Abstract

The Madden-Julian Oscillation (MJO) simulation diagnostics developed by MJO Working Group and the process-oriented MJO simulation diagnostics developed by MJO Task Force are applied to 37 Coupled Model Intercomparison Project phase 5 (CMIP5) models in order to assess model skill in representing amplitude, period, and coherent eastward propagation of the MJO, and to establish a link between MJO simulation skill and parameterized physical processes. Process-oriented diagnostics include the Relative Humidity Composite based on Precipitation (RHCP), Normalized Gross Moist Stability (NGMS), and the Greenhouse Enhancement Factor (GEF). Numerous scalar metrics are developed to quantify the results. Most CMIP5 models underestimate MJO amplitude, especially when outgoing longwave radiation (OLR) is used in the evaluation, and exhibit too fast phase speed while lacking coherence between eastward propagation of precipitation/convection and the wind field. The RHCP-metric, indicative of the sensitivity of simulated convection to low-level environmental moisture, and the NGMS-metric, indicative of the efficiency of a convective atmosphere for exporting moist static energy out of the column, show robust correlations with a large number of MJO skill metrics. The GEF-metric, indicative of the strength of the column-integrated longwave radiative heating due to cloud-radiation interaction, is also correlated with the MJO skill metrics, but shows relatively lower correlations compared to the RHCP- and NGMS-metrics. Our results suggest that modifications to processes associated with moisture-convection coupling and the gross moist stability might be the most fruitful for improving simulations of the MJO. Though the GEF-metric exhibits lower correlations with the MJO skill metrics, the longwave radiation feedback is highly relevant for simulating the weak precipitation anomaly regime that may be important for the establishment of shallow convection and the transition to deep convection.

Highlights

  • The Madden-Julian oscillation (MJO) is the dominant mode of tropical intraseasonal variability, and is characterized by eastward-propagating, planetary-scale envelops of convective cloud clusters that are tightly coupled with the largescale wind field

  • The Coupled Model Intercomparison Project phase 5 (CMIP5) models are validated against daily rainfall analyses from the Global Precipitation Climatology Project (GPCP; Huffman et al 2001) for 1997–2010 and the Tropical Rainfall Measuring Mission (TRMM 3B42 version 6; Huffman et al 2007) for 1998–2010, outgoing longwave radiation (OLR) from the Advanced Very High Resolution Radiometer (AVHRR; Liebmann and Smith 1996) for 1985–2004 and the Clouds and the Earth’s Radiant Energy System (CERES; Loeb et al 2009) for 2001–2010, specific humidity, air temperature, geopotential height, pressure velocity from the ECMWF Reanalysis (ERA-interim; Dee et al 2011) for 1985–2004, upper (250 hPa) and lower (850 hPa) tropospheric zonal winds (U250 and U850 hereafter) from the ECMWF Reanalysis and the NCEP–NCAR reanalysis (Kalnay et al 1996) for 1985–2004

  • This study applies the MJO diagnostics developed by the MJO Working Group (MJOWG) to 37 CMIP5 models, and formulates numerous MJO skill metrics that are used to assess the model performance in simulating the prominent features of the MJO

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Summary

Introduction

The Madden-Julian oscillation (MJO) is the dominant mode of tropical intraseasonal variability, and is characterized by eastward-propagating, planetary-scale envelops of convective cloud clusters that are tightly coupled with the largescale wind field. Kim et al (2014) presented the RHCP (Relative Humidity Composite based on Precipitation) diagnostic that indicates the sensitivity of simulated convection to low-level environmental moisture They showed that the amount of 700–850 hPa RH increase required for a transition from weak to strong rain regimes had a robust statistical relationship with the East/West power ratio of equatorial precipitation (correlation coefficient is about 0.72 when 28 models are used).

Participating models and validation datasets
MJO simulation diagnostics and MJO skill metrics
37 NorESM1-M
Process‐oriented diagnosis
Findings
Summary and discussion

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