Li et al. (2026) Layer‐Dependent Diurnal Moist Static Energy Biases in the Unified Forecast System During the MJO Preconditioning Stage: A DYNAMO Case Study

Identification

• Journal: Journal of Geophysical Research Atmospheres
• Year: 2026
• Date: 2026-08-05
• Authors: Weiwei Li, Shan Sun, Lisa Bengtsson, Man Zhang, Jimy Dudhia, Evelyn Grell, Julia M. Simonson, Tracy Hertneky, Louisa B. Nance
• DOI: 10.1029/2026jd046470

Research Groups

• National Science Foundation National Center for Atmospheric Research, Boulder, CO, USA
• Developmental Testbed Center, Boulder, CO, USA
• NOAA Oceanic and Atmospheric Research/Global Systems Laboratory, Boulder, CO, USA
• NOAA Oceanic and Atmospheric Research/Physical Sciences Laboratory, Boulder, CO, USA
• University of Colorado Boulder/Cooperative Institute for Research in Environmental Sciences, Boulder, CO, USA

Short Summary

This study applies a hierarchical modeling and evaluation approach to diagnose the vertical structure and diurnal evolution of moist static energy (MSE) in the Unified Forecast System (UFS), focusing on two Madden-Julian Oscillation (MJO) events from the DYNAMO field campaign. The results reveal a coherent, layer-dependent loop of interconnected physics deficiencies contributing to MSE biases.

Objective

• Investigate the diurnal variation of MSE represented in the UFS during MJO events.
• Identify key physical processes governing MSE bias on the diurnal timescale in the model.
• Evaluate how these processes distribute energy vertically on the diurnal timescale.

Study Configuration

• Spatial Scale: Global, with a focus on the central equatorial Indian Ocean and the Maritime Continent.
• Temporal Scale: Diurnal (day-night cycle) during two MJO events from the DYNAMO field campaign.

Methodology and Data

• Models used: Unified Forecast System (UFS), including the Global Forecast System (GFS), and the Common Community Physics Package Single-Column Model (CCPP SCM).
• Data sources: Observations from the Cooperative Indian Ocean Experiment on Intraseasonal Variability in the Year 2011 (CINDY2011)/DYNAMO field campaign, including radiosonde data, satellite imagery, and reanalysis products.

Main Results

• The UFS forecasts exhibit a consistent underestimation of MSE throughout the atmospheric column.
• The diurnal evolution of MSE is misrepresented, with premature near-surface anomalies and a persistent positive bias in the mid-troposphere during nighttime and early morning hours.
• The local rate of change of MSE (MSE tendency) is substantially underestimated on the diurnal timescale.

Contributions

• This study provides process-level insights into the representation of MSE in global models, highlighting the importance of vertically dependent physical processes in shaping the diurnal evolution of tropical energetics.
• The results have implications for improving MJO prediction in the UFS and related forecast systems by addressing deficiencies in convective parameterization and energy distribution.

Funding

• National Science Foundation (NSF)
• NOAA Oceanic and Atmospheric Research (OAR)
• University of Colorado Boulder/Cooperative Institute for Research in Environmental Sciences (CIRES)

Citation

@article{Li2026LayerDependent,
  author = {Li, Weiwei and Sun, Shan and Bengtsson, Lisa and Zhang, Man and Dudhia, Jimy and Grell, Evelyn and Simonson, Julia M. and Hertneky, Tracy and Nance, Louisa B.},
  title = {Layer‐Dependent Diurnal Moist Static Energy Biases in the Unified Forecast System During the MJO Preconditioning Stage: A DYNAMO Case Study},
  journal = {Journal of Geophysical Research Atmospheres},
  year = {2026},
  doi = {10.1029/2026jd046470},
  url = {https://doi.org/10.1029/2026jd046470}
}