Record Warmth of 2023 and 2024 was Highly Predictable and Resulted From ENSO Transition and Northern Hemisphere Absorbed Shortwave Anomalies

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Conflicts of Interest

Identified Weaknesses

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Paper Summary

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2023's Heatwave: Mostly Predictable, Thanks to El Niño and Sunshine!

A climate model successfully predicted about 75% of the record-breaking global temperature increase observed in 2023. The study identified the transition to El Niño and increased absorbed shortwave radiation in the Northern Hemisphere during spring and summer as key drivers of the warming.

Possible Conflicts of Interest

None identified.

Identified Weaknesses

Reliance on Models and Reanalysis Data with Limitations

The study relies on climate models and reanalysis data, which have known limitations and biases. For example, the forecast model does not include factors like solar cycle variability or shipping emissions, which could have influenced the observed warming. Additionally, the model did not account for aerosols from the Hunga Tonga eruption, which might have had a cooling effect.

Need for Further Investigation into Complex Interactions

While the study identifies El Niño and net absorbed TOA SW radiation as key drivers of the 2023 warming, the complex interplay of these and other factors needs further investigation. It's crucial to disentangle the relative contributions of each driver to fully understand the observed temperature surge.

Model Underestimation of Anomalies over Land

The study acknowledges that the forecast model underestimates the magnitude of observed anomalies, particularly over land. This highlights a potential limitation in the model's ability to accurately represent land-atmosphere interactions and their influence on temperature changes.

Rating Explanation

This study presents a strong analysis of the 2023 global temperature surge, combining observational data with climate model simulations and forecasts. The methodology is sound, and the findings provide valuable insights into the drivers and predictability of the warming event. While limitations exist regarding the model's accuracy and the complexity of climate interactions, the overall research is robust and contributes significantly to our understanding of climate change.

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