MJO baseline metrics

Overview

The MJO consists of large-scale regions of enhanced and suppressed convection, and associated circulation anomalies in the tropics that propagate eastward, mainly over the eastern hemisphere, with a time scale of ~30-60 days (Madden and Julian 1971, 1972, 1994). Its large-scale nature and period are easily seen via frequency-wavenumber decomposition of near-equatorial data (10°S to 10°N), which partitions the raw anomalies into eastward and westward propagating components and also as a function of frequency (cycles/day). The frequency-wavenumber decomposition technique has been widely used to assess if models properly represent this basic characteristic of the MJO (e.g., CLIVAR MJO Working Group 2009; Kim et al. 2009; Ahn et al. 2017).

Here we apply the frequency-wavenumber decomposition method to precipitation from observations (GPCP-based; 1997-2010) and the CMIP5 and CMIP6 Historical simulations for 1985-2004. For disturbances with wavenumbers 1-3 and frequencies corresponding to 30-60 days it is clear in observations that the eastward propagating signal dominates over its westward propagating counterpart. Thus, an important metric is the eastward/westward power ratio (EWR) for the above-mentioned wavenumbers and frequencies, which is about 2.5 in observations.

The EWR results are based on the work of Ahn et al. (2017). Implementation of these and other MJO analysis into the PMP is part of a PCMDI collaboration with Prof. Daehyun Kim (University of Washington) and the WGNE MJO Task Force.

Demo

• PMP demo Jupyter notebook

Results

• Interactive graphics for PMP-calculated MJO Metrics

• Description for the results

References

• Ahn, M.-S., D. Kim, K. R. Sperber, I.-S. Kang, E. Maloney, D. Waliser, H. Hendon, 2017: MJO simulation in CMIP5 climate models: MJO skill metrics and process-oriented diagnosis. Clim. Dynam., 49, 4023-4045. doi: 10.1007/s00382-017-3558-4.

• CLIVAR Madden-Julian Oscillation Working Group (Waliser, D., K. Sperber, H. Hendon, D. Kim, E. Maloney, M. Wheeler, K. Weickmann,, C. Zhang, L. Donner, J. Gottschalck, W. Higgins, I.-S. Kang, D. Legler, M. Moncrieff, S. Schubert, W. Stern, F. Vitart, B. Wang, W. Wang, and S. Woolnough), 2009: MJO simulation diagnostics. J. Clim., 22, 3006-3029. doi: 10.1175/2008JCLI2731.1.

• Kim, D., K. R. Sperber, W. S. Stern, D. Waliser, I.-S. Kang, E. Maloney, W. Wang, K. Weickmann, J. Benedict, M. Khairoutdinov, M.-I. Lee, R. Neale, M. Suarez, K. Thayer-Calder, and G. Zhang, 2009: Application of MJO simulation diagnostics to climate models. J. Clim., 22, 6413-6436. doi: 10.1175/2009JCLI3063.1.