Convectively coupled equatorial waves

By G. Kiladis, M. Wheeler, P. Haertel, K. Straub, P. Roundy. 2009

930 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/c651971a868b4c61a6e6523c4bd475fe7849e2e7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. E. Maloney
2. Chidong Zhang
3. David A. Randall
4. Duane Waliser
5. Daehyun Kim
6. A. Sobel
7. C. DeMott
8. Andrew J. Majda

In Global and Planetary Change

1. E. Maloney
2. Chidong Zhang
3. David A. Randall
4. Duane Waliser
5. Daehyun Kim
6. A. Sobel
7. C. DeMott
8. Á. Adames

Citations in the corpus

• A Comparison of OLR and Circulation-Based Indices for Tracking the MJO (2014, background): “coupled modes, since those are generally associated with a much smaller OLR spatial scale than the intraseasonal EOFs (Kiladis et al. 2009).”
• The Roles of Equatorial Trapped Waves and Internal Inertia–Gravity Waves in Driving the Quasi-Biennial Oscillation. Part I: Zonal Mean Wave Forcing (2010, background): “Convectively coupled EQWs could be the source of EQWs propagating into the stratosphere (Wheeler et al. 2000; Kawatani et al. 2009; Kiladis et al. 2009).”
• MJO and Convectively Coupled Equatorial Waves Simulated by CMIP5 Climate Models (2013, background): “These so-called convectively coupled equatorial waves (CCEWs) include Kelvin, equatorial Rossby (ER), mixed Rossby–gravity (MRG), eastward inertio-gravity (EIG), and westward inertio-gravity (WIG) waves (Takayabu 1994; WK; Kiladis et al. 2009).”
• LMDZ5B: the atmospheric component of the IPSL climate model with revisited parameterizations for clouds and convection (2013, methodology): “, Kiladis et al. 2009) or how it relates to the Madden-Julian Oscillation (MJO, Zhang 2005; Waliser et al. 2009). The raw spectrum of rainfall anomalies (Fig. 21a–c) was computed for each latitude between 15S and 15N, for successive overlapping segments of data (256-day long, with 206 days of overla”
• Three-Dimensional Structure and Evolution of the MJO and Its Relation to the Mean Flow (2014, background): “10c), the MJO-related easterly anomalies along 328N at the date line overlie the climatological-mean jet exit region and are thereby capable of extracting kinetic energy from themean flow, as described in Simmons et al. (1983) and Nakamura et al.”
• An Idealized Semi-Empirical Framework for Modeling the Madden–Julian Oscillation (2012, background): “consistent with the speed found in observations by Maloney and Shaman (2008) for the observed propagation of the MJO into the Atlantic, and that found in GCM simulations for the Kelvin wave response to the switching on of a localized SST anomaly (Maloney and Sobel 2007).”
• Multiscale Convective Organization and the YOTC Virtual Global Field Campaign (2012, background): “As the leading mode of tropical intraseasonal variability (e.g., Zhang 2005; Kiladis et al. 2009) and unforced convective organization ranging from cumulus to planetary scales, with cloud clusters and superclusters on the intervening scales (Nakazawa 1988), the MJO inf luences a wide range of weathe”
• A stochastic multicloud model for tropical convection (2010, background): “However, tropical convective systems have genuine multiscale and multiphysics dynamics in the sense that the larger scale features are not just a simple linear/rescaling transformation of the smaller scale features, unlike homogeneous turbulence, but they enjoy many dynamical differences as well [54”
• Global‐scale convective aggregation: Implications for the Madden‐Julian Oscillation (2015, background): “Tropical convection is organized on a wide range of scales, from gregarious cumulus towers to squall lines, cyclones and convectively coupled waves [Mapes, 1993; Kiladis et al., 2009].”
• Fifty Years of Research on the Madden‐Julian Oscillation: Recent Progress, Challenges, and Perspectives (2020, background): “The dynamical structures and cloud morphology of the MCSs and CCEWs display a large degree of self‐similarity to theMJO (Figure 2), with shallow convection at their leading edge, followed by deep convection and then stratiform precipitation (Kiladis et al., 2009; Mapes et al., 2006).”
• The GFDL Global Atmosphere and Land Model AM4.0/LM4.0: 1. Simulation Characteristics With Prescribed SSTs (2018, background): “We show the tropical symmetric (158S–158N) power spectrum, with background removed following Wheeler and Kiladis (1999), from both the upper (200 hPa) troposphere zonal wind (U200) and OLR.”