrade the MJO through changing the basic state on which the MJO operates. The Super‐Parameterized Community Atmospheric Model (SPCAM3) produces perhaps the best representation of the MJO among contemporary models, which improves further in a coupled configuration (SPCCSM3) despite considerable mean state biases in tropical sea surface temperatures and rainfall. We implement an atmosphere‐ocean‐mixed‐layer configuration of SPCAM3 (SPCAM3‐KPP) and use a flux‐correction technique to isolate the effects of coupling and mean state biases on the MJO. When constrained to the observed ocean mean state, air‐sea coupling does not substantially alter the MJO in SPCAM3, in contrast to previous studies. When constrained to the SPCCSM ocean mean state, SPCAM3‐KPP fails to produce an MJO, in stark contrast to the strong MJO in SPCCSM3. Further KPP simulations demonstrate that the MJO in SPCCSM3 arises from an overly strong sensitivity to El Niño–Southern Oscillation events. Our results show that simulated interannual variability and coupled‐model mean state biases affect the perceived response of the MJO to coupling. This is particularly concerning in the context of internal variability in coupled models, as many previous MJO sensitivity studies in coupled models used relatively short (20‐ to 50‐year) simulations that undersample interannual‐decadal variability. Diagnosing the effects of coupling on the MJO requires simulations that carefully control for mean state biases and interannual variability.

Fifty Years of Research on the Madden‐Julian Oscillation: Recent Progress, Challenges, and Perspectives

“…Recent studies provide the context for critical issues (section 2) and prevailing theories (section 3.2) of the MJO. The coupled feedbacks analyzed in DeMott et al (2019) and Klingaman and Demott (2020) and their effects on the mean moisture distribution strongly support the WTG moisture mode theory of the MJO. The increased BL moisture export east of MJO convection in two CGCMs in DeMott et al (2019) supports the trio‐interaction theory; the surprising result that the two other CGCMs exhibited weaker BL moisture export, despite improved MJO propagation, suggests a need for greater scrutiny of BL‐moisture‐convection feedbacks in models and observations.…”

“…Klingaman and Demott (2020) demonstrated that the MJO response to ENSO in a CGCM may lead to incorrect perceptions of how intraseasonal coupled feedbacks affect MJO. In the full CGCM, the MJO improved substantially with coupling, compared to the corresponding AGCM with prescribed CGCM SSTs (DeMott et al, 2014).…”

“…It is best practice to force the AGCM with CGCM monthly mean SSTs. Klingaman and Demott (2020) demonstrated that it is then helpful to diagnose MJO sensitivity to ENSO. Finally, thermodynamic ocean feedbacks to the MJO are best understood in an AGCM coupled to a 1‐D ocean mixed‐layer model constrained to observed, CGCM, or ENSO states.…”

Effects of Coupling a Stochastic Convective Parameterization with Zhang-McFarlane Scheme on Precipitation Simulation in the DOE E3SMv1 Atmosphere Model

“…For any changes in model physics parameterization that improve some aspects of the model performance, it is important that other aspects are not degraded. It is known in the climate modeling community that improved intraseasonal variability is often accompanied by a degradation of the mean state (e.g., Kim et al 2011;Klingaman and Demott, 2020). We showed that the mean states in tropospheric temperature, moisture as well as precipitation are not much different with or without the use of the stochastic convection scheme, and neither are the responses of mean precipitation and precipitation extremes to climate warming.…”

Changes to the Madden‐Julian Oscillation in Coupled and Uncoupled Aquaplanet Simulations With 4xCO2

“…Because we want to ensure an identical SST climate between uncoupled and coupled runs for the uncoupled climate change experiments described below, these SST climatologies from the coupled runs are used to force the uncoupled runs rather than starting from Equation 1. We note that the two SST profiles from the control CO 2 and the abrupt 4xCO 2 simulations with SOM show subtle differences in shape near the equator relative to the QOBS profile in Equation 1 that was used to derived Q flux because of the increased rainfall and associated strong turbulent fluxes into the atmosphere produced in this region with coupling ( Figure 1a, see also Klingaman & Demott, 2020). The mean precipitation patterns are characterized by a double Intertropical Convergence Zone (ITCZ) with maximum precipitation located near 10°in both hemispheres ( Figure 1b).…”