MJO Simulation Diagnostics

By Duane Waliser, K. Sperber, H. Hendon, Daehyun Kim, E. Maloney, M. Wheeler, K. Weickmann, Chidong Zhang, Leo Donner, Jon Gottschalck and 9 more. 2009

320 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/f510047319c7ae90b7ee1c3373fdc7e79bb52c7c

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. C. DeMott
3. N. Klingaman
4. Chidong Zhang
5. Daehyun Kim
6. Hai Lin
7. Á. Adames
8. Xianan Jiang

In Global and Planetary Change

1. E. Maloney
2. C. DeMott
3. N. Klingaman
4. Chidong Zhang
5. Daehyun Kim
6. Hai Lin
7. Á. Adames
8. Xianan Jiang

Citations in the corpus

• Evaluation of CMIP6 DECK Experiments With CNRM‐CM6‐1 (2019, background): “A common way to diagnose this variability consists in computing the space‐time coherence squared and phase lag spectra between the daily averaged outgoing longwave radiation (OLR) and 850‐hPa zonal wind (Waliser et al., 2009; Wheeler & Kiladis, 1999), as shown on Figure 19.”
• Overview of the Norwegian Earth System Model (NorESM2) and key climate response of CMIP6 DECK, historical, and scenario simulations (2020, background): “…characterised by a specific feature in wavenumber–frequency spectrum of equatorial 850 hPa zonal wind (U850) and outgoing long-wave radiation (OLR; Waliser et al., 2009), associated with wavenumbers 1–3, a maximum at wavenumber 1, and periods between 30 and 80 d. NorESM2-LM and NorESM2-MM…”
• Atmospheric component of the MPI‐M Earth System Model: ECHAM6 (2013, methodology): “Nov-Apr 20–100day filtered OLR (color) and 850 hPa wind anomalies regressed on the MJO index constructed from the square amplitude of the first two principle component time series derived from the multivariate EOF, following Waliser et al. [2009]. STEVENS ET AL.”
• Fifty Years of Research on the Madden‐Julian Oscillation: Recent Progress, Challenges, and Perspectives (2020, background): “3 of 64 efforts to develop advanced MJO process‐oriented diagnostics (Gottschalck et al., 2010; Jiang, D. Kim, Maloney, 2020; D. Kim et al., 2009; Waliser et al., 2009; Wheeler & Maloney, 2013, see details in sections 3.3 and 3.4).”
• MJO and Convectively Coupled Equatorial Waves Simulated by CMIP5 Climate Models (2013, methodology): “Lag correlations between each longitude and a given longitude have been recommended to reveal zonal propagation by the MJO Working Group (Waliser et al. 2009) and used in various studies (e.g., Lin et al. 2006; Kim et al. 2011b; Weaver et al. 2011).”