Environmental Sources of Error in the Navy ESPC MJO Forecasts and MJO Teleconnections

Abstract We examine the environmental conditions that lead to well- and poorly predicted MJO events in the Navy Earth System Prediction Capability (ESPC) global coupled forecast system. Individual MJO events are tracked using an MJO tracking algorithm following Chikira (2014). Good and poor forecasts are determined by how well the forecasted MJO object matches with the observed MJO objects. The primary difference between good and poor MJO forecasts is location and timing of forecasted MJO events. Good MJO forecasts capture the evolution of observed environmental moisture and low-level wind anomalies, while poor MJO forecasts do not build sufficient moisture anomalies to support the MJO’s amplifications and propagation. The poor forecasts struggle to simulate the horizontal advection and evaporation. The errors in the evaporation are likely driven by errors in the environmental and MJO-scale zonal wind anomalies. The errors in the evolution of the horizontal advection are largely driven by the evolution of the environmental wind and moisture gradient, which induces errors in the evolution of the zonal moisture advection. The effect of the good and poor MJO forecasts on the extended range MJO teleconnections is examined. It is found that MJO teleconnections are best simulated following the MJO’s enhanced convection over the Maritime Continent. There are systematic biases in the MJO-induced Rossby wave trains in the Navy ESPC, in some cases despite a good representation of the MJO. A northeastward tilt in the subtropical jet exit region is identified in the Navy ESPC and is another possible cause of these biases in the Rossby wave trains.

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Publication Details

Journal
Monthly Weather Review
Published
2025-04-24
DOI
https://doi.org/10.1175/mwr-d-24-0205.1
Primary Topic
Offshore Engineering and Technologies
Type
article
Field-Weighted Citation Impact
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article

Environmental Sources of Error in the Navy ESPC MJO Forecasts and MJO Teleconnections

Matthew A. Janiga, Carolyn A. Reynolds, Stephanie S. Rushley
Monthly Weather Review
Offshore Engineering and Technologies
article

Environmental Sources of Error in the Navy ESPC MJO Forecasts and MJO Teleconnections

Matthew A. Janiga, Carolyn A. Reynolds, Stephanie S. Rushley
article en

Abstract

Abstract We examine the environmental conditions that lead to well- and poorly predicted MJO events in the Navy Earth System Prediction Capability (ESPC) global coupled forecast system. Individual MJO events are tracked using an MJO tracking algorithm following Chikira (2014). Good and poor forecasts are determined by how well the forecasted MJO object matches with the observed MJO objects. The primary difference between good and poor MJO forecasts is location and timing of forecasted MJO events. Good MJO forecasts capture the evolution of observed environmental moisture and low-level wind anomalies, while poor MJO forecasts do not build sufficient moisture anomalies to support the MJO’s amplifications and propagation. The poor forecasts struggle to simulate the horizontal advection and evaporation. The errors in the evaporation are likely driven by errors in the environmental and MJO-scale zonal wind anomalies. The errors in the evolution of the horizontal advection are largely driven by the evolution of the environmental wind and moisture gradient, which induces errors in the evolution of the zonal moisture advection. The effect of the good and poor MJO forecasts on the extended range MJO teleconnections is examined. It is found that MJO teleconnections are best simulated following the MJO’s enhanced convection over the Maritime Continent. There are systematic biases in the MJO-induced Rossby wave trains in the Navy ESPC, in some cases despite a good representation of the MJO. A northeastward tilt in the subtropical jet exit region is identified in the Navy ESPC and is another possible cause of these biases in the Rossby wave trains.

Monthly Weather ReviewVol. 153(6)
Naval Research Laboratory Marine Meteorology Division
Openalex Percentile: Top 89%
Offshore Engineering and Technologies
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