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Creators/Authors contains: "Kang, Wanying"

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  1. Abstract

    We examine the hypothesis that the observed connection between the stratospheric quasi-biennial oscillation (QBO) and the strength of the Madden–Julian oscillation (MJO) is modulated by the sea surface temperature (SST)—for example, by El Niño–Southern Oscillation (ENSO). A composite analysis shows that, globally, La Niña SSTs are remarkably similar to those that occur during the easterly phase of the QBO. A maximum covariance analysis suggests that MJO power and SST are strongly linked on both the ENSO time scale and the QBO time scale. We analyze simulations with a modified configuration of version 2 of the Community Earth System Model, with a high top and fine vertical resolution. The model is able to simulate ENSO, the QBO, and the MJO. The ocean-coupled version of the model simulates the QBO, ENSO, and MJO, but does not simulate the observed QBO–MJO connection. When driven with prescribed observed SST anomalies based on composites for QBO east and QBO west (QBOE and QBOW), however, the same atmospheric model produces a modest enhancement of MJO power during QBOE relative to QBOW, as observed. We explore the possibility that the SST anomalies are forced by the QBO itself. Indeed, composite Hovmöller diagrams based on observations show the propagation of QBO zonal wind anomalies all the way from the upper stratosphere to the surface. Also, subsurface ocean temperature composites reveal a similarity between the western Pacific and Indian Ocean subsurface signal between La Niña and QBOE.

     
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  2. Abstract

    The slope of the quasi-linear relation between planetary outgoing longwave radiation (OLR) and surface temperature (TS) is an important parameter measuring the sensitivity of Earth’s climate system. The primary objective of this study is to seek a general explanation for the quasi-linear OLR–TSrelation that remains valid regardless of the strength of the atmospheric window’s narrowing effect on planetary thermal emission at higher temperatures. The physical understanding of the quasi-linear OLR–TSrelation and its slope is gained from observation analysis, climate simulations with radiative–convective equilibrium and general circulation models, and a series of online feedback suppression experiments. The observed quasi-linear OLR–TSrelation manifests a climate footprint of radiative (such as the greenhouse effect) and nonradiative processes (poleward energy transport). The former acts to increase the meridional gradient of surface temperature and the latter decreases the meridional gradient of atmospheric temperatures, causing the flattening of the meridional profile of the OLR. Radiative processes alone can lead to a quasi-linear OLR–TSrelation that is more steeply sloped. The atmospheric poleward energy transport alone can also lead to a quasi-linear OLR–TSrelation by rerouting part of the OLR to be emitted from a warmer place to a colder place. The combined effects of radiative and nonradiative processes make the quasi-linear OLR–TSrelation less sloped with a higher degree of linearity. In response to anthropogenic radiative forcing, the slope of the quasi-linear OLR–TSrelation is further reduced via stronger water vapor feedback and enhanced poleward energy transport.

    Significance Statement

    The slope of the quasi-linear relation between planetary outgoing longwave radiation (OLR) and surface temperature (TS) is an important parameter measuring the sensitivity of Earth’s climate system. The observed quasi-linear OLR–TSrelation manifests a climate footprint of radiative (greenhouse effect) and nonradiative processes (poleward energy transport). Radiative processes alone can lead to a quasi-linear OLR–TSrelation that is more steeply sloped. The atmospheric poleward energy transport alone can also lead to a quasi-linear OLR–TSrelation by rerouting part of the OLR to be emitted from a warmer place to a colder place. The combined effects of radiative and nonradiative processes make the quasi-linear OLR–TSrelation less sloped with a higher degree of linearity.

     
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