Initialization shock in the ocean circulation reduces skill in decadal predictions of the North Atlantic subpolar gyre
Due to large northward transports of heat, the Atlantic Ocean circulation is strongly affecting the climate of various regions. Its internal variability has been shown to be predictable decades ahead within climate models, providing the hope that synchronizing ocean circulation with observations can...
Published in: | Frontiers in Climate |
---|---|
Main Authors: | , , , , , , |
Other Authors: | |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Frontiers Media
2023
|
Subjects: | |
Online Access: | http://hdl.handle.net/2117/397595 https://doi.org/10.3389/fclim.2023.1273770 |
Summary: | Due to large northward transports of heat, the Atlantic Ocean circulation is strongly affecting the climate of various regions. Its internal variability has been shown to be predictable decades ahead within climate models, providing the hope that synchronizing ocean circulation with observations can improve decadal predictions, notably of the North Atlantic subpolar gyre (SPG). Climate predictions require a starting point which is a reconstruction of the past climate. This is usually done with data assimilation methods that blend available observations and climate model states together. There is no unique method to derive initial conditions. Moreover, initialization can be implemented with full-field observations or their anomalies superimposed on the model's climatology to avoid strong drifts in predictions. How critical ocean circulation drifts (following the initialization step) are for prediction skill has not been assessed yet. We analyze this possible connection using the dataset of twelve prediction systems from the World Meteorological Organization Lead Centre for Annual-to-Decadal Climate Prediction. We find a wide variety of initial errors for the Atlantic meridional overturning circulation (AMOC) related to a dynamically imbalanced AMOC cell leading to strongly displaced or multiple maxima in the overturning structures. This likely results in a blend of model drift and initial shock. We identify that the AMOC initialization influences the quality of SPG predictions. When predictions show a large initial error in their AMOC, they usually have low skill for predicting internal variability of the SPG for a time horizon of 6-10 years. Full-field initialized predictions with low AMOC drift show better prediction skill of the SPG than those with a large AMOC drift. Nevertheless, while the anomaly-initialized predictions do not experience large drifts, they show low SPG skill when skill also present in historical runs is removed using a residual correlation metric. Thus, reducing initial shock and model ... |
---|